CRC - Sivasampu S Wahab YF Ong SM Ismail SA Goh PP ......Sivasampu S, Wahab YF, Ong SM, Ismail SA, Goh PP, Jeyaindran SNational Medical . Care Statistics (NMCS) 2014. Kuala Lumpur:

1

Sivasampu SWahab YF

Ong SMIsmail SA

Goh PPJeyaindran S

National Medical Care Statistics 2014 January 2016 ©Ministry of Health Malaysia Published by The National Healthcare Statistics Initiative (NHSI) National Clinical Research Centre National Institutes of Health 3rd Floor, MMA House 124, Jalan Pahang 53000 Kuala Lumpur Malaysia Tel : (603) 4043 9300/9400 Fax : (603) 4043 9500 Email : [email protected] Website : http://www.crc.gov.my/nhsi This report is copyrighted. Reproduction and dissemination of this report in part or in whole for research, educational or non-commercial purposes is authorised without any prior written permission from the copyright holders, provided that the source is fully acknowledged. Suggested citation: Sivasampu S, Wahab YF, Ong SM, Ismail SA, Goh PP, Jeyaindran S. National Medical Care Statistics (NMCS) 2014. Kuala Lumpur: National Clinical Research Centre, National Healthcare Statistics Initiative; 2016. Report No.: NCRC/HSU/2016.1. NMRR Approval No. NMRR-09-842-4718. Supported by the Ministry of Health Malaysia. This report is also available electronically on the website of the National Healthcare Statistics Initiative at http://www.crc.gov.my/nhsi Funding: The National Healthcare Statistics Initiative was funded by a grant from Ministry of Health Malaysia. NMRR Approval No. NMRR-09-842-4718

Please note that there is potential for minor corrections of data in this report. Do check the online version at http://www.crc.gov.my/nhsi/ for any amendments. Thank you.

ISSN 2289-1811

7722 89 1810 08

National Medical Care Statistics 2014 January 2016 ©Ministry of Health Malaysia Published by The National Healthcare Statistics Initiative (NHSI) National Clinical Research Centre National Institutes of Health 3rd Floor, MMA House 124, Jalan Pahang 53000 Kuala Lumpur Malaysia Tel : (603) 4043 9300/9400 Fax : (603) 4043 9500 Email : [email protected] Website : http://www.crc.gov.my/nhsi This report is copyrighted. Reproduction and dissemination of this report in part or in whole for research, educational or non-commercial purposes is authorised without any prior written permission from the copyright holders, provided that the source is fully acknowledged. Suggested citation: Sivasampu S, Wahab YF, Ong SM, Ismail SA, Goh PP, Jeyaindran S. National Medical Care Statistics (NMCS) 2014. Kuala Lumpur: National Clinical Research Centre, National Healthcare Statistics Initiative; 2016. Report No.: NCRC/HSU/2016.1. NMRR Approval No. NMRR-09-842-4718. Supported by the Ministry of Health Malaysia. This report is also available electronically on the website of the National Healthcare Statistics Initiative at http://www.crc.gov.my/nhsi Funding: The National Healthcare Statistics Initiative was funded by a grant from Ministry of Health Malaysia. NMRR Approval No. NMRR-09-842-4718

Please note that there is potential for minor corrections of data in this report. Do check the online version at http://www.crc.gov.my/nhsi/ for any amendments. Thank you.

ISSN 2289-1811

7722 89 1810 08

ii National Medical Care Statistics 2014

TABLE OF CONTENTS

TABLE OF CONTENTS ..................................................................................................................... ii

LIST OF TABLES ............................................................................................................................... v

LIST OF FIGURES .......................................................................................................................... vii

ACKNOWLEDGEMENTS ................................................................................................................. ix

NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM ............................................... x

ABBREVIATIONS ............................................................................................................................. xi

SYMBOLS .......................................................................................................................................... xii

EXECUTIVE SUMMARY ................................................................................................................... 1

CHAPTER 1 INTRODUCTION .................................................................................................... 7

1.1 Background ...................................................................................................... 8

1.2 Objectives ......................................................................................................... 8

1.3 Definitions ....................................................................................................... 9

1.4 Research Questions ....................................................................................... 10

CHAPTER 2 METHODOLOGY .................................................................................................. 11

2.1 Sample Size Calculation and Sampling Methods ........................................ 12

2.2 Data Collection and Follow-Up .................................................................... 19

2.3 Research Pack and Questionnaire ............................................................... 19

2.4 Data Management ......................................................................................... 20

2.5 Data Analysis ................................................................................................ 25

2.6 Ethics Approval ............................................................................................. 27

2.7 Limitations .................................................................................................... 27

CHAPTER 3 RESPONSE RATE ................................................................................................ 29

3.1 Response Rate ............................................................................................... 30

3.2 The Encounters ............................................................................................. 32

CHAPTER 4 THE PRACTICES ................................................................................................. 33

4.1 Primary Care Clinics in Malaysia ................................................................ 34

4.2 Attendances ................................................................................................... 35

4.3 Operating Days and Hours ........................................................................... 35

4.4 Type of Practice ............................................................................................. 36

4.5 Provider Workload ........................................................................................ 36

4.6 Computer Use ................................................................................................ 37

4.7 Workforce ....................................................................................................... 38

CHAPTER 5 THE DOCTORS ..................................................................................................... 41

5.1 Characteristics of the Doctors ...................................................................... 42

5.2 Gender ............................................................................................................ 44

5.3 Age Distribution ............................................................................................ 45

5.4 Experience ..................................................................................................... 45

5.5 Place of Graduation ....................................................................................... 46

5.6 Postgraduate Qualification ........................................................................... 47

5.7 Working Hours .............................................................................................. 48

CHAPTER 6 THE PATIENTS .................................................................................................... 49

6.1 Characteristics of the Patients ..................................................................... 50

6.2 Age-Gender Distribution ............................................................................... 53

6.3 Nationality and Ethnicity ............................................................................. 54

6.4 Mode of Payment ........................................................................................... 56

6.5 Individual Income ......................................................................................... 56

6.6 Education Level ............................................................................................. 58

6.7 Medical Certificate and Duration of Sick Leave .......................................... 58

CHAPTER 7 REASONS FOR ENCOUNTER .......................................................................... 61

7.1 Number of Reasons for Encounter per Visit ................................................ 62

7.2 Reasons for Encounter by ICPC-2 Components .......................................... 63

7.3 Reasons for Encounter by ICPC-2 Chapters ................................................ 65

7.4 Most Common Reasons for Encounter in Public and Private Clinics ........ 67

CHAPTER 8 DIAGNOSES .......................................................................................................... 69

8.1 Number of Diagnoses per Encounter ........................................................... 70

8.2 Diagnoses by ICPC-2 Components ............................................................... 71

8.3 Diagnoses by ICPC-2 Chapters .................................................................... 72

8.4 Most Common Diagnoses Managed in Public and Private Clinics ............. 75

CHAPTER 9 MEDICATIONS ..................................................................................................... 79

9.1 Number of Medications Prescribed per Encounter ..................................... 80

9.2 Types of Medications Prescribed .................................................................. 83

9.3 Most Frequently Prescribed Medications in Public and Private

Clinics ............................................................................................................ 89

iii

TABLE OF CONTENTS

TABLE OF CONTENTS ..................................................................................................................... ii

LIST OF TABLES ............................................................................................................................... v

LIST OF FIGURES .......................................................................................................................... vii

ACKNOWLEDGEMENTS ................................................................................................................. ix

NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM ............................................... x

ABBREVIATIONS ............................................................................................................................. xi

SYMBOLS .......................................................................................................................................... xii

EXECUTIVE SUMMARY ................................................................................................................... 1

CHAPTER 1 INTRODUCTION .................................................................................................... 7

1.1 Background ...................................................................................................... 8

1.2 Objectives ......................................................................................................... 8

1.3 Definitions ....................................................................................................... 9

1.4 Research Questions ....................................................................................... 10

CHAPTER 2 METHODOLOGY .................................................................................................. 11

2.1 Sample Size Calculation and Sampling Methods ........................................ 12

2.2 Data Collection and Follow-Up .................................................................... 19

2.3 Research Pack and Questionnaire ............................................................... 19

2.4 Data Management ......................................................................................... 20

2.5 Data Analysis ................................................................................................ 25

2.6 Ethics Approval ............................................................................................. 27

2.7 Limitations .................................................................................................... 27

CHAPTER 3 RESPONSE RATE ................................................................................................ 29

3.1 Response Rate ............................................................................................... 30

3.2 The Encounters ............................................................................................. 32

CHAPTER 4 THE PRACTICES ................................................................................................. 33

4.1 Primary Care Clinics in Malaysia ................................................................ 34

4.2 Attendances ................................................................................................... 35

4.3 Operating Days and Hours ........................................................................... 35

4.4 Type of Practice ............................................................................................. 36

4.5 Provider Workload ........................................................................................ 36

4.6 Computer Use ................................................................................................ 37

4.7 Workforce ....................................................................................................... 38

CHAPTER 5 THE DOCTORS ..................................................................................................... 41

5.1 Characteristics of the Doctors ...................................................................... 42

5.2 Gender ............................................................................................................ 44

5.3 Age Distribution ............................................................................................ 45

5.4 Experience ..................................................................................................... 45

5.5 Place of Graduation ....................................................................................... 46

5.6 Postgraduate Qualification ........................................................................... 47

5.7 Working Hours .............................................................................................. 48

CHAPTER 6 THE PATIENTS .................................................................................................... 49

6.1 Characteristics of the Patients ..................................................................... 50

6.2 Age-Gender Distribution ............................................................................... 53

6.3 Nationality and Ethnicity ............................................................................. 54

6.4 Mode of Payment ........................................................................................... 56

6.5 Individual Income ......................................................................................... 56

6.6 Education Level ............................................................................................. 58

6.7 Medical Certificate and Duration of Sick Leave .......................................... 58

CHAPTER 7 REASONS FOR ENCOUNTER .......................................................................... 61

7.1 Number of Reasons for Encounter per Visit ................................................ 62

7.2 Reasons for Encounter by ICPC-2 Components .......................................... 63

7.3 Reasons for Encounter by ICPC-2 Chapters ................................................ 65

7.4 Most Common Reasons for Encounter in Public and Private Clinics ........ 67

CHAPTER 8 DIAGNOSES .......................................................................................................... 69

8.1 Number of Diagnoses per Encounter ........................................................... 70

8.2 Diagnoses by ICPC-2 Components ............................................................... 71

8.3 Diagnoses by ICPC-2 Chapters .................................................................... 72

8.4 Most Common Diagnoses Managed in Public and Private Clinics ............. 75

CHAPTER 9 MEDICATIONS ..................................................................................................... 79

9.1 Number of Medications Prescribed per Encounter ..................................... 80

9.2 Types of Medications Prescribed .................................................................. 83

9.3 Most Frequently Prescribed Medications in Public and Private

Clinics ............................................................................................................ 89

iv National Medical Care Statistics 2014

CHAPTER 10 INVESTIGATIONS ............................................................................................... 95

10.1 Number of Investigations per Encounter .................................................... 96

10.2 Types of Investigations Ordered ................................................................... 96

10.3 Most Frequently Ordered Investigations in Public and Private

Clinics ............................................................................................................. 99

10.4 Diagnoses with Investigations Ordered ..................................................... 100

CHAPTER 11 ADVICE/COUNSELLING AND PROCEDURES ........................................... 103

11.1 Number of Advice/Counselling and Procedures ........................................ 104

11.2 Types of Advice/Counselling ....................................................................... 105

11.3 Most Common Advice/Counselling Provided in Public and Private

Clinics .......................................................................................................... 106

11.4 Types of Procedures .................................................................................... 108

11.5 Most Common Procedures Performed in Public and Private Clinics ....... 109

11.6 Diagnoses with Advice/Counselling and Procedures ................................. 110

CHAPTER 12 FOLLOW-UPS AND REFERRALS .................................................................. 113

12.1 Number of Follow-Ups and Referrals ........................................................ 114

12.2 Types of Referrals ........................................................................................ 115

12.3 Most Frequently Followed Up Diagnoses .................................................. 116

12.4 Most Frequently Referred Diagnoses ......................................................... 117

APPENDICES .................................................................................................................................. 119

Appendix 1: Additional Tables .............................................................................. 120

Appendix 2: NMCS 2014 Primary Care Provider’s Profile Questionnaire ......... 121

Appendix 3: NMCS 2014 Survey Form ................................................................ 122

Appendix 4: ICPC-2 and ICPC-2 PLUS groups ................................................... 123

Appendix 5: Participants of NMCS 2014 ............................................................. 133

Appendix 6: List of Definitions ............................................................................. 143

LIST OF TABLES

Table 2.1.1 Sample size (primary sampling units) for NMCS 2014 ........................................... 13

Table 2.1.2 Inclusion and exclusion criteria for the clinics sampled in the survey ................... 14

Table 2.4.1 Data entry error rate for NMCS 2014 ...................................................................... 22

Table 2.4.2 ICPC-2 chapters ......................................................................................................... 23

Table 2.4.3 ICPC-2 components .................................................................................................... 24

Table 2.5.1 Strata according to state/region and sector .............................................................. 25

Table 3.1.1 Total number of clinics sampled and responded for NMCS 2014 ........................... 30

Table 3.1.2 Total number of encounters received for NMCS 2014 ............................................. 31

Table 3.2.1 Observed and weighted dataset for NMCS 2014 ..................................................... 32

Table 4.3.1 Operating days and hours of public clinics in 2014 ................................................. 35

Table 4.3.2 Operating days and hours of private clinics in 2014 ............................................... 36

Table 4.4.1 Type of practice for private clinics in 2014 ............................................................... 36

Table 4.7.1 Healthcare workforce by sector in primary care clinics in 2014 ............................. 38

Table 5.1.1 Characteristics of primary care doctors in 2014 ...................................................... 43

Table 6.1.1 Characteristics of primary care patients in 2014 ..................................................... 51

Table 7.2.1 Reasons for encounter by ICPC-2 components in primary care clinics in 2014 ..... 63

Table 7.2.2 Reasons for encounter by ICPC-2 components in public clinics in 2014 ................ 64

Table 7.2.3 Reasons for encounter by ICPC-2 components in private clinics in 2014 ............... 64

Table 7.3.1 Reasons for encounter by ICPC-2 chapters and the most common individual

reasons for encounter within each chapter in primary care clinics in 2014 ........... 65

Table 8.2.1 Diagnoses by ICPC-2 components in primary care clinics in 2014 ......................... 72

Table 8.3.1 Diagnosis by ICPC-2 chapters and the most common individual diagnoses

within each chapter in NMCS 2014 .......................................................................... 73

Table 8.4.1 Thirty most common diagnoses managed in public clinics in 2014 ........................ 76

Table 8.4.2 Thirty most common diagnoses managed in private clinics in 2014 ...................... 77

Table 9.1.1 Number of encounters with and without medical prescription in primary

care clinics in 2014 ..................................................................................................... 80

Table 9.1.2 Number of medications prescribed in primary care clinics in 2014 ........................ 81

Table 9.2.1 Prescribed medications by ATC levels in primary care clinics in 2014 .................. 84

Table 9.2.2 Prescribed medications by ATC level 1 in public clinics in 2014 ............................ 88

Table 9.2.3 Prescribed medications by ATC level 1 in private clinics in 2014 .......................... 89

Table 9.3.1 Thirty most frequently prescribed medications in public clinics in 2014 ............... 91

Table 9.3.2 Thirty most frequently prescribed medications in private clinics in 2014 ............. 92

Table 10.1.1 Number of encounters with investigations ordered in primary care clinics in

2014 ............................................................................................................................. 96

v

CHAPTER 10 INVESTIGATIONS ............................................................................................... 95

10.1 Number of Investigations per Encounter .................................................... 96

10.2 Types of Investigations Ordered ................................................................... 96

10.3 Most Frequently Ordered Investigations in Public and Private

Clinics ............................................................................................................. 99

10.4 Diagnoses with Investigations Ordered ..................................................... 100

CHAPTER 11 ADVICE/COUNSELLING AND PROCEDURES ........................................... 103

11.1 Number of Advice/Counselling and Procedures ........................................ 104

11.2 Types of Advice/Counselling ....................................................................... 105

11.3 Most Common Advice/Counselling Provided in Public and Private

Clinics .......................................................................................................... 106

11.4 Types of Procedures .................................................................................... 108

11.5 Most Common Procedures Performed in Public and Private Clinics ....... 109

11.6 Diagnoses with Advice/Counselling and Procedures ................................. 110

CHAPTER 12 FOLLOW-UPS AND REFERRALS .................................................................. 113

12.1 Number of Follow-Ups and Referrals ........................................................ 114

12.2 Types of Referrals ........................................................................................ 115

12.3 Most Frequently Followed Up Diagnoses .................................................. 116

12.4 Most Frequently Referred Diagnoses ......................................................... 117

APPENDICES .................................................................................................................................. 119

Appendix 1: Additional Tables .............................................................................. 120

Appendix 2: NMCS 2014 Primary Care Provider’s Profile Questionnaire ......... 121

Appendix 3: NMCS 2014 Survey Form ................................................................ 122

Appendix 4: ICPC-2 and ICPC-2 PLUS groups ................................................... 123

Appendix 5: Participants of NMCS 2014 ............................................................. 133

Appendix 6: List of Definitions ............................................................................. 143

LIST OF TABLES

Table 2.1.1 Sample size (primary sampling units) for NMCS 2014 ........................................... 13

Table 2.1.2 Inclusion and exclusion criteria for the clinics sampled in the survey ................... 14

Table 2.4.1 Data entry error rate for NMCS 2014 ...................................................................... 22

Table 2.4.2 ICPC-2 chapters ......................................................................................................... 23

Table 2.4.3 ICPC-2 components .................................................................................................... 24

Table 2.5.1 Strata according to state/region and sector .............................................................. 25

Table 3.1.1 Total number of clinics sampled and responded for NMCS 2014 ........................... 30

Table 3.1.2 Total number of encounters received for NMCS 2014 ............................................. 31

Table 3.2.1 Observed and weighted dataset for NMCS 2014 ..................................................... 32

Table 4.3.1 Operating days and hours of public clinics in 2014 ................................................. 35

Table 4.3.2 Operating days and hours of private clinics in 2014 ............................................... 36

Table 4.4.1 Type of practice for private clinics in 2014 ............................................................... 36

Table 4.7.1 Healthcare workforce by sector in primary care clinics in 2014 ............................. 38

Table 5.1.1 Characteristics of primary care doctors in 2014 ...................................................... 43

Table 6.1.1 Characteristics of primary care patients in 2014 ..................................................... 51

Table 7.2.1 Reasons for encounter by ICPC-2 components in primary care clinics in 2014 ..... 63

Table 7.2.2 Reasons for encounter by ICPC-2 components in public clinics in 2014 ................ 64

Table 7.2.3 Reasons for encounter by ICPC-2 components in private clinics in 2014 ............... 64

Table 7.3.1 Reasons for encounter by ICPC-2 chapters and the most common individual

reasons for encounter within each chapter in primary care clinics in 2014 ........... 65

Table 8.2.1 Diagnoses by ICPC-2 components in primary care clinics in 2014 ......................... 72

Table 8.3.1 Diagnosis by ICPC-2 chapters and the most common individual diagnoses

within each chapter in NMCS 2014 .......................................................................... 73

Table 8.4.1 Thirty most common diagnoses managed in public clinics in 2014 ........................ 76

Table 8.4.2 Thirty most common diagnoses managed in private clinics in 2014 ...................... 77

Table 9.1.1 Number of encounters with and without medical prescription in primary

care clinics in 2014 ..................................................................................................... 80

Table 9.1.2 Number of medications prescribed in primary care clinics in 2014 ........................ 81

Table 9.2.1 Prescribed medications by ATC levels in primary care clinics in 2014 .................. 84

Table 9.2.2 Prescribed medications by ATC level 1 in public clinics in 2014 ............................ 88

Table 9.2.3 Prescribed medications by ATC level 1 in private clinics in 2014 .......................... 89

Table 9.3.1 Thirty most frequently prescribed medications in public clinics in 2014 ............... 91

Table 9.3.2 Thirty most frequently prescribed medications in private clinics in 2014 ............. 92

Table 10.1.1 Number of encounters with investigations ordered in primary care clinics in

2014 ............................................................................................................................. 96

vi National Medical Care Statistics 2014

Table 10.2.1 Types of investigations by ICPC-2 process codes in primary care clinics in

2014 ............................................................................................................................. 97

Table 10.4.1 Top 10 diagnoses for which investigations were most frequently ordered in

primary care clinics in 2014 .................................................................................... 101

Table 11.1.1 Number of encounters managed with advice and counselling in primary care

clinics in 2014 ........................................................................................................... 104

Table 11.1.2 Number of encounters managed with procedures in primary care clinics in

2014 ........................................................................................................................... 104

Table 11.2.1 Types of advice and counselling provided in primary care clinics in 2014 ........... 105

Table 11.4.1 Types of procedures provided in primary care clinics in 2014 .............................. 108

Table 11.6.1 Ten most common diagnoses managed with advice/counselling in primary

care clinics in 2014 ................................................................................................... 111

Table 11.6.2 Ten most common diagnoses managed with procedures in primary care

clinics in 2014 ........................................................................................................... 112

Table 12.1.1 Visit dispositions of primary care patients by sector in 2014 ................................ 114

Table 12.2.1 Types of referrals in primary care in 2014 ............................................................. 115

Table 12.2.2 Types of referrals in public clinics in 2014 ............................................................. 116

Table 12.2.3 Types of referrals in private clinics in 2014 ........................................................... 116

Table 12.3.1 Top 10 diagnoses for follow-up in primary care in 2014 ........................................ 117

Table 12.4.1 Top 10 diagnoses for referral in primary care in 2014 .......................................... 118

LIST OF FIGURES

Figure 2.1.1 Study design for NMCS 2014 .................................................................................... 16

Figure 2.1.2 Consort diagram – public primary care clinics 2014 ............................................... 17

Figure 2.1.3 Consort diagram – private primary care clinics 2014 .............................................. 18

Figure 4.1.1 Number of primary care clinics per 10,000 population in 2012 .............................. 34

Figure 4.6.1 Types of computer use in primary care by sector in 2014 ....................................... 37

Figure 4.7.1 Primary care clinics with family medicine specialists by sector in 2014 ................ 39

Figure 5.2.1 Distribution of public and private doctors by gender in 2014 ................................. 44

Figure 5.3.1 Distribution of public and private doctors by age group in 2014 ............................ 45

Figure 5.4.1 Distribution of public and private doctors by years of experience in 2014 ............. 46

Figure 5.5.1 Distribution of public and private doctors by place of graduation in 2014 ............. 47

Figure 5.6.1 Distribution of public and private doctors by postgraduate qualification in

2014 ............................................................................................................................. 48

Figure 6.2.1 Distribution of public patients by age and gender in 2014 ...................................... 53

Figure 6.2.2 Distribution of private patients by age and gender in 2014 .................................... 54

Figure 6.3.1 Distribution of public and private patients by nationality in 2014 ........................ 55

Figure 6.3.2 Distribution of public and private patients by ethnicity in 2014 ............................ 55

Figure 6.4.1 Distribution of private patients by mode of payment in 2014 ................................. 56

Figure 6.5.1 Distribution of public and private patients by type of income in 2014 ................... 57

Figure 6.5.2 Distribution of primary care patients by income and sector in 2014 ...................... 57

Figure 6.6.1 Distribution of public and private patients by education level in 2014 .................. 58

Figure 6.7.1 Distribution of public and private patients by issuance of medical certificate

in 2014 ........................................................................................................................ 59

Figure 6.7.2 Distribution of public and private patients by duration of sick leave in 2014 ....... 59

Figure 7.1.1 Number of reasons for encounter per visit in primary care clinics in 2014 ............ 62

Figure 7.4.1 Top 10 reasons for encounter in public clinics in 2014 ............................................ 67

Figure 7.4.2 Top 10 reasons for encounter in private clinics in 2014 .......................................... 68

Figure 8.1.1 Number of diagnoses managed per encounter in primary care clinics in 2014 ...... 70

Figure 8.1.2 Age- and gender- specific rates of diagnoses managed per 100 encounters by

sector in 2014 ............................................................................................................. 71

Figure 9.1.1 Number of medications prescribed per encounter in primary care clinics in

2014 ............................................................................................................................. 81

Figure 9.1.2 Age- and gender- specific prescription rates per 100 encounters by sector in

2014 ............................................................................................................................. 82

Figure 10.1.1 Number of investigations ordered per encounter in primary care clinics in

2014 ............................................................................................................................. 97

Figure 10.3.1 Top 10 investigations ordered in public clinics in 2014 ............................................ 99

vii

Table 10.2.1 Types of investigations by ICPC-2 process codes in primary care clinics in

2014 ............................................................................................................................. 97

Table 10.4.1 Top 10 diagnoses for which investigations were most frequently ordered in

primary care clinics in 2014 .................................................................................... 101

Table 11.1.1 Number of encounters managed with advice and counselling in primary care

clinics in 2014 ........................................................................................................... 104

Table 11.1.2 Number of encounters managed with procedures in primary care clinics in

2014 ........................................................................................................................... 104

Table 11.2.1 Types of advice and counselling provided in primary care clinics in 2014 ........... 105

Table 11.4.1 Types of procedures provided in primary care clinics in 2014 .............................. 108

Table 11.6.1 Ten most common diagnoses managed with advice/counselling in primary

care clinics in 2014 ................................................................................................... 111

Table 11.6.2 Ten most common diagnoses managed with procedures in primary care

clinics in 2014 ........................................................................................................... 112

Table 12.1.1 Visit dispositions of primary care patients by sector in 2014 ................................ 114

Table 12.2.1 Types of referrals in primary care in 2014 ............................................................. 115

Table 12.2.2 Types of referrals in public clinics in 2014 ............................................................. 116

Table 12.2.3 Types of referrals in private clinics in 2014 ........................................................... 116

Table 12.3.1 Top 10 diagnoses for follow-up in primary care in 2014 ........................................ 117

Table 12.4.1 Top 10 diagnoses for referral in primary care in 2014 .......................................... 118

LIST OF FIGURES

Figure 2.1.1 Study design for NMCS 2014 .................................................................................... 16

Figure 2.1.2 Consort diagram – public primary care clinics 2014 ............................................... 17

Figure 2.1.3 Consort diagram – private primary care clinics 2014 .............................................. 18

Figure 4.1.1 Number of primary care clinics per 10,000 population in 2012 .............................. 34

Figure 4.6.1 Types of computer use in primary care by sector in 2014 ....................................... 37

Figure 4.7.1 Primary care clinics with family medicine specialists by sector in 2014 ................ 39

Figure 5.2.1 Distribution of public and private doctors by gender in 2014 ................................. 44

Figure 5.3.1 Distribution of public and private doctors by age group in 2014 ............................ 45

Figure 5.4.1 Distribution of public and private doctors by years of experience in 2014 ............. 46

Figure 5.5.1 Distribution of public and private doctors by place of graduation in 2014 ............. 47

Figure 5.6.1 Distribution of public and private doctors by postgraduate qualification in

2014 ............................................................................................................................. 48

Figure 6.2.1 Distribution of public patients by age and gender in 2014 ...................................... 53

Figure 6.2.2 Distribution of private patients by age and gender in 2014 .................................... 54

Figure 6.3.1 Distribution of public and private patients by nationality in 2014 ........................ 55

Figure 6.3.2 Distribution of public and private patients by ethnicity in 2014 ............................ 55

Figure 6.4.1 Distribution of private patients by mode of payment in 2014 ................................. 56

Figure 6.5.1 Distribution of public and private patients by type of income in 2014 ................... 57

Figure 6.5.2 Distribution of primary care patients by income and sector in 2014 ...................... 57

Figure 6.6.1 Distribution of public and private patients by education level in 2014 .................. 58

Figure 6.7.1 Distribution of public and private patients by issuance of medical certificate

in 2014 ........................................................................................................................ 59

Figure 6.7.2 Distribution of public and private patients by duration of sick leave in 2014 ....... 59

Figure 7.1.1 Number of reasons for encounter per visit in primary care clinics in 2014 ............ 62

Figure 7.4.1 Top 10 reasons for encounter in public clinics in 2014 ............................................ 67

Figure 7.4.2 Top 10 reasons for encounter in private clinics in 2014 .......................................... 68

Figure 8.1.1 Number of diagnoses managed per encounter in primary care clinics in 2014 ...... 70

Figure 8.1.2 Age- and gender- specific rates of diagnoses managed per 100 encounters by

sector in 2014 ............................................................................................................. 71

Figure 9.1.1 Number of medications prescribed per encounter in primary care clinics in

2014 ............................................................................................................................. 81

Figure 9.1.2 Age- and gender- specific prescription rates per 100 encounters by sector in

2014 ............................................................................................................................. 82

Figure 10.1.1 Number of investigations ordered per encounter in primary care clinics in

2014 ............................................................................................................................. 97

Figure 10.3.1 Top 10 investigations ordered in public clinics in 2014 ............................................ 99

viii National Medical Care Statistics 2014

Figure 10.3.2 Top 10 investigations ordered in private clinics in 2014 ....................................... 100

Figure 11.3.1 Ten most common advice/counselling provided in public clinics in 2014 ............. 107

Figure 11.3.2 Ten most common advice/counselling provided in private clinics in 2014 ........... 107

Figure 11.5.1 Ten most common procedures performed in public clinics in 2014 ....................... 109

Figure 11.5.2 Ten most common procedures performed in private clinics in 2014 ..................... 110

ACKNOWLEDGEMENTS

National Healthcare Statistics Initiative team would like to thank the Director General of Health Malaysia for his continuous support towards this survey and permission to publish this report.

We would like to express our sincere appreciation to the following contributors for participating, guiding, advising and supporting us in our endeavour:

• Deputy Director-General of Health (Research and Technical Support), Ministry of Health (MOH)

• Deputy Director-General of Health (Medical), MOH • Deputy Director-General of Health (Public Health), MOH • Director of the Clinical Research Centre, National Institutes of Health, MOH • Health Informatics Centre, MOH • Director of the Family Health Development Division, MOH • Director of the Planning and Development Division, MOH • Director of the Private Medical Practice Division, MOH (Cawangan Kawalan Amalan

Perubatan Swasta, CKAPS) • State level Private Medical Practice Control Units (Unit Kawalan Amalan Perubatan

Swasta, UKAPS). • Malaysian Medical Council, Malaysian Medical Association, Academy of Family Physicians

Malaysia.

This report would not have been possible without the support and participation of the primary care clinics’ providers and their patients in the National Medical Care Survey 2014. Our sincerest gratitude goes out to them in making this project a success.

Last but not least, we thank Ms. Lim Huy Ming for her contributions in editing this report.

National Healthcare Statistics Initiative (NHSI) Primary Care Team Healthcare Statistics Unit National Clinical Research Centre Ministry of Health, Malaysia.

ix

Figure 10.3.2 Top 10 investigations ordered in private clinics in 2014 ....................................... 100

Figure 11.3.1 Ten most common advice/counselling provided in public clinics in 2014 ............. 107

Figure 11.3.2 Ten most common advice/counselling provided in private clinics in 2014 ........... 107

Figure 11.5.1 Ten most common procedures performed in public clinics in 2014 ....................... 109

Figure 11.5.2 Ten most common procedures performed in private clinics in 2014 ..................... 110

ACKNOWLEDGEMENTS

National Healthcare Statistics Initiative team would like to thank the Director General of Health Malaysia for his continuous support towards this survey and permission to publish this report.

We would like to express our sincere appreciation to the following contributors for participating, guiding, advising and supporting us in our endeavour:

• Deputy Director-General of Health (Research and Technical Support), Ministry of Health (MOH)

• Deputy Director-General of Health (Medical), MOH • Deputy Director-General of Health (Public Health), MOH • Director of the Clinical Research Centre, National Institutes of Health, MOH • Health Informatics Centre, MOH • Director of the Family Health Development Division, MOH • Director of the Planning and Development Division, MOH • Director of the Private Medical Practice Division, MOH (Cawangan Kawalan Amalan

Perubatan Swasta, CKAPS) • State level Private Medical Practice Control Units (Unit Kawalan Amalan Perubatan

Swasta, UKAPS). • Malaysian Medical Council, Malaysian Medical Association, Academy of Family Physicians

Malaysia.

This report would not have been possible without the support and participation of the primary care clinics’ providers and their patients in the National Medical Care Survey 2014. Our sincerest gratitude goes out to them in making this project a success.

Last but not least, we thank Ms. Lim Huy Ming for her contributions in editing this report.

National Healthcare Statistics Initiative (NHSI) Primary Care Team Healthcare Statistics Unit National Clinical Research Centre Ministry of Health, Malaysia.

x National Medical Care Statistics 2014

ABBREVIATIONS

ACE Angiotensin converting enzyme

ATC WHO Anatomical Therapeutic Chemical classification system

BEACH Bettering the Evaluation and Care of Health

CI Confidence interval

CKAPS Cawangan Kawalan Amalan Perubatan Swasta (Private Medical Practice Division)

FMS Family medicine specialist

FOMEMA Foreign Workers Medical Examination Monitoring Agency

FRACGP Fellowship of the Royal Australian College of General Practitioners

FRCGP Fellowship of the Royal College of General Practitioners

FTE Full-time-equivalent

GP General practice or practitioner

HbA1c Glycated haemoglobin

ICPC International Classification of Primary Care

IQR Interquartile range

MAFP Membership of the Academy of Family Physicians of Malaysia

MOH Ministry of Health, Malaysia

MRCGP Membership of the Royal College of General Practitioners

MREC Medical Research and Ethics Committee, Ministry of Health Malaysia

MYR Malaysian Ringgit

NCRC National Clinical Research Centre

NEC Not elsewhere classified

NHEWS National Healthcare Establishment & Workforce Survey (Primary Care)

NHSI National Healthcare Statistics Initiative

NMCS National Medical Care Survey

NOS Not otherwise specified

PSU Primary sampling unit

QSU Quaternary sampling unit

REC Research Evaluation Committee

RFE Reason for encounter

SOCSO Social Security Organisation

SSU Secondary sampling unit

TSU Tertiary sampling unit

UKAPS Unit Kawalan Amalan Perubatan Swasta (Private Medical Practice Control Units)

WHO World Health Organisation

WONCA World Organization of National Colleges, Academies and Academic Associations of General Practitioners/Family Physicians

WP Wilayah Persekutuan (Federal Territories)

NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM

Principal Investigator

YBhg. Datuk Dr. Jeyaindran Tan Sri Sinnadurai

Principal Co -Investigator Dr. Sheamini Sivasampu

Dr. Goh Pik Pin

Research Evaluation Committee

(REC)

Dr. Kamaliah Mohd. Noh

Professor Dr. Khoo Ee Ming

Professor Dr. Ng Chirk Jenn

Professor Dr. Teng Cheong Lieng

Dr Baizury Bashah

Ms. Siti Fauziah Abu

Project Managers Dr. Yasmin Farhana Abdul Wahab

Mr. Ong Su Miin

Members of Research Team

Dr. Chin May Chien

Dr. Kirubashni Mohan

Ms. Thilagaa Rajanthren

Ms. Pavityra Velayutham

Mr. Amirul Amin Kamaruzzaman

Ms. Nur Rafidah Mohd Noor

Ms. Juliana Mohd Noor

Survey Coordinator

Ms. Siti Aminah Ismail

Data Analysis Mr. Ong Su Miin

Database

Developers/Administrators Altus Solutions Sdn. Bhd.

xi

ABBREVIATIONS

ACE Angiotensin converting enzyme

ATC WHO Anatomical Therapeutic Chemical classification system

BEACH Bettering the Evaluation and Care of Health

CI Confidence interval

CKAPS Cawangan Kawalan Amalan Perubatan Swasta (Private Medical Practice Division)

FMS Family medicine specialist

FOMEMA Foreign Workers Medical Examination Monitoring Agency

FRACGP Fellowship of the Royal Australian College of General Practitioners

FRCGP Fellowship of the Royal College of General Practitioners

FTE Full-time-equivalent

GP General practice or practitioner

HbA1c Glycated haemoglobin

ICPC International Classification of Primary Care

IQR Interquartile range

MAFP Membership of the Academy of Family Physicians of Malaysia

MOH Ministry of Health, Malaysia

MRCGP Membership of the Royal College of General Practitioners

MREC Medical Research and Ethics Committee, Ministry of Health Malaysia

MYR Malaysian Ringgit

NCRC National Clinical Research Centre

NEC Not elsewhere classified

NHEWS National Healthcare Establishment & Workforce Survey (Primary Care)

NHSI National Healthcare Statistics Initiative

NMCS National Medical Care Survey

NOS Not otherwise specified

PSU Primary sampling unit

QSU Quaternary sampling unit

REC Research Evaluation Committee

RFE Reason for encounter

SOCSO Social Security Organisation

SSU Secondary sampling unit

TSU Tertiary sampling unit

UKAPS Unit Kawalan Amalan Perubatan Swasta (Private Medical Practice Control Units)

WHO World Health Organisation

WONCA World Organization of National Colleges, Academies and Academic Associations of General Practitioners/Family Physicians

WP Wilayah Persekutuan (Federal Territories)

NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM

Principal Investigator

YBhg. Datuk Dr. Jeyaindran Tan Sri Sinnadurai

Principal Co -Investigator Dr. Sheamini Sivasampu

Dr. Goh Pik Pin

Research Evaluation Committee

(REC)

Dr. Kamaliah Mohd. Noh

Professor Dr. Khoo Ee Ming

Professor Dr. Ng Chirk Jenn

Professor Dr. Teng Cheong Lieng

Dr Baizury Bashah

Ms. Siti Fauziah Abu

Project Managers Dr. Yasmin Farhana Abdul Wahab

Mr. Ong Su Miin

Members of Research Team

Dr. Chin May Chien

Dr. Kirubashni Mohan

Ms. Thilagaa Rajanthren

Ms. Pavityra Velayutham

Mr. Amirul Amin Kamaruzzaman

Ms. Nur Rafidah Mohd Noor

Ms. Juliana Mohd Noor

Survey Coordinator

Ms. Siti Aminah Ismail

Data Analysis Mr. Ong Su Miin

Database

Developers/Administrators Altus Solutions Sdn. Bhd.

xii National Medical Care Statistics 2014

SYMBOLS

– Not applicable

> More than

≥ More than or equal to

< Less than

% Percentage

All error bars in the figures included in this report represent 95% confidence intervals (CIs).

EXECUTIVE SUMMARY

The National Medical Care Survey (NMCS) is a provider-based survey which aims to study the characteristics and morbidity pattern of patients as well as healthcare activities in terms of investigations, procedures, counselling and visit dispositions provided at primary care level in Malaysia. NMCS 2014 covered public and private clinics from 13 states and three federal territories in Malaysia. The clinics were stratified according to sector and state and selected through random sampling. Healthcare providers from these clinics recorded details of patients they managed on the day of survey, which was randomly allocated between January and May 2014.

Primary care clinics

In NMCS 2014, a total of 129 public clinics out of 139 sampled (92.8%) and 416 private clinics out of 1,002 sampled (41.5%) responded. The survey data were weighted to produce unbiased national estimates for 664 public clinics and 4,810 private clinics in Malaysia which were staffed with medical doctors.

• The median attendance rate in public clinics was 111.5 visits per day, compared to 33.0 per day in private clinics.

• A large majority (82.8%) of public clinics operated five days per week. After-hours services (extended-hours and/or on-call services) were provided in addition to the standard-hour operation in 47.9% of public clinics.

• Most (54.0%) private clinics operated six days per week. Only 5.0% of the private clinics provided 24-hour services.

• Three-quarters (75.3%) of the private clinics were solo practices. • The median number of patients seen per full time equivalent (FTE) doctor in the private

sector was 25.9 patients per day. • Only 19.4% of public clinics had a functional computer system installed in the practice,

compared to 71.6% for private clinics. Computer system was mainly used for registration (83.7%) and medical record keeping (83.3%) purposes in the public sector and for billing purpose (79.6%) in the private sector.

• Public clinics were staffed with 26.4 health professionals on average, with a median of three doctors, six staff nurses, seven community nurses, three assistant medical officers and one pharmacist per clinic. In contrast, private practices had only 5.6 health professionals on average, with a median of one doctor and three clinic assistants in each clinic.

• Family medicine specialists (FMS) were available in 40.1% of public clinics, compared to 2.9% in the private sector.

The doctors

A total of 936 doctors participated in NMCS 2014: 490 (52.4%) from public clinics and 446 (47.6%) from private clinics. The survey responses were weighted to produce national estimates for 10,964 doctors (2,992 public and 7,972 private) working in primary care in Malaysia.

• Female doctors accounted for a higher proportion of the doctor workforce in the public sector compared to the private sector (70.5% versus 39.7%, respectively).

• The vast majority (79.9%) of the doctors in public clinics were between 25 and 34 years old, compared to only 4.2% in the private sector. In contrast, 69.9% of the doctors in private

1

SYMBOLS

– Not applicable

> More than

≥ More than or equal to

< Less than

% Percentage

All error bars in the figures included in this report represent 95% confidence intervals (CIs).

EXECUTIVE SUMMARY

The National Medical Care Survey (NMCS) is a provider-based survey which aims to study the characteristics and morbidity pattern of patients as well as healthcare activities in terms of investigations, procedures, counselling and visit dispositions provided at primary care level in Malaysia. NMCS 2014 covered public and private clinics from 13 states and three federal territories in Malaysia. The clinics were stratified according to sector and state and selected through random sampling. Healthcare providers from these clinics recorded details of patients they managed on the day of survey, which was randomly allocated between January and May 2014.

Primary care clinics

In NMCS 2014, a total of 129 public clinics out of 139 sampled (92.8%) and 416 private clinics out of 1,002 sampled (41.5%) responded. The survey data were weighted to produce unbiased national estimates for 664 public clinics and 4,810 private clinics in Malaysia which were staffed with medical doctors.

• The median attendance rate in public clinics was 111.5 visits per day, compared to 33.0 per day in private clinics.

• A large majority (82.8%) of public clinics operated five days per week. After-hours services (extended-hours and/or on-call services) were provided in addition to the standard-hour operation in 47.9% of public clinics.

• Most (54.0%) private clinics operated six days per week. Only 5.0% of the private clinics provided 24-hour services.

• Three-quarters (75.3%) of the private clinics were solo practices. • The median number of patients seen per full time equivalent (FTE) doctor in the private

sector was 25.9 patients per day. • Only 19.4% of public clinics had a functional computer system installed in the practice,

compared to 71.6% for private clinics. Computer system was mainly used for registration (83.7%) and medical record keeping (83.3%) purposes in the public sector and for billing purpose (79.6%) in the private sector.

• Public clinics were staffed with 26.4 health professionals on average, with a median of three doctors, six staff nurses, seven community nurses, three assistant medical officers and one pharmacist per clinic. In contrast, private practices had only 5.6 health professionals on average, with a median of one doctor and three clinic assistants in each clinic.

• Family medicine specialists (FMS) were available in 40.1% of public clinics, compared to 2.9% in the private sector.

The doctors

A total of 936 doctors participated in NMCS 2014: 490 (52.4%) from public clinics and 446 (47.6%) from private clinics. The survey responses were weighted to produce national estimates for 10,964 doctors (2,992 public and 7,972 private) working in primary care in Malaysia.

• Female doctors accounted for a higher proportion of the doctor workforce in the public sector compared to the private sector (70.5% versus 39.7%, respectively).

• The vast majority (79.9%) of the doctors in public clinics were between 25 and 34 years old, compared to only 4.2% in the private sector. In contrast, 69.9% of the doctors in private

2 National Medical Care Statistics 2014

clinics were 45 years or older, while only 6.2% of doctors in public clinics fell in the same age group.

• The majority (62.0%) of the doctors had been working in the primary care setting for 10 years or more (median: 13 years).

• Overseas trained doctors accounted for the greater proportion (51.5%) of the primary care doctor workforce.

• Nearly one-sixth (15.7%) of the doctors had at least one postgraduate qualification. Most of these doctors specialised in family medicine (87.3% in the public sector and 38.9% in the private sector).

The patients

A total of 27,587 encounters (15,470 in public clinics and 12,117 in private clinics) were captured in NMCS 2014. Post-stratification weighting translated this figure into a total of 325,818 primary care encounters: 131,624 (40.4%) in public clinics and 194,194 (59.6%) in private clinics.

• Females accounted for 53.6% of all primary care encounters. The proportions of male and female patients were similar across all age groups, except among the adult age groups (20–39 years and 40–59 years) in public clinics, for which significantly higher proportions of females were reported.

• The public clinics were utilised by a relatively older patient population compared to the private clinics. Patients aged 40–59 years accounted for the greatest proportion (30.3%) of public clinic encounters, while most (44.3%) private patients were between 20 and 39 years of age. The elderly patients constituted a significantly higher proportion of the patient population in the public sector than in the private sector (22.9% versus 9.7%, respectively).

• Malays were the largest ethnic group utilising primary care (65.6% of encounters in public clinics and 60.4% in private clinics), followed by Chinese (14.4% in public clinics and 26.1% in private clinics) and Indian patients (11.9% in public clinics and 10.0% in private clinics).

• All patient encounters in the public sector were covered by government subsidies, while most of the encounters in the private sector were paid for through out-of-pocket payments (59.7%) and third-party payments (39.1%).

• More than half (55.2%) of the patients had a monthly personal income between MYR 1,000 and MYR 2,999 (parental income excluded). In general, patients who visited private clinics had higher incomes than those who utilised public clinics.

• The vast majority (89.0%) of patients had received some form of formal education (primary to tertiary levels). In general, the level of educational attainment was higher among private patients than among those who presented to public clinics.

• Medical certificates were issued to 31.2% of patients (9.9% of patients in public clinics and 33.4% in private clinics). The duration of sick leave given ranged from 0.5 to 20 days.

Reasons for seeking treatment

A total of 597,563 patient-reported reasons for encounter (RFEs) were recorded at 325,818 encounters (252,050 RFEs in public clinics and 345,513 in private clinics), translating into an average of 183.4 RFEs per 100 patient encounters (weighted data).

• More than half (53.0%) of the patients presented with two or more RFEs per encounter. Most (61.4%) of the RFEs were expressed in terms of a symptom or complaint.

• The three most commonly recorded RFEs in public clinics were all chronic diseases: hypertension (31.3 per 100 encounters), diabetes (22.5 per 100 encounters) and lipid disorder (18.5 per 100 encounters).

• In contrast, in private clinics, patient encounters were mostly for acute complaints: fever (28.3 per 100 encounters), cough (26.5 per 100 encounters) and runny nose/rhinorrhoea (19.4 per 100 encounters).

Diagnoses managed

A total of 436,743 diagnoses were made in primary care clinics, at a rate of 134.0 diagnoses per 100 patient encounters (weighted data).

• More diagnoses were managed overall at encounters in public clinics (154.9 diagnoses per 100 encounters) than in private clinics (119.9 diagnoses per 100 encounters).

• Only a single diagnosis was managed at 75.2% of the encounters (63.0% of encounters in public clinics and 83.5% in private clinics).

• The number of diagnoses increased with patient age for both sectors, with the increase being more pronounced in the public sector, especially for age groups over 40 years.

• More than three-quarters (77.9%) of diagnoses were recorded as diagnoses or diseases; only 16.6% remained undiagnosed symptoms or complaints.

• The three most frequently managed diagnoses in public clinics were non-communicable diseases: hypertension (33.1 per 100 encounters), diabetes (23.4 per 100 encounters) and lipid disorder (22.1 per 100 encounters). These chronic illnesses were managed at much lower rates in private clinics (6.5, 3.0 and 2.9 diagnoses per 100 encounters, respectively).

• By comparison, majority of the cases managed by private primary care providers were acute illnesses. The most common diagnoses in private clinics were upper respiratory tract infections (22.7% of all diagnoses in private clinics and 27.2 per 100 encounters), hypertension (6.5 per 100 encounters) and gastroenteritis (5.4 per 100 encounters).

Medications prescribed

A total of 864,552 medications were recorded, at rates of 265.3 medications per 100 encounters and 198.0 medications per 100 diagnoses (weighted data).

• Medications were prescribed for 89.9% of all encounters (86.7% of encounters in public clinics and 92.1% in private clinics).

• The medication prescribing rates were higher in the private sector (276.8 medications per 100 encounters and 230.8 per 100 diagnoses) than in the public sector (248.5 per 100 encounters and 160.4 per 100 diagnoses).

• Nearly 60% of the encounters in private clinics were prescribed with three or more medications, compared to 45.8% in the public sector.

• The prescription rates were higher in the private sector for patients who were less than 40 years old compared to those in the public sector regardless of gender. The trends were reversed for patients aged 40 years and above for both genders.

• The top three classes of medications prescribed in public clinics were cardiovascular agents (34.1%), alimentary tract and metabolism agents (24.7%) and respiratory agents (14.1%), while those most frequently prescribed in private clinics were respiratory agents (27.4%), alimentary tract and metabolism agents (17.4%) and musculoskeletal medications (15.5%).

• Seven out of the 10 most commonly prescribed medications in public clinics were for chronic diseases (amlodipine, lovastatin, metformin, perindopril, gliclazide, hydrochlorothiazide and simvastatin), accounting for 35.2% of all medications prescribed in public clinics. The three medications for acute conditions in the list were paracetamol, chlorphenamine and diphenhydramine.

3

clinics were 45 years or older, while only 6.2% of doctors in public clinics fell in the same age group.

• The majority (62.0%) of the doctors had been working in the primary care setting for 10 years or more (median: 13 years).

• Overseas trained doctors accounted for the greater proportion (51.5%) of the primary care doctor workforce.

• Nearly one-sixth (15.7%) of the doctors had at least one postgraduate qualification. Most of these doctors specialised in family medicine (87.3% in the public sector and 38.9% in the private sector).

The patients


• Females accounted for 53.6% of all primary care encounters. The proportions of male and female patients were similar across all age groups, except among the adult age groups (20–39 years and 40–59 years) in public clinics, for which significantly higher proportions of females were reported.

• The public clinics were utilised by a relatively older patient population compared to the private clinics. Patients aged 40–59 years accounted for the greatest proportion (30.3%) of public clinic encounters, while most (44.3%) private patients were between 20 and 39 years of age. The elderly patients constituted a significantly higher proportion of the patient population in the public sector than in the private sector (22.9% versus 9.7%, respectively).

• Malays were the largest ethnic group utilising primary care (65.6% of encounters in public clinics and 60.4% in private clinics), followed by Chinese (14.4% in public clinics and 26.1% in private clinics) and Indian patients (11.9% in public clinics and 10.0% in private clinics).

• All patient encounters in the public sector were covered by government subsidies, while most of the encounters in the private sector were paid for through out-of-pocket payments (59.7%) and third-party payments (39.1%).

• More than half (55.2%) of the patients had a monthly personal income between MYR 1,000 and MYR 2,999 (parental income excluded). In general, patients who visited private clinics had higher incomes than those who utilised public clinics.

• The vast majority (89.0%) of patients had received some form of formal education (primary to tertiary levels). In general, the level of educational attainment was higher among private patients than among those who presented to public clinics.

• Medical certificates were issued to 31.2% of patients (9.9% of patients in public clinics and 33.4% in private clinics). The duration of sick leave given ranged from 0.5 to 20 days.

Reasons for seeking treatment

A total of 597,563 patient-reported reasons for encounter (RFEs) were recorded at 325,818 encounters (252,050 RFEs in public clinics and 345,513 in private clinics), translating into an average of 183.4 RFEs per 100 patient encounters (weighted data).

• More than half (53.0%) of the patients presented with two or more RFEs per encounter. Most (61.4%) of the RFEs were expressed in terms of a symptom or complaint.

• The three most commonly recorded RFEs in public clinics were all chronic diseases: hypertension (31.3 per 100 encounters), diabetes (22.5 per 100 encounters) and lipid disorder (18.5 per 100 encounters).

• In contrast, in private clinics, patient encounters were mostly for acute complaints: fever (28.3 per 100 encounters), cough (26.5 per 100 encounters) and runny nose/rhinorrhoea (19.4 per 100 encounters).

Diagnoses managed

A total of 436,743 diagnoses were made in primary care clinics, at a rate of 134.0 diagnoses per 100 patient encounters (weighted data).

• More diagnoses were managed overall at encounters in public clinics (154.9 diagnoses per 100 encounters) than in private clinics (119.9 diagnoses per 100 encounters).

• Only a single diagnosis was managed at 75.2% of the encounters (63.0% of encounters in public clinics and 83.5% in private clinics).

• The number of diagnoses increased with patient age for both sectors, with the increase being more pronounced in the public sector, especially for age groups over 40 years.

• More than three-quarters (77.9%) of diagnoses were recorded as diagnoses or diseases; only 16.6% remained undiagnosed symptoms or complaints.

• The three most frequently managed diagnoses in public clinics were non-communicable diseases: hypertension (33.1 per 100 encounters), diabetes (23.4 per 100 encounters) and lipid disorder (22.1 per 100 encounters). These chronic illnesses were managed at much lower rates in private clinics (6.5, 3.0 and 2.9 diagnoses per 100 encounters, respectively).

• By comparison, majority of the cases managed by private primary care providers were acute illnesses. The most common diagnoses in private clinics were upper respiratory tract infections (22.7% of all diagnoses in private clinics and 27.2 per 100 encounters), hypertension (6.5 per 100 encounters) and gastroenteritis (5.4 per 100 encounters).

Medications prescribed

A total of 864,552 medications were recorded, at rates of 265.3 medications per 100 encounters and 198.0 medications per 100 diagnoses (weighted data).

• Medications were prescribed for 89.9% of all encounters (86.7% of encounters in public clinics and 92.1% in private clinics).

• The medication prescribing rates were higher in the private sector (276.8 medications per 100 encounters and 230.8 per 100 diagnoses) than in the public sector (248.5 per 100 encounters and 160.4 per 100 diagnoses).


• The prescription rates were higher in the private sector for patients who were less than 40 years old compared to those in the public sector regardless of gender. The trends were reversed for patients aged 40 years and above for both genders.

• The top three classes of medications prescribed in public clinics were cardiovascular agents (34.1%), alimentary tract and metabolism agents (24.7%) and respiratory agents (14.1%), while those most frequently prescribed in private clinics were respiratory agents (27.4%), alimentary tract and metabolism agents (17.4%) and musculoskeletal medications (15.5%).

• Seven out of the 10 most commonly prescribed medications in public clinics were for chronic diseases (amlodipine, lovastatin, metformin, perindopril, gliclazide, hydrochlorothiazide and simvastatin), accounting for 35.2% of all medications prescribed in public clinics. The three medications for acute conditions in the list were paracetamol, chlorphenamine and diphenhydramine.


• In contrast, the 10 most frequently prescribed medications in private clinics were all medications for acute conditions (paracetamol, diclofenac, diphenhydramine, chlorphenamine, mefenamic acid, butylscopolamine, amoxicillin, pseudoephedrine, cetirizine and prednisolone).

Investigations ordered

Of all 325,818 primary care encounters, 22.6% had investigations ordered (39.6% in public clinics and 11.1% in private clinics). A total of 143,758 orders for investigations were recorded, at rates of 44.1 per 100 encounters and 32.9 per 100 diagnoses (weighted data).

• The ordering rates of investigations were much higher in public clinics (82.5 investigations per 100 encounters and 53.2 per 100 diagnoses) than in private clinics (18.1 per 100 encounters and 15.1 per 100 diagnoses).

• Majority (82.0%) of the investigations recorded were pathological/laboratory tests. Diagnostic radiology/imaging test constituted 9.3% of all investigations.

• Chemistry tests accounted for 55.8% of all investigations and 68.0% of all laboratory tests ordered. The most common chemistry tests ordered were glucose tests (7.6 per 100 encounters); tests for electrolytes, urea and creatinine (4.5 per 100 encounters); and lipid tests (4.5 per 100 encounters).

• Glucose and/or glucose tolerance test was the most frequently ordered individual investigation in both public and private sectors (15.1 per 100 encounters in public clinics and 2.5 per 100 encounters in private clinics).

• Diabetes, hypertension and lipid disorder were the most common diagnoses for which investigations were ordered. Together, these three chronic diseases represented half (49.9%) of all diagnoses for which investigations were ordered.

Advice/counselling and procedures

A total of 111,707 advice/counselling (34.3 per 100 encounters and 25.6 per 100 diagnoses) and 25,001 procedures (7.7 per 100 encounters and 5.7 per 100 diagnoses) were provided by primary care providers (weighted data).

• Out of the 325,818 encounters recorded, 24.5% were managed with at least one form of advice/counselling (37.5% in public clinics and 15.6% in private clinics), and 6.9% had some procedures performed at the time of visit (5.0% in public clinics and 8.2% in private clinics).

• The top three most frequently provided types of advice/counselling were general advice/education, advice/counselling on nutrition or weight management, and advice/counselling on lifestyle. Together, these accounted for 72.9% of all advice and counselling provided in primary care clinics.

• Injection/infiltration was the most common procedure performed and accounted for 27.9% of all procedures performed in primary care clinics, followed by procedure for dressing, pressure or compression of wounds at 21.4%.

• Advice/counselling and procedures were provided as part of the patient management for 23.5% and 5.0% of all diagnoses, respectively. The most common diagnoses managed with advice and counselling were hypertension (20.6% of all diagnoses managed with advice and counselling), diabetes (18.5%) and lipid disorder (13.9%), while asthma (8.5%), musculoskeletal symptoms or complaints (5.4%) and skin laceration/cut (5.4%) were the three diagnoses most frequently managed with a procedure.

Follow-ups and referrals

About one-third (29.7%) of the patients presenting to primary care had a referral or follow-up appointment (weighted data). Follow-up appointments were scheduled for 89,641 patients (27.5 per 100 encounters and 20.5 per 100 diagnoses), while referrals were issued for 11,068 patients (3.4 per 100 encounters and 2.5 per 100 diagnoses).

• Both follow-up rate and referrals rate were higher in the public sector compared to the private sector (49.2% versus 12.9% and 5.8% versus 1.8%, respectively).

• Referrals in public clinics were most often to medical specialists (34.0% of all referrals in public clinics, 2.0 per 100 encounters), followed by referrals within primary care (1.3 per 100 encounters) and those to hospitals (1.3 per 100 encounters).

• Nearly half (47.7%) of all referrals recorded in the private sector were for medical specialists (0.8 per 100 encounters), while hospital referrals constituted most of the other half (41.1%).

• The leading diagnoses for follow-up were hypertension (28.5% of all diagnoses with follow-up appointments), diabetes (20.2%) and lipid disorder (18.5%). These three chronic diseases were also the three most commonly referred diagnoses (diabetes: 11.9%, hypertension: 10.2%, lipid disorder: 5.3%).

Differences in primary care activities since NMCS 2012

The data presented in this report are by far the most comprehensive and detailed information on healthcare activities of both public and private primary care clinics in Malaysia. These data confirm and extend the findings of the previous NMCS, which was conducted in three states and two regions in 2012. The findings of both NMCS 2012 and NMCS 2014 are largely similar. The major changes are summarised below. Note that the classification of advice/counselling, procedures, follow-ups and referrals followed different approaches in the two surveys, and direct comparisons could not therefore be made for these primary care activities.

• Antenatal check-up was the fourth most common RFE recorded in public clinics in 2012, accounting for 18.0% of all RFEs in public clinics. In 2014, antenatal examination represented only 9.3% of all RFEs in public clinics, ranking seventh among the top RFEs recorded in the public sector.

• Metformin was the second most frequently prescribed medications (17.1 per 100 encounters) in the public sector in 2012, followed by amlodipine (15.9 per 100 encounters) and lovastatin (14.8 per 100 encounters). In NMCS 2014, higher prescribing rates were recorded for all three medications, but the rates of increment were higher for amlodipine and lovastatin. As a result, amlodipine had become the second most frequently prescribed medication (20.0 per 100 encounters) in public clinics in 2014, followed by lovastatin (17.5 per 100 encounters) and metformin (17.4 per 100 encounters).

• The ordering rate for obstetric ultrasonography in public clinics had dropped from 9.2 per 100 encounters in 2012 to 3.2 per 100 encounters in 2014. This corresponds with the reduced number of antenatal encounters seen in public clinics in 2014.

• In private clinics, lipid profile test was ordered more frequently in 2014 than in 2012 (1.8 per 100 encounters versus 0.6 per 100 encounters, respectively). An opposite trend was observed for the ordering rate of chest x-ray, which declined from 2.2 per 100 encounters in 2012 to 0.7 per 100 encounters in 2014.

5

• In contrast, the 10 most frequently prescribed medications in private clinics were all medications for acute conditions (paracetamol, diclofenac, diphenhydramine, chlorphenamine, mefenamic acid, butylscopolamine, amoxicillin, pseudoephedrine, cetirizine and prednisolone).

Investigations ordered

Of all 325,818 primary care encounters, 22.6% had investigations ordered (39.6% in public clinics and 11.1% in private clinics). A total of 143,758 orders for investigations were recorded, at rates of 44.1 per 100 encounters and 32.9 per 100 diagnoses (weighted data).

• The ordering rates of investigations were much higher in public clinics (82.5 investigations per 100 encounters and 53.2 per 100 diagnoses) than in private clinics (18.1 per 100 encounters and 15.1 per 100 diagnoses).

• Majority (82.0%) of the investigations recorded were pathological/laboratory tests. Diagnostic radiology/imaging test constituted 9.3% of all investigations.

• Chemistry tests accounted for 55.8% of all investigations and 68.0% of all laboratory tests ordered. The most common chemistry tests ordered were glucose tests (7.6 per 100 encounters); tests for electrolytes, urea and creatinine (4.5 per 100 encounters); and lipid tests (4.5 per 100 encounters).

• Glucose and/or glucose tolerance test was the most frequently ordered individual investigation in both public and private sectors (15.1 per 100 encounters in public clinics and 2.5 per 100 encounters in private clinics).

• Diabetes, hypertension and lipid disorder were the most common diagnoses for which investigations were ordered. Together, these three chronic diseases represented half (49.9%) of all diagnoses for which investigations were ordered.

Advice/counselling and procedures

A total of 111,707 advice/counselling (34.3 per 100 encounters and 25.6 per 100 diagnoses) and 25,001 procedures (7.7 per 100 encounters and 5.7 per 100 diagnoses) were provided by primary care providers (weighted data).

• Out of the 325,818 encounters recorded, 24.5% were managed with at least one form of advice/counselling (37.5% in public clinics and 15.6% in private clinics), and 6.9% had some procedures performed at the time of visit (5.0% in public clinics and 8.2% in private clinics).

• The top three most frequently provided types of advice/counselling were general advice/education, advice/counselling on nutrition or weight management, and advice/counselling on lifestyle. Together, these accounted for 72.9% of all advice and counselling provided in primary care clinics.

• Injection/infiltration was the most common procedure performed and accounted for 27.9% of all procedures performed in primary care clinics, followed by procedure for dressing, pressure or compression of wounds at 21.4%.

• Advice/counselling and procedures were provided as part of the patient management for 23.5% and 5.0% of all diagnoses, respectively. The most common diagnoses managed with advice and counselling were hypertension (20.6% of all diagnoses managed with advice and counselling), diabetes (18.5%) and lipid disorder (13.9%), while asthma (8.5%), musculoskeletal symptoms or complaints (5.4%) and skin laceration/cut (5.4%) were the three diagnoses most frequently managed with a procedure.

Follow-ups and referrals

About one-third (29.7%) of the patients presenting to primary care had a referral or follow-up appointment (weighted data). Follow-up appointments were scheduled for 89,641 patients (27.5 per 100 encounters and 20.5 per 100 diagnoses), while referrals were issued for 11,068 patients (3.4 per 100 encounters and 2.5 per 100 diagnoses).

• Both follow-up rate and referrals rate were higher in the public sector compared to the private sector (49.2% versus 12.9% and 5.8% versus 1.8%, respectively).

• Referrals in public clinics were most often to medical specialists (34.0% of all referrals in public clinics, 2.0 per 100 encounters), followed by referrals within primary care (1.3 per 100 encounters) and those to hospitals (1.3 per 100 encounters).

• Nearly half (47.7%) of all referrals recorded in the private sector were for medical specialists (0.8 per 100 encounters), while hospital referrals constituted most of the other half (41.1%).

• The leading diagnoses for follow-up were hypertension (28.5% of all diagnoses with follow-up appointments), diabetes (20.2%) and lipid disorder (18.5%). These three chronic diseases were also the three most commonly referred diagnoses (diabetes: 11.9%, hypertension: 10.2%, lipid disorder: 5.3%).

Differences in primary care activities since NMCS 2012

The data presented in this report are by far the most comprehensive and detailed information on healthcare activities of both public and private primary care clinics in Malaysia. These data confirm and extend the findings of the previous NMCS, which was conducted in three states and two regions in 2012. The findings of both NMCS 2012 and NMCS 2014 are largely similar. The major changes are summarised below. Note that the classification of advice/counselling, procedures, follow-ups and referrals followed different approaches in the two surveys, and direct comparisons could not therefore be made for these primary care activities.

• Antenatal check-up was the fourth most common RFE recorded in public clinics in 2012, accounting for 18.0% of all RFEs in public clinics. In 2014, antenatal examination represented only 9.3% of all RFEs in public clinics, ranking seventh among the top RFEs recorded in the public sector.

• Metformin was the second most frequently prescribed medications (17.1 per 100 encounters) in the public sector in 2012, followed by amlodipine (15.9 per 100 encounters) and lovastatin (14.8 per 100 encounters). In NMCS 2014, higher prescribing rates were recorded for all three medications, but the rates of increment were higher for amlodipine and lovastatin. As a result, amlodipine had become the second most frequently prescribed medication (20.0 per 100 encounters) in public clinics in 2014, followed by lovastatin (17.5 per 100 encounters) and metformin (17.4 per 100 encounters).

• The ordering rate for obstetric ultrasonography in public clinics had dropped from 9.2 per 100 encounters in 2012 to 3.2 per 100 encounters in 2014. This corresponds with the reduced number of antenatal encounters seen in public clinics in 2014.

• In private clinics, lipid profile test was ordered more frequently in 2014 than in 2012 (1.8 per 100 encounters versus 0.6 per 100 encounters, respectively). An opposite trend was observed for the ordering rate of chest x-ray, which declined from 2.2 per 100 encounters in 2012 to 0.7 per 100 encounters in 2014.

CHAPTER oneIntroduction


Specific objectives

To collect information on clinical activities in primary care setting in Malaysia, including:

• The characteristics of patients seen • Mode of payment for primary care services • Reasons people seek medical care • Problems managed, and for each problem managed:

o Pharmacological treatment prescribed, including the dose and frequency o Non-pharmacological treatment provided, including procedures and counselling o Investigations ordered, including pathology and imaging o Follow up in primary care and referrals to secondary or tertiary care o Issuance of medical certificate and duration of sick leave

1.3 DEFINITIONS

Definitions of primary care were adapted from the American Association of Family Physicians.4 The few terms that were taken are:

a) Primary care – The care provided by physicians specifically trained for and skilled in comprehensive first

contact and continuing care for persons with any undiagnosed sign, symptom, or health concern (the "undifferentiated" patient) not limited by problem origin (biological, behavioural, or social), organ system, or diagnosis.

– The care involved includes health promotion, disease prevention, health maintenance, counselling, patient education, diagnosis and treatment of acute and chronic illnesses in a variety of healthcare settings (e.g., office, inpatient, critical care, long-term care, home care, day care, etc.). Primary care is performed and managed by a personal physician, often collaborating with other health professionals and utilising consultation or referral as appropriate.

b) Primary care setting – Primary care setting serves as the patient's first point of entry into the healthcare system and

as the continuing focal point for all needed healthcare services. Primary care practices provide patients with ready access to their own personal physician or to an established back-up physician when the primary physician is not available.

c) Primary care doctors – Medical doctors or family medicine specialists (FMS) who provide primary care in the primary

care setting.

Primary healthcare in Malaysia is provided by both public and private healthcare providers. Government clinics (Klinik Kesihatan) are funded by the government, while the private sector provides services on a fee-for-service basis. In this report, the terms ‘public clinics’ and ‘private clinics’ are used to describe these two types of primary care clinics.

CHAPTER 1: INTRODUCTION

1.1 BACKGROUND

The National Healthcare Statistics Initiative (NHSI) is a family of surveys which aims to support evidence-based health policy-making and research in Malaysia. It was initiated in 2009 by the Healthcare Statistics Unit (HSU) of the National Clinical Research Centre (NCRC) in collaborations with various stakeholders. Over the past six years, the NHSI has grown and managed to gain local and international recognition due to the usefulness of its reliable and timely data, which fill in the gap between research and policy. Annual reports are published for the surveys under NHSI.

As one of the four members of NHSI, the National Medical Care Survey (NMCS) was first launched in 2010 and had its fair share of challenges. After consulting local and international researchers as well as stakeholders, a pilot study was conducted in 2012. The continued support from the Family Medicine Research Centre team at the University of Sydney in Australia, which conducts a series of primary care research under the Bettering the Evaluation and Care of Health (BEACH) program,1 has been a major contributing factor to NMCS. In addition, the revised methodology and an able steering Research Evaluation Committee had ensured the success of NMCS 2012.

The questionnaire for NMCS 2014 was adapted from BEACH and NMCS 2012. Validation was done before proceeding with the improved forms for the 2014 project. The valuable information and experience gained from NMCS 2012 contributed tremendously to the improvement of methodology, data collection strategies and analysis methods for NMCS 2014.

While the NMCS 2012 was a pilot study that involved only three states and two regions, the NMCS 2014 was conducted at national level. In fact, NMCS 2014 is the first nationwide study on public and private primary care in Malaysia, where public and private clinics were randomly sampled from all 13 states and three federal territories to be included in the survey. At the national level, NMCS 2014 is providing information to the National Strategic Plan for Non-Communicable Disease (NSPNCD) 2010–2014 and the Malaysian Health System Reform (MHSR) research on the clinical management of diseases and utilisation pattern in primary care settings.2,3

1.2 OBJECTIVES

General objectives

1. To collect reliable and valid data in primary care setting. 2. To examine patient characteristics and utilisation pattern and the relationship these factors have

with health service activities. 3. To provide accurate and timely data to various stakeholders, including government bodies, primary

care practitioners, consumers, researchers and the pharmaceutical industry. 4. To establish an on-going database of doctor-patient encounter information.

9Chapter 1 : Introduction

Specific objectives

To collect information on clinical activities in primary care setting in Malaysia, including:

• The characteristics of patients seen • Mode of payment for primary care services • Reasons people seek medical care • Problems managed, and for each problem managed:

o Pharmacological treatment prescribed, including the dose and frequency o Non-pharmacological treatment provided, including procedures and counselling o Investigations ordered, including pathology and imaging o Follow up in primary care and referrals to secondary or tertiary care o Issuance of medical certificate and duration of sick leave

1.3 DEFINITIONS

Definitions of primary care were adapted from the American Association of Family Physicians.4 The few terms that were taken are:

a) Primary care – The care provided by physicians specifically trained for and skilled in comprehensive first

contact and continuing care for persons with any undiagnosed sign, symptom, or health concern (the "undifferentiated" patient) not limited by problem origin (biological, behavioural, or social), organ system, or diagnosis.

– The care involved includes health promotion, disease prevention, health maintenance, counselling, patient education, diagnosis and treatment of acute and chronic illnesses in a variety of healthcare settings (e.g., office, inpatient, critical care, long-term care, home care, day care, etc.). Primary care is performed and managed by a personal physician, often collaborating with other health professionals and utilising consultation or referral as appropriate.

b) Primary care setting – Primary care setting serves as the patient's first point of entry into the healthcare system and

as the continuing focal point for all needed healthcare services. Primary care practices provide patients with ready access to their own personal physician or to an established back-up physician when the primary physician is not available.

c) Primary care doctors – Medical doctors or family medicine specialists (FMS) who provide primary care in the primary

care setting.

Primary healthcare in Malaysia is provided by both public and private healthcare providers. Government clinics (Klinik Kesihatan) are funded by the government, while the private sector provides services on a fee-for-service basis. In this report, the terms ‘public clinics’ and ‘private clinics’ are used to describe these two types of primary care clinics.

CHAPTER 1: INTRODUCTION

1.1 BACKGROUND

The National Healthcare Statistics Initiative (NHSI) is a family of surveys which aims to support evidence-based health policy-making and research in Malaysia. It was initiated in 2009 by the Healthcare Statistics Unit (HSU) of the National Clinical Research Centre (NCRC) in collaborations with various stakeholders. Over the past six years, the NHSI has grown and managed to gain local and international recognition due to the usefulness of its reliable and timely data, which fill in the gap between research and policy. Annual reports are published for the surveys under NHSI.

As one of the four members of NHSI, the National Medical Care Survey (NMCS) was first launched in 2010 and had its fair share of challenges. After consulting local and international researchers as well as stakeholders, a pilot study was conducted in 2012. The continued support from the Family Medicine Research Centre team at the University of Sydney in Australia, which conducts a series of primary care research under the Bettering the Evaluation and Care of Health (BEACH) program,1 has been a major contributing factor to NMCS. In addition, the revised methodology and an able steering Research Evaluation Committee had ensured the success of NMCS 2012.

The questionnaire for NMCS 2014 was adapted from BEACH and NMCS 2012. Validation was done before proceeding with the improved forms for the 2014 project. The valuable information and experience gained from NMCS 2012 contributed tremendously to the improvement of methodology, data collection strategies and analysis methods for NMCS 2014.

While the NMCS 2012 was a pilot study that involved only three states and two regions, the NMCS 2014 was conducted at national level. In fact, NMCS 2014 is the first nationwide study on public and private primary care in Malaysia, where public and private clinics were randomly sampled from all 13 states and three federal territories to be included in the survey. At the national level, NMCS 2014 is providing information to the National Strategic Plan for Non-Communicable Disease (NSPNCD) 2010–2014 and the Malaysian Health System Reform (MHSR) research on the clinical management of diseases and utilisation pattern in primary care settings.2,3

1.2 OBJECTIVES

General objectives

1. To collect reliable and valid data in primary care setting. 2. To examine patient characteristics and utilisation pattern and the relationship these factors have

with health service activities. 3. To provide accurate and timely data to various stakeholders, including government bodies, primary

care practitioners, consumers, researchers and the pharmaceutical industry. 4. To establish an on-going database of doctor-patient encounter information.


1.4 RESEARCH QUESTIONS

No. Question Answered by

1 What types of patients are seen by primary care practitioners? Demographic characteristics

2 What is the source of payment for primary care services? Mode of payment

3 What motivates patients to seek care in the primary care setting? Patient’s reasons for visit

4 What are the actual diagnoses/problems managed by primary care practitioners? Doctor’s diagnosis/problems managed

5 What are the pharmacological treatments prescribed by primary care practitioners for each diagnosis? Pharmacological interventions

6 What are the procedures and imaging ordered by primary care practitioners for the diagnoses/problems? Non-pharmacological interventions

7 What types of counselling are offered by primary care practitioners for the diagnoses/problems? Non-pharmacological interventions

8 Is there any continuity of care in primary care setting? Referrals/follow-up

9 What is the extent of the loss of productivity for the morbidities in primary care setting?

Medical certificate (MC) and duration of sick leave

10 What are the characteristics of the primary care providers seeing the patients? Providers’ characteristics

11 What are the characteristics of the clinics the patients visit in primary care? Clinic establishments and workforce

All research questions are addressed in this report. While most questions are reported in a chapter of its own, some related questions are discussed together within relevant chapters.

REFERENCES

1. Bettering the Evaluation and Care of Health (BEACH) [Internet]. Sydney (Australia): University of Sydney, Family Medicine Research Centre; c2002-2015 [updated 2015 Sep 15, cited 2015 Oct 12]; [about 1 screen]. Available from: http://sydney.edu.au/medicine/fmrc/beach/index.php

2. Ministry of Health Malaysia. National Strategic Plan for Non-Communicable Disease (NSPNCD): medium term strategic plan to further strengthen the cardiovascular diseases & diabetes prevention & control program in Malaysia (2010–2014). Putrajaya (Malaysia): Ministry of Health Malaysia, Disease Control Division; 2010. 40 p.

3. Malaysia Health Systems Research Study [Internet]. Boston (MA): Harvard T.H. Chan School of Public Health; [cited 2015 Oct 12]; [about 3 screens]. Available from: http://www.hsph.harvard.edu/global-health-systems-cluster/projects/malaysia-health-systems-reform/

4. American Association of Family Physicians (AAFP). Primary Care [Internet]. Leadwood (KS): American Association of Family Physicians; [cited 2015 Mar 23]; [about 4 screens]. Available from: http://www.aafp.org/online/en/home/policy/policies/p/primarycare.html
















REFERENCES





1.4 Research Questions















REFERENCES



3. Malaysia Health Systems Research Study [Internet]. Boston (MA): Harvard T.H. Chan School of Public Health; [cited 2015 Oct 12]; [about 3 screens]. Available from: http://www.hsph. harvard.edu/global-health-systems-cluster/projects/malaysia-health-systems-reform/

4. American Association of Family Physicians (AAFP). Primary Care [Internet]. Leadwood (KS): American Association of Family Physicians; [cited 2015 Mar 23]; [about 4 screens]. Available from: http://www.aafp.org/online/en/home/policy/policies/p/primarycare.htm

CHAPTER twoMethodology
















REFERENCES




















REFERENCES





1.4 Research Questions















REFERENCES



3. Malaysia Health Systems Research Study [Internet]. Boston (MA): Harvard T.H. Chan School of Public Health; [cited 2015 Oct 12]; [about 3 screens]. Available from: http://www.hsph. harvard.edu/global-health-systems-cluster/projects/malaysia-health-systems-reform/

4. American Association of Family Physicians (AAFP). Primary Care [Internet]. Leadwood (KS): American Association of Family Physicians; [cited 2015 Mar 23]; [about 4 screens]. Available from: http://www.aafp.org/online/en/home/policy/policies/p/primarycare.htm


CHAPTER 2: METHODOLOGY

The 2014 National Medical Care Survey (NMCS) is a national cross-sectional study of primary care activities. It utilised a multi-stage stratified cluster sampling design, with the primary care clinics acting as primary sampling units (PSUs). Random sampling of primary care clinics was performed for all states and federal territories in Malaysia, namely, Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah, Sarawak, Selangor, Terengganu and Wilayah Persekutuan (WP) Kuala Lumpur. Two federal territories were combined with the neighbouring states (WP Labuan with Sabah and WP Putrajaya with Selangor) in view of the geographical proximity and demographic similarities.

The data collection lasted 17 weeks, from 7 January 2014 to 15 May 2014. All sampled clinics were randomly allocated one day for data recording in their respective clinics, and all service providers working on that particular day were involved in data collection.

2.1 SAMPLE SIZE CALCULATION AND SAMPLING METHODS

Ideally, we would like to randomly sample the units of analysis which are the encounters; however this is not feasible in our current system. The reasons being we do not have an exhaustive list of primary care patients and it would not be practical, financially and logistically, to sample patients from all over the country. Hence the sampling could only be done via the clinics which act as a cluster of encounters. The cluster effect of such sampling method will be adjusted in the analysis using statistical programme.

Sample size calculation

The number of encounters needed for the NMCS 2014 was first determined for each sector based on the formula proposed by Cochran1 by using the proportion of upper respiratory tract infection encounters from NMCS 2010. This number was then adjusted for the design effect (assumed to be 2) and expected response rate from each sector.

Subsequently, the adjusted number of encounters was proportionately distributed to each state and by using the average number of doctors per clinic and the average number of encounters per doctor from NHEWS Primary Care 2010, the number of clinics to be sampled for each stratum was calculated. We expected a minimum of 30 encounters from each clinic.

The final sample consisted of 139 public clinics and 1,002 private clinics (Table 2.1.1). For Melaka and Perlis, all public clinics were sampled because the total number of clinics in these strata was less than 30, the minimum acceptable sample size for each stratum.2

Table 2.1.1: Sample size (primary sampling units) for NMCS 2014

State/federal territory Public

Private

Population Sample

Population Sample

Johor 93 11

709 117

Kedah 56 7

298 55

Kelantan 64 7

192 45

Melaka 29 26

186 31

Negeri Sembilan 46 6

233 40

Pahang 79 6

201 42

Perak 83 11

510 73

Perlis 9 9

30 10

Pulau Pinang 30 5

398 70

Sabah & WP Labuan 92 9

311 65

Sarawak 196 10

225 34

Selangor & WP Putrajaya 76 15

1,520 270

Terengganu 45 5

148 30

WP Kuala Lumpur 13 12

685 120

Total 911 139 5,646 1,002

Sampling methods

The sampling frame of public and private clinics was generated by matching the list of clinics from National Healthcare Establishments and Workforce Survey (NHEWS) 2012 with several sources:

• The list of public clinics (Klinik Kesihatan) from the Family Health Development Division, Ministry of Health (MOH) Malaysia.

• The list of registered private clinics from the Private Medical Practice Division, Ministry of Health Malaysia (often referred to as the Cawangan Kawalan Amalan Perubatan Swasta (CKAPS).

Both lists were updated as of 31st December 2012 and these were regarded as the most recent lists of the public and private clinics at the period of survey.

As for clinics that were not matched from the lists, subsequent verification by telephone calls was done to determine the existence or current operational status of the establishments. Those that were found to be closed or do not meet our inclusion and exclusion criteria were removed from the sampling frame (Table 2.1.2).

13Chapter 2 : Methodology

CHAPTER 2: METHODOLOGY

The 2014 National Medical Care Survey (NMCS) is a national cross-sectional study of primary care activities. It utilised a multi-stage stratified cluster sampling design, with the primary care clinics acting as primary sampling units (PSUs). Random sampling of primary care clinics was performed for all states and federal territories in Malaysia, namely, Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah, Sarawak, Selangor, Terengganu and Wilayah Persekutuan (WP) Kuala Lumpur. Two federal territories were combined with the neighbouring states (WP Labuan with Sabah and WP Putrajaya with Selangor) in view of the geographical proximity and demographic similarities.

The data collection lasted 17 weeks, from 7 January 2014 to 15 May 2014. All sampled clinics were randomly allocated one day for data recording in their respective clinics, and all service providers working on that particular day were involved in data collection.

2.1 SAMPLE SIZE CALCULATION AND SAMPLING METHODS

Ideally, we would like to randomly sample the units of analysis which are the encounters; however this is not feasible in our current system. The reasons being we do not have an exhaustive list of primary care patients and it would not be practical, financially and logistically, to sample patients from all over the country. Hence the sampling could only be done via the clinics which act as a cluster of encounters. The cluster effect of such sampling method will be adjusted in the analysis using statistical programme.

Sample size calculation

The number of encounters needed for the NMCS 2014 was first determined for each sector based on the formula proposed by Cochran1 by using the proportion of upper respiratory tract infection encounters from NMCS 2010. This number was then adjusted for the design effect (assumed to be 2) and expected response rate from each sector.

Subsequently, the adjusted number of encounters was proportionately distributed to each state and by using the average number of doctors per clinic and the average number of encounters per doctor from NHEWS Primary Care 2010, the number of clinics to be sampled for each stratum was calculated. We expected a minimum of 30 encounters from each clinic.

The final sample consisted of 139 public clinics and 1,002 private clinics (Table 2.1.1). For Melaka and Perlis, all public clinics were sampled because the total number of clinics in these strata was less than 30, the minimum acceptable sample size for each stratum.2

Table 2.1.1: Sample size (primary sampling units) for NMCS 2014

State/federal territory Public

Private

Population Sample

Population Sample

Johor 93 11

709 117

Kedah 56 7

298 55

Kelantan 64 7

192 45

Melaka 29 26

186 31

Negeri Sembilan 46 6

233 40

Pahang 79 6

201 42

Perak 83 11

510 73

Perlis 9 9

30 10

Pulau Pinang 30 5

398 70

Sabah & WP Labuan 92 9

311 65

Sarawak 196 10

225 34

Selangor & WP Putrajaya 76 15

1,520 270

Terengganu 45 5

148 30

WP Kuala Lumpur 13 12

685 120

Total 911 139 5,646 1,002

Sampling methods

The sampling frame of public and private clinics was generated by matching the list of clinics from National Healthcare Establishments and Workforce Survey (NHEWS) 2012 with several sources:

• The list of public clinics (Klinik Kesihatan) from the Family Health Development Division, Ministry of Health (MOH) Malaysia.

• The list of registered private clinics from the Private Medical Practice Division, Ministry of Health Malaysia (often referred to as the Cawangan Kawalan Amalan Perubatan Swasta (CKAPS).

Both lists were updated as of 31st December 2012 and these were regarded as the most recent lists of the public and private clinics at the period of survey.

As for clinics that were not matched from the lists, subsequent verification by telephone calls was done to determine the existence or current operational status of the establishments. Those that were found to be closed or do not meet our inclusion and exclusion criteria were removed from the sampling frame (Table 2.1.2).


Table 2.1.2: Inclusion and exclusion criteria for the clinics sampled in the survey

Inclusion criteria • MOH Health Clinics (Klinik Kesihatan) which provide primary care services

• Private medical clinics registered with CKAPS and provide primary care services

Exclusion criteria • Outpatient departments within hospital or maternity homes

• Public clinics with the following criteria:

– Health clinics without permanent medical doctors (Klinik Kesihatan)

– Clinics which provide only maternal and child health services (Klinik Kesihatan Ibu dan Anak)

– Rural health clinics (Klinik Desa)

– 1 Malaysia clinics

• Private clinics with the following criteria:

– Aesthetic clinics

– Charity clinics

– Diagnostic centres

– Homeopathy clinics

– In-house clinics/clinics which are affiliated with specific companies

– Specialist clinics /clinics which provide specialised care/ e.g. paediatric, cardiology, occupational therapy

– Clinics which operate less than 5 days a week

– Clinics which participated in NMCS 2012

Sample selection was conducted by stratified random cluster sampling, incorporating several stages. The details are described below.

Stratification

Stage 1: Stratification by sector

– Each state or federal territory was stratified by either public or private sector.

Stage 2: Stratification by sampling regions

– Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah & WP Labuan, Sarawak, Selangor & WP Putrajaya, WP Kuala Lumpur and Terengganu.

Cluster sampling

Stage 1: Sampling of clinics (primary sampling unit)

– Random sampling of clinics was based on random numbers generated using Microsoft Excel 2007. – If a selected clinic was discovered to not fulfill the inclusion and exclusion criteria when contacted,

the clinic was omitted and another clinic was randomly selected to replace it.

Stage 2: Sampling of survey date (secondary sampling unit)

– Each sampled clinic was randomly assigned a date for data collection within the study period. – The following days were excluded:

o public holidays o weekends, including Friday, Saturday and Sunday o Monday (Mondays are usually the busiest for public primary care clinics) o a week before and during the festive season (Chinese New Year)

– If the clinic was closed on the date of survey, the doctor had the option to change the survey date to the next available working day, given that the research team was informed of the new survey date.

Stage 3: Sampling of doctors (including assistant medical officers & trained nurses in the public clinics) (tertiary sampling unit)

– All doctors (including assistant medical officers and some trained nurses in public clinics) in the sampled clinics who were on-duty on the day of survey were included.

– Locum doctors were included. – As for doctors who are trained in clinical specialities, only family medicine specialists were

included.

Sampling of encounters

– Record of all patient encounters seen by each health care personnel mentioned above on the survey date.

Following Figure 2.1.1 shows the study design of NMCS 2014, while Figure 2.1.2 and Figure 2.1.3 are consort diagrams which show the number of clinics sampled from each state for public and private sector respectively.


Table 2.1.2: Inclusion and exclusion criteria for the clinics sampled in the survey

Inclusion criteria • MOH Health Clinics (Klinik Kesihatan) which provide primary care services

• Private medical clinics registered with CKAPS and provide primary care services

Exclusion criteria • Outpatient departments within hospital or maternity homes

• Public clinics with the following criteria:

– Health clinics without permanent medical doctors (Klinik Kesihatan)

– Clinics which provide only maternal and child health services (Klinik Kesihatan Ibu dan Anak)

– Rural health clinics (Klinik Desa)

– 1 Malaysia clinics

• Private clinics with the following criteria:

– Aesthetic clinics

– Charity clinics

– Diagnostic centres

– Homeopathy clinics

– In-house clinics/clinics which are affiliated with specific companies

– Specialist clinics /clinics which provide specialised care/ e.g. paediatric, cardiology, occupational therapy

– Clinics which operate less than 5 days a week

– Clinics which participated in NMCS 2012

Sample selection was conducted by stratified random cluster sampling, incorporating several stages. The details are described below.

Stratification

Stage 1: Stratification by sector

– Each state or federal territory was stratified by either public or private sector.

Stage 2: Stratification by sampling regions

– Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah & WP Labuan, Sarawak, Selangor & WP Putrajaya, WP Kuala Lumpur and Terengganu.

Cluster sampling

Stage 1: Sampling of clinics (primary sampling unit)

– Random sampling of clinics was based on random numbers generated using Microsoft Excel 2007. – If a selected clinic was discovered to not fulfill the inclusion and exclusion criteria when contacted,

the clinic was omitted and another clinic was randomly selected to replace it.

Stage 2: Sampling of survey date (secondary sampling unit)

– Each sampled clinic was randomly assigned a date for data collection within the study period. – The following days were excluded:

o public holidays o weekends, including Friday, Saturday and Sunday o Monday (Mondays are usually the busiest for public primary care clinics) o a week before and during the festive season (Chinese New Year)

– If the clinic was closed on the date of survey, the doctor had the option to change the survey date to the next available working day, given that the research team was informed of the new survey date.

Stage 3: Sampling of doctors (including assistant medical officers & trained nurses in the public clinics) (tertiary sampling unit)

– All doctors (including assistant medical officers and some trained nurses in public clinics) in the sampled clinics who were on-duty on the day of survey were included.

– Locum doctors were included. – As for doctors who are trained in clinical specialities, only family medicine specialists were

included.

Sampling of encounters

– Record of all patient encounters seen by each health care personnel mentioned above on the survey date.

Following Figure 2.1.1 shows the study design of NMCS 2014, while Figure 2.1.2 and Figure 2.1.3 are consort diagrams which show the number of clinics sampled from each state for public and private sector respectively.


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ure

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ure

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Fig

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Fig

ure

2.1

.3: C

on

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m –

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ary

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re c

lin

ics

2014

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lis

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ched

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2.2 DATA COLLECTION AND FOLLOW-UP

The sampled clinics were each sent an invitation letter to attend a briefing in major towns in each state. Briefings for doctors in the public clinics were held on weekdays, whereas briefings for private doctors were conducted between October and December 2013 according to the convenience of the private doctors for maximum attendances. A research pack which contained the survey forms and instructions were distributed during the briefings.

To encourage further participation, representatives of clinics that did not attend the briefing were later contacted by telephone. If the doctor refused to participate, the team did not pursue further. However, if they agreed to participate the research pack was sent either by:

• courier service (Poslaju) followed by telephone call to ensure that the research kit is received. Briefing would be done over the phone to explain about the survey form

• personal visit to the clinics (within the vicinity of Klang valley), where a short private briefing would be given by the research team to the doctor/nurse in-charge

A telephone call-reminder was made to the clinic about the project and to answer any questions pertaining to the survey at two weeks and one day before the survey date. Instructions would be repeated when necessary. After the survey date, follow-up phone call(s) were made if the research pack was not returned after three weeks, and subsequently at five weeks.

Various approaches were also taken to increase the acceptance and response rates of private clinics in particular, including:

a) Approaching the top management of the chain clinics/group practices. b) Obtaining a written endorsement from the Malaysian Medical Association (MMA). c) Getting support and assistance from Malaysian Medical Association (MMA) at the state level. d) Presentation of the NMCS 2012 results through general practitioners’ seminar and a series of

articles in MMA bulletin. e) Organising private (individual) briefings alongside Medical Practice Division’s enforcement

activities.

Data was collected using a self-administered questionnaire. The details of the patients managed on the date assigned to each clinic were filled by the health providers. Upon completion of data collection, participants were given certificates, which they would later use to claim for continuing professional education (CPD) points. A clinic-specific feedback, a satisfaction survey on the prescribers, and a copy of the National Medical Care Statistics 2014 report will also be sent to all participants.

2.3 RESEARCH PACK AND QUESTIONNAIRE

A pre-testing session of the questionnaire was carried out by convenience sampling of doctors from public and private clinics. The questionnaire was modified from the prior form developed in NMCS 20122 which was adapted from the Better Bettering the Evaluation and Care of Health (BEACH) survey from Australia.4 A total of 30 encounters were recorded, and comments from the doctors based on the pre-testing were taken into consideration to further improvise the form. The NMCS 2014 form was modified based on these feedbacks and the finalised form is enclosed in Appendix 3.


Fig

ure

2.1

.3: C

on

sort

dia

gra

m –

pri

va

te p

rim

ary

ca

re c

lin

ics

2014

Per

lis

n =

10

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ah

n =

55

Pu

lau

P

ina

ng

n =

70

Per

ak

n =

73

Sel

an

go

r &

W

P P

utr

aja

ya

n =

270

Neg

eri

Sem

bil

an

n =

40

Mel

ak

a

n =

31

Jo

ho

r

n =

117

Pa

ha

ng

n =

42

Ter

eng

ga

nu

n =

30

Kel

an

tan

n =

45

Sa

ba

h &

W

P L

ab

ua

n

n =

65

Sa

raw

ak

n =

34

WP

Ku

ala

Lu

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ur

n =

120

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mp

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nic

s

n =

1,0

02

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tal

nu

mb

er o

f p

riv

ate

pri

ma

ry c

are

cli

nic

s, N

= 5

,646

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KA

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lis

t as

of

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ecem

ber

2012

mat

ched

wit

h N

HS

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ase)

Cli

nic

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clu

ded

n

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74

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cial

ist

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ics

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ic c

lin

ics

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se c

lin

ics

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nic

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te l

ess

than

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ays

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k

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nic

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sed

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nic

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ifte

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le

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laju

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our

Par

tici

pate

d in

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CS

201

2

Cli

nic

sa

mp

lin

g f

ram

e

N =

5,3

72

2.2 DATA COLLECTION AND FOLLOW-UP

The sampled clinics were each sent an invitation letter to attend a briefing in major towns in each state. Briefings for doctors in the public clinics were held on weekdays, whereas briefings for private doctors were conducted between October and December 2013 according to the convenience of the private doctors for maximum attendances. A research pack which contained the survey forms and instructions were distributed during the briefings.

To encourage further participation, representatives of clinics that did not attend the briefing were later contacted by telephone. If the doctor refused to participate, the team did not pursue further. However, if they agreed to participate the research pack was sent either by:

• courier service (Poslaju) followed by telephone call to ensure that the research kit is received. Briefing would be done over the phone to explain about the survey form

• personal visit to the clinics (within the vicinity of Klang valley), where a short private briefing would be given by the research team to the doctor/nurse in-charge

A telephone call-reminder was made to the clinic about the project and to answer any questions pertaining to the survey at two weeks and one day before the survey date. Instructions would be repeated when necessary. After the survey date, follow-up phone call(s) were made if the research pack was not returned after three weeks, and subsequently at five weeks.

Various approaches were also taken to increase the acceptance and response rates of private clinics in particular, including:

a) Approaching the top management of the chain clinics/group practices. b) Obtaining a written endorsement from the Malaysian Medical Association (MMA). c) Getting support and assistance from Malaysian Medical Association (MMA) at the state level. d) Presentation of the NMCS 2012 results through general practitioners’ seminar and a series of

articles in MMA bulletin. e) Organising private (individual) briefings alongside Medical Practice Division’s enforcement

activities.

Data was collected using a self-administered questionnaire. The details of the patients managed on the date assigned to each clinic were filled by the health providers. Upon completion of data collection, participants were given certificates, which they would later use to claim for continuing professional education (CPD) points. A clinic-specific feedback, a satisfaction survey on the prescribers, and a copy of the National Medical Care Statistics 2014 report will also be sent to all participants.

2.3 RESEARCH PACK AND QUESTIONNAIRE

A pre-testing session of the questionnaire was carried out by convenience sampling of doctors from public and private clinics. The questionnaire was modified from the prior form developed in NMCS 20122 which was adapted from the Better Bettering the Evaluation and Care of Health (BEACH) survey from Australia.4 A total of 30 encounters were recorded, and comments from the doctors based on the pre-testing were taken into consideration to further improvise the form. The NMCS 2014 form was modified based on these feedbacks and the finalised form is enclosed in Appendix 3.


Each research pack contained:

• Survey pads – 40 forms – One set of instructions – One case study – One example of a completed form

• NMCS 2014 summary information – Objectives of the NMCS 2014 – Brief description of project and project team – Individual survey date of the clinics

• Public notice – Notice to be displayed in the participating clinic to inform patients that the clinic is currently

undertaking the NMCS survey

• ICPC-2-code list – ICPC-2-Code list

Also included in the research pack:

• Call letter – Letter signed by the Director of the State Health Departments to inform the participating

clinics of the survey

• Prepaid envelope – One envelope for every two survey pads

2.4 DATA MANAGEMENT

Data entry

Prior to the start of data entry, all data entry personnel were given reference materials containing a description of the study, examples of the questionnaire, classification and coding systems, data entry rules and regulations. This was followed by two sessions of data entry training of at least 2 hours each session. Data is then transferred from paper to an electronic format through a data entry web application by trained data entry personnel.

Session 1: Demonstration and practical session

• Slide presentation on data entry module • Live demonstration of data entry module • Live demonstration of coding systems • Discussion on data entry and coding systems • Practical session – practice data entry and coding of 20 test questionnaires per data entry

personnel

Session 2: Question and answer

• Feedback was provided to data entry personnel on data entry and coding issues from the 20 test questionnaires

Standardisations to the data entry rules and coding systems were also periodically updated and conveyed to all data entry personnel.

Data quality assurance

The data entry application was loaded with previous coding history from NMCS 2012 and also current coding entry to ease the coding process and to ensure consistency of coding.

Software based quality assurance measures were also built into the data entry applications either as a quality measure or to facilitate the data entry process. For example warnings prompt when there was a duplication of identification card number being entered, warnings prompt of missing mandatory fields, auto-generation of date of birth and age through identification card number when available etc.

Validity checks were put in place during data entry to minimise entry of illogical data and warnings would pop-up if extreme values were entered to prompt the data entry personnel to re-check the data. These include validation on the date of birth entered, gender counter check via identification card number when available, unable to enter the same diagnosis within the same encounter etc.

In addition to the aforementioned measures, double data entry was also incorporated as part of the quality assurance of the data. This form of quality check has been recommended and known to correct data entry errors from the original entry.5

Double data entry was done for more than 10% of the total entries (2,894 out of 27,808 forms) in six batches, where Batch 1 was completed in June 2014 and Batch 6 in October 2014. Questionnaires that were to be entered a second time were identified by random selection of clinics. The data entry personnel were blinded to the assignment of clinics for double data entry.

For each batch of double data entry, all discrepancies between the first and second set of records were verified by checking either with the original forms or the coding definitions. Errors were defined as deviations of either the first or second entry from the original questionnaire by alphanumeric characters or assigning the wrong code for a variable. However those errors that were due illegible handwriting were not regarded as an error. A correct third record was then updated into the database. The percentage of data entry error for each available variable was then calculated by obtaining the proportion of errors per total cases within the variable. The variables with the highest rates of data entry error were then compared.


Each research pack contained:

• Survey pads – 40 forms – One set of instructions – One case study – One example of a completed form

• NMCS 2014 summary information – Objectives of the NMCS 2014 – Brief description of project and project team – Individual survey date of the clinics

• Public notice – Notice to be displayed in the participating clinic to inform patients that the clinic is currently

undertaking the NMCS survey

• ICPC-2-code list – ICPC-2-Code list

Also included in the research pack:

• Call letter – Letter signed by the Director of the State Health Departments to inform the participating

clinics of the survey

• Prepaid envelope – One envelope for every two survey pads

2.4 DATA MANAGEMENT

Data entry

Prior to the start of data entry, all data entry personnel were given reference materials containing a description of the study, examples of the questionnaire, classification and coding systems, data entry rules and regulations. This was followed by two sessions of data entry training of at least 2 hours each session. Data is then transferred from paper to an electronic format through a data entry web application by trained data entry personnel.

Session 1: Demonstration and practical session

• Slide presentation on data entry module • Live demonstration of data entry module • Live demonstration of coding systems • Discussion on data entry and coding systems • Practical session – practice data entry and coding of 20 test questionnaires per data entry

personnel

Session 2: Question and answer

• Feedback was provided to data entry personnel on data entry and coding issues from the 20 test questionnaires

Standardisations to the data entry rules and coding systems were also periodically updated and conveyed to all data entry personnel.

Data quality assurance

The data entry application was loaded with previous coding history from NMCS 2012 and also current coding entry to ease the coding process and to ensure consistency of coding.

Software based quality assurance measures were also built into the data entry applications either as a quality measure or to facilitate the data entry process. For example warnings prompt when there was a duplication of identification card number being entered, warnings prompt of missing mandatory fields, auto-generation of date of birth and age through identification card number when available etc.

Validity checks were put in place during data entry to minimise entry of illogical data and warnings would pop-up if extreme values were entered to prompt the data entry personnel to re-check the data. These include validation on the date of birth entered, gender counter check via identification card number when available, unable to enter the same diagnosis within the same encounter etc.

In addition to the aforementioned measures, double data entry was also incorporated as part of the quality assurance of the data. This form of quality check has been recommended and known to correct data entry errors from the original entry.5

Double data entry was done for more than 10% of the total entries (2,894 out of 27,808 forms) in six batches, where Batch 1 was completed in June 2014 and Batch 6 in October 2014. Questionnaires that were to be entered a second time were identified by random selection of clinics. The data entry personnel were blinded to the assignment of clinics for double data entry.

For each batch of double data entry, all discrepancies between the first and second set of records were verified by checking either with the original forms or the coding definitions. Errors were defined as deviations of either the first or second entry from the original questionnaire by alphanumeric characters or assigning the wrong code for a variable. However those errors that were due illegible handwriting were not regarded as an error. A correct third record was then updated into the database. The percentage of data entry error for each available variable was then calculated by obtaining the proportion of errors per total cases within the variable. The variables with the highest rates of data entry error were then compared.


Classification of data (data coding)

International Classification of Primary Care (ICPC)

The International Classification of Primary Care Second Edition (ICPC-2) was used to classify the following data elements:

• Reasons for encounter • Diagnoses • Investigations • Procedures • Advice/counselling

The ICPC-2 is accepted by the World Health Organization (WHO) as a member of the WHO Family of International Classifications.9 It was published in 1987 by the World Organisation of Family Doctors (WONCA) and used in more than 45 countries as the standard for data classification in primary care. The ICPC-2 has a bi-axial structure, with 17 chapters based on body systems (Table 2.4.2) and seven components (Table 2.4.3) with rubrics bearing a letter and two-digit numeric code.

The data were entered and coded using ICPC-2 PLUS, an extended clinical terminology classified according to ICPC-2. ICPC-2 PLUS coding system contains extended terms commonly used in general practice that are more specific, and helps to ensure accurate classification to ICPC-2 during data entry. ICPC-2 PLUS was developed in 1995, and is maintained and regularly updated by the Family Medicine Research Centre (FMRC) of the University of Sydney.10 Also known as BEACH coding system, ICPC-2 PLUS is primarily used in Australia especially for the national study of general practice activity, the BEACH program.4

Table 2.4.2: ICPC-2 chapters

Code ICPC-2 chapter Code ICPC-2 chapter

A General B Blood, immune system

D Digestive F Eye

H Ear K Circulatory

L Musculoskeletal N Neurological

P Psychological R Respiratory

S Skin T Endocrine, nutritional & metabolic

U Urological W Women’s health, pregnancy, family planning

X Female genital Y Male genital

Z Social problems

Table 2.4.1: Data entry error rate for NMCS 2014

Variables Data entry error (%)

Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Batch 6

Coded variables

ICPC-2+ code 3.5 1.5 4.8 3.0 6.0 1.9

ATC code 1.3 0.9 1.5 2.3 1.2 1.8

Non-coded variables

Nationality 16.3 0.0 0.0 0.4 0.7 0.3

Procedures/other treatments/ counselling 8.9 1.2 1.1 2.0 3.0 1.5

Diagnosis not specified for which medical certificated was issued 6.2 2.1 0.0 1.3 0.2 0.5

The three variables for the non-coding section were the variables with the highest data entry error rate for batch 1. There was marked improvement in error rate for these variables from batches 1 to 5. Increase of data entry error rate for the coded variables can be attributed to recruitment of new data entry personnel, resulting in more variations in coding. While many of the errors were random errors but coding errors were largely occurring in a systematic manner; where a data entry personnel with a misconception of the correct codes for certain diseases/medications, makes a consistent error throughout all forms entered.

There does not appear to have a general consensus of acceptable data entry error rate worldwide. Previous study shown that error rates detected by double-entry method for clinical databases ranged from 2.3 to 5.2% for demographic data while for treatment data, it ranged from 10.0 to 26.9%6. Similarly, Fontaine P et. al reported an overall rate of 7.3% for data entry strategies used in clinical trial.7

Double entry has been recognised as the gold standard in transferring of data into an electronic database but it substantially increases the amount of time and costs of data entry. Costs of resources have been reported to be increased by up to 2.5 times with double data entry compared to single entry5. Also, additional software solutions and manual checking mechanisms are required when performing checks on discrepancies and putting in corrections.

An alternative recommendation is a trade-off between acceptable data accuracy and cost-effectiveness using single data entry with concurrent quality control measures, exploratory data analysis and post-entry logic checks.5,6 It is also recognised that double entry detects errors where exploratory analysis misses while on the other hand not all discrepancies found by exploratory data analysis is identified by double entry.8 Hence, suggests that double data entry alone may not necessarily be sufficient as a sole data quality checking method.

All the errors which were detected (coded and non-coded) were corrected by referring to the original forms and by discussion among the investigators and the Research Evaluation Committee. Further logic checks and exploratory analyses were also conducted during data cleaning to question the plausibility and ensure the validity of the data. A protocol with validation rules for cleaning as well as data inconsistency rules was compiled for the purpose of data cleaning.




Coded variables

ICPC-2+ code 3.5 1.5 4.8 3.0 6.0 1.9

ATC code 1.3 0.9 1.5 2.3 1.2 1.8

Non-coded variables

Nationality 16.3 0.0 0.0 0.4 0.7 0.3











Coded variables

ICPC-2+ code 3.5 1.5 4.8 3.0 6.0 1.9

ATC code 1.3 0.9 1.5 2.3 1.2 1.8

Non-coded variables

Nationality 16.3 0.0 0.0 0.4 0.7 0.3


















D Digestive F Eye

H Ear K Circulatory






Z Social problems










D Digestive F Eye

H Ear K Circulatory






Z Social problems




Coded variables

ICPC-2+ code 3.5 1.5 4.8 3.0 6.0 1.9

ATC code 1.3 0.9 1.5 2.3 1.2 1.8

Non-coded variables

Nationality 16.3 0.0 0.0 0.4 0.7 0.3











Coded variables

ICPC-2+ code 3.5 1.5 4.8 3.0 6.0 1.9

ATC code 1.3 0.9 1.5 2.3 1.2 1.8

Non-coded variables

Nationality 16.3 0.0 0.0 0.4 0.7 0.3









Table 2.4.3: ICPC-2 components

ICPC-2 components Code

1. Complaints and symptoms 01–29

2. Diagnostics, screening and preventive 30–49

3. Medication, treatment, procedures 50–59

4. Test results 60–61

5. Administrative 62

6. Referrals 63–69

7. Diagnoses, diseases 70–99

– infectious

– neoplastic

– injuries

– congenital anomalies

– others

The National Clinical Research Centre has been granted a free research licence from WONCA for the usage of ICPC-2 codes in the NHSI project which is valid from February 2011 till end of 2014 whereas the ICPC-2 PLUS was obtained under a free licence from the University of Sydney. Results were reported at the ICPC-2 classification level. Some of the diagnoses were grouped together by combining several ICPC-2 or ICPC-2 PLUS codes (Appendix 4). Classification of pathology and imaging test according to ICPC-2 can be very broad (e.g. HbA1c test is classified under T34 - Blood test endo/metabolic). Hence, results for Chapter 10 were presented as ICPC-2 PLUS. Anatomical Therapeutic Chemical (ATC) classification Medications were coded and classified using the Anatomical Therapeutic Chemical (ATC) classification system. ATC has been recommended by the WHO and used in many countries including Malaysia, as a global standard for classifying medications for drug utilisation research, evaluating trend of drug consumption and for international comparisons.11,12 Medications are classified into groups at five different levels, with the following example: • Level 1: C - Cardiovascular system • Level 2: C10 - Serum lipid reducing agents • Level 3: C10A - Cholesterol of triglyceride reducers • Level 4: C10AA - HMG CoA reductase inhibitors • Level 5: C10AA01 – Simvastatin

The ATC licence was purchased from the WHO Collaborating Centre for Drug Statistics Methodology. Medications were entered as free text in generic (non-proprietary) or brand name, and coded by trained data entry personnel according to the Guidelines for ATC Classification and DDD assignment 2012.11 In certain cases, the doctors might not specify the medications down to the generic level hence it could only be coded to ATC level 3 or 4.

2.5 DATA ANALYSIS

Weighting

The data presented in this report were weighted to adjust for over and under representativeness of any strata in the sample as well as to account for non-respondents. Table 2.5.1 shows the 28 weighting strata that were defined for the study population, by state/region and sector. The components incorporated in the estimation of total weights are described below.

Table 2.5.1: Strata according to state/region and sector

State/federal territory Sector Stratum

Johor Public J1

Private J2

Kedah Public K1

Private K2

Kelantan Public D1

Private D2

Melaka Public M1

Private M2

Negeri Sembilan Public N1

Private N2

Pahang Public C1

Private C2

Perak Public A1

Private A2

Perlis Public R1

Private R2

Pulau Pinang Public P1

Private P2

Sabah & WP Labuan Public SB1

Private SB2

Sarawak Public SW1

Private SW2

Selangor & WP Putrajaya Public B1

Private B2

WP Kuala Lumpur Public W1

Private W2


Table 2.4.3: ICPC-2 components

ICPC-2 components Code

1. Complaints and symptoms 01–29

2. Diagnostics, screening and preventive 30–49

3. Medication, treatment, procedures 50–59

4. Test results 60–61

5. Administrative 62

6. Referrals 63–69

7. Diagnoses, diseases 70–99

– infectious

– neoplastic

– injuries

– congenital anomalies

– others

The National Clinical Research Centre has been granted a free research licence from WONCA for the usage of ICPC-2 codes in the NHSI project which is valid from February 2011 till end of 2014 whereas the ICPC-2 PLUS was obtained under a free licence from the University of Sydney. Results were reported at the ICPC-2 classification level. Some of the diagnoses were grouped together by combining several ICPC-2 or ICPC-2 PLUS codes (Appendix 4). Classification of pathology and imaging test according to ICPC-2 can be very broad (e.g. HbA1c test is classified under T34 - Blood test endo/metabolic). Hence, results for Chapter 10 were presented as ICPC-2 PLUS. Anatomical Therapeutic Chemical (ATC) classification Medications were coded and classified using the Anatomical Therapeutic Chemical (ATC) classification system. ATC has been recommended by the WHO and used in many countries including Malaysia, as a global standard for classifying medications for drug utilisation research, evaluating trend of drug consumption and for international comparisons.11,12 Medications are classified into groups at five different levels, with the following example: • Level 1: C - Cardiovascular system • Level 2: C10 - Serum lipid reducing agents • Level 3: C10A - Cholesterol of triglyceride reducers • Level 4: C10AA - HMG CoA reductase inhibitors • Level 5: C10AA01 – Simvastatin

The ATC licence was purchased from the WHO Collaborating Centre for Drug Statistics Methodology. Medications were entered as free text in generic (non-proprietary) or brand name, and coded by trained data entry personnel according to the Guidelines for ATC Classification and DDD assignment 2012.11 In certain cases, the doctors might not specify the medications down to the generic level hence it could only be coded to ATC level 3 or 4.

2.5 DATA ANALYSIS

Weighting

The data presented in this report were weighted to adjust for over and under representativeness of any strata in the sample as well as to account for non-respondents. Table 2.5.1 shows the 28 weighting strata that were defined for the study population, by state/region and sector. The components incorporated in the estimation of total weights are described below.

Table 2.5.1: Strata according to state/region and sector

State/federal territory Sector Stratum

Johor Public J1

Private J2

Kedah Public K1

Private K2

Kelantan Public D1

Private D2

Melaka Public M1

Private M2

Negeri Sembilan Public N1

Private N2

Pahang Public C1

Private C2

Perak Public A1

Private A2

Perlis Public R1

Private R2

Pulau Pinang Public P1

Private P2

Sabah & WP Labuan Public SB1

Private SB2

Sarawak Public SW1

Private SW2

Selangor & WP Putrajaya Public B1

Private B2

WP Kuala Lumpur Public W1

Private W2


Sampling weight

Sampling weight is the inverse of the probability of selecting a unit.13 The sampling weight of each stratum calculated as follow14:

𝑺𝑺𝑺𝑺𝒋𝒋 = 𝑴𝑴𝒋𝒋

𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 + 𝒎𝒎𝒋𝒋.𝒏𝒏𝒏𝒏𝒏𝒏 + 𝒎𝒎𝒋𝒋.𝒆𝒆𝒆𝒆𝒆𝒆

where Mj is the total number of primary care clinics that can be sampled in the jth strata (population), mj.res is the number of primary care clinics responded for strata j, mj.non is the number of primary care clinics who did not respond in the jth strata, and mj.exc is the number of clinics excluded after being sampled for strata j.

Activity weight

The activity weight for each clinic was calculated to account for the different level of activities of each clinic. It was calculated as follows:

𝑨𝑨𝑨𝑨𝒋𝒋𝒋𝒋 = 𝑵𝑵𝒋𝒋𝒋𝒋 𝒏𝒏𝒋𝒋𝒋𝒋

where Njk is the expected patients’ visits per day of the kth clinic in the jth strata while njk is the number of encounters we received from the kth clinic in the jth strata.

Adjustment for non-response

To account for less than 100% response rate, adjustment for the non-response is required.12 The non-response adjustment weight was calculated as follows:

𝑨𝑨𝒋𝒋 = 𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 + 𝒎𝒎𝒋𝒋.𝒏𝒏𝒏𝒏𝒏𝒏

𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓

where mj.res is the number of primary care clinics responded for strata j and mj.non is the number of primary care clinics who did not respond in the jth strata.

Total weight

The final weight for each stratum was calculated as the multiplication of the sampling weight, activity weight and adjustment for non-response.

𝐹𝐹𝐹𝐹!" = 𝑆𝑆𝑆𝑆!×𝐴𝐴𝐴𝐴!"×𝐴𝐴!

The weighted estimates were generated using the survey package in R.

Statistical analysis

Analysis was done in R15 with an R package called "survey: analysis of complex survey samples".16 Results are presented as number of unweighted counts, weighted counts, proportions and rate per 100 encounters along with 95% confidence interval (CI). Rate per 100 diagnoses are reported for management that can occur at more than once per diagnosis.

2.6 ETHICS APPROVAL

The study was approved by the Medical Research and Ethics Committee (MREC) (Approval Number: NMRR-09-842-4718). As per previous study, a public notice was placed at each participating clinic to inform patients that their prescription data would be collected for research purposes. Patients had the right to decline to participate at any point of time throughout the study period.

2.7 LIMITATIONS

1. The survey is self-administered and therefore precision of data depends largely on the completeness of recording by respondents, hence may not accurately reflect true practice.

2. The survey is encounter-based and reflects the morbidity pattern observed in the primary care setting rather than the prevalence of disease in the community.

3. The morbidity patterns reflect only those morbidities managed during the recorded encounters. There may be co-morbidity in the same patient which was not expected to be managed during the encounter and hence was not recorded.

4. This is a cross-sectional study. Therefore, no conclusions may be generated on the outcomes of management of acute and chronic diseases in the primary care setting. Prescriptions, procedures, imaging and referrals reported were those provided at the present point of encounter and did not necessarily indicate that the patient has not already received them in a previous encounter.

5. Maternal child health encounters in public clinics were mostly attended by trained nurses. NMCS 2014 might miss those cases as not all the trained nurses were involved in the study.

6. The sampling of public clinics can be improved by incorporating the classification of the type of clinics, which is based on the workload of the clinic.

7. Verification of data received via audit process was not done. All data received were presumed to be accurate and precise.

8. Benchmarking the sample against population data cannot be performed as there is no readily available primary care population data, be it the providers or the patients.

9. Non-respondent details were not recorded; hence non-response analysis to compare the sample and the non-respondent cannot be performed.


Sampling weight

Sampling weight is the inverse of the probability of selecting a unit.13 The sampling weight of each stratum calculated as follow14:

𝑺𝑺𝑺𝑺𝒋𝒋 = 𝑴𝑴𝒋𝒋

𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 + 𝒎𝒎𝒋𝒋.𝒏𝒏𝒏𝒏𝒏𝒏 + 𝒎𝒎𝒋𝒋.𝒆𝒆𝒆𝒆𝒆𝒆

where Mj is the total number of primary care clinics that can be sampled in the jth strata (population), mj.res is the number of primary care clinics responded for strata j, mj.non is the number of primary care clinics who did not respond in the jth strata, and mj.exc is the number of clinics excluded after being sampled for strata j.

Activity weight

The activity weight for each clinic was calculated to account for the different level of activities of each clinic. It was calculated as follows:

𝑨𝑨𝑨𝑨𝒋𝒋𝒋𝒋 = 𝑵𝑵𝒋𝒋𝒋𝒋 𝒏𝒏𝒋𝒋𝒋𝒋

where Njk is the expected patients’ visits per day of the kth clinic in the jth strata while njk is the number of encounters we received from the kth clinic in the jth strata.

Adjustment for non-response

To account for less than 100% response rate, adjustment for the non-response is required.12 The non-response adjustment weight was calculated as follows:

𝑨𝑨𝒋𝒋 = 𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 + 𝒎𝒎𝒋𝒋.𝒏𝒏𝒏𝒏𝒏𝒏

𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓

where mj.res is the number of primary care clinics responded for strata j and mj.non is the number of primary care clinics who did not respond in the jth strata.

Total weight

The final weight for each stratum was calculated as the multiplication of the sampling weight, activity weight and adjustment for non-response.

𝐹𝐹𝐹𝐹!" = 𝑆𝑆𝑆𝑆!×𝐴𝐴𝐴𝐴!"×𝐴𝐴!

The weighted estimates were generated using the survey package in R.

Statistical analysis

Analysis was done in R15 with an R package called "survey: analysis of complex survey samples".16 Results are presented as number of unweighted counts, weighted counts, proportions and rate per 100 encounters along with 95% confidence interval (CI). Rate per 100 diagnoses are reported for management that can occur at more than once per diagnosis.

2.6 ETHICS APPROVAL

The study was approved by the Medical Research and Ethics Committee (MREC) (Approval Number: NMRR-09-842-4718). As per previous study, a public notice was placed at each participating clinic to inform patients that their prescription data would be collected for research purposes. Patients had the right to decline to participate at any point of time throughout the study period.

2.7 LIMITATIONS

1. The survey is self-administered and therefore precision of data depends largely on the completeness of recording by respondents, hence may not accurately reflect true practice.

2. The survey is encounter-based and reflects the morbidity pattern observed in the primary care setting rather than the prevalence of disease in the community.

3. The morbidity patterns reflect only those morbidities managed during the recorded encounters. There may be co-morbidity in the same patient which was not expected to be managed during the encounter and hence was not recorded.

4. This is a cross-sectional study. Therefore, no conclusions may be generated on the outcomes of management of acute and chronic diseases in the primary care setting. Prescriptions, procedures, imaging and referrals reported were those provided at the present point of encounter and did not necessarily indicate that the patient has not already received them in a previous encounter.

5. Maternal child health encounters in public clinics were mostly attended by trained nurses. NMCS 2014 might miss those cases as not all the trained nurses were involved in the study.

6. The sampling of public clinics can be improved by incorporating the classification of the type of clinics, which is based on the workload of the clinic.

7. Verification of data received via audit process was not done. All data received were presumed to be accurate and precise.

8. Benchmarking the sample against population data cannot be performed as there is no readily available primary care population data, be it the providers or the patients.

9. Non-respondent details were not recorded; hence non-response analysis to compare the sample and the non-respondent cannot be performed.


REFERENCES

1. Cochran WG. Sampling techniques. 2nd ed. New York: John Wiley and Sons, Inc; 1963. 2. Meza RA, Angelis M, Britt H, Miles DA, Seneta E, Bridges-Webb C. Development of sample size

models for national general practice surveys. Aust J Public Health. 1995 Feb;19(1):34-40. 3. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National

Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia.

4. Britt H, Miller GC, Henderson J, Charles J, Valenti L, Harrison C, et al. General practice activity in Australia 2011–12. Sydney (Australia): Sydney University Press; 2012. p. 184-5. (General practice series; no. 31).

5. Büchele G, Och B, Bolte G, Weiland SK. Single vs. double data entry. Epidemiology. 2005 Jan;16(1);130-1.

6. Goldberg SI, Niemierko A, Turchin A. Analysis of data errors in clinical research databases. AMIA Annu Symp Proc. 2008 Nov 6:242-6.

7. Fontaine P, Mendenhall TJ, Peterson K, Speedie SM. The “Measuring Outcomes of Clinical Connectivity” (MOCC) trial: investigating data entry errors in the Electronic Primary Care Research Network (ePCRN). J Am Board Fam Med. 2007 Mar-Apr;20(2):151-9.

8. Day S, Fayers P, Harvey D. Double data entry: what value, what price? Control Clin Trials. 1998 Feb;19(1):15-24.

9. World Health Organization. World Health Organization family of international classifications [Internet]. Geneva (Switzerland): World Health Organization; 2004 June [cited 2014 Feb 8]. Available from: http://www.who.int/classifications/en/WHOFICFamily.pdf

10. ICPC-2 - International Classification for Primary Care [Internet]. Sydney (Australia): University of Sydney, Family Medicine Research Centre; c2002-2015 [updated 2012 Nov 22, cited 2014 Jan 12]; [about 1 screen]. Available from: http://sydney.edu.au/medicine/fmrc/icpc-2/index.php

11. WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment 2012. Oslo (Norway): WHO Collaborating Centre for Drug Statistics Methodology; 2011.

12. Lian LM, Kamarudin A, Siti Fauziah A, Nik Nor Aklima NO, Norazida AR, editors. Malaysian Statistics on Medicine 2008. Kuala Lumpur (Malaysia): Ministry of Health Malaysia, Pharmaceutical Services Division and Clinical Research Centre; 2013. 166 p.

13. Hahs-Vaughn DL. A primer for using and understanding weights with national datasets. J Exp Educ. 2005;73(3):221-48.

14. Foy P. Calculation of sampling weights. In: Martin MO, Kelly DL, editors. Third International Mathematics and Science Study technical report. Vol. 2, Implementation and analysis – primary and middle school years. Chestnut Hill (MA): Boston College, Center for the Study of Testing, Evaluation, and Educational Policy; c1997. p. 71-9.

15. R Development Core Team. R: a language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing; 2015. Available from: https://www.R-project.org

16. Lumley T. Analysis of complex survey samples. J Stat Softw. 2004 Apr;9(8):1-19.

CHAPTER threeResponse Rate

REFERENCES

1. Cochran WG. Sampling techniques. 2nd ed. New York: John Wiley and Sons, Inc; 1963. 2. Meza RA, Angelis M, Britt H, Miles DA, Seneta E, Bridges-Webb C. Development of sample size

models for national general practice surveys. Aust J Public Health. 1995 Feb;19(1):34-40. 3. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National

Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia.

4. Britt H, Miller GC, Henderson J, Charles J, Valenti L, Harrison C, et al. General practice activity in Australia 2011–12. Sydney (Australia): Sydney University Press; 2012. p. 184-5. (General practice series; no. 31).

5. Büchele G, Och B, Bolte G, Weiland SK. Single vs. double data entry. Epidemiology. 2005 Jan;16(1);130-1.

6. Goldberg SI, Niemierko A, Turchin A. Analysis of data errors in clinical research databases. AMIA Annu Symp Proc. 2008 Nov 6:242-6.

7. Fontaine P, Mendenhall TJ, Peterson K, Speedie SM. The “Measuring Outcomes of Clinical Connectivity” (MOCC) trial: investigating data entry errors in the Electronic Primary Care Research Network (ePCRN). J Am Board Fam Med. 2007 Mar-Apr;20(2):151-9.

8. Day S, Fayers P, Harvey D. Double data entry: what value, what price? Control Clin Trials. 1998 Feb;19(1):15-24.

9. World Health Organization. World Health Organization family of international classifications [Internet]. Geneva (Switzerland): World Health Organization; 2004 June [cited 2014 Feb 8]. Available from: http://www.who.int/classifications/en/WHOFICFamily.pdf

10. ICPC-2 - International Classification for Primary Care [Internet]. Sydney (Australia): University of Sydney, Family Medicine Research Centre; c2002-2015 [updated 2012 Nov 22, cited 2014 Jan 12]; [about 1 screen]. Available from: http://sydney.edu.au/medicine/fmrc/icpc-2/index.php

11. WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment 2012. Oslo (Norway): WHO Collaborating Centre for Drug Statistics Methodology; 2011.

12. Lian LM, Kamarudin A, Siti Fauziah A, Nik Nor Aklima NO, Norazida AR, editors. Malaysian Statistics on Medicine 2008. Kuala Lumpur (Malaysia): Ministry of Health Malaysia, Pharmaceutical Services Division and Clinical Research Centre; 2013. 166 p.

13. Hahs-Vaughn DL. A primer for using and understanding weights with national datasets. J Exp Educ. 2005;73(3):221-48.

14. Foy P. Calculation of sampling weights. In: Martin MO, Kelly DL, editors. Third International Mathematics and Science Study technical report. Vol. 2, Implementation and analysis – primary and middle school years. Chestnut Hill (MA): Boston College, Center for the Study of Testing, Evaluation, and Educational Policy; c1997. p. 71-9.

15. R Development Core Team. R: a language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing; 2015. Available from: https://www.R-project.org

16. Lumley T. Analysis of complex survey samples. J Stat Softw. 2004 Apr;9(8):1-19.


CHAPTER 3: RESPONSE RATE

3.1 RESPONSE RATE

This chapter describes the survey sample and the response rate for NMCS 2014. A total of 139 public clinics and 1,002 private clinics were sampled in NMCS 2014. The clinics are listed in Appendix 5. The response rates were calculated as the number of clinics that responded by returning the NMCS 2014 questionnaire divided by the number of clinics in the sample. Table 3.1.1 shows the number of clinics sampled, number of clinics responded to the survey and the clinic response rate for each state or federal territory.

Table 3.1.1: Total number of clinics sampled and responded for NMCS 2014

State/federal territory

Public

Private

Number of clinics sampled

Number of clinics

responded

Response rate (%)


Number of clinics

responded

Response rate (%)

Johor 11 10 90.9

117 43 36.7

Kedah 7 7 100.0

55 22 40.0

Kelantan 7 7 100.0

45 22 48.9

Melaka 26 23 88.5

31 14 45.2

Negeri Sembilan 6 5 83.3

40 19 47.5

Pahang 6 6 100.0

42 18 42.9

Perak 11 11 100.0

73 30 41.1

Perlis 9 7 77.8

10 7 70.0

Pulau Pinang 5 5 100.0

70 33 47.1

Sabah & WP Labuan 9 7 77.8

65 26 40.0

Sarawak 10 10 100.0

34 16 47.1

Selangor & WP Putrajaya 15 14 93.3

270 102 37.8

Terengganu 5 5 100.0

30 18 60.0

WP Kuala Lumpur 12 12 100.0

120 46 38.3

Total 139 129 92.8

1,002 416 41.5

Overall, more than three quarters of public clinics from thirteen states and three federal territories responded to NMCS 2014. The maximum response rate was 100.0% while the minimum is 77.8%, which gave the overall response rate of 92.8% in public sector. As for private sector, the lowest response rate was only 37.6%, bringing the overall response rate to 41.5%, in spite of our fervent attempts to persuade the GPs to participate.

Response rates by encounters are reported in Table 3.1.2. These response rates were calculated as the number of encounters that were recorded for NMCS 2014 divided by the expected number of encounters in the sample for each stratum to form a national representative data.

Table 3.1.2: Total number of encounters received for NMCS 2014


Public

Private

Number of encounters

expected

Number of encounter responded

Response rate (%)


expected

Number of

encounter responded

Response rate (%)

Johor 1,164 1,753 100.0

3,597 1,295 36.0

Kedah 746 627 84.0

1,694 803 47.4

Kelantan 778 621 79.8

1,395 607 43.5

Melaka 450 2,357 100.0

941 325 34.5


1,223 739 60.4

Pahang 698 494 70.8

1,277 532 41.7

Perak 1,174 1,375 100.0

2,228 807 36.2

Perlis 152 581 100.0

320 323 100.0


2,139 917 42.9

Sabah& WP Labuan 927 709 76.5

1,997 736 36.9

Sarawak 1,062 947 89.2

1,056 567 53.7

Selangor & WP Putrajaya 1,627 1,707 100.0

8,265 2,691 32.6


929 575 61.9

WP Kuala Lumpur 397 2,612 100.0

3,671 1,200 32.7

Total 10,951 15,470 100.0

30,732 12,117 39.4

Response rate by encounters obtained from public clinics of all thirteen states and three federal territories were overwhelming and some exceeded 100.0%. WP Kuala Lumpur recorded the highest response rate with more than six times encounters that were required for the study, while the lowest was 70.8% from Pahang. As for private sector, the minimum response rate by encounters was 32.7% from WP Kuala Lumpur, while Perlis recorded the maximum response rate of 100.0%. The overall response rate for public and private sector was 100.0% and 39.4%, respectively.

The low response rate however, has already been anticipated and accounted for. When calculating sample size, the sampling matrix had included an estimation of a 30.0% drop-out rate from the public and a 70.0% drop-out rate from the private sector.

This huge estimated rate of drop-out from the private sector was expected based on previous studies conducted comparing public and private health sectors in Malaysia. The reported response rate from private clinics in these studies was between 26.0% and 33.0%.1,2 The same observation was made in Australia in the BEACH survey, with only 25.9% and 25.2% of the contactable general practitioners agreed and completed the survey in 2013-14 and 2012-13 respectively.3,4

31Chapter 3 : Response Rate

CHAPTER 3: RESPONSE RATE

3.1 RESPONSE RATE

This chapter describes the survey sample and the response rate for NMCS 2014. A total of 139 public clinics and 1,002 private clinics were sampled in NMCS 2014. The clinics are listed in Appendix 5. The response rates were calculated as the number of clinics that responded by returning the NMCS 2014 questionnaire divided by the number of clinics in the sample. Table 3.1.1 shows the number of clinics sampled, number of clinics responded to the survey and the clinic response rate for each state or federal territory.

Table 3.1.1: Total number of clinics sampled and responded for NMCS 2014


Public

Private


Number of clinics

responded

Response rate (%)


Number of clinics

responded

Response rate (%)

Johor 11 10 90.9

117 43 36.7

Kedah 7 7 100.0

55 22 40.0

Kelantan 7 7 100.0

45 22 48.9

Melaka 26 23 88.5

31 14 45.2


40 19 47.5

Pahang 6 6 100.0

42 18 42.9

Perak 11 11 100.0

73 30 41.1

Perlis 9 7 77.8

10 7 70.0


70 33 47.1

Sabah & WP Labuan 9 7 77.8

65 26 40.0

Sarawak 10 10 100.0

34 16 47.1

Selangor & WP Putrajaya 15 14 93.3

270 102 37.8


30 18 60.0

WP Kuala Lumpur 12 12 100.0

120 46 38.3

Total 139 129 92.8

1,002 416 41.5

Overall, more than three quarters of public clinics from thirteen states and three federal territories responded to NMCS 2014. The maximum response rate was 100.0% while the minimum is 77.8%, which gave the overall response rate of 92.8% in public sector. As for private sector, the lowest response rate was only 37.6%, bringing the overall response rate to 41.5%, in spite of our fervent attempts to persuade the GPs to participate.

Response rates by encounters are reported in Table 3.1.2. These response rates were calculated as the number of encounters that were recorded for NMCS 2014 divided by the expected number of encounters in the sample for each stratum to form a national representative data.

Table 3.1.2: Total number of encounters received for NMCS 2014


Public

Private


expected

Number of encounter responded

Response rate (%)


expected

Number of

encounter responded

Response rate (%)

Johor 1,164 1,753 100.0

3,597 1,295 36.0

Kedah 746 627 84.0

1,694 803 47.4

Kelantan 778 621 79.8

1,395 607 43.5

Melaka 450 2,357 100.0

941 325 34.5


1,223 739 60.4

Pahang 698 494 70.8

1,277 532 41.7

Perak 1,174 1,375 100.0

2,228 807 36.2

Perlis 152 581 100.0

320 323 100.0


2,139 917 42.9

Sabah& WP Labuan 927 709 76.5

1,997 736 36.9

Sarawak 1,062 947 89.2

1,056 567 53.7

Selangor & WP Putrajaya 1,627 1,707 100.0

8,265 2,691 32.6


929 575 61.9

WP Kuala Lumpur 397 2,612 100.0

3,671 1,200 32.7

Total 10,951 15,470 100.0

30,732 12,117 39.4

Response rate by encounters obtained from public clinics of all thirteen states and three federal territories were overwhelming and some exceeded 100.0%. WP Kuala Lumpur recorded the highest response rate with more than six times encounters that were required for the study, while the lowest was 70.8% from Pahang. As for private sector, the minimum response rate by encounters was 32.7% from WP Kuala Lumpur, while Perlis recorded the maximum response rate of 100.0%. The overall response rate for public and private sector was 100.0% and 39.4%, respectively.

The low response rate however, has already been anticipated and accounted for. When calculating sample size, the sampling matrix had included an estimation of a 30.0% drop-out rate from the public and a 70.0% drop-out rate from the private sector.

This huge estimated rate of drop-out from the private sector was expected based on previous studies conducted comparing public and private health sectors in Malaysia. The reported response rate from private clinics in these studies was between 26.0% and 33.0%.1,2 The same observation was made in Australia in the BEACH survey, with only 25.9% and 25.2% of the contactable general practitioners agreed and completed the survey in 2013-14 and 2012-13 respectively.3,4


3.2 THE ENCOUNTERS

A total of 27,813 encounters were collected for NMCS 2014. Of these, 226 encounters were excluded from analysis; 61 of incomplete forms and 165 with data inconsistencies. The final encounters for analysis were 27,587; 15,470 from public and 12,117 from private. The dataset were weighted to adjust for over and under representativeness of data (see Section 2.5). Table 3.2.1 shows the observed and weighted total for each data element. The final weighted patient encounters were 325,818, and the results are presented as weighted estimates in this report.

Table 3.2.1: Observed and weighted dataset for NMCS 2014

Variable Observed

Weighted

Overall Public Private


Encounters 27,587 15,470 12,117

325,818 131,624 194,194

Reasons for encounter 50,642 29,478 21,164

597,563 252,050 345,513

Diagnoses 38,151 23,760 14,391

436,743 203,868 232,874

Medications 70,711 38,296 32,415

864,552 327,087 537,465

Investigations 14,208 12,182 2,026

143,758 108,557 35,201

Advice/counselling and procedures 12,926 9,500 3,426

136,708 77,670 59,038

Follow-up and referrals 9,841 8,143 1,698

100,709 72,418 28,291

REFERENCES

1. Teng CL, Tong SF, Khoo EM, Lee V, Zailinawati AH, Mimi O, et al. Antibiotics for URTI and UTI – prescribing in Malaysian primary care settings. Aust Fam Physician. 2011 May;40(5):325-9.

2. Mimi O, Tong SF, Nordin S, Teng CL, Khoo EM, Abdul-Rahman A, et al. A comparison of morbidity patterns in public and private primary care clinics in Malaysia. Malays Fam Physician. 2011 Apr 30;6(1):19-25.

3. Britt H, Miller GC, Henderson J, Bayram C, Harrison C, Valenti L, et al. General practice activity in Australia 2013–14. Sydney (Australia): Sydney University Press; 2014. (General practice series; no. 36).

4. Britt H, Miller GC, Henderson J, Bayram C, Valenti L, Harrison C, et al. General practice activity in Australia 2012–13. Sydney (Australia): Sydney University Press; 2013. (General practice series; no. 33).

CHAPTER fourThe Practices

3.2 THE ENCOUNTERS

A total of 27,813 encounters were collected for NMCS 2014. Of these, 226 encounters were excluded from analysis; 61 of incomplete forms and 165 with data inconsistencies. The final encounters for analysis were 27,587; 15,470 from public and 12,117 from private. The dataset were weighted to adjust for over and under representativeness of data (see Section 2.5). Table 3.2.1 shows the observed and weighted total for each data element. The final weighted patient encounters were 325,818, and the results are presented as weighted estimates in this report.

Table 3.2.1: Observed and weighted dataset for NMCS 2014

Variable Observed

Weighted



Encounters 27,587 15,470 12,117

325,818 131,624 194,194

Reasons for encounter 50,642 29,478 21,164

597,563 252,050 345,513

Diagnoses 38,151 23,760 14,391

436,743 203,868 232,874

Medications 70,711 38,296 32,415

864,552 327,087 537,465

Investigations 14,208 12,182 2,026

143,758 108,557 35,201

Advice/counselling and procedures 12,926 9,500 3,426

136,708 77,670 59,038

Follow-up and referrals 9,841 8,143 1,698

100,709 72,418 28,291

REFERENCES

1. Teng CL, Tong SF, Khoo EM, Lee V, Zailinawati AH, Mimi O, et al. Antibiotics for URTI and UTI – prescribing in Malaysian primary care settings. Aust Fam Physician. 2011 May;40(5):325-9.

2. Mimi O, Tong SF, Nordin S, Teng CL, Khoo EM, Abdul-Rahman A, et al. A comparison of morbidity patterns in public and private primary care clinics in Malaysia. Malays Fam Physician. 2011 Apr 30;6(1):19-25.

3. Britt H, Miller GC, Henderson J, Bayram C, Harrison C, Valenti L, et al. General practice activity in Australia 2013–14. Sydney (Australia): Sydney University Press; 2014. (General practice series; no. 36).

4. Britt H, Miller GC, Henderson J, Bayram C, Valenti L, Harrison C, et al. General practice activity in Australia 2012–13. Sydney (Australia): Sydney University Press; 2013. (General practice series; no. 33).


CHAPTER 4: THE PRACTICES

This chapter reports the characteristics of public and private primary care clinics. The data was obtained through the healthcare provider profile form (Appendix 2), which was completed by the healthcare providers during data collection. Information captured included the practice characteristics and the sociodemographic characteristics of the healthcare providers, the latter of which will be reported in the next chapter.

4.1 PRIMARY CARE CLINICS IN MALAYSIA

Primary care services in Malaysia exist in two parallel systems—a heavily subsidised public sector and a private sector largely funded by out-of-pocket payments. According to data from the Ministry of Health Malaysia, there were 911 public clinics and 5,646 private clinics in Malaysia in 2012 (see Chapter 2), corresponding to a public-to-private ratio of 1:6.

With a population of about 29.2 million, the density of primary care clinics in Malaysia was 2.2 clinics per 10,000 population in 2012 (Figure 4.1.1), with the highest density recorded in WP Kuala Lumpur (4.1 clinics per 10,000 population). Majority of the more urbanised West Coast states (Selangor, Pulau Pinang, Negeri Sembilan, Melaka, Perak and Johor) had a density of 2.3–2.8 clinics per 10,000 population. In comparison, Singapore reported a density of 2.8 general practitioner practices per 10,000 population in 2013,1,2 whereas Australia had 3.3 general practitioner practices per 10,000 population in 2011.3,4

Figure 4.1.1: Number of primary care clinics per 10,000 population in 2012

2.2 4.1

2.8 2.7 2.6

2.6 2.5

2.3 1.8 1.8 1.8 1.8

1.7 1.6

1.6 1.1 1.1

0 1 2 3 4 5

Malaysia WP Kuala Lumpur

Selangor Pulau Pinang

Negeri Sembilan Melaka

Perak Johor

Pahang Kedah

Terengganu WP Putrajaya

Sarawak Perlis

Kelantan Sabah

WP Labuan

Number of clinics per 10,000 population

In the NMCS 2014 survey, a total of 129 public clinics out of 139 sampled (92.8%) and 409 private clinics out of 1,002 sampled (40.8%) responded to the healthcare provider profile questionnaire. These clinics were nationally representative by sector with regard to facilities, services and workforce, and survey data were weighted to produce unbiased national estimates.

4.2 ATTENDANCES

Private clinics outnumber public clinics in quantity nationwide. However, data from NMCS 2014 show that more patients were seen in the public clinics, which reported a median attendance rate of 111.5 presentations per day (IQR: 71.9–264.3), compared to 33.0 per day (IQR: 25.0–50.0) in private clinics. These findings extend our previous results from 2012, which showed similar patterns of primary care attendances in all five states studied.5

4.3 OPERATING DAYS AND HOURS

Public clinics

Table 4.3.1 shows the operating days and hours of public clinics in 2014.

• As with other government establishments in Malaysia, a large majority (82.8%) of public clinics operated five days in a week (Monday to Friday).

• About one-eighth (12.6%) of the public clinics reported operating seven days per week, while the remaining 4.7% had a six-day-per-week operation.

• Slightly more than half (52.1%) of the public clinics operated during the standard office hours (between 8.00 a.m. to 5.00 p.m.) only.

• The remaining 47.9% of public clinics also provided after-hours services in addition to the standard-hour operation. On-call services (at least one healthcare provider could be called to help in cases of emergency) were provided in 39.6% of clinics, while extended-hours services (regular clinic operation beyond the standard office hours) were available in 8.5% of the clinics.

Table 4.3.1: Operating days and hours of public clinics in 2014

Clinic operation Unweighted

count (n = 129)

Weighted count

(n = 664)

Percent of clinics (95% CI) (n = 664)

Operating days

5 days/week 110 550 82.8 (75.4–90.2)

6 days/week 8 31 4.7 (1.1–8.2)

7 days/week 11 83 12.6 (5.8–19.3)

Operating hours

Office hours 77 346 52.1 (42.5–61.7)

Office hours + on call services 37 262 39.4 (30.3–48.5)

Office hours + extended hours 14 55 8.3 (3.5–13.1)

Office hours + extended hours + on call services 1 1 0.2 (0.0–0.4)

35Chapter 4 : The Practices

CHAPTER 4: THE PRACTICES

This chapter reports the characteristics of public and private primary care clinics. The data was obtained through the healthcare provider profile form (Appendix 2), which was completed by the healthcare providers during data collection. Information captured included the practice characteristics and the sociodemographic characteristics of the healthcare providers, the latter of which will be reported in the next chapter.

4.1 PRIMARY CARE CLINICS IN MALAYSIA

Primary care services in Malaysia exist in two parallel systems—a heavily subsidised public sector and a private sector largely funded by out-of-pocket payments. According to data from the Ministry of Health Malaysia, there were 911 public clinics and 5,646 private clinics in Malaysia in 2012 (see Chapter 2), corresponding to a public-to-private ratio of 1:6.

With a population of about 29.2 million, the density of primary care clinics in Malaysia was 2.2 clinics per 10,000 population in 2012 (Figure 4.1.1), with the highest density recorded in WP Kuala Lumpur (4.1 clinics per 10,000 population). Majority of the more urbanised West Coast states (Selangor, Pulau Pinang, Negeri Sembilan, Melaka, Perak and Johor) had a density of 2.3–2.8 clinics per 10,000 population. In comparison, Singapore reported a density of 2.8 general practitioner practices per 10,000 population in 2013,1,2 whereas Australia had 3.3 general practitioner practices per 10,000 population in 2011.3,4

Figure 4.1.1: Number of primary care clinics per 10,000 population in 2012

2.2 4.1

2.8 2.7 2.6

2.6 2.5

2.3 1.8 1.8 1.8 1.8

1.7 1.6

1.6 1.1 1.1

0 1 2 3 4 5

Malaysia WP Kuala Lumpur

Selangor Pulau Pinang

Negeri Sembilan Melaka

Perak Johor

Pahang Kedah

Terengganu WP Putrajaya

Sarawak Perlis

Kelantan Sabah

WP Labuan

Number of clinics per 10,000 population

In the NMCS 2014 survey, a total of 129 public clinics out of 139 sampled (92.8%) and 409 private clinics out of 1,002 sampled (40.8%) responded to the healthcare provider profile questionnaire. These clinics were nationally representative by sector with regard to facilities, services and workforce, and survey data were weighted to produce unbiased national estimates.

4.2 ATTENDANCES

Private clinics outnumber public clinics in quantity nationwide. However, data from NMCS 2014 show that more patients were seen in the public clinics, which reported a median attendance rate of 111.5 presentations per day (IQR: 71.9–264.3), compared to 33.0 per day (IQR: 25.0–50.0) in private clinics. These findings extend our previous results from 2012, which showed similar patterns of primary care attendances in all five states studied.5

4.3 OPERATING DAYS AND HOURS

Public clinics

Table 4.3.1 shows the operating days and hours of public clinics in 2014.

• As with other government establishments in Malaysia, a large majority (82.8%) of public clinics operated five days in a week (Monday to Friday).

• About one-eighth (12.6%) of the public clinics reported operating seven days per week, while the remaining 4.7% had a six-day-per-week operation.

• Slightly more than half (52.1%) of the public clinics operated during the standard office hours (between 8.00 a.m. to 5.00 p.m.) only.

• The remaining 47.9% of public clinics also provided after-hours services in addition to the standard-hour operation. On-call services (at least one healthcare provider could be called to help in cases of emergency) were provided in 39.6% of clinics, while extended-hours services (regular clinic operation beyond the standard office hours) were available in 8.5% of the clinics.

Table 4.3.1: Operating days and hours of public clinics in 2014

Clinic operation Unweighted

count (n = 129)

Weighted count

(n = 664)

Percent of clinics (95% CI) (n = 664)

Operating days

5 days/week 110 550 82.8 (75.4–90.2)

6 days/week 8 31 4.7 (1.1–8.2)

7 days/week 11 83 12.6 (5.8–19.3)

Operating hours

Office hours 77 346 52.1 (42.5–61.7)

Office hours + on call services 37 262 39.4 (30.3–48.5)

Office hours + extended hours 14 55 8.3 (3.5–13.1)

Office hours + extended hours + on call services 1 1 0.2 (0.0–0.4)


Private clinics

The operating days and hours of private clinics are shown in Table 4.3.2. Note that private clinics which operated less than five days in a week were excluded from NMCS 2014. As a result, the operating days and hours of these clinics were not captured by the survey.

• More than half (54.0%) of the clinics in the private sector operated six days per week. • Clinics which operated Monday through Sunday represented 40.2% of all private clinics, while only

5.8% of the private clinics operated five days in a week. • Only 5.0% of the clinics in the private sector provided 24-hour services.

Table 4.3.2: Operating days and hours of private clinics in 2014

Clinic operation Unweighted count (n = 409)

Weighted count (n = 4,810)

Percent of clinics (95% CI)

(n = 4,810)

Operating days

5 days/week 24 280 5.8 (3.6–8.0)

6 days/week 222 2,597 54.0 (49.3–58.7)

7 days/week 163 1,933 40.2 (35.5–44.9)

Operating hours

< 24 hours/day 390 4,570 95.0 (92.9–97.1)

24 hours/day 19 240 5.0 (2.9–7.1)

4.4 TYPE OF PRACTICE

• All public clinics were collaborative practices staffed with multiple healthcare providers who worked under salaried employment with the government.

• About a quarter (24.7%) of the private clinics operated as group practices, while the remaining were solo practices (Table 4.4.1). A similar figure has been reported in our previous report.5

Table 4.4.1: Type of practice for private clinics in 2014

Type of practice Unweighted count

(n = 409) Weighted count

(n = 4,810)


(n = 4,810)

Group 98 1,188 24.7 (20.6–28.8)

Individual 311 3,622 75.3 (71.2–79.4)

4.5 PROVIDER WORKLOAD

• Overall, the median number of patients seen per full-time-equivalent (FTE) doctor in the private sector was 25.9 (IQR: 17.1–40.0) patients per day.

• The public clinic attendances were recorded at the clinic level and could not be disaggregated by healthcare providers. Hence, the patient volume per FTE doctor could not be calculated for the public clinics.

4.6 COMPUTER USE

The implementation of health information technology, such as electronic health records, may appear difficult and cumbersome. However, significant benefits can be reaped from the adoption of health information technology, including improved technical efficiency, increased adherence to guidelines, enhanced disease surveillance, reduced medication errors, decreased utilisation of care and reduction in healthcare costs.6,7

Only 19.4% of public clinics (n = 129) reported having a functional computer system in the practice. In contrast, 71.6% of the private clinics surveyed (n = 3,443) reported the use of computers in the practice. Figure 4.6.1 illustrates the extent of computer use in each sector.

• Amongst the clinics which reported the use of computers, only 18.1% of public clinics and 36.6% of private clinics were fully computerised.

• In the public sector, the computer system was mainly used for registration (83.7%) and medical record keeping (83.3%) purposes, whereas in the private sector the main reason for using a computer system was for billing purpose (79.6%).

Figure 4.6.1: Types of computer use in primary care by sector in 2014

18.1 18.1

63.8

83.3 83.7

27.2 36.6

79.6

44.7

57.3

69.8

16.0

0

10

20

30

40

50

60

70

80

90

100

Fully computerised

Billing Dispensing Medical records

Registration Others

Per

cen

t o

f cl

inic

s (%

)

Public Private

37

Private clinics

The operating days and hours of private clinics are shown in Table 4.3.2. Note that private clinics which operated less than five days in a week were excluded from NMCS 2014. As a result, the operating days and hours of these clinics were not captured by the survey.

• More than half (54.0%) of the clinics in the private sector operated six days per week. • Clinics which operated Monday through Sunday represented 40.2% of all private clinics, while only

5.8% of the private clinics operated five days in a week. • Only 5.0% of the clinics in the private sector provided 24-hour services.

Table 4.3.2: Operating days and hours of private clinics in 2014

Clinic operation Unweighted count (n = 409)



(n = 4,810)

Operating days

5 days/week 24 280 5.8 (3.6–8.0)

6 days/week 222 2,597 54.0 (49.3–58.7)

7 days/week 163 1,933 40.2 (35.5–44.9)

Operating hours

< 24 hours/day 390 4,570 95.0 (92.9–97.1)

24 hours/day 19 240 5.0 (2.9–7.1)

4.4 TYPE OF PRACTICE

• All public clinics were collaborative practices staffed with multiple healthcare providers who worked under salaried employment with the government.

• About a quarter (24.7%) of the private clinics operated as group practices, while the remaining were solo practices (Table 4.4.1). A similar figure has been reported in our previous report.5

Table 4.4.1: Type of practice for private clinics in 2014

Type of practice Unweighted count

(n = 409) Weighted count

(n = 4,810)


(n = 4,810)

Group 98 1,188 24.7 (20.6–28.8)

Individual 311 3,622 75.3 (71.2–79.4)

4.5 PROVIDER WORKLOAD

• Overall, the median number of patients seen per full-time-equivalent (FTE) doctor in the private sector was 25.9 (IQR: 17.1–40.0) patients per day.

• The public clinic attendances were recorded at the clinic level and could not be disaggregated by healthcare providers. Hence, the patient volume per FTE doctor could not be calculated for the public clinics.

4.6 COMPUTER USE

The implementation of health information technology, such as electronic health records, may appear difficult and cumbersome. However, significant benefits can be reaped from the adoption of health information technology, including improved technical efficiency, increased adherence to guidelines, enhanced disease surveillance, reduced medication errors, decreased utilisation of care and reduction in healthcare costs.6,7

Only 19.4% of public clinics (n = 129) reported having a functional computer system in the practice. In contrast, 71.6% of the private clinics surveyed (n = 3,443) reported the use of computers in the practice. Figure 4.6.1 illustrates the extent of computer use in each sector.

• Amongst the clinics which reported the use of computers, only 18.1% of public clinics and 36.6% of private clinics were fully computerised.

• In the public sector, the computer system was mainly used for registration (83.7%) and medical record keeping (83.3%) purposes, whereas in the private sector the main reason for using a computer system was for billing purpose (79.6%).

Figure 4.6.1: Types of computer use in primary care by sector in 2014

18.1 18.1

63.8

83.3 83.7

27.2 36.6

79.6

44.7

57.3

69.8

16.0

0

10

20

30

40

50

60

70

80

90

100

Fully computerised

Billing Dispensing Medical records

Registration Others

Per

cen

t o

f cl

inic

s (%

)

Public Private


Figure 4.7.1: Primary care clinics with family medicine specialists by sector in 2014

REFERENCES

1. Singapore Department of Statistics. Population trends 2014. Singapore: Singapore Ministry of Trade and Industry, Department of Statistics; 2014.

2. Primary healthcare services [Internet]. Singapore: Singapore Ministry of Health; [updated 2015 Jan 2, cited 2015 Sep 13]; [about 1 screen]. Available from: https://www.moh.gov.sg/content/moh_web/home/our_healthcare_system/Healthcare_Services/Primary_Care.html

3. Hordacre AL, Howard S, Moretti C, Kalucy E. Moving ahead. Report of the 2006–2007 Annual Survey of Divisions of General Practice. Adelaide (Australia): Primary Health Care Research and Information Service; 2008. Supported by the Australian Government Department of Health and Ageing.

4. Australian Government Department of Immigration and Border Protection. The people of Australia: statistics from the 2011 Census. Canberra (Australia): Department of Immigration and Border Protection (AU); 2014.

5. Hwong WY, Sivasampu S, Aisyah A, Shantha Kumar C, Goh PP, Hisham AN, editors. National Healthcare Establishment & Workforce Statistics (Primary Care) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 44 p. Report No.: NCRC/HSU/2013.2. Grant No.: NMRR-09-842-4718. Supported by the Ministry of Health Malaysia.

6. DesRoches CM, Campbell EG, Rao SR, Donelan K, Ferris TG, Jha A, et al. Electronic health records in ambulatory care — a national survey of physicians. N Engl J Med. 2008 Jul 3;359(1):50-60.

7. Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006 May 16;144(10):742-52.

59.9

97.1 40.1

2.9

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f cl

inic

s (%

)

Yes

No

4.7 WORKFORCE

Information regarding the workforce, which was gathered through the healthcare provider profile questionnaire (see Section 3 of Appendix 2), is reported here. Table 4.7.1 shows the distribution of primary care workforce in the public and private sectors by their designation. Doctors with postgraduate qualifications other than family medicine specialists (FMS) were included in the non-FMS category of doctors.

• A median of three doctors, six staff nurses, three assistant medical officers, seven community nurses and one pharmacist were working in a public clinic in 2014.

• In the private clinics, a median of one doctor and three clinic assistants were present in each clinic.

Table 4.7.1: Healthcare workforce by sector in primary care clinics in 2014

Designation

Public Private

Unweighted count

Weighted count

Number of personnel per clinic,

median (IQR)

Unweighted count

Weighted count


median (IQR)

FMS 58 268 0 (0–1) 12 140 0 (0–0)

Doctor 606 2,734 3 (2–6) 659 7,856 1 (1–2)

Assistant medical officer 433 2,038 3 (2–3) 5 49 0 (0–0)

Pharmacist 338 1,394 1 (1–2) 4 33 0 (0–0)

Nurses

Staff nurse 1,029 4,699 6 (4–9) 233 2,922 0 (0–0)

Community nurse 1,341 6,398 7 (5–12)

6 83 0 (0–0)

Clinic assistant 4 26 NA

1,363 15,667 3 (2–4)

Note: FMS – Family medicine specialist; NA – Not applicable.

Family medicine specialists (FMS) constitute an integral part of the provision of quality primary care service to the public. The distribution of clinics with family medicine specialist is shown in Figure 4.7.1. Other doctors with postgraduate qualifications will be discussed in the next chapter.

• Two out of every five public clinics had a family medicine specialist in the practice. • In comparison, only three out of 100 private clinics reported having a family medicine specialist in

the practice.

39

Figure 4.7.1: Primary care clinics with family medicine specialists by sector in 2014

REFERENCES

1. Singapore Department of Statistics. Population trends 2014. Singapore: Singapore Ministry of Trade and Industry, Department of Statistics; 2014.

2. Primary healthcare services [Internet]. Singapore: Singapore Ministry of Health; [updated 2015 Jan 2, cited 2015 Sep 13]; [about 1 screen]. Available from: https://www.moh.gov.sg/content/moh_web/home/our_healthcare_system/Healthcare_Services/Primary_Care.html

3. Hordacre AL, Howard S, Moretti C, Kalucy E. Moving ahead. Report of the 2006–2007 Annual Survey of Divisions of General Practice. Adelaide (Australia): Primary Health Care Research and Information Service; 2008. Supported by the Australian Government Department of Health and Ageing.

4. Australian Government Department of Immigration and Border Protection. The people of Australia: statistics from the 2011 Census. Canberra (Australia): Department of Immigration and Border Protection (AU); 2014.

5. Hwong WY, Sivasampu S, Aisyah A, Shantha Kumar C, Goh PP, Hisham AN, editors. National Healthcare Establishment & Workforce Statistics (Primary Care) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 44 p. Report No.: NCRC/HSU/2013.2. Grant No.: NMRR-09-842-4718. Supported by the Ministry of Health Malaysia.

6. DesRoches CM, Campbell EG, Rao SR, Donelan K, Ferris TG, Jha A, et al. Electronic health records in ambulatory care — a national survey of physicians. N Engl J Med. 2008 Jul 3;359(1):50-60.

7. Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006 May 16;144(10):742-52.

59.9

97.1 40.1

2.9

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f cl

inic

s (%

)

Yes

No

Chapter 4 : The Practices

4.7 WORKFORCE

Information regarding the workforce, which was gathered through the healthcare provider profile questionnaire (see Section 3 of Appendix 2), is reported here. Table 4.7.1 shows the distribution of primary care workforce in the public and private sectors by their designation. Doctors with postgraduate qualifications other than family medicine specialists (FMS) were included in the non-FMS category of doctors.

• A median of three doctors, six staff nurses, three assistant medical officers, seven community nurses and one pharmacist were working in a public clinic in 2014.

• In the private clinics, a median of one doctor and three clinic assistants were present in each clinic.

Table 4.7.1: Healthcare workforce by sector in primary care clinics in 2014

Designation

Public Private

Unweighted count

Weighted count


median (IQR)

Unweighted count

Weighted count


median (IQR)

FMS 58 268 0 (0–1) 12 140 0 (0–0)

Doctor 606 2,734 3 (2–6) 659 7,856 1 (1–2)

Assistant medical officer 433 2,038 3 (2–3) 5 49 0 (0–0)

Pharmacist 338 1,394 1 (1–2) 4 33 0 (0–0)

Nurses

Staff nurse 1,029 4,699 6 (4–9) 233 2,922 0 (0–0)

Community nurse 1,341 6,398 7 (5–12)

6 83 0 (0–0)

Clinic assistant 4 26 NA

1,363 15,667 3 (2–4)

Note: FMS – Family medicine specialist; NA – Not applicable.

Family medicine specialists (FMS) constitute an integral part of the provision of quality primary care service to the public. The distribution of clinics with family medicine specialist is shown in Figure 4.7.1. Other doctors with postgraduate qualifications will be discussed in the next chapter.

• Two out of every five public clinics had a family medicine specialist in the practice. • In comparison, only three out of 100 private clinics reported having a family medicine specialist in

the practice.

CHAPTER fiveThe Doctors


Table 5.1.1: Characteristics of primary care doctors in 2014

Characteristics Unweighted

count (n = 936)

Weighted count

(n = 10,964)

Percent of doctors (95% CI)

Sector

Public 490 2,992 27.3 (24.0–30.6)

Private 446 7,972 72.7 (69.4–76.0)

Gender

Male 426 5,668 51.9 (47.2–56.6)

Female 508 5,263 48.2 (43.4–52.9)

Missinga 2 33 -

Age (years)

25–34 392 2,714 25.1 (22.0–28.3)

35–44 185 2,444 22.6 (18.8–26.5)

45–54 190 3,313 30.7 (25.6–35.7)

55–64 120 1,634 15.1 (12.2–18.0)

≥ 65 40 696 6.5 (4.0–8.9)

Missinga 9 162 -

Experience in primary care (years)

< 5 383 2,790 25.8 (22.5–29.2)

5–9 122 1,312 12.2 (9.2–15.1)

≥ 10 422 6,699 62.0 (57.8–66.3)

Missinga 9 162 -

Place of graduation

Local 456 5,314 48.5 (43.8–53.2)

Foreign 479 5,641 51.5 (46.8–56.2)

Missinga 1 9 -

Postgraduate qualification

With postgraduate qualifications 120 1,717 15.7 (12.3–19.0)

Masters in family medicine 25 135 7.9 (4.2–11.6)

MAFP/FRACGP 8 99 5.7 (1.2–10.3)

MRCGP/FRCGP 4 54 3.2 (0.0–6.3)

Diploma in family medicine 31 486 28.3 (18.1–38.5)

Others 55 1,017 59.2 (48.6–69.9)

No postgraduate qualifications 816 9,247 84.3 (81.0–87.7)

a Missing data excluded from analysis Note: MAFP – Membership of the Academy of Family Physicians of Malaysia; FRACGP – Fellowship of the Royal Australian College of General Practitioners; MRCGP – Membership of the Royal College of General Practitioners; FRCGP – Fellowship of the Royal College of General Practitioners; IQR – interquartile range.

Working hours per week

Median (IQR)

Overall - - 45 (40–50)

Public - - 44 (40–45)

Private - - 48 (40–55)



count (n = 936)

Weighted count

(n = 10,964)


Sector

Public 490 2,992 27.3 (24.0–30.6)

Private 446 7,972 72.7 (69.4–76.0)

Gender

Male 426 5,668 51.9 (47.2–56.6)

Female 508 5,263 48.2 (43.4–52.9)

Missinga 2 33 -

Age (years)

25–34 392 2,714 25.1 (22.0–28.3)

35–44 185 2,444 22.6 (18.8–26.5)

45–54 190 3,313 30.7 (25.6–35.7)

55–64 120 1,634 15.1 (12.2–18.0)

≥ 65 40 696 6.5 (4.0–8.9)

Missinga 9 162 -


< 5 383 2,790 25.8 (22.5–29.2)

5–9 122 1,312 12.2 (9.2–15.1)

≥ 10 422 6,699 62.0 (57.8–66.3)

Missinga 9 162 -

Place of graduation

Local 456 5,314 48.5 (43.8–53.2)

Foreign 479 5,641 51.5 (46.8–56.2)

Missinga 1 9 -




MAFP/FRACGP 8 99 5.7 (1.2–10.3)

MRCGP/FRCGP 4 54 3.2 (0.0–6.3)


Others 55 1,017 59.2 (48.6–69.9)




Median (IQR)

Overall - - 45 (40–50)

Public - - 44 (40–45)

Private - - 48 (40–55)

CHAPTER 5: THE DOCTORS

A recent report published by the Association of American Medical Colleges projected that by 2025 the primary care physician demand in the United States will grow by 17% and exceed supply by 12,500 to 31,100 physicians, with population aging and growth accounting for the majority of the increase in demand.1 Malaysia will likely face a similar trend of primary care doctor shortage, with the proportion of the elderly population (people aged 60 and over) projected to increase from 8.8% in 2014 to 12.2% in 2025 and 16.3% in 2040.2 A multi-pronged strategy, which should include innovation in healthcare delivery models, expansion of health professional training capacity, and greater and more effective use of health technologies, is required to address the looming crisis in primary care doctor shortage.

The supply and quality of primary healthcare workforce is highly influenced by the undergraduate and postgraduate education of health professionals. Malaysia has a well-established undergraduate health professional education system to support the development of primary care workforce.3 Postgraduate training programmes in family medicine have also been in existence since the late 1980s and early 1990s to support and promote the provision of comprehensive and continuing primary care.4 However, it was only in 1997 that the first graduates of the Masters in Family Medicine programme from the local universities entered the public system. Nonetheless, the rapid proliferation of training institutions for health professionals with limited quality assurance, the changing demography and disease burdens, the increasing feminisation of healthcare workforce, and the rising community expectations continue to present significant challenges to the delivery of quality primary healthcare.3,5-7

This chapter reports the characteristics of primary care doctors in both public and private sectors. The information on the participating doctors was acquired through the healthcare provider profile questionnaire (Appendix 2).

5.1 CHARACTERISTICS OF THE DOCTORS

A total of 936 doctors from public (n = 490) and private clinics (n = 446) participated in NMCS 2014. Nine (1.0%) of the returned healthcare provider profile questionnaires included incomplete responses to survey items. Analyses were performed using all available data, with missing values excluded from the analysis of the corresponding parameters. The survey responses were weighted to produce national estimates.

Table 5.1.1 shows the characteristics of primary care doctors in Malaysia for 2014.

• The majority (72.7%) of primary care doctors were working in the private sector. • Slightly more than half (51.9%) of the doctors were male. • Nearly half (47.7%) of the doctors were less than 45 years old (median age: 45.0 years, IQR: 34–53

years). • The majority (62.0%) of the doctors had been working in the primary care setting for 10 years or

more (median: 13 years, IQR: 4–21 years). • Overseas trained doctors accounted for the greater proportion (51.5%) of the primary care doctor

workforce. • Nearly one-sixth (15.7%) of the doctors had at least one postgraduate qualification. • Median working hours was 45 hours per week (IQR: 40–50 hours per week).

43



count (n = 936)

Weighted count

(n = 10,964)


Sector

Public 490 2,992 27.3 (24.0–30.6)

Private 446 7,972 72.7 (69.4–76.0)

Gender

Male 426 5,668 51.9 (47.2–56.6)

Female 508 5,263 48.2 (43.4–52.9)

Missinga 2 33 -

Age (years)

25–34 392 2,714 25.1 (22.0–28.3)

35–44 185 2,444 22.6 (18.8–26.5)

45–54 190 3,313 30.7 (25.6–35.7)

55–64 120 1,634 15.1 (12.2–18.0)

≥ 65 40 696 6.5 (4.0–8.9)

Missinga 9 162 -


< 5 383 2,790 25.8 (22.5–29.2)

5–9 122 1,312 12.2 (9.2–15.1)

≥ 10 422 6,699 62.0 (57.8–66.3)

Missinga 9 162 -

Place of graduation

Local 456 5,314 48.5 (43.8–53.2)

Foreign 479 5,641 51.5 (46.8–56.2)

Missinga 1 9 -




MAFP/FRACGP 8 99 5.7 (1.2–10.3)

MRCGP/FRCGP 4 54 3.2 (0.0–6.3)


Others 55 1,017 59.2 (48.6–69.9)




Median (IQR)

Overall - - 45 (40–50)

Public - - 44 (40–45)

Private - - 48 (40–55)



count (n = 936)

Weighted count

(n = 10,964)


Sector

Public 490 2,992 27.3 (24.0–30.6)

Private 446 7,972 72.7 (69.4–76.0)

Gender

Male 426 5,668 51.9 (47.2–56.6)

Female 508 5,263 48.2 (43.4–52.9)

Missinga 2 33 -

Age (years)

25–34 392 2,714 25.1 (22.0–28.3)

35–44 185 2,444 22.6 (18.8–26.5)

45–54 190 3,313 30.7 (25.6–35.7)

55–64 120 1,634 15.1 (12.2–18.0)

≥ 65 40 696 6.5 (4.0–8.9)

Missinga 9 162 -


< 5 383 2,790 25.8 (22.5–29.2)

5–9 122 1,312 12.2 (9.2–15.1)

≥ 10 422 6,699 62.0 (57.8–66.3)

Missinga 9 162 -

Place of graduation

Local 456 5,314 48.5 (43.8–53.2)

Foreign 479 5,641 51.5 (46.8–56.2)

Missinga 1 9 -




MAFP/FRACGP 8 99 5.7 (1.2–10.3)

MRCGP/FRCGP 4 54 3.2 (0.0–6.3)


Others 55 1,017 59.2 (48.6–69.9)




Median (IQR)

Overall - - 45 (40–50)

Public - - 44 (40–45)

Private - - 48 (40–55)

Chapter 5 : The Doctors

CHAPTER 5: THE DOCTORS

A recent report published by the Association of American Medical Colleges projected that by 2025 the primary care physician demand in the United States will grow by 17% and exceed supply by 12,500 to 31,100 physicians, with population aging and growth accounting for the majority of the increase in demand.1 Malaysia will likely face a similar trend of primary care doctor shortage, with the proportion of the elderly population (people aged 60 and over) projected to increase from 8.8% in 2014 to 12.2% in 2025 and 16.3% in 2040.2 A multi-pronged strategy, which should include innovation in healthcare delivery models, expansion of health professional training capacity, and greater and more effective use of health technologies, is required to address the looming crisis in primary care doctor shortage.

The supply and quality of primary healthcare workforce is highly influenced by the undergraduate and postgraduate education of health professionals. Malaysia has a well-established undergraduate health professional education system to support the development of primary care workforce.3 Postgraduate training programmes in family medicine have also been in existence since the late 1980s and early 1990s to support and promote the provision of comprehensive and continuing primary care.4 However, it was only in 1997 that the first graduates of the Masters in Family Medicine programme from the local universities entered the public system. Nonetheless, the rapid proliferation of training institutions for health professionals with limited quality assurance, the changing demography and disease burdens, the increasing feminisation of healthcare workforce, and the rising community expectations continue to present significant challenges to the delivery of quality primary healthcare.3,5-7

This chapter reports the characteristics of primary care doctors in both public and private sectors. The information on the participating doctors was acquired through the healthcare provider profile questionnaire (Appendix 2).

5.1 CHARACTERISTICS OF THE DOCTORS

A total of 936 doctors from public (n = 490) and private clinics (n = 446) participated in NMCS 2014. Nine (1.0%) of the returned healthcare provider profile questionnaires included incomplete responses to survey items. Analyses were performed using all available data, with missing values excluded from the analysis of the corresponding parameters. The survey responses were weighted to produce national estimates.

Table 5.1.1 shows the characteristics of primary care doctors in Malaysia for 2014.

• The majority (72.7%) of primary care doctors were working in the private sector. • Slightly more than half (51.9%) of the doctors were male. • Nearly half (47.7%) of the doctors were less than 45 years old (median age: 45.0 years, IQR: 34–53

years). • The majority (62.0%) of the doctors had been working in the primary care setting for 10 years or

more (median: 13 years, IQR: 4–21 years). • Overseas trained doctors accounted for the greater proportion (51.5%) of the primary care doctor

workforce. • Nearly one-sixth (15.7%) of the doctors had at least one postgraduate qualification. • Median working hours was 45 hours per week (IQR: 40–50 hours per week).


5.2 GENDER

Figure 5.2.1 shows the distribution of public and private doctors by gender.

• Overall, more than half of the primary care doctors in Malaysia were males (51.9%). • More than two-thirds (70.5%) of the public primary care doctors were females. • In comparison, the proportion of female doctors in the private sector was 39.7%.

Figure 5.2.1: Distribution of public and private doctors by gender in 2014

Note: Missing data excluded from analysis.

29.5

60.3

70.5

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

Female

Male

39.7

5.3 AGE DISTRIBUTION

The age distribution of primary care doctors is shown in Figure 5.3.1.

• Most (30.7%) of the primary care doctors in Malaysia fell in the age group of 45–54 years, followed by those aged 25–34 years old (25.1%).

• The vast majority (79.9%) of doctors practising in the public sector were within the youngest age group (25–34 years). Only 6.2% of the public doctors were 45 years or older.

• In contrast, most (40.2%) of the doctors in the private sector were between the ages of 45 and 54, while those aged 25–34 years accounted for only 4.2% of doctors in private practices.

• The median age for doctors in public sector was 30 years old (IQR: 28–33 years), whereas the private sector was 49 years old (IQR: 43–57 years).

Figure 5.3.1: Distribution of public and private doctors by age group in 2014


5.4 EXPERIENCE

Figure 5.4.1 presents the distribution of public and private doctors by years of experience in primary care.

• Nearly two-thirds (62.0%) of the primary care doctors had practised in primary care for 10 years or more.

• The vast majority (74.8%) of the public sector doctors had less than five years of primary care experience. Conversely, in the private practice, 81.1% of the doctors had more than 10 years of experience in primary care.

8.9 0.3

20.8

5.9

40.2

13.9

26.0 79.9

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

25–34 years

35–44 years

45–54 years

55–64 years

≥ 65 years

4.2

45

5.2 GENDER

Figure 5.2.1 shows the distribution of public and private doctors by gender.

• Overall, more than half of the primary care doctors in Malaysia were males (51.9%). • More than two-thirds (70.5%) of the public primary care doctors were females. • In comparison, the proportion of female doctors in the private sector was 39.7%.

Figure 5.2.1: Distribution of public and private doctors by gender in 2014


29.5

60.3

70.5

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

Female

Male

39.7

5.3 AGE DISTRIBUTION

The age distribution of primary care doctors is shown in Figure 5.3.1.

• Most (30.7%) of the primary care doctors in Malaysia fell in the age group of 45–54 years, followed by those aged 25–34 years old (25.1%).

• The vast majority (79.9%) of doctors practising in the public sector were within the youngest age group (25–34 years). Only 6.2% of the public doctors were 45 years or older.

• In contrast, most (40.2%) of the doctors in the private sector were between the ages of 45 and 54, while those aged 25–34 years accounted for only 4.2% of doctors in private practices.

• The median age for doctors in public sector was 30 years old (IQR: 28–33 years), whereas the private sector was 49 years old (IQR: 43–57 years).

Figure 5.3.1: Distribution of public and private doctors by age group in 2014


5.4 EXPERIENCE

Figure 5.4.1 presents the distribution of public and private doctors by years of experience in primary care.

• Nearly two-thirds (62.0%) of the primary care doctors had practised in primary care for 10 years or more.

• The vast majority (74.8%) of the public sector doctors had less than five years of primary care experience. Conversely, in the private practice, 81.1% of the doctors had more than 10 years of experience in primary care.

8.9 0.3

20.8

5.9

40.2

13.9

26.0 79.9

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

25–34 years

35–44 years

45–54 years

55–64 years

≥ 65 years

4.2



Figure 5.4.1: Distribution of public and private doctors by years of experience in 2014


These findings were consistent with the age distribution of doctors in the public and private sectors. The public-private differences in age structure and experience could be plausibly attributed to the regulations governing medical practice in Malaysia. Medical graduates are required to fulfil several years of mandatory public service before they are allowed to move to private practice. This could have profound implications for patient care, with a greater burden being placed on senior doctors who remain in the public sector, while the expertise of the more experienced doctors is underutilised in the private sector.3

5.5 PLACE OF GRADUATION

Undergraduate medical degrees awarded by 33 local medical schools (11 public and 22 private) and 375 accredited foreign medical schools are recognised by the Malaysian Medical Council.8 Graduates from recognised institutions are eligible for registration to practise medicine in Malaysia, while international medical graduates who hold unrecognised degrees must pass the qualifying examination to be eligible for registration. Figure 5.5.1 shows the distribution of primary care doctors by their place of graduation.

• More than half (51.5%) of the doctors in primary care obtained their medical degree from a foreign country.

• The proportions of locally trained and overseas trained doctors were about the same within and across sectors, with 49.9% of doctors in the public sector and 48.0% of private sector doctors graduated from medical schools in Malaysia.

12.2

81.1

13.0

11.8

74.8 7.1

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

< 5 years

5–9 years

≥ 10 years

Figure 5.5.1: Distribution of public and private doctors by place of graduation in 2014


5.6 POSTGRADUATE QUALIFICATION

Primary care doctors may specialise in family medicine via Master of Family Medicine programmes, Membership of the Academy of Family Physicians of Malaysia (MAFP), Fellowship of the Royal Australian College of General Practitioners (FRACGP), or Membership or Fellowship of the Royal College of General Practitioners (MRCGP/FRCGP). To qualify as a family medicine specialist in Malaysia, the postgraduate degree must be credentialed by the Ministry of Health. Other postgraduate qualifications include Diploma in Family Medicine, diplomas in occupational health, dermatology, diagnostic ultrasound/radiography, master’s degrees in public health, and Membership of the Royal College of Physicians.

Figure 5.6.1 shows the distribution of primary care doctors by postgraduate qualification.

• Only 15.7% of the primary care doctors held at least one postgraduate qualification. • A higher proportion of doctors in the private sector held at least one postgraduate qualification

compared to the public sector (18.8% versus 7.3%, respectively).

50.1 52.0

49.9 48.0

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

Local

Foreign

47

Figure 5.4.1: Distribution of public and private doctors by years of experience in 2014


These findings were consistent with the age distribution of doctors in the public and private sectors. The public-private differences in age structure and experience could be plausibly attributed to the regulations governing medical practice in Malaysia. Medical graduates are required to fulfil several years of mandatory public service before they are allowed to move to private practice. This could have profound implications for patient care, with a greater burden being placed on senior doctors who remain in the public sector, while the expertise of the more experienced doctors is underutilised in the private sector.3

5.5 PLACE OF GRADUATION

Undergraduate medical degrees awarded by 33 local medical schools (11 public and 22 private) and 375 accredited foreign medical schools are recognised by the Malaysian Medical Council.8 Graduates from recognised institutions are eligible for registration to practise medicine in Malaysia, while international medical graduates who hold unrecognised degrees must pass the qualifying examination to be eligible for registration. Figure 5.5.1 shows the distribution of primary care doctors by their place of graduation.

• More than half (51.5%) of the doctors in primary care obtained their medical degree from a foreign country.

• The proportions of locally trained and overseas trained doctors were about the same within and across sectors, with 49.9% of doctors in the public sector and 48.0% of private sector doctors graduated from medical schools in Malaysia.

12.2

81.1

13.0

11.8

74.8 7.1

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

< 5 years

5–9 years

≥ 10 years

Figure 5.5.1: Distribution of public and private doctors by place of graduation in 2014


5.6 POSTGRADUATE QUALIFICATION

Primary care doctors may specialise in family medicine via Master of Family Medicine programmes, Membership of the Academy of Family Physicians of Malaysia (MAFP), Fellowship of the Royal Australian College of General Practitioners (FRACGP), or Membership or Fellowship of the Royal College of General Practitioners (MRCGP/FRCGP). To qualify as a family medicine specialist in Malaysia, the postgraduate degree must be credentialed by the Ministry of Health. Other postgraduate qualifications include Diploma in Family Medicine, diplomas in occupational health, dermatology, diagnostic ultrasound/radiography, master’s degrees in public health, and Membership of the Royal College of Physicians.

Figure 5.6.1 shows the distribution of primary care doctors by postgraduate qualification.

• Only 15.7% of the primary care doctors held at least one postgraduate qualification. • A higher proportion of doctors in the private sector held at least one postgraduate qualification

compared to the public sector (18.8% versus 7.3%, respectively).

50.1 52.0

49.9 48.0

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

Local

Foreign



Figure 5.6.1: Distribution of public and private doctors by postgraduate qualification in 2014

5.7 WORKING HOURS

• Overall, the median working hours per week for primary care doctors was 45.0 (IQR: 40.0–50.0). • The median working hours per week was 44.0 (IQR: 40.0–45.0) in public clinics and 48.0

(IQR: 40.0–55.0) in private clinics. • Generally, doctors in the public sector had more stable working hours compared with their

counterparts in the private sector, as reflected in the smaller IQR of hours worked per week for the public sector.

REFERENCES

1. Dall T, West T, Chakrabarti R, Lacobucci W; IHS Inc. The complexities of physician supply and demand: projections from 2013 to 2025. Washington, DC: Association of American Medical Colleges; 2015. 59 p.

2. Department of Statistics Malaysia. Population projections Malaysia 2010-2040. Kuala Lumpur (Malaysia): Department of Statistics (MY); 2013 Jan.

3. World Health Organization Regional Office for the Western Pacific. Human resources for health country profiles: Malaysia. Geneva (Switzerland): World Health Organization; 2014. 47 p.

4. Kwa SK. Family medicine specialisation in Malaysia [Internet]. Kuala Lumpur (Malaysia): Family Medicine Specialists Association of Malaysia; [cited 2015 Sep 18]; [about 4 screens]. Available from: http://fms-malaysia.org/home/?page_id=175

5. Truglio J1, Graziano M, Vedanthan R, Hahn S, Rios C, Hendel-Paterson B, et al. Global health and primary care: increasing burden of chronic diseases and need for integrated training. Mt Sinai J Med. 2012 Jul-Aug;79(4):464-74.

6. Hedden L, Barer ML, Cardiff K, McGrail KM, Law MR, Bourgeault IL. The implications of the feminization of the primary care physician workforce on service supply: a systematic review. Hum Resour Health. 2014 Jun 4;12:32.

7. KPMG. Health workforce in Australia and factors for current shortages. Adelaide (Australia): National Health Workforce Taskforce (AU); 2009 Apr.

8. Medical Act 1971. Second Schedule: List of Registrable Qualifications (Nov. 9, 2011).

92.7 81.2

7.3 18.8

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

With postgraduate qualification

No postgraduate qualification

Figure 5.6.1: Distribution of public and private doctors by postgraduate qualification in 2014

5.7 WORKING HOURS

• Overall, the median working hours per week for primary care doctors was 45.0 (IQR: 40.0–50.0). • The median working hours per week was 44.0 (IQR: 40.0–45.0) in public clinics and 48.0

(IQR: 40.0–55.0) in private clinics. • Generally, doctors in the public sector had more stable working hours compared with their

counterparts in the private sector, as reflected in the smaller IQR of hours worked per week for the public sector.

REFERENCES

1. Dall T, West T, Chakrabarti R, Lacobucci W; IHS Inc. The complexities of physician supply and demand: projections from 2013 to 2025. Washington, DC: Association of American Medical Colleges; 2015. 59 p.


3. World Health Organization Regional Office for the Western Pacific. Human resources for health country profiles: Malaysia. Geneva (Switzerland): World Health Organization; 2014. 47 p.

4. Kwa SK. Family medicine specialisation in Malaysia [Internet]. Kuala Lumpur (Malaysia): Family Medicine Specialists Association of Malaysia; [cited 2015 Sep 18]; [about 4 screens]. Available from: http://fms-malaysia.org/home/?page_id=175

5. Truglio J1, Graziano M, Vedanthan R, Hahn S, Rios C, Hendel-Paterson B, et al. Global health and primary care: increasing burden of chronic diseases and need for integrated training. Mt Sinai J Med. 2012 Jul-Aug;79(4):464-74.

6. Hedden L, Barer ML, Cardiff K, McGrail KM, Law MR, Bourgeault IL. The implications of the feminization of the primary care physician workforce on service supply: a systematic review. Hum Resour Health. 2014 Jun 4;12:32.

7. KPMG. Health workforce in Australia and factors for current shortages. Adelaide (Australia): National Health Workforce Taskforce (AU); 2009 Apr.

8. Medical Act 1971. Second Schedule: List of Registrable Qualifications (Nov. 9, 2011).

92.7 81.2

7.3 18.8

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f d

oct

ors

(%

)

With postgraduate qualification

No postgraduate qualification

CHAPTER sixThe Patients


CHAPTER 6: THE PATIENTS

The characteristics of patients presenting to primary care are reported in this chapter. These include the sociodemographic characteristics (age, gender, nationality, ethnicity, individual income and education level) and mode of payment. Issuance of medical certificates and duration of sick leaves given (if any) during primary care visits are also reported here.

6.1 CHARACTERISTICS OF THE PATIENTS


Table 6.1.1 shows the characteristics of primary care patients in Malaysia for 2014.

• Females accounted for the greater proportion (53.6%) of all encounters. • The median age of the patients was 35.7 years (IQR: 23.5–52.7 years), and the age distribution was

as follows: infants < 1 year: 2.3%, 1–4 years: 5.7%, 5–19 years: 11.7%, 20–39 years: 37.3%, 40–59 years: 28.0%, and ≥ 60 years: 15.0%.

• Malaysians made up 93.3% of all encounters. Majority of the patients were Malay (62.6%), followed by Chinese (21.2%), Indian (10.8%) and other ethnic groups (5.4%).

• Most (43.0%) patient encounters were paid for by government subsidies, followed by out-of-pocket payments (34.1%) and third-party payments (22.3%).

• About two-thirds (64.0%) of patients reported having personal income. More than half (55.2%) of the patients had a monthly personal income between MYR 1,000 and MYR 2,999 (parental income excluded).

• The vast majority (89.0%) of patients had received some form of formal education: 20.8% had primary education, 46.9% had completed at least some secondary education, and 21.3% had tertiary education.

• Medical certificates were issued to 31.2% of patients. Most (83.3%) of the issuances took place in the private sector. The duration of sick leave given ranged from 0.5 to 20 days.

Table 6.1.1: Characteristics of primary care patients in 2014


count (n = 27,587)


Percent of patients (95% CI)

Sector

Public 15,470 131,624 40.4 (34.9–45.9)

Private 12,117 194,194 59.6 (54.1–65.1)

Gender

Male 12,108 149,026 46.4 (45.1–47.8)

Female 15,030 171,904 53.6 (52.2–54.9)

Missinga 449 4,889 -

Age (years)

< 1 776 7,611 2.3 (1.9–2.8)

1–4 1,599 18,582 5.7 (5.1–6.3)

5–19 3,599 38,060 11.7 (10.9–12.6)

20–39 8,899 120,897 37.3 (35.1–39.4)

40–59 7,728 90,706 28.0 (26.7–29.2)

≥ 60 4,882 48,610 15.0 (13.5–16.4)


Nationality

Malaysian 25,622 297,259 93.3 (91.9–94.6)

Non-Malaysian 1,424 21,487 6.7 (5.4–8.1)


Ethnicity

Malay 16,428 188,777 62.6 (59.0–66.2)

Chinese 5,234 63,959 21.2 (18.2–24.2)

Indian 2,673 32,551 10.8 (9.1–12.5)

Othersb 1,634 16,367 5.4 (3.8–7.0)

Missinga 1,618 24,164 -

Mode of payment

Government subsidies 15,473 131,653 43.0 (37.3–48.6)

Out of pocket 7,005 104,435 34.1 (30.4–37.7)

Third party payer 3,903 68,332 22.3 (19.3–25.3)

Combinationsc 53 1,007 0.3 (0.2–0.4)

Othersd 61 1,035 0.3 (0.2–0.5)

Missinga 1,092 19,356 -

Type of income

No income 9,466 96,344 36.0 (33.3–38.7)

Income 11,846 155,607 58.1 (55.3–61.0)

Pension 1,333 14,110 5.3 (4.5–6.1)

Parental incomee 142 1,581 0.6 (0.3–0.8)

Missinga 4,800 58,176 -

51

CHAPTER 6: THE PATIENTS

The characteristics of patients presenting to primary care are reported in this chapter. These include the sociodemographic characteristics (age, gender, nationality, ethnicity, individual income and education level) and mode of payment. Issuance of medical certificates and duration of sick leaves given (if any) during primary care visits are also reported here.

6.1 CHARACTERISTICS OF THE PATIENTS


Table 6.1.1 shows the characteristics of primary care patients in Malaysia for 2014.

• Females accounted for the greater proportion (53.6%) of all encounters. • The median age of the patients was 35.7 years (IQR: 23.5–52.7 years), and the age distribution was

as follows: infants < 1 year: 2.3%, 1–4 years: 5.7%, 5–19 years: 11.7%, 20–39 years: 37.3%, 40–59 years: 28.0%, and ≥ 60 years: 15.0%.

• Malaysians made up 93.3% of all encounters. Majority of the patients were Malay (62.6%), followed by Chinese (21.2%), Indian (10.8%) and other ethnic groups (5.4%).

• Most (43.0%) patient encounters were paid for by government subsidies, followed by out-of-pocket payments (34.1%) and third-party payments (22.3%).

• About two-thirds (64.0%) of patients reported having personal income. More than half (55.2%) of the patients had a monthly personal income between MYR 1,000 and MYR 2,999 (parental income excluded).

• The vast majority (89.0%) of patients had received some form of formal education: 20.8% had primary education, 46.9% had completed at least some secondary education, and 21.3% had tertiary education.

• Medical certificates were issued to 31.2% of patients. Most (83.3%) of the issuances took place in the private sector. The duration of sick leave given ranged from 0.5 to 20 days.

Table 6.1.1: Characteristics of primary care patients in 2014


count (n = 27,587)



Sector

Public 15,470 131,624 40.4 (34.9–45.9)

Private 12,117 194,194 59.6 (54.1–65.1)

Gender

Male 12,108 149,026 46.4 (45.1–47.8)

Female 15,030 171,904 53.6 (52.2–54.9)


Age (years)

< 1 776 7,611 2.3 (1.9–2.8)

1–4 1,599 18,582 5.7 (5.1–6.3)

5–19 3,599 38,060 11.7 (10.9–12.6)

20–39 8,899 120,897 37.3 (35.1–39.4)

40–59 7,728 90,706 28.0 (26.7–29.2)

≥ 60 4,882 48,610 15.0 (13.5–16.4)


Nationality

Malaysian 25,622 297,259 93.3 (91.9–94.6)

Non-Malaysian 1,424 21,487 6.7 (5.4–8.1)


Ethnicity

Malay 16,428 188,777 62.6 (59.0–66.2)

Chinese 5,234 63,959 21.2 (18.2–24.2)

Indian 2,673 32,551 10.8 (9.1–12.5)

Othersb 1,634 16,367 5.4 (3.8–7.0)

Missinga 1,618 24,164 -

Mode of payment

Government subsidies 15,473 131,653 43.0 (37.3–48.6)

Out of pocket 7,005 104,435 34.1 (30.4–37.7)

Third party payer 3,903 68,332 22.3 (19.3–25.3)

Combinationsc 53 1,007 0.3 (0.2–0.4)

Othersd 61 1,035 0.3 (0.2–0.5)

Missinga 1,092 19,356 -

Type of income

No income 9,466 96,344 36.0 (33.3–38.7)

Income 11,846 155,607 58.1 (55.3–61.0)

Pension 1,333 14,110 5.3 (4.5–6.1)

Parental incomee 142 1,581 0.6 (0.3–0.8)

Missinga 4,800 58,176 -


Table 6.1.1 (continued): Characteristics of primary care patients in 2014


count (n = 27,587)



Monthly income (MYR)f

< 400 398 3,657 2.3 (1.6–2.9)

400–499 139 1,351 0.8 (0.6–1.1)

500–699 539 5,364 3.3 (2.6–4.1)

700–999 1,519 18,198 11.3 (9.7–12.9)

1,000–1,999 4,298 51,678 32.1 (29.2–35.0)

2,000–2,999 2,643 37,155 23.1 (21.4–24.7)

3,000–3,999 1,596 22,948 14.3 (13.2–15.3)

4,000–4,999 557 9,477 5.9 (4.2–7.6)

≥ 5,000 728 11,180 6.9 (5.9–8.0)


Education level

No formal education 2,756 28,109 11.0 (9.7–12.2)

Primary 4,855 53,200 20.8 (19.5–22.1)

Secondary 10,264 119,959 46.9 (45.1–48.6)

Tertiary 3,962 54,601 21.3 (19.2–23.5)

Missinga 5,750 69,949 -

Issuance of medical certificate

Yes 5,224 77,884 31.2 (28.6–33.7)

Public 1,636 12,972 5.2 (3.9–6.5)

Private 3,588 64,912 26.0 (22.7–29.3)

No 15,397 171,917 68.8 (66.3–71.4)

Missinga 6,966 76,017 -

Duration of sick leave (days)g

0.5–1 3,978 59,532 79.9 (76.1–83.6)

1.5–2 840 12,622 16.9 (13.9–20.0)

3–7 140 2,138 2.9 (1.8–3.9)

> 7 14 245 0.3 (0.0–0.7)

Missinga 252 3,347 - a Missing data excluded from analysis b Include all ethnic groups that do not fall into the three groups listed c Combination of two or more modes of payment d Includes Foreign Workers Medical Examination Monitoring Agency (FOMEMA), Social Security Organisation (SOCSO) and no

payment e Patients below age 15 with income recorded f Patients with missing income, patients who reported no income and patients below age 15 were excluded g Encounters with missing sick leave entry or without sick leave were excluded

6.2 AGE-GENDER DISTRIBUTION

Figure 6.2.1 and Figure 6.2.2 show the age-gender distribution of patients attending public clinics and private clinics, respectively.

• Females accounted for 59.6% of encounters in public clinics. The proportion of female patients was significantly higher among the adult age groups (20–39 years: 19.0% versus 8.1%; 40–59 years: 18.4% versus 11.8%), while no significant gender differences were observed among infants, children, adolescents and the elderly.

• In the private sector, the proportions of male and female patients were similar, both overall and across all age groups.

• Patients aged 40–59 years accounted for the greatest proportion (30.3%) of encounters recorded in public clinics, while most (44.3%) patients who presented to private clinics were between 20 and 39 years of age.

• Nearly one-quarter (22.9%) of the patients who visited public clinics were 60 years and older, about 2.6 times higher than the projected proportion of elderly in the general population for 2014 reported by the Department of Statistics Malaysia (8.8%).1 In contrast, the proportion of elderly patients in private clinics (9.7%) was similar to the projected proportion of elderly population.

Figure 6.2.1: Distribution of public patients by age and gender in 2014


< 1 1–4 5–19 20–39 40–59 ≥ 60

Female 1.5 2.5 6.0 19.0 18.4 12.3

Male 1.6 2.4 5.9 8.1 11.8 10.7

0

5

10

15

20

25

30

35

40

45

Per

cen

t o

f en

cou

nte

rs (

%)

Age group (years)

53

Table 6.1.1 (continued): Characteristics of primary care patients in 2014


count (n = 27,587)



Monthly income (MYR)f

< 400 398 3,657 2.3 (1.6–2.9)

400–499 139 1,351 0.8 (0.6–1.1)

500–699 539 5,364 3.3 (2.6–4.1)

700–999 1,519 18,198 11.3 (9.7–12.9)

1,000–1,999 4,298 51,678 32.1 (29.2–35.0)

2,000–2,999 2,643 37,155 23.1 (21.4–24.7)

3,000–3,999 1,596 22,948 14.3 (13.2–15.3)

4,000–4,999 557 9,477 5.9 (4.2–7.6)

≥ 5,000 728 11,180 6.9 (5.9–8.0)


Education level

No formal education 2,756 28,109 11.0 (9.7–12.2)

Primary 4,855 53,200 20.8 (19.5–22.1)

Secondary 10,264 119,959 46.9 (45.1–48.6)

Tertiary 3,962 54,601 21.3 (19.2–23.5)

Missinga 5,750 69,949 -

Issuance of medical certificate

Yes 5,224 77,884 31.2 (28.6–33.7)

Public 1,636 12,972 5.2 (3.9–6.5)

Private 3,588 64,912 26.0 (22.7–29.3)

No 15,397 171,917 68.8 (66.3–71.4)

Missinga 6,966 76,017 -

Duration of sick leave (days)g

0.5–1 3,978 59,532 79.9 (76.1–83.6)

1.5–2 840 12,622 16.9 (13.9–20.0)

3–7 140 2,138 2.9 (1.8–3.9)

> 7 14 245 0.3 (0.0–0.7)

Missinga 252 3,347 - a Missing data excluded from analysis b Include all ethnic groups that do not fall into the three groups listed c Combination of two or more modes of payment d Includes Foreign Workers Medical Examination Monitoring Agency (FOMEMA), Social Security Organisation (SOCSO) and no

payment e Patients below age 15 with income recorded f Patients with missing income, patients who reported no income and patients below age 15 were excluded g Encounters with missing sick leave entry or without sick leave were excluded

6.2 AGE-GENDER DISTRIBUTION

Figure 6.2.1 and Figure 6.2.2 show the age-gender distribution of patients attending public clinics and private clinics, respectively.

• Females accounted for 59.6% of encounters in public clinics. The proportion of female patients was significantly higher among the adult age groups (20–39 years: 19.0% versus 8.1%; 40–59 years: 18.4% versus 11.8%), while no significant gender differences were observed among infants, children, adolescents and the elderly.

• In the private sector, the proportions of male and female patients were similar, both overall and across all age groups.

• Patients aged 40–59 years accounted for the greatest proportion (30.3%) of encounters recorded in public clinics, while most (44.3%) patients who presented to private clinics were between 20 and 39 years of age.

• Nearly one-quarter (22.9%) of the patients who visited public clinics were 60 years and older, about 2.6 times higher than the projected proportion of elderly in the general population for 2014 reported by the Department of Statistics Malaysia (8.8%).1 In contrast, the proportion of elderly patients in private clinics (9.7%) was similar to the projected proportion of elderly population.

Figure 6.2.1: Distribution of public patients by age and gender in 2014


< 1 1–4 5–19 20–39 40–59 ≥ 60

Female 1.5 2.5 6.0 19.0 18.4 12.3

Male 1.6 2.4 5.9 8.1 11.8 10.7

0

5

10

15

20

25

30

35

40

45

Per

cen

t o

f en

cou

nte

rs (

%)

Age group (years)

Chapter 6 : The Patients


Figure 6.2.2: Distribution of private patients by age and gender in 2014


6.3 NATIONALITY AND ETHNICITY

Figure 6.3.1 and Figure 6.3.2 show the breakdown of patient encounters in public and private clinics by nationality and ethnicity, respectively.

• Majority of the patients in both public and private clinics were Malaysians; non-Malaysians (permanent residents and foreigners) constituted only 3.3% of the public patient population and 9.1% of the private patient population. The distribution of patients in the private sector was similar to the projected population composition for 2014 reported by the Department of Statistics Malaysia (Malaysians: 92.0%; non-Malaysians: 8.0%),1 while the public sector recorded a proportion of non-Malaysians smaller than that in the general population.

• Malay patients were the largest ethnic group utilising primary care (65.6% of encounters in public clinics and 60.4% in private clinics), followed by Chinese (14.4% in public clinics and 26.1% in private clinics) and Indian patients (11.9% in public clinics and 10.0% in private clinics). In comparison with the projected ethnic composition of the Malaysian population for 2014 (Malay: 50.6%; Chinese: 21.9%; Indian: 6.6%; other ethnic groups: 20.8%),1 a greater proportion of Malays was seen in both public and private clinics, while the opposite held true for the Indian population. The proportion of Chinese was lower in the public patient population and higher in the private patient population compared to that in the general population.

< 1 1–4 5–19 20–39 40–59 ≥ 60

Female 1.0 2.9 5.5 22.7 12.6 5.0

Male 0.8 3.3 6.0 21.6 13.9 4.7

0

5

10

15

20

25

30

35

40

45

Per

cen

t o

f en

cou

nte

rs (

%)

Age group (years)

Figure 6.3.1: Distribution of public and private patients by nationality in 2014


Figure 6.3.2: Distribution of public and private patients by ethnicity in 2014

* Include all ethnic groups that do not fall into the three groups listed Note: Missing data excluded from analysis.

3.3 9.1

96.7 90.9

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

Malaysian

Non-Malaysian

8.1 3.5

11.9

10.0

14.4 26.1

65.6 60.4

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

Malay

Chinese

Indian

Others*

55

Figure 6.2.2: Distribution of private patients by age and gender in 2014


6.3 NATIONALITY AND ETHNICITY

Figure 6.3.1 and Figure 6.3.2 show the breakdown of patient encounters in public and private clinics by nationality and ethnicity, respectively.

• Majority of the patients in both public and private clinics were Malaysians; non-Malaysians (permanent residents and foreigners) constituted only 3.3% of the public patient population and 9.1% of the private patient population. The distribution of patients in the private sector was similar to the projected population composition for 2014 reported by the Department of Statistics Malaysia (Malaysians: 92.0%; non-Malaysians: 8.0%),1 while the public sector recorded a proportion of non-Malaysians smaller than that in the general population.

• Malay patients were the largest ethnic group utilising primary care (65.6% of encounters in public clinics and 60.4% in private clinics), followed by Chinese (14.4% in public clinics and 26.1% in private clinics) and Indian patients (11.9% in public clinics and 10.0% in private clinics). In comparison with the projected ethnic composition of the Malaysian population for 2014 (Malay: 50.6%; Chinese: 21.9%; Indian: 6.6%; other ethnic groups: 20.8%),1 a greater proportion of Malays was seen in both public and private clinics, while the opposite held true for the Indian population. The proportion of Chinese was lower in the public patient population and higher in the private patient population compared to that in the general population.

< 1 1–4 5–19 20–39 40–59 ≥ 60

Female 1.0 2.9 5.5 22.7 12.6 5.0

Male 0.8 3.3 6.0 21.6 13.9 4.7

0

5

10

15

20

25

30

35

40

45

Per

cen

t o

f en

cou

nte

rs (

%)

Age group (years)

Figure 6.3.1: Distribution of public and private patients by nationality in 2014


Figure 6.3.2: Distribution of public and private patients by ethnicity in 2014

* Include all ethnic groups that do not fall into the three groups listed Note: Missing data excluded from analysis.

3.3 9.1

96.7 90.9

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

Malaysian

Non-Malaysian

8.1 3.5

11.9

10.0

14.4 26.1

65.6 60.4

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

Malay

Chinese

Indian

Others*



Figure 6.5.1: Distribution of public and private patients by type of income in 2014

a Patients below age 15 with income recorded


Figure 6.5.2: Distribution of primary care patients by income and sector in 2014

Note: Patients with missing income, patients who reported no income and patients below age 15 were excluded.

0.7 0.5 7.0 4.0

46.8

66.9

45.5

28.6

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f P

ati

ents

(%

)

No income

Income

Pension

Parental income*

0.3 6.2

19.5 16.3

10.7

4.8 6.0 2.8

8.4

12.6

6.8

3.6

1.1 0.9

0

5

10

15

20

25

30

35

Per

cen

t o

f en

cou

nte

rs (

%)

Monthly income (MYR)

Public

Private

6.4 MODE OF PAYMENT

The provision of primary care was funded by different mechanisms in different sectors.

• All patient encounters in public clinics were paid for by government subsidies. • In the private sector, more than half (59.7%) of the encounters were paid for through out-of-pocket

payments, while nearly all of the remaining encounters (39.1%) were paid, either fully or partially, by third party payers, such as private insurance, employers and managed care organisations (Figure 6.4.1).

Figure 6.4.1: Distribution of private patients by mode of payment in 2014

* Combination of two or more modes of payment

† Includes Foreign Workers Medical Examination Monitoring Agency (FOMEMA), Social Security Organisation (SOCSO) and no

payment Note: Missing data excluded from analysis.

6.5 INDIVIDUAL INCOME

Individual income of patients presenting to primary care was captured in NMCS 2014. For patients less than 15 years old who had income reported in the survey questionnaires, the type of income was assumed to be parental income. Figure 6.5.1 shows the distribution of public and private patients by type of income, while the income distribution of patients who reported having a personal income is presented in Figure 6.5.2.

• Nearly half (45.5%) of the patients seen in public clinics reported having no income. In contrast, more than two-thirds (70.9%) of private patients reported having personal income, including 4.0% who were on pension.

• In general, patients who visited private clinics had higher incomes than those who presented to public clinics. Nearly two-thirds (63.0%) of the patients who earned less than MYR 1,000 per month attended public clinics, while private patients constituted 79.3% of the patients who had a monthly income of MYR 3,000 or over.

Out of pocket 59.7%

Third party payer 39.1%

Combination* 0.6%

Others† 0.6%

57

Figure 6.5.1: Distribution of public and private patients by type of income in 2014

a Patients below age 15 with income recorded


Figure 6.5.2: Distribution of primary care patients by income and sector in 2014

Note: Patients with missing income, patients who reported no income and patients below age 15 were excluded.

0.7 0.5 7.0 4.0

46.8

66.9

45.5

28.6

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f P

ati

ents

(%

)

No income

Income

Pension

Parental income*

0.3 6.2

19.5 16.3

10.7

4.8 6.0 2.8

8.4

12.6

6.8

3.6

1.1 0.9

0

5

10

15

20

25

30

35

Per

cen

t o

f en

cou

nte

rs (

%)

Monthly income (MYR)

Public

Private

6.4 MODE OF PAYMENT

The provision of primary care was funded by different mechanisms in different sectors.

• All patient encounters in public clinics were paid for by government subsidies. • In the private sector, more than half (59.7%) of the encounters were paid for through out-of-pocket

payments, while nearly all of the remaining encounters (39.1%) were paid, either fully or partially, by third party payers, such as private insurance, employers and managed care organisations (Figure 6.4.1).

Figure 6.4.1: Distribution of private patients by mode of payment in 2014

* Combination of two or more modes of payment

† Includes Foreign Workers Medical Examination Monitoring Agency (FOMEMA), Social Security Organisation (SOCSO) and no

payment Note: Missing data excluded from analysis.

6.5 INDIVIDUAL INCOME

Individual income of patients presenting to primary care was captured in NMCS 2014. For patients less than 15 years old who had income reported in the survey questionnaires, the type of income was assumed to be parental income. Figure 6.5.1 shows the distribution of public and private patients by type of income, while the income distribution of patients who reported having a personal income is presented in Figure 6.5.2.

• Nearly half (45.5%) of the patients seen in public clinics reported having no income. In contrast, more than two-thirds (70.9%) of private patients reported having personal income, including 4.0% who were on pension.

• In general, patients who visited private clinics had higher incomes than those who presented to public clinics. Nearly two-thirds (63.0%) of the patients who earned less than MYR 1,000 per month attended public clinics, while private patients constituted 79.3% of the patients who had a monthly income of MYR 3,000 or over.

Out of pocket 59.7%

Third party payer 39.1%

Combination* 0.6%

Others† 0.6%



6.6 EDUCATION LEVEL

Patient education level is an important determinant of patient outcomes.2-4 Figure 6.6.1 presents the distribution of patients by educational level for both public and private sectors.

• In general, private patients reported higher levels of educational attainment compared to those who presented to public clinics.

• More than one-quarter (28.0%) of patients in the private sector had attained or completed education at the tertiary level, compared to only 12.3% in the public sector.

• Patients who had not undertaken any formal education accounted for a higher proportion of encounters in public clinics than in private clinics (13.4% versus 9.2%, respectively).

• Nearly half of the patients seen in public and private clinics (47.6% and 46.3%, respectively) had completed at least some secondary education.

Figure 6.6.1: Distribution of public and private patients by education level in 2014


6.7 MEDICAL CERTIFICATE AND DURATION OF SICK LEAVE

A total of 77,884 (31.2%) patients were issued medical certificates during their visit to primary care clinics.

• Medical certificates were issued three times more frequently in private clinics than in the public settings (41.5% versus 13.9% of encounters, respectively) (Figure 6.7.1).

• About 80% of the medical certificates issued in both public and private clinics entitled the patient to a sick leave of half to one day (Figure 6.7.2).

12.3

28.0

47.6

46.3

26.7

16.5

13.4 9.2

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

No formal education

Primary

Secondary

Tertiary

Figure 6.7.1: Distribution of public and private patients by issuance of medical certificate in 2014


Figure 6.7.2: Distribution of public and private patients by duration of sick leave in 2014

Note: Encounters with missing sick leave entry or without sick leave were excluded

86.1

58.5

13.9

41.5

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

Yes

No

1.1 0.2 4.9 2.5

13.9 17.5

80.1 79.8

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

0.5–1 day

1.5–2 days

3–7 days

> 7 days

59

6.6 EDUCATION LEVEL

Patient education level is an important determinant of patient outcomes.2-4 Figure 6.6.1 presents the distribution of patients by educational level for both public and private sectors.

• In general, private patients reported higher levels of educational attainment compared to those who presented to public clinics.

• More than one-quarter (28.0%) of patients in the private sector had attained or completed education at the tertiary level, compared to only 12.3% in the public sector.

• Patients who had not undertaken any formal education accounted for a higher proportion of encounters in public clinics than in private clinics (13.4% versus 9.2%, respectively).

• Nearly half of the patients seen in public and private clinics (47.6% and 46.3%, respectively) had completed at least some secondary education.

Figure 6.6.1: Distribution of public and private patients by education level in 2014


6.7 MEDICAL CERTIFICATE AND DURATION OF SICK LEAVE

A total of 77,884 (31.2%) patients were issued medical certificates during their visit to primary care clinics.

• Medical certificates were issued three times more frequently in private clinics than in the public settings (41.5% versus 13.9% of encounters, respectively) (Figure 6.7.1).

• About 80% of the medical certificates issued in both public and private clinics entitled the patient to a sick leave of half to one day (Figure 6.7.2).

12.3

28.0

47.6

46.3

26.7

16.5

13.4 9.2

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

No formal education

Primary

Secondary

Tertiary

Figure 6.7.1: Distribution of public and private patients by issuance of medical certificate in 2014


Figure 6.7.2: Distribution of public and private patients by duration of sick leave in 2014

Note: Encounters with missing sick leave entry or without sick leave were excluded

86.1

58.5

13.9

41.5

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

Yes

No

1.1 0.2 4.9 2.5

13.9 17.5

80.1 79.8

0

10

20

30

40

50

60

70

80

90

100

Public Private

Per

cen

t o

f p

ati

ents

(%

)

0.5–1 day

1.5–2 days

3–7 days

> 7 days



REFERENCES


2. Paksima N, Pahk B, Romo S, Egol KA. The association of education level on outcome after distal radius fracture. Hand (N Y). 2014 Mar;9(1):75-9.

3. Khattak M, Sandhu GS, Desilva R, Goldfarb-Rumyantzev AS. Association of education level with dialysis outcome. Hemodial Int. 2012 Jan;16(1):82-8.

4. Konski A, Berkey BA, Kian Ang K, Fu KK. Effect of education level on outcome of patients treated on Radiation Therapy Oncology Group Protocol 90-03. Cancer. 2003 Oct 1;98(7):1497-503.

CHAPTER sevenReasons for Encounter

REFERENCES


2. Paksima N, Pahk B, Romo S, Egol KA. The association of education level on outcome after distal radius fracture. Hand (N Y). 2014 Mar;9(1):75-9.

3. Khattak M, Sandhu GS, Desilva R, Goldfarb-Rumyantzev AS. Association of education level with dialysis outcome. Hemodial Int. 2012 Jan;16(1):82-8.

4. Konski A, Berkey BA, Kian Ang K, Fu KK. Effect of education level on outcome of patients treated on Radiation Therapy Oncology Group Protocol 90-03. Cancer. 2003 Oct 1;98(7):1497-503.


CHAPTER 7: REASONS FOR ENCOUNTER

This chapter concerns the reasons for encounter (RFEs), which refer to the reasons why patients present to primary care clinics. The RFEs could be a symptom or complaint, planned or unplanned follow-up on a known health condition or problem, health screening or medical check-up request (by patients or their employers), or a need for investigative, therapeutic and/or administrative procedures. This study adopted a patient-centred approach and aimed to identify the reasons for seeking health care from the patients’ perspective.

7.1 NUMBER OF REASONS FOR ENCOUNTER PER VISIT

In NMCS 2014, a total of 597,563 reasons for encounter (weighted count) were captured. Figure 7.1.1 shows the number of RFEs per visit by sector (public and private) in 2014.

• About half of the patients included in the survey presented with only a single reason for encounter (44.1% in public clinics and 49.1% in private clinics).

Figure 7.1.1: Number of reasons for encounter per visit in primary care clinics in 2014


One Two Three ≥ Four

Public 44.1 27.8 20.3 7.8

Private 49.1 27.5 17.0 6.4

0

10

20

30

40

50

60

Per

cen

t o

f en

cou

nte

rs (

%)

Number of RFEs per encounter

7.2 REASONS FOR ENCOUNTER BY ICPC-2 COMPONENTS

All reasons for encounter were coded using the International Classification of Primary Care Second Edition (ICPC-2) coding system (see Appendix 4). As detailed in Chapter 2, the biaxial classification system allows for the classification of patients’ reasons for encounter according to the aspects of the consultation (components) and the body systems involved (chapters). This section is devoted to the distributions of reasons for presentation to primary care providers according to the seven ICPC-2 components. The distributions of reasons for encounters based on the 17 ICPC-2 chapters will be presented in the next section.

Table 7.2.1 presents the overall distribution of RFEs by ICPC-2 components.

• Out of the 597,563 RFEs captured, 61.4% were symptom- and complaint-based, making “symptoms and complaints” the top RFE.

• The second most common RFE was “diagnosis/diseases”, which constituted 27.4% of all RFEs. Most (90.9%) of the RFEs classified under this component were for “other diagnosis/diseases”, a classification for diagnosis/diseases which did not fit into the categories of infectious diseases, injuries, neoplasms and congenital anomalies.

• RFEs were also expressed as processes of care, which accounted for 11.2% of all RFEs. These included diagnostic and preventive procedures as well as requests for medications, test results, medical certificates and referrals.

Table 7.2.1: Reasons for encounter by ICPC-2 components in primary care clinics in 2014

Table 7.2.2 and Table 7.2.3 show the breakdown of RFE distribution by sectors (public and private, respectively). In public clinics, “diagnosis/diseases” was the main RFE (44.4% of all RFEs, 85.0 per 100 encounters), whereas patients presented to private clinics mainly for symptom-based complaints (77.9%). These results are consistent with the findings of NMCS 2012.1

RFE (ICPC-2 component) Unweighted

count Weighted

count

Percent of total RFEs

(n = 597,563)

Rate per 100 encounters

(95% CI) (n = 325,818)

Symptom & complaint 28,502 366,841 61.4 112.6 (106.1–119.1)

Diagnosis, diseases 16,008 163,666 27.4 50.2 (45.0–55.4)

Infectious diseases 641 8,781 1.5 2.7 (2.2–3.2)

Injuries 485 5,852 1.0 1.8 (1.5–2.1)

Neoplasms 16 165 0.0 0.1 (0.0–0.1)

Congenital anomalies 10 52 0.0 0.0 (0.0–0.0)

Other diagnoses/diseases 14,856 148,816 24.9 45.7 (40.4–51.0)

Diagnostic screening & preventive 5,298 56,610 9.5 17.4 (15.3–19.5)

Medication, treatment procedures 464 6,062 1.0 1.9 (1.5–2.2)

Test results 226 2,225 0.4 0.7 (0.4–1.0)

Referrals & other reason for encounter 110 1,551 0.3 0.5 (0.3–0.7)

Administrative 34 607 0.1 0.2 (0.0–0.3)

Total 50,642 597,563 100.0 183.4 (178.1–188.7)

63

CHAPTER 7: REASONS FOR ENCOUNTER

This chapter concerns the reasons for encounter (RFEs), which refer to the reasons why patients present to primary care clinics. The RFEs could be a symptom or complaint, planned or unplanned follow-up on a known health condition or problem, health screening or medical check-up request (by patients or their employers), or a need for investigative, therapeutic and/or administrative procedures. This study adopted a patient-centred approach and aimed to identify the reasons for seeking health care from the patients’ perspective.

7.1 NUMBER OF REASONS FOR ENCOUNTER PER VISIT

In NMCS 2014, a total of 597,563 reasons for encounter (weighted count) were captured. Figure 7.1.1 shows the number of RFEs per visit by sector (public and private) in 2014.

• About half of the patients included in the survey presented with only a single reason for encounter (44.1% in public clinics and 49.1% in private clinics).

Figure 7.1.1: Number of reasons for encounter per visit in primary care clinics in 2014



Public 44.1 27.8 20.3 7.8

Private 49.1 27.5 17.0 6.4

0

10

20

30

40

50

60

Per

cen

t o

f en

cou

nte

rs (

%)

Number of RFEs per encounter

7.2 REASONS FOR ENCOUNTER BY ICPC-2 COMPONENTS

All reasons for encounter were coded using the International Classification of Primary Care Second Edition (ICPC-2) coding system (see Appendix 4). As detailed in Chapter 2, the biaxial classification system allows for the classification of patients’ reasons for encounter according to the aspects of the consultation (components) and the body systems involved (chapters). This section is devoted to the distributions of reasons for presentation to primary care providers according to the seven ICPC-2 components. The distributions of reasons for encounters based on the 17 ICPC-2 chapters will be presented in the next section.

Table 7.2.1 presents the overall distribution of RFEs by ICPC-2 components.

• Out of the 597,563 RFEs captured, 61.4% were symptom- and complaint-based, making “symptoms and complaints” the top RFE.

• The second most common RFE was “diagnosis/diseases”, which constituted 27.4% of all RFEs. Most (90.9%) of the RFEs classified under this component were for “other diagnosis/diseases”, a classification for diagnosis/diseases which did not fit into the categories of infectious diseases, injuries, neoplasms and congenital anomalies.

• RFEs were also expressed as processes of care, which accounted for 11.2% of all RFEs. These included diagnostic and preventive procedures as well as requests for medications, test results, medical certificates and referrals.

Table 7.2.1: Reasons for encounter by ICPC-2 components in primary care clinics in 2014

Table 7.2.2 and Table 7.2.3 show the breakdown of RFE distribution by sectors (public and private, respectively). In public clinics, “diagnosis/diseases” was the main RFE (44.4% of all RFEs, 85.0 per 100 encounters), whereas patients presented to private clinics mainly for symptom-based complaints (77.9%). These results are consistent with the findings of NMCS 2012.1


count Weighted

count


(n = 597,563)


(95% CI) (n = 325,818)




Injuries 485 5,852 1.0 1.8 (1.5–2.1)

Neoplasms 16 165 0.0 0.1 (0.0–0.1)





Test results 226 2,225 0.4 0.7 (0.4–1.0)


Administrative 34 607 0.1 0.2 (0.0–0.3)

Total 50,642 597,563 100.0 183.4 (178.1–188.7)

Chapter 7 : Reasons for Encounter


Table 7.2.2: Reasons for encounter by ICPC-2 components in public clinics in 2014

RFE (ICPC-2 component) Unweighted count

Weighted count


(n = 597,563)


(95% CI) (n = 325,818)




Injuries 194 1,535 0.6 1.2 (0.9–1.4)

Neoplasms 8 33 0.0 0.0 (0.0–0.1)





Test results 196 1,784 0.7 1.4 (0.7–2.1)


Administrative 32 529 0.2 0.4 (0.0–0.8)

Total 29,478 252,050 100.0 191.5 (182.5–200.5)

Table 7.2.3: Reasons for encounter by ICPC-2 components in private clinics in 2014


count Weighted

count


(n = 597,563)

Rate per 100 encounters (95% CI)

(n = 325,818)




Injuries 291 4,316 1.3 2.2 (1.9–2.6)

Neoplasms 8 132 0.0 0.1 (0.0–0.1)





Test results 30 442 0.1 0.2 (0.1–0.4)

Referrals & other reason for encounter 22 443 0.1 0.2 (0.1–0.4)

Administrative 2 77 0.0 0.0 (0.0–0.1)

Total 21,164 345,513 100.0 177.9 (171.4–184.4)



Weighted count


(n = 597,563)


(95% CI) (n = 325,818)




Injuries 194 1,535 0.6 1.2 (0.9–1.4)

Neoplasms 8 33 0.0 0.0 (0.0–0.1)





Test results 196 1,784 0.7 1.4 (0.7–2.1)


Administrative 32 529 0.2 0.4 (0.0–0.8)

Total 29,478 252,050 100.0 191.5 (182.5–200.5)



count Weighted

count


(n = 597,563)


(n = 325,818)




Injuries 291 4,316 1.3 2.2 (1.9–2.6)

Neoplasms 8 132 0.0 0.1 (0.0–0.1)





Test results 30 442 0.1 0.2 (0.1–0.4)


Administrative 2 77 0.0 0.0 (0.0–0.1)

Total 21,164 345,513 100.0 177.9 (171.4–184.4)

7.3 REASONS FOR ENCOUNTER BY ICPC-2 CHAPTERS

Table 7.3.1 shows the overall distribution of RFEs when categorised according to ICPC-2 chapters. Note that in some instances, related RFEs within a certain ICPC-2 chapter were collapsed into a single RFE.

• The most common RFEs were respiratory conditions, which accounted for 26.8% of all RFEs (49.2 per 100 patient encounters).

• General and unspecified conditions were the second most frequent RFEs (20.3% of all RFEs). Among these conditions, fever was the most frequently reported reason for visit (62.9% of all general and unspecified conditions).

• Chronic conditions under the endocrine, metabolic and nutritional category accounted for 12.7% of all RFEs, with 10.9 RFEs per 100 encounters recorded for diabetes and 9.1 per 100 encounters for lipid disorder. For reference, the National Health Morbidity Survey (NHMS) 2011 reported the prevalence for diabetes and hypercholesterolemia in Malaysia to be at 15.2% and 35.1%, respectively.2

Table 7.3.1: Reasons for encounter by ICPC-2 chapters and the most common individual reasons for encounter within each chapter in primary care clinics in 2014

RFE (ICPC-2 chapter) Unweighted count

Weighted count


(n = 597,563)


(95% CI) (n = 325,818)

Respiratory 12,660 160,186 26.8 49.2 (46.1–52.2)

Cough 6,022 74,905 12.5 23.0 (21.7–24.3)

Runny nose/rhinorrhoea 4,328 53,469 9.0 16.4 (15.1–17.7)

Pain/sore throat* 982 14,030 2.4 4.3 (3.5–5.2)

Asthma 623 7,834 1.3 2.4 (1.9–2.9)

General & unspecified 9,740 121,203 20.3 37.2 (35.3–39.1)

Fever 6,071 76,242 12.8 23.4 (22.0–24.8)

Medical examination* 878 10,273 1.7 3.2 (2.5–3.8)

Blood test 576 6,524 1.1 2.0 (1.5–2.5)

Dressing/pressure/compress/tamponade* 310 4,106 0.7 1.3 (1.0–1.5)

Pain general/multiple sites 258 3,642 0.6 1.1 (0.9–1.3)

Endocrine, metabolic and nutritional 7,831 76,009 12.7 23.3 (19.4–27.3)

Diabetes - non-gestational* 3,588 35,390 5.9 10.9 (9.0–12.7)

Diabetes type 2 2,986 29,437 4.9 9.0 (7.2–10.8)

Diabetes - unspecified 510 5,228 0.9 1.6 (1.0–2.3)

Lipid disorder 3,194 29,520 4.9 9.1 (7.3–10.9)

Blood test endocrine/metabolic 664 7,211 1.2 2.2 (1.6–2.9)

Cardiovascular 6,029 58,483 9.8 18.0 (15.8–20.1)

Hypertension - cardiovascular* 5,518 53,495 9.0 16.4 (14.5–18.4)

65



Weighted count


(n = 597,563)


(95% CI) (n = 325,818)




Injuries 194 1,535 0.6 1.2 (0.9–1.4)

Neoplasms 8 33 0.0 0.0 (0.0–0.1)





Test results 196 1,784 0.7 1.4 (0.7–2.1)


Administrative 32 529 0.2 0.4 (0.0–0.8)

Total 29,478 252,050 100.0 191.5 (182.5–200.5)



count Weighted

count


(n = 597,563)


(n = 325,818)




Injuries 291 4,316 1.3 2.2 (1.9–2.6)

Neoplasms 8 132 0.0 0.1 (0.0–0.1)





Test results 30 442 0.1 0.2 (0.1–0.4)


Administrative 2 77 0.0 0.0 (0.0–0.1)

Total 21,164 345,513 100.0 177.9 (171.4–184.4)



Weighted count


(n = 597,563)


(95% CI) (n = 325,818)




Injuries 194 1,535 0.6 1.2 (0.9–1.4)

Neoplasms 8 33 0.0 0.0 (0.0–0.1)





Test results 196 1,784 0.7 1.4 (0.7–2.1)


Administrative 32 529 0.2 0.4 (0.0–0.8)

Total 29,478 252,050 100.0 191.5 (182.5–200.5)



count Weighted

count


(n = 597,563)


(n = 325,818)




Injuries 291 4,316 1.3 2.2 (1.9–2.6)

Neoplasms 8 132 0.0 0.1 (0.0–0.1)





Test results 30 442 0.1 0.2 (0.1–0.4)


Administrative 2 77 0.0 0.0 (0.0–0.1)

Total 21,164 345,513 100.0 177.9 (171.4–184.4)


7.3 REASONS FOR ENCOUNTER BY ICPC-2 CHAPTERS

Table 7.3.1 shows the overall distribution of RFEs when categorised according to ICPC-2 chapters. Note that in some instances, related RFEs within a certain ICPC-2 chapter were collapsed into a single RFE.

• The most common RFEs were respiratory conditions, which accounted for 26.8% of all RFEs (49.2 per 100 patient encounters).

• General and unspecified conditions were the second most frequent RFEs (20.3% of all RFEs). Among these conditions, fever was the most frequently reported reason for visit (62.9% of all general and unspecified conditions).

• Chronic conditions under the endocrine, metabolic and nutritional category accounted for 12.7% of all RFEs, with 10.9 RFEs per 100 encounters recorded for diabetes and 9.1 per 100 encounters for lipid disorder. For reference, the National Health Morbidity Survey (NHMS) 2011 reported the prevalence for diabetes and hypercholesterolemia in Malaysia to be at 15.2% and 35.1%, respectively.2

Table 7.3.1: Reasons for encounter by ICPC-2 chapters and the most common individual reasons for encounter within each chapter in primary care clinics in 2014

RFE (ICPC-2 chapter) Unweighted count

Weighted count


(n = 597,563)


(95% CI) (n = 325,818)

Respiratory 12,660 160,186 26.8 49.2 (46.1–52.2)

Cough 6,022 74,905 12.5 23.0 (21.7–24.3)

Runny nose/rhinorrhoea 4,328 53,469 9.0 16.4 (15.1–17.7)

Pain/sore throat* 982 14,030 2.4 4.3 (3.5–5.2)

Asthma 623 7,834 1.3 2.4 (1.9–2.9)


Fever 6,071 76,242 12.8 23.4 (22.0–24.8)


Blood test 576 6,524 1.1 2.0 (1.5–2.5)

Dressing/pressure/compress/tamponade* 310 4,106 0.7 1.3 (1.0–1.5)

Pain general/multiple sites 258 3,642 0.6 1.1 (0.9–1.3)


Diabetes - non-gestational* 3,588 35,390 5.9 10.9 (9.0–12.7)

Diabetes type 2 2,986 29,437 4.9 9.0 (7.2–10.8)


Lipid disorder 3,194 29,520 4.9 9.1 (7.3–10.9)

Blood test endocrine/metabolic 664 7,211 1.2 2.2 (1.6–2.9)

Cardiovascular 6,029 58,483 9.8 18.0 (15.8–20.1)



Table 7.3.1 (continued): Reasons for encounter by ICPC-2 chapters and the most common individual reasons for encounter within each chapter in primary care clinics in 2014

RFE (ICPC-2 chapter) Unweighted

count Weighted

count


(n = 597,563)


(95% CI) (n = 325,818)

Digestive 3,903 50,539 8.5 15.5 (14.4–16.7)

Abdominal pain* 1,193 16,010 2.7 4.9 (4.4–5.4)

Diarrhoea 1,149 15,285 2.6 4.7 (4.3–5.1)

Vomiting 440 4,988 0.8 1.5 (1.3–1.8)

Musculoskeletal 2,628 36,097 6.0 11.1 (10.1–12.1)

Musculoskeletal symptom/complaints* 1,533 20,217 3.4 6.2 (5.4–7.0)

Back problems* 726 10,720 1.8 3.3 (2.8–3.7)

Skin 1,930 25,111 4.2 7.7 (6.5–8.9)

Rash* 535 7,006 1.2 2.2 (1.5–2.8)

Pruritus 474 5,972 1.0 1.8 (1.2–2.5)

Neurological 1,578 21,824 3.7 6.7 (5.9–7.5)

Headache - all* 1,015 14,788 2.5 4.5 (4.0–5.1)

Headache 975 13,901 2.3 4.3 (3.8–4.8)

Vertigo/dizziness 382 5,003 0.8 1.5 (1.2–1.9)

Pregnancy, childbearing, family planning 1,902 17,628 3.0 5.4 (4.4–6.4)

Medical examination - pregnancy* 1,567 14,412 2.4 4.4 (3.5–5.3)

Urological 602 7,352 1.2 2.3 (1.8–2.7)

Urinary problem* 228 2,862 0.5 0.9 (0.7–1.1)

Eye 632 7,322 1.2 2.3 (1.9–2.6)

Symptom/complaint eye* 458 5,095 0.9 1.6 (1.2–1.9)

Female genital 377 5,214 0.9 1.6 (1.3–1.9)

Menstrual problems* 193 3,109 0.5 1.0 (0.7–1.2)

Psychological 296 4,281 0.7 1.3 (0.8–1.8)

Ear 256 3,244 0.5 1.0 (0.8–1.2)

Blood, blood forming organs & immune mechanism 221 2,430 0.4 0.8 (0.5–1.0)

Male genital 56 639 0.1 0.2 (0.1–0.3)

Social problems 1 2 0.0 0.0 (0.0–0.0)

Total 50,642 597,563 100.0 183.4 (178.1–188.7)

*Comprise multiple ICPC-2 codes (see Appendix 4)

7.4 MOST COMMON REASONS FOR ENCOUNTER IN PUBLIC AND PRIVATE CLINICS

NMCS 2012 reported that the main reason for utilisation of primary care in the public sector was non-communicable diseases, with hypertension being the top reason for encounter, followed by diabetes and lipid disorder.1 Similar pattern was observed in NMCS 2014 (Figure 7.4.1).

• Patients who visited public clinics reported 191.5 RFEs per 100 encounters, slightly more than those in private clinics (177.9 per 100 encounters).

• A distinct difference observed between the two sectors when comparing the 10 commonest RFEs is the pattern of diseases presenting to each sector. The top three RFEs reported in public clinics were chronic diseases, whereas in private clinics, patient encounters were mostly for acute complaints.

• Blood tests related to endocrine/metabolic conditions were among the top 10 reasons for visit to public clinics. This utilisation could be due to periodic check-up on existing non-communicable diseases and demonstrates the utilisation of primary health care other than for consultations and medications.

Figure 7.4.1: Top 10 reasons for encounter in public clinics in 2014


3.9

4.2

4.4

9.3

12.0

16.2

17.8

18.5

22.5

31.3

0 5 10 15 20 25 30 35 40

Blood test endo/metabolic

Medical examination*

Musculoskeletal symptom/complaints*

Medical examination - pregnancy*

Runny nose/rhinorrhoea

Fever

Cough

Lipid disorder

Diabetes - all*

Hypertension - all*


67

Table 7.3.1 (continued): Reasons for encounter by ICPC-2 chapters and the most common individual reasons for encounter within each chapter in primary care clinics in 2014

RFE (ICPC-2 chapter) Unweighted

count Weighted

count


(n = 597,563)


(95% CI) (n = 325,818)

Digestive 3,903 50,539 8.5 15.5 (14.4–16.7)

Abdominal pain* 1,193 16,010 2.7 4.9 (4.4–5.4)

Diarrhoea 1,149 15,285 2.6 4.7 (4.3–5.1)

Vomiting 440 4,988 0.8 1.5 (1.3–1.8)



Back problems* 726 10,720 1.8 3.3 (2.8–3.7)

Skin 1,930 25,111 4.2 7.7 (6.5–8.9)

Rash* 535 7,006 1.2 2.2 (1.5–2.8)

Pruritus 474 5,972 1.0 1.8 (1.2–2.5)

Neurological 1,578 21,824 3.7 6.7 (5.9–7.5)

Headache - all* 1,015 14,788 2.5 4.5 (4.0–5.1)

Headache 975 13,901 2.3 4.3 (3.8–4.8)



Medical examination - pregnancy* 1,567 14,412 2.4 4.4 (3.5–5.3)

Urological 602 7,352 1.2 2.3 (1.8–2.7)

Urinary problem* 228 2,862 0.5 0.9 (0.7–1.1)

Eye 632 7,322 1.2 2.3 (1.9–2.6)

Symptom/complaint eye* 458 5,095 0.9 1.6 (1.2–1.9)

Female genital 377 5,214 0.9 1.6 (1.3–1.9)


Psychological 296 4,281 0.7 1.3 (0.8–1.8)

Ear 256 3,244 0.5 1.0 (0.8–1.2)


Male genital 56 639 0.1 0.2 (0.1–0.3)

Social problems 1 2 0.0 0.0 (0.0–0.0)

Total 50,642 597,563 100.0 183.4 (178.1–188.7)



7.4 MOST COMMON REASONS FOR ENCOUNTER IN PUBLIC AND PRIVATE CLINICS

NMCS 2012 reported that the main reason for utilisation of primary care in the public sector was non-communicable diseases, with hypertension being the top reason for encounter, followed by diabetes and lipid disorder.1 Similar pattern was observed in NMCS 2014 (Figure 7.4.1).

• Patients who visited public clinics reported 191.5 RFEs per 100 encounters, slightly more than those in private clinics (177.9 per 100 encounters).

• A distinct difference observed between the two sectors when comparing the 10 commonest RFEs is the pattern of diseases presenting to each sector. The top three RFEs reported in public clinics were chronic diseases, whereas in private clinics, patient encounters were mostly for acute complaints.

• Blood tests related to endocrine/metabolic conditions were among the top 10 reasons for visit to public clinics. This utilisation could be due to periodic check-up on existing non-communicable diseases and demonstrates the utilisation of primary health care other than for consultations and medications.

Figure 7.4.1: Top 10 reasons for encounter in public clinics in 2014


3.9

4.2

4.4

9.3

12.0

16.2

17.8

18.5

22.5

31.3

0 5 10 15 20 25 30 35 40

Blood test endo/metabolic

Medical examination*


Medical examination - pregnancy*


Fever

Cough

Lipid disorder

Diabetes - all*

Hypertension - all*



Figure 7.4.2: Top 10 reasons for encounter in private clinics in 2014


REFERENCES

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-4718. Supported by the Ministry of Health Malaysia.

2. Institute for Public Health (IPH). National Health and Morbidity Survey 2011 (NHMS 2011). Vol. 2: Non Communicable Diseases; 2011. 188 p. Report No.: MOH/S/IKU/04.12(TR). Grant No.: NMRR-10-757-6837. Supported by the Ministry of Health Malaysia.

4.5

6.2

6.2

6.2

6.3

6.4

7.5

19.4

26.5

28.3

0 5 10 15 20 25 30 35 40

Back problems*

Headache - all*

Diarrhoea

Pain/sore throat*

Hypertension - cardiovascular*

Abdominal pain*



Cough

Fever


Figure 7.4.2: Top 10 reasons for encounter in private clinics in 2014


REFERENCES


2. Institute for Public Health (IPH). National Health and Morbidity Survey 2011 (NHMS 2011). Vol. 2: Non Communicable Diseases; 2011. 188 p. Report No.: MOH/S/IKU/04.12(TR). Grant No.: NMRR-10-757-6837. Supported by the Ministry of Health Malaysia.

4.5

6.2

6.2

6.2

6.3

6.4

7.5

19.4

26.5

28.3

0 5 10 15 20 25 30 35 40

Back problems*

Headache - all*

Diarrhoea

Pain/sore throat*


Abdominal pain*



Cough

Fever


CHAPTER eightDiagnoses


CHAPTER 8: DIAGNOSES

In this chapter, diagnoses reported by primary care providers at the time of visit are presented and discussed. During an encounter, a patient might present with an existing or new problem(s), and the healthcare provider would record the problems as symptoms or diagnoses. Healthcare providers could record more than one diagnosis for each encounter. Note that only diagnoses managed and reported for each encounter were captured.

8.1 NUMBER OF DIAGNOSES PER ENCOUNTER

A total of 436,743 diagnoses were recorded in NMCS 2014, at a rate of 134.0 diagnoses per 100 encounters. Distributions of recorded diagnoses according to sectors were as follows:

• Public clinics: 154.9 diagnoses per 100 encounters • Private clinics: 119.9 diagnoses per 100 encounters

Figure 8.1.1 presents the number of diagnoses per visit by sectors in 2014.

• More than three-quarters (83.5%) of patients who presented to private clinics had a single diagnosis per visit, compared with 63.0% of their counterparts in public clinics.

Figure 8.1.1: Number of diagnoses managed per encounter in primary care clinics in 2014



Public 63.0 20.4 15.5 1.2

Private 83.5 13.4 2.9 0.3

0

10

20

30

40

50

60

70

80

90

Per

cen

t o

f en

cou

nte

rs (

%)

Number of diagnoses per encounter

Figure 8.1.2 shows the age- and gender-specific rate of diagnoses in public and private clinics in 2014. In keeping with our previous findings in 2012,1 the number of diagnoses increased with increasing age for both sectors, with the increase being more pronounced in the public sector, especially for age groups over 40 years.

Figure 8.1.2: Age- and gender- specific rates of diagnoses managed per 100 encounters by sector in 2014


8.2 DIAGNOSES BY ICPC-2 COMPONENTS

Diagnoses managed in primary care were categorised by ICPC-2 components (based on the aspects of the consultation). Table 8.2.1 shows the distribution of diagnoses by these components in terms of proportion of all diagnoses and rate per 100 encounters.

• Diagnosis of diseases accounted for 77.9% of all diagnoses. Nearly half (47.4%) of all diagnoses were categorised as “other diagnosis/diseases”, a classification for diagnoses which did not fit into the categories of infectious diseases, injuries, neoplasms and congenital anomalies. This was followed by infectious diseases (27.5%), which were recorded at a rate of 36.9 diagnoses per 100 encounters.

• The second most frequent diagnosis by ICPC-2 component was the “symptoms and complaints” category, which was reported at a rate of 22.2 diagnoses per 100 encounters.

192.8

209.6

139.9

145.8

0

50

100

150

200

250

< 1 1–4 5–19 20–39 40–59 ≥ 60

Ra

te p

er 1

00 e

nco

un

ters

Age group (years)

Public; male

Public; female

Private; male

Private; female

71

CHAPTER 8: DIAGNOSES

In this chapter, diagnoses reported by primary care providers at the time of visit are presented and discussed. During an encounter, a patient might present with an existing or new problem(s), and the healthcare provider would record the problems as symptoms or diagnoses. Healthcare providers could record more than one diagnosis for each encounter. Note that only diagnoses managed and reported for each encounter were captured.

8.1 NUMBER OF DIAGNOSES PER ENCOUNTER

A total of 436,743 diagnoses were recorded in NMCS 2014, at a rate of 134.0 diagnoses per 100 encounters. Distributions of recorded diagnoses according to sectors were as follows:

• Public clinics: 154.9 diagnoses per 100 encounters • Private clinics: 119.9 diagnoses per 100 encounters

Figure 8.1.1 presents the number of diagnoses per visit by sectors in 2014.

• More than three-quarters (83.5%) of patients who presented to private clinics had a single diagnosis per visit, compared with 63.0% of their counterparts in public clinics.

Figure 8.1.1: Number of diagnoses managed per encounter in primary care clinics in 2014



Public 63.0 20.4 15.5 1.2

Private 83.5 13.4 2.9 0.3

0

10

20

30

40

50

60

70

80

90

Per

cen

t o

f en

cou

nte

rs (

%)

Number of diagnoses per encounter

Chapter 8 : Diagnoses

Figure 8.1.2 shows the age- and gender-specific rate of diagnoses in public and private clinics in 2014. In keeping with our previous findings in 2012,1 the number of diagnoses increased with increasing age for both sectors, with the increase being more pronounced in the public sector, especially for age groups over 40 years.

Figure 8.1.2: Age- and gender- specific rates of diagnoses managed per 100 encounters by sector in 2014


8.2 DIAGNOSES BY ICPC-2 COMPONENTS

Diagnoses managed in primary care were categorised by ICPC-2 components (based on the aspects of the consultation). Table 8.2.1 shows the distribution of diagnoses by these components in terms of proportion of all diagnoses and rate per 100 encounters.

• Diagnosis of diseases accounted for 77.9% of all diagnoses. Nearly half (47.4%) of all diagnoses were categorised as “other diagnosis/diseases”, a classification for diagnoses which did not fit into the categories of infectious diseases, injuries, neoplasms and congenital anomalies. This was followed by infectious diseases (27.5%), which were recorded at a rate of 36.9 diagnoses per 100 encounters.

• The second most frequent diagnosis by ICPC-2 component was the “symptoms and complaints” category, which was reported at a rate of 22.2 diagnoses per 100 encounters.

192.8

209.6

139.9

145.8

0

50

100

150

200

250

< 1 1–4 5–19 20–39 40–59 ≥ 60

Ra

te p

er 1

00 e

nco

un

ters

Age group (years)

Public; male

Public; female

Private; male

Private; female


Table 8.2.1: Diagnoses by ICPC-2 components in primary care clinics in 2014

Diagnosis

(ICPC-2 component) Unweighted

count Weighted

count

Percent of total

diagnoses (n = 436,743)


(95% CI) (n = 325,818)


Infectious diseases 9,625 120,114 27.5 36.9 (34.8–38.9)

Injuries 1,006 12,720 2.9 3.9 (3.4–4.4)

Neoplasms 35 374 0.1 0.1 (0.1–0.2)


Other 19,610 206,830 47.4 63.5 (58.0–69.0)




Test results 11 141 0.0 0.0 (0.0–0.1)


Administrative 12 99 0.0 0.0 (0.0–0.1)

Total 38,151 436,743 100.0 134.0 (130.6–137.5)

8.3 DIAGNOSES BY ICPC-2 CHAPTERS

Table 8.3.1 presents the distribution of diagnoses according to ICPC-2 chapters (classified based on the body systems involved) and the most frequent diagnoses within each chapter. The conditions are reported in descending order of percentage of all diagnoses.

• The most frequent problem that presented to primary care was respiratory-related. This amounted to 23.4% of all diagnoses and 31.4% of all patient encounters in primary care. Majority of the patients (71.7%) were managed for an upper respiratory tract infection. Asthma only accounted for 2.9 diagnoses per 100 patient encounters recorded in primary care.

• The second most frequently managed problem was under the endocrine, metabolic and nutritional chapter (17.4% of all diagnoses), which includes diabetes and lipid disorder. Non-gestational diabetes (type 1, type 2 and unspecified type inclusive) accounted for 8.1% of all diagnoses, while lipid disorder was reported at a rate of 10.6 diagnoses per 100 patient encounters (7.9% of all diagnoses).

• Cardiovascular diseases ranked third among the leading diagnoses in primary care, representing 14.3% of all diagnoses. Hypertension, the cardiovascular disease which was also the second most frequent condition seen in primary care, accounted for 12.8% of all diagnoses and 17.2% of all patient encounters.

Table 8.3.1: Diagnosis by ICPC-2 chapters and the most common individual diagnoses within each chapter in NMCS 2014

Diagnosis

(ICPC-2 chapter) Unweighted

count Weighted

count

Percent of total



(95% CI) (n = 325,818)

Respiratory 8,164 102,329 23.4 31.4 (29.9–32.9)

Upper respiratory tract infection 5,928 73,345 16.8 22.5 (21.1–23.9)

Asthma 718 9,343 2.1 2.9 (2.3–3.4)

Tonsillitis 416 4,662 1.1 1.4 (1.2–1.7)

Cough 283 3,468 0.8 1.1 (0.8–1.3)

Acute bronchitis 146 2,069 0.5 0.6 (0.4–0.8)


Non-gestational diabetes* 3,609 35,443 8.1 10.9 (9.0–12.8)

Diabetes type 2 2,993 29,024 6.7 8.9 (7.0–10.8)


Lipid disorder 3,693 34,668 7.9 10.6 (8.7–12.6)

Cardiovascular 6,337 62,233 14.3 19.1 (16.9–21.3)


Ischaemic heart disease* 236 2,160 0.5 0.7 (0.5–0.8)


Fever 900 11,267 2.6 3.5 (2.9–4.1)


Disease/condition of unspecified nature/site 400 5,330 1.2 1.6 (1.2–2.1)

Digestive 2,833 37,011 8.5 11.4 (10.6–12.2)

Gastroenteritis* 981 13,139 3.0 4.0 (3.5–4.6)

Stomach function disorder 687 8,748 2.0 2.7 (2.3–3.1)

Abdominal pain* 171 2,573 0.6 0.8 (0.6–1.0)

Diarrheoa 186 2,387 0.6 0.7 (0.6–0.9)



Back problems* 414 6,812 1.6 2.1 (1.7–2.5)

Arthritis - all* 257 4,278 1.0 1.3 (0.7–1.9)

Osteoarthritis* 176 3,215 0.7 1.0 (0.4–1.6)

Sprain/strain* 134 2,242 0.5 0.7 (0.5–0.9)

73

Table 8.2.1: Diagnoses by ICPC-2 components in primary care clinics in 2014

Diagnosis

(ICPC-2 component) Unweighted

count Weighted

count

Percent of total



(95% CI) (n = 325,818)


Infectious diseases 9,625 120,114 27.5 36.9 (34.8–38.9)

Injuries 1,006 12,720 2.9 3.9 (3.4–4.4)

Neoplasms 35 374 0.1 0.1 (0.1–0.2)


Other 19,610 206,830 47.4 63.5 (58.0–69.0)




Test results 11 141 0.0 0.0 (0.0–0.1)


Administrative 12 99 0.0 0.0 (0.0–0.1)

Total 38,151 436,743 100.0 134.0 (130.6–137.5)

8.3 DIAGNOSES BY ICPC-2 CHAPTERS

Table 8.3.1 presents the distribution of diagnoses according to ICPC-2 chapters (classified based on the body systems involved) and the most frequent diagnoses within each chapter. The conditions are reported in descending order of percentage of all diagnoses.

• The most frequent problem that presented to primary care was respiratory-related. This amounted to 23.4% of all diagnoses and 31.4% of all patient encounters in primary care. Majority of the patients (71.7%) were managed for an upper respiratory tract infection. Asthma only accounted for 2.9 diagnoses per 100 patient encounters recorded in primary care.

• The second most frequently managed problem was under the endocrine, metabolic and nutritional chapter (17.4% of all diagnoses), which includes diabetes and lipid disorder. Non-gestational diabetes (type 1, type 2 and unspecified type inclusive) accounted for 8.1% of all diagnoses, while lipid disorder was reported at a rate of 10.6 diagnoses per 100 patient encounters (7.9% of all diagnoses).

• Cardiovascular diseases ranked third among the leading diagnoses in primary care, representing 14.3% of all diagnoses. Hypertension, the cardiovascular disease which was also the second most frequent condition seen in primary care, accounted for 12.8% of all diagnoses and 17.2% of all patient encounters.


Table 8.3.1: Diagnosis by ICPC-2 chapters and the most common individual diagnoses within each chapter in NMCS 2014

Diagnosis

(ICPC-2 chapter) Unweighted

count Weighted

count

Percent of total



(95% CI) (n = 325,818)

Respiratory 8,164 102,329 23.4 31.4 (29.9–32.9)

Upper respiratory tract infection 5,928 73,345 16.8 22.5 (21.1–23.9)

Asthma 718 9,343 2.1 2.9 (2.3–3.4)

Tonsillitis 416 4,662 1.1 1.4 (1.2–1.7)

Cough 283 3,468 0.8 1.1 (0.8–1.3)

Acute bronchitis 146 2,069 0.5 0.6 (0.4–0.8)



Diabetes type 2 2,993 29,024 6.7 8.9 (7.0–10.8)


Lipid disorder 3,693 34,668 7.9 10.6 (8.7–12.6)

Cardiovascular 6,337 62,233 14.3 19.1 (16.9–21.3)


Ischaemic heart disease* 236 2,160 0.5 0.7 (0.5–0.8)


Fever 900 11,267 2.6 3.5 (2.9–4.1)


Disease/condition of unspecified nature/site 400 5,330 1.2 1.6 (1.2–2.1)

Digestive 2,833 37,011 8.5 11.4 (10.6–12.2)

Gastroenteritis* 981 13,139 3.0 4.0 (3.5–4.6)

Stomach function disorder 687 8,748 2.0 2.7 (2.3–3.1)

Abdominal pain* 171 2,573 0.6 0.8 (0.6–1.0)

Diarrheoa 186 2,387 0.6 0.7 (0.6–0.9)



Back problems* 414 6,812 1.6 2.1 (1.7–2.5)

Arthritis - all* 257 4,278 1.0 1.3 (0.7–1.9)

Osteoarthritis* 176 3,215 0.7 1.0 (0.4–1.6)

Sprain/strain* 134 2,242 0.5 0.7 (0.5–0.9)


Table 8.3.1 (continued): Diagnosis by ICPC-2 chapters and the most common individual diagnoses within each chapter in NMCS 2014

Diagnosis (ICPC-2 chapter)

Unweighted count

Weighted count

Percent of total



(95% CI) (n = 325,818)

Skin 2,225 27,587 6.3 8.5 (7.7–9.2)

Dermatitis* 585 7,298 1.7 2.2 (1.9–2.6)

Dermatitis, contact/allergic 560 7,070 1.6 2.2 (1.8–2.5)

Dermatitis, atopic eczema 18 155 0.0 0.1 (0.0–0.1)

Injury skin - all* 226 3,018 0.7 0.9 (0.7–1.2)

Urticaria 165 2,951 0.7 0.9 (0.5–1.4)


Medical examination - pregnancy* 990 9,458 2.2 2.9 (2.3–3.6)

Neurological 996 14,103 3.2 4.3 (3.7–4.9)

Headache - all* 627 9,097 2.1 2.8 (2.4–3.2)

Headache 351 5,106 1.2 1.6 (1.2–1.9)

Migraine 187 2,878 0.7 0.9 (0.7–1.1)


Eye 548 5,981 1.4 1.8 (1.6–2.0)

Conjunctivitis* 310 3,343 0.8 1.0 (0.9–1.2)

Urological 486 5,969 1.4 1.8 (1.6–2.1)

Urinary tract infection* 302 3,729 0.9 1.1 (0.9–1.3)

Female genital 388 5,114 1.2 1.6 (1.3–1.8)


Psychological 363 4,674 1.1 1.4 (0.9–1.9)

Ear 269 3,389 0.8 1.0 (0.9–1.2)


Male genital 57 684 0.2 0.2 (0.1–0.3)

Social problems 15 135 0.0 0.0 (0.0–0.1)

Total 38,151 436,743 100.0 134.0 (130.6–137.5)

* Comprise multiple ICPC-2 codes (see Appendix 4)

The range and frequency of diagnoses managed in primary care have been studied internationally, and similar patterns were observed across countries. The 10 most commonly managed problems in general practice in Australia were hypertension, immunisation, upper respiratory tract infection, depression, diabetes, lipid disorder, general check-up, osteoarthritis, back complaint and prescription request.2 Closer to home, the top primary diagnoses seen in primary care clinics in Singapore were upper respiratory infection (13%), essential hypertension (7%), type 2 diabetes mellitus (6%) and hyperlipidaemia (5%).3

8.4 MOST COMMON DIAGNOSES MANAGED IN PUBLIC AND PRIVATE CLINICS

Significant differences were observed in the types of problems most commonly managed in the public and private spheres of Malaysia’s two-tier health system. Table 8.4.1 and Table 8.4.2 list the top 30 diagnoses in descending order of frequency for public and private clinics, respectively, reflecting the general morbidity pattern among primary care patients in 2014.

Public clinics

The top three diseases managed in the public sector were all chronic diseases. Together, they accounted for 50.8% of all diagnoses managed in government health clinics (Table 8.4.1).

• Hypertension, which was reported at a rate of 33.1 diagnoses per 100 encounters, accounted for 21.4% of all diagnoses.

• The second most frequent condition was diabetes, which accounted for 15.1% of all diagnoses, followed by lipid disorder at 14.3%.

• Approximately one-sixth (15.6%) of patients who sought treatment in public clinics were diagnosed with an upper respiratory tract infections (10.1% of all diagnoses).

• Antenatal check-ups accounted for 3.9% of all diagnoses and ranked fifth among the top diagnoses managed in public primary care clinics.

Private clinics

Table 8.4.2 lists the 30 most frequently managed diagnoses in private clinics in 2014. Together, these diagnoses accounted for approximately two-thirds (76.0%) of all diagnoses in private clinics; the top 10 diagnoses amounted to 52.9% of all diagnoses.

• More than one-quarter (27.2%) of patients seeking treatment in private clinics were diagnosed with an upper respiratory tract infection, which accounted for 22.7% of all diagnoses.

• Hypertension is the second most common condition managed in private clinics, occurring at rate of 6.5 diagnoses per 100 encounters (5.4% of all diagnoses).

• Ranking third to fifth among the top diagnoses in private clinics were acute conditions—gastroenteritis (4.5% of all diagnoses), musculoskeletal symptoms/complaints (3.7%) and fever (3.2%)—which accounted for 28.7% of the top five diagnoses.

• Diabetes and lipid disorders, which were the second and third most common diagnoses in public clinics, accounted for only 2.5% and 2.4% of all diagnoses managed in private clinics, respectively.

75

Table 8.3.1 (continued): Diagnosis by ICPC-2 chapters and the most common individual diagnoses within each chapter in NMCS 2014

Diagnosis (ICPC-2 chapter)

Unweighted count

Weighted count

Percent of total



(95% CI) (n = 325,818)

Skin 2,225 27,587 6.3 8.5 (7.7–9.2)

Dermatitis* 585 7,298 1.7 2.2 (1.9–2.6)


Dermatitis, atopic eczema 18 155 0.0 0.1 (0.0–0.1)

Injury skin - all* 226 3,018 0.7 0.9 (0.7–1.2)

Urticaria 165 2,951 0.7 0.9 (0.5–1.4)


Medical examination - pregnancy* 990 9,458 2.2 2.9 (2.3–3.6)

Neurological 996 14,103 3.2 4.3 (3.7–4.9)

Headache - all* 627 9,097 2.1 2.8 (2.4–3.2)

Headache 351 5,106 1.2 1.6 (1.2–1.9)

Migraine 187 2,878 0.7 0.9 (0.7–1.1)


Eye 548 5,981 1.4 1.8 (1.6–2.0)

Conjunctivitis* 310 3,343 0.8 1.0 (0.9–1.2)

Urological 486 5,969 1.4 1.8 (1.6–2.1)

Urinary tract infection* 302 3,729 0.9 1.1 (0.9–1.3)

Female genital 388 5,114 1.2 1.6 (1.3–1.8)


Psychological 363 4,674 1.1 1.4 (0.9–1.9)

Ear 269 3,389 0.8 1.0 (0.9–1.2)


Male genital 57 684 0.2 0.2 (0.1–0.3)

Social problems 15 135 0.0 0.0 (0.0–0.1)

Total 38,151 436,743 100.0 134.0 (130.6–137.5)


The range and frequency of diagnoses managed in primary care have been studied internationally, and similar patterns were observed across countries. The 10 most commonly managed problems in general practice in Australia were hypertension, immunisation, upper respiratory tract infection, depression, diabetes, lipid disorder, general check-up, osteoarthritis, back complaint and prescription request.2 Closer to home, the top primary diagnoses seen in primary care clinics in Singapore were upper respiratory infection (13%), essential hypertension (7%), type 2 diabetes mellitus (6%) and hyperlipidaemia (5%).3


8.4 MOST COMMON DIAGNOSES MANAGED IN PUBLIC AND PRIVATE CLINICS

Significant differences were observed in the types of problems most commonly managed in the public and private spheres of Malaysia’s two-tier health system. Table 8.4.1 and Table 8.4.2 list the top 30 diagnoses in descending order of frequency for public and private clinics, respectively, reflecting the general morbidity pattern among primary care patients in 2014.

Public clinics

The top three diseases managed in the public sector were all chronic diseases. Together, they accounted for 50.8% of all diagnoses managed in government health clinics (Table 8.4.1).

• Hypertension, which was reported at a rate of 33.1 diagnoses per 100 encounters, accounted for 21.4% of all diagnoses.

• The second most frequent condition was diabetes, which accounted for 15.1% of all diagnoses, followed by lipid disorder at 14.3%.

• Approximately one-sixth (15.6%) of patients who sought treatment in public clinics were diagnosed with an upper respiratory tract infections (10.1% of all diagnoses).

• Antenatal check-ups accounted for 3.9% of all diagnoses and ranked fifth among the top diagnoses managed in public primary care clinics.

Private clinics

Table 8.4.2 lists the 30 most frequently managed diagnoses in private clinics in 2014. Together, these diagnoses accounted for approximately two-thirds (76.0%) of all diagnoses in private clinics; the top 10 diagnoses amounted to 52.9% of all diagnoses.

• More than one-quarter (27.2%) of patients seeking treatment in private clinics were diagnosed with an upper respiratory tract infection, which accounted for 22.7% of all diagnoses.

• Hypertension is the second most common condition managed in private clinics, occurring at rate of 6.5 diagnoses per 100 encounters (5.4% of all diagnoses).

• Ranking third to fifth among the top diagnoses in private clinics were acute conditions—gastroenteritis (4.5% of all diagnoses), musculoskeletal symptoms/complaints (3.7%) and fever (3.2%)—which accounted for 28.7% of the top five diagnoses.

• Diabetes and lipid disorders, which were the second and third most common diagnoses in public clinics, accounted for only 2.5% and 2.4% of all diagnoses managed in private clinics, respectively.


Table 8.4.1: Thirty most common diagnoses managed in public clinics in 2014

Rank Diagnosis Unweighted

count (n = 23,760)

Weighted count

(n = 203,868)

Percent of total



(95% CI) (n = 131,624)

1 Hypertension - all* 4,966 43,597 21.4 33.1 (29.8–36.4)

Hypertension - Cardiovascular* 4,927 43,292 21.2 32.9 (29.6–36.2)

Hypertension in pregnancy 39 305 0.2 0.2 (0.1–0.4)

2 Diabetes - all* 3,334 30,776 15.1 23.4 (20.1–26.7)

Diabetes type 2 2,691 24,798 12.2 18.8 (15.4–22.3)


Gestational diabetes 141 1,152 0.6 0.9 (0.6–1.2)

3 Lipid disorder 3,366 29,115 14.3 22.1 (19.3–25.0)

4 Upper respiratory tract infection 2,687 20,527 10.1 15.6 (14.2–17.0)

5 Medical examination - pregnancy* 881 7,864 3.9 6.0 (4.3–7.6)

6 Musculoskeletal symptom/complaints*

552 5,028 2.5 3.8 (3.1–4.6)

7 Asthma 420 4,272 2.1 3.3 (2.4–4.1)

8 Fever 420 3,870 1.9 2.9 (2.1–3.8)

9 Medical examination* 404 3,488 1.7 2.7 (1.9–3.4)

10 Gastroenteritis* 361 2,741 1.3 2.1 (1.7–2.5)

11 Stomach function disorder 319 2,500 1.2 1.9 (1.6–2.2)

12 High risk pregnancy* 235 1,873 0.9 1.4 (0.8–2.0)

13 Headache - all* 223 1,849 0.9 1.4 (1.0–1.8)

Headache 134 1,153 0.6 0.9 (0.6–1.2)

14 Ischaemic heart disease* 215 1,821 0.9 1.4 (1.0–1.7)

15 Disease/condition of unspecified nature/site

167 1,712 0.8 1.3 (0.9–1.7)

16 Urinary tract infection* 166 1,460 0.7 1.1 (0.8–1.4)

17 Tonsillitis 194 1,396 0.7 1.1 (0.8–1.4)

18 Dermatitis* 198 1,340 0.7 1.0 (0.7–1.3)


19 Conjunctivitis* 164 1,167 0.6 0.9 (0.7–1.1)

20 Cough 98 972 0.5 0.7 (0.3–1.1)

21 Anaemia* 98 964 0.5 0.7 (0.4–1.0)

22 Viral disease 84 910 0.5 0.7 (0.4–1.0)

23 Contraception, female* 96 906 0.4 0.7 (0.4–1.0)

24 Arthritis - all* 93 878 0.4 0.7 (0.4–0.9)

25 Perinatal morbidity, other 151 872 0.4 0.7 (0.3–1.0)

26 Fear of infection; general 60 731 0.4 0.6 (0.1–1.0)

27 Gout 93 707 0.4 0.5 (0.4–0.7)

28 Back problems* 83 672 0.3 0.5 (0.3–0.7)

29 Fear of respiratory disease 61 635 0.3 0.5 (0.2–0.8)

30 Allergy/allergic reaction 72 610 0.3 0.6 (0.3–0.6)


Table 8.4.2: Thirty most common diagnoses managed in private clinics in 2014


count (n = 14,391)

Weighted count

(n = 232,874)

Percent of total



(95% CI) (n = 194,194)


2 Hypertension - cardiovascular* 820 12,648 5.4 6.5 (5.7–7.3)


4 Musculoskeletal symptom/complaints* 549 8,523 3.7 4.4 (3.8–5.0)

5 Fever 480 7,397 3.2 3.8 (3.0–4.7)

6 Headache - all* 404 7,249 3.1 3.7 (3.1–4.3)

Headache 217 3,953 1.7 2.0 (1.5–2.6)

Migraine 137 2,449 1.1 1.3 (0.9–1.6)


8 Back problems* 331 6,141 2.6 3.2 (2.5–3.8)

9 Dermatitis* 387 5,959 2.6 3.1 (2.5–3.7)


10 Diabetes - all* 416 5,818 2.5 3.0 (2.5–3.5)

Diabetes type 2 302 4,225 1.8 2.2 (1.7–2.6)


11 Lipid disorder 327 5,552 2.4 2.9 (1.8–4.0)

12 Asthma 298 5,071 2.2 2.6 (1.9–3.4)



233 3,617 1.6 1.9 (1.2–2.5)

15 Arthritis - all* 164 3,400 1.5 1.8 (0.7–2.8)

Osteoarthritis* 95 2,473 1.1 1.3 (0.3–2.3)

16 Tonsillitis 222 3,266 1.4 1.7 (1.3–2.1)

17 Menstrual problems* 146 2,509 1.1 1.3 (1.0–1.6)

18 Cough 185 2,496 1.1 1.3 (0.9–1.6)

19 Vertigo/dizziness 144 2,493 1.1 1.3 (0.9–1.7)

20 Urticaria 109 2,414 1.0 1.2 (0.5–2.0)

21 Abdominal pain* 133 2,332 1.0 1.2 (0.9–1.5)


23 Conjunctivitis* 146 2,175 0.9 1.1 (0.9–1.4)

24 Diarrheoa 146 2,147 0.9 1.1 (0.8–1.4)

25 Sprain/strain* 102 2,017 0.9 1.0 (0.8–1.3)

26 Acute bronchitis 131 1,959 0.8 1.0 (0.7–1.3)


28 Dermatophytosis 111 1,538 0.7 0.8 (0.6–1.0)

29 Respiratory infection* 43 1,433 0.6 0.7 (0.0–1.9)

30 Sinusitis 79 1,422 0.6 0.7 (0.5–1.0)


77

Table 8.4.1: Thirty most common diagnoses managed in public clinics in 2014


count (n = 23,760)

Weighted count

(n = 203,868)

Percent of total



(95% CI) (n = 131,624)


Hypertension - Cardiovascular* 4,927 43,292 21.2 32.9 (29.6–36.2)


2 Diabetes - all* 3,334 30,776 15.1 23.4 (20.1–26.7)

Diabetes type 2 2,691 24,798 12.2 18.8 (15.4–22.3)


Gestational diabetes 141 1,152 0.6 0.9 (0.6–1.2)

3 Lipid disorder 3,366 29,115 14.3 22.1 (19.3–25.0)



6 Musculoskeletal symptom/complaints*

552 5,028 2.5 3.8 (3.1–4.6)

7 Asthma 420 4,272 2.1 3.3 (2.4–4.1)

8 Fever 420 3,870 1.9 2.9 (2.1–3.8)




12 High risk pregnancy* 235 1,873 0.9 1.4 (0.8–2.0)

13 Headache - all* 223 1,849 0.9 1.4 (1.0–1.8)

Headache 134 1,153 0.6 0.9 (0.6–1.2)

14 Ischaemic heart disease* 215 1,821 0.9 1.4 (1.0–1.7)


167 1,712 0.8 1.3 (0.9–1.7)


17 Tonsillitis 194 1,396 0.7 1.1 (0.8–1.4)

18 Dermatitis* 198 1,340 0.7 1.0 (0.7–1.3)


19 Conjunctivitis* 164 1,167 0.6 0.9 (0.7–1.1)

20 Cough 98 972 0.5 0.7 (0.3–1.1)

21 Anaemia* 98 964 0.5 0.7 (0.4–1.0)

22 Viral disease 84 910 0.5 0.7 (0.4–1.0)

23 Contraception, female* 96 906 0.4 0.7 (0.4–1.0)

24 Arthritis - all* 93 878 0.4 0.7 (0.4–0.9)

25 Perinatal morbidity, other 151 872 0.4 0.7 (0.3–1.0)

26 Fear of infection; general 60 731 0.4 0.6 (0.1–1.0)

27 Gout 93 707 0.4 0.5 (0.4–0.7)

28 Back problems* 83 672 0.3 0.5 (0.3–0.7)

29 Fear of respiratory disease 61 635 0.3 0.5 (0.2–0.8)

30 Allergy/allergic reaction 72 610 0.3 0.6 (0.3–0.6)



Table 8.4.2: Thirty most common diagnoses managed in private clinics in 2014


count (n = 14,391)

Weighted count

(n = 232,874)

Percent of total



(95% CI) (n = 194,194)





5 Fever 480 7,397 3.2 3.8 (3.0–4.7)

6 Headache - all* 404 7,249 3.1 3.7 (3.1–4.3)

Headache 217 3,953 1.7 2.0 (1.5–2.6)

Migraine 137 2,449 1.1 1.3 (0.9–1.6)


8 Back problems* 331 6,141 2.6 3.2 (2.5–3.8)

9 Dermatitis* 387 5,959 2.6 3.1 (2.5–3.7)


10 Diabetes - all* 416 5,818 2.5 3.0 (2.5–3.5)

Diabetes type 2 302 4,225 1.8 2.2 (1.7–2.6)


11 Lipid disorder 327 5,552 2.4 2.9 (1.8–4.0)

12 Asthma 298 5,071 2.2 2.6 (1.9–3.4)



233 3,617 1.6 1.9 (1.2–2.5)

15 Arthritis - all* 164 3,400 1.5 1.8 (0.7–2.8)

Osteoarthritis* 95 2,473 1.1 1.3 (0.3–2.3)

16 Tonsillitis 222 3,266 1.4 1.7 (1.3–2.1)

17 Menstrual problems* 146 2,509 1.1 1.3 (1.0–1.6)

18 Cough 185 2,496 1.1 1.3 (0.9–1.6)

19 Vertigo/dizziness 144 2,493 1.1 1.3 (0.9–1.7)

20 Urticaria 109 2,414 1.0 1.2 (0.5–2.0)

21 Abdominal pain* 133 2,332 1.0 1.2 (0.9–1.5)


23 Conjunctivitis* 146 2,175 0.9 1.1 (0.9–1.4)

24 Diarrheoa 146 2,147 0.9 1.1 (0.8–1.4)

25 Sprain/strain* 102 2,017 0.9 1.0 (0.8–1.3)

26 Acute bronchitis 131 1,959 0.8 1.0 (0.7–1.3)


28 Dermatophytosis 111 1,538 0.7 0.8 (0.6–1.0)

29 Respiratory infection* 43 1,433 0.6 0.7 (0.0–1.9)

30 Sinusitis 79 1,422 0.6 0.7 (0.5–1.0)



REFERENCES


2. Cooke G, Valenti L, Glasziou P, Britt H. Common general practice presentations and publication frequency. Aust Fam Physician. 2013 Jan-Feb;42(1-2):65-8.

3. National Healthcare Group Polyclinics (SG). Advancing family medicine, transforming primary healthcare [Internet]. Singapore: National Healthcare Group Polyclinics; c2014 [cited 2015 Apr 8]. Available from: https://www.nhgp.com.sg/uploadedFiles/About_Us/NHGP_Corporate%20brochure_DPS_Web.pdf

REFERENCES


2. Cooke G, Valenti L, Glasziou P, Britt H. Common general practice presentations and publication frequency. Aust Fam Physician. 2013 Jan-Feb;42(1-2):65-8.

3. National Healthcare Group Polyclinics (SG). Advancing family medicine, transforming primary healthcare [Internet]. Singapore: National Healthcare Group Polyclinics; c2014 [cited 2015 Apr 8]. Available from: https://www.nhgp.com.sg/uploadedFiles/About_Us/NHGP_Corporate%20brochure_DPS_Web.pdf

CHAPTER nineMedications


CHAPTER 9: MEDICATIONS

During primary care encounters, patients were prescribed medications for their conditions as deemed necessary by the respective healthcare providers. The providers were instructed to record the medications prescribed in generic or brand names, the dosage form, route of administration, dose, frequency and duration of therapy. Note that NMCS 2014 captured only the medications prescribed and not the medications dispensed. Hence, the data presented here do not reflect the actual consumption of medications in the primary care setting.

9.1 NUMBER OF MEDICATIONS PRESCRIBED PER ENCOUNTER

Number of encounters with medical prescription

Table 9.1.1 presents the number of encounters with and without medical prescription in primary care clinics in 2014.

• A total of 292,906 (89.9%) encounters were prescribed with at least one medication. • The percentage of encounters during which medications were prescribed was higher in private

clinics compared to public clinics (92.1% versus 86.6%, respectively).

Table 9.1.1: Number of encounters with and without medical prescription in primary care clinics in 2014

Number of encounters Unweighted

count Weighted count Percent of encounters

(95% CI)

Overall

With medication 24,523 292,906 89.9 (88.9–90.9)

Without medication 3,064 32,912 10.1 (9.1–11.1)

Public

With medication 13,387 114,048 86.7 (84.8–88.5)


Private

With medication 11,136 178,857 92.1 (91.0–93.2)

Without medication 981 15,337 7.9 (6.8–9.0)

Number of medications prescribed

Table 9.1.2 shows the total number of medications prescribed and the prescription rates by encounters and by diagnoses in primary care clinics in 2014.

• A total of 864,552 medications were prescribed, of which 37.8% were prescribed in the public sector while the remaining 62.2% were prescribed in the private sector.

• The medication prescribing rate in the public sector was 248.5 medications per 100 encounters, which was lower compared to the private sector, which recorded a rate of 276.8 medications per 100 encounters.

• The public-private difference was even greater when the prescription rate per diagnosis was examined. For every 100 diagnoses, approximately 70 more medications were prescribed in the private sector than in the public sector (230.8 medications versus 160.4 medications, respectively).

Table 9.1.2: Number of medications prescribed in primary care clinics in 2014

Number of medications

Unweighted count

Weighted count

Percent of prescribed

medications (95% CI)

(n = 864,552)


(95% CI) (n = 325,818)

Rate per 100 diagnoses (95% CI)

(n = 436,743)

Overall 70,711 864,552 100.0 265.3 (256.7–274.0) 198.0 (190.8–205.1)

Public 38,296 327,087 37.8 (31.8–43.8) 248.5 (236.7–260.3) 160.4 (156.5–164.4)

Private 32,415 537,465 62.2 (56.2–68.2) 276.8 (265.3–288.2) 230.8 (221.7–239.9)

Number of medications prescribed per encounter

Below is the pattern of prescription in the public and private sectors as presented in Figure 9.1.1.

• Generally, the primary care prescription pattern observed in NMCS 2014 was similar to the pattern observed in NMCS 2012.1

• More encounters in the public sector (13.4%) were not prescribed with any medication compared to the private sector (7.9%). This may be explained by the fact that the public sector had more diagnostic, screening and preventive encounters, which most likely did not require any medication.


• The highest number of medications prescribed per encounter was 15 and 13 in the public and the private sectors, respectively.

Figure 9.1.1: Number of medications prescribed per encounter in primary care clinics in 2014

Nil One Two Three ≥ Four

Public 13.4 18.5 22.4 20.1 25.7

Private 7.9 12.5 21.1 27.0 31.5

0

5

10

15

20

25

30

35

40

Per

cen

t o

f en

cou

nte

rs (

%)

Number of medications per encounter

81

CHAPTER 9: MEDICATIONS

During primary care encounters, patients were prescribed medications for their conditions as deemed necessary by the respective healthcare providers. The providers were instructed to record the medications prescribed in generic or brand names, the dosage form, route of administration, dose, frequency and duration of therapy. Note that NMCS 2014 captured only the medications prescribed and not the medications dispensed. Hence, the data presented here do not reflect the actual consumption of medications in the primary care setting.

9.1 NUMBER OF MEDICATIONS PRESCRIBED PER ENCOUNTER

Number of encounters with medical prescription

Table 9.1.1 presents the number of encounters with and without medical prescription in primary care clinics in 2014.

• A total of 292,906 (89.9%) encounters were prescribed with at least one medication. • The percentage of encounters during which medications were prescribed was higher in private

clinics compared to public clinics (92.1% versus 86.6%, respectively).

Table 9.1.1: Number of encounters with and without medical prescription in primary care clinics in 2014

Number of encounters Unweighted


(95% CI)

Overall

With medication 24,523 292,906 89.9 (88.9–90.9)


Public

With medication 13,387 114,048 86.7 (84.8–88.5)


Private

With medication 11,136 178,857 92.1 (91.0–93.2)

Without medication 981 15,337 7.9 (6.8–9.0)

Number of medications prescribed

Table 9.1.2 shows the total number of medications prescribed and the prescription rates by encounters and by diagnoses in primary care clinics in 2014.

• A total of 864,552 medications were prescribed, of which 37.8% were prescribed in the public sector while the remaining 62.2% were prescribed in the private sector.

• The medication prescribing rate in the public sector was 248.5 medications per 100 encounters, which was lower compared to the private sector, which recorded a rate of 276.8 medications per 100 encounters.

• The public-private difference was even greater when the prescription rate per diagnosis was examined. For every 100 diagnoses, approximately 70 more medications were prescribed in the private sector than in the public sector (230.8 medications versus 160.4 medications, respectively).

Chapter 9 : Medications

Table 9.1.2: Number of medications prescribed in primary care clinics in 2014

Number of medications

Unweighted count

Weighted count


medications (95% CI)

(n = 864,552)


(95% CI) (n = 325,818)


(n = 436,743)

Overall 70,711 864,552 100.0 265.3 (256.7–274.0) 198.0 (190.8–205.1)

Public 38,296 327,087 37.8 (31.8–43.8) 248.5 (236.7–260.3) 160.4 (156.5–164.4)

Private 32,415 537,465 62.2 (56.2–68.2) 276.8 (265.3–288.2) 230.8 (221.7–239.9)

Number of medications prescribed per encounter

Below is the pattern of prescription in the public and private sectors as presented in Figure 9.1.1.

• Generally, the primary care prescription pattern observed in NMCS 2014 was similar to the pattern observed in NMCS 2012.1

• More encounters in the public sector (13.4%) were not prescribed with any medication compared to the private sector (7.9%). This may be explained by the fact that the public sector had more diagnostic, screening and preventive encounters, which most likely did not require any medication.


• The highest number of medications prescribed per encounter was 15 and 13 in the public and the private sectors, respectively.

Figure 9.1.1: Number of medications prescribed per encounter in primary care clinics in 2014


Public 13.4 18.5 22.4 20.1 25.7

Private 7.9 12.5 21.1 27.0 31.5

0

5

10

15

20

25

30

35

40

Per

cen

t o

f en

cou

nte

rs (

%)

Number of medications per encounter


Age- and gender-specific prescription rate

Age- and gender-specific prescription rates per 100 encounters in public and private clinics are presented in Figure 9.1.2.

• The prescription rates were higher in the private sector for patients who were less than 40 years old compared to those in the public sector regardless of the gender. The trends were reversed for patients aged 40 years and above for both genders.

• The lowest prescription rate was recorded in the infant age group (less than one year old) for both sectors. Nevertheless, the prescription rate for infants was more than two times higher in the private sector compared to the public sector for both genders.

• No marked differences in prescription rate were observed between genders in different age groups for both sectors, except for the 20–39 and the 60 and above age groups in the public sector. In these two age groups, the differences were approximately 40 medications per 100 encounters. Similar trends were observed in NMCS 2012.1

• For both sectors, elderly females (aged 60 years and above) were prescribed more medications than their male counterparts: 353.8 versus 312.8 medications per 100 encounters in public clinics and 295.0 versus 268.3 medications per 100 encounters in private clinics.

• Of all age and gender groups, the elderly female patients in public clinics had the highest prescription rate (353.8 medications per 100 encounters, as reported above).

Figure 9.1.2: Age- and gender- specific prescription rates per 100 encounters by sector in 2014

97.4

312.8

80.1

353.8

211.4

268.3

227.2

295.0

0

50

100

150

200

250

300

350

400

< 1 1–4 5–19 20–39 40–59 ≥ 60

Ra

te p

er 1

00 e

nco

un

ters

Age group (years)

Public; male

Public; female

Private; male

Private; female

9.2 TYPES OF MEDICATIONS PRESCRIBED

The implication of the escalating healthcare costs in Malaysia, driven by the rising burden of chronic diseases and the hike in drug prices, has been the subject of much discussion. Table 9.2.1 shows the distribution of medications prescribed to primary care patients by the Anatomical Therapeutic Chemical (ATC) classification in 2014. The medications are reported according to their anatomical main group (ATC level 1), pharmacological subgroup (ATC level 3) and chemical substance (ATC level 5) in decreasing order of frequency. Only medications which accounted for at least 0.5% of all prescribed medications were included in the table.

• Consistent with our findings in NMCS 2012,1 the most common medications prescribed were respiratory system agents (22.4% of all medications), and systemic antihistamines contributed to more than half of all respiratory agents prescribed.

• The second most frequently prescribed drugs were the alimentary tract and metabolism agents (20.2% of all medications), which were prescribed at a rate of 53.6 medications per 100 encounters. Blood glucose lowering agents like metformin, gliclazide and glibenclamide, which were prescribed at a rate of 14.3 per 100 encounters, represented 26.7% of the alimentary tract and metabolism agents prescribed.

• Medications for cardiovascular system were prescribed at a rate of 41.0 per 100 encounters, making them the third most commonly prescribed drugs. This group of drugs constituted 15.4% of all medications prescribed in primary care clinics.

Table 9.2.2 and Table 9.2.3 present the distribution of the prescribed medications according to the ATC level 1 index classification in the public and private sectors, respectively.

• The top three medications prescribed in public clinics were cardiovascular agents (34.1%), alimentary tract and metabolism agents (24.7%) and respiratory system agents (14.1%). Among these three categories, oral hypoglycaemic agents, lipid modifying agents and calcium channel blockers were the predominant therapeutic agents prescribed in public clinics (see Table 9.3.1).

• Respiratory medications were the most frequently prescribed medications in private clinics, accounting for 27.4% of all medications prescribed in private clinics. This was followed by alimentary tract and metabolism agents at 17.4% (48.2 per 100 encounters) and musculoskeletal medications at 15.5% (43.0 per 100 encounters).

• Prescription drugs for cardiovascular system were recorded at a rate of 11.3 medications per 100 encounters, amounting to 4.1% of all medications prescribed in private clinics.

The prescription patterns in both public and private clinics were reflective of the types of diseases managed in the respective spheres of primary care, where chronic diseases such as dyslipidaemia, hypertension and diabetes were the predominant diagnoses managed in public clinics, while respiratory and cardiovascular diseases were the most common diagnoses in private clinics (see Chapter 8).

83

Age- and gender-specific prescription rate

Age- and gender-specific prescription rates per 100 encounters in public and private clinics are presented in Figure 9.1.2.

• The prescription rates were higher in the private sector for patients who were less than 40 years old compared to those in the public sector regardless of the gender. The trends were reversed for patients aged 40 years and above for both genders.

• The lowest prescription rate was recorded in the infant age group (less than one year old) for both sectors. Nevertheless, the prescription rate for infants was more than two times higher in the private sector compared to the public sector for both genders.

• No marked differences in prescription rate were observed between genders in different age groups for both sectors, except for the 20–39 and the 60 and above age groups in the public sector. In these two age groups, the differences were approximately 40 medications per 100 encounters. Similar trends were observed in NMCS 2012.1

• For both sectors, elderly females (aged 60 years and above) were prescribed more medications than their male counterparts: 353.8 versus 312.8 medications per 100 encounters in public clinics and 295.0 versus 268.3 medications per 100 encounters in private clinics.

• Of all age and gender groups, the elderly female patients in public clinics had the highest prescription rate (353.8 medications per 100 encounters, as reported above).

Figure 9.1.2: Age- and gender- specific prescription rates per 100 encounters by sector in 2014

97.4

312.8

80.1

353.8

211.4

268.3

227.2

295.0

0

50

100

150

200

250

300

350

400

< 1 1–4 5–19 20–39 40–59 ≥ 60

Ra

te p

er 1

00 e

nco

un

ters

Age group (years)

Public; male

Public; female

Private; male

Private; female


9.2 TYPES OF MEDICATIONS PRESCRIBED

The implication of the escalating healthcare costs in Malaysia, driven by the rising burden of chronic diseases and the hike in drug prices, has been the subject of much discussion. Table 9.2.1 shows the distribution of medications prescribed to primary care patients by the Anatomical Therapeutic Chemical (ATC) classification in 2014. The medications are reported according to their anatomical main group (ATC level 1), pharmacological subgroup (ATC level 3) and chemical substance (ATC level 5) in decreasing order of frequency. Only medications which accounted for at least 0.5% of all prescribed medications were included in the table.

• Consistent with our findings in NMCS 2012,1 the most common medications prescribed were respiratory system agents (22.4% of all medications), and systemic antihistamines contributed to more than half of all respiratory agents prescribed.

• The second most frequently prescribed drugs were the alimentary tract and metabolism agents (20.2% of all medications), which were prescribed at a rate of 53.6 medications per 100 encounters. Blood glucose lowering agents like metformin, gliclazide and glibenclamide, which were prescribed at a rate of 14.3 per 100 encounters, represented 26.7% of the alimentary tract and metabolism agents prescribed.

• Medications for cardiovascular system were prescribed at a rate of 41.0 per 100 encounters, making them the third most commonly prescribed drugs. This group of drugs constituted 15.4% of all medications prescribed in primary care clinics.

Table 9.2.2 and Table 9.2.3 present the distribution of the prescribed medications according to the ATC level 1 index classification in the public and private sectors, respectively.

• The top three medications prescribed in public clinics were cardiovascular agents (34.1%), alimentary tract and metabolism agents (24.7%) and respiratory system agents (14.1%). Among these three categories, oral hypoglycaemic agents, lipid modifying agents and calcium channel blockers were the predominant therapeutic agents prescribed in public clinics (see Table 9.3.1).

• Respiratory medications were the most frequently prescribed medications in private clinics, accounting for 27.4% of all medications prescribed in private clinics. This was followed by alimentary tract and metabolism agents at 17.4% (48.2 per 100 encounters) and musculoskeletal medications at 15.5% (43.0 per 100 encounters).

• Prescription drugs for cardiovascular system were recorded at a rate of 11.3 medications per 100 encounters, amounting to 4.1% of all medications prescribed in private clinics.

The prescription patterns in both public and private clinics were reflective of the types of diseases managed in the respective spheres of primary care, where chronic diseases such as dyslipidaemia, hypertension and diabetes were the predominant diagnoses managed in public clinics, while respiratory and cardiovascular diseases were the most common diagnoses in private clinics (see Chapter 8).


Table 9.2.1: Prescribed medications by ATC levels in primary care clinics in 2014

ATC Level 1

Unweighted count

Weighted count


medications (n = 864,552)


(95% CI) (n = 325,818)


(n = 436,743)

ATC Level 3

ATC Level 5

Respiratory system 14,485 193,365 22.4 59.4 (55.2–63.5) 44.3 (40.6–47.9)

Antihistamines for systemic use 8,203 105,576 12.2 32.4 (30.1–34.7) 24.2 (22.2–26.2)

Diphenhydramine, combinations 2,477 30,118 3.5 9.2 (8.2–10.3) 6.9 (6.0–7.8)

Chlorphenamine 2,514 29,057 3.4 8.9 (7.6–10.3) 6.7 (5.6–7.7)

Cetirizine 757 11,290 1.3 3.5 (2.9–4.1) 2.6 (2.1–3.1)

Dexchlorpheniramine 549 9,951 1.2 3.1 (2.3–3.8) 2.3 (1.7–2.9)

Loratadine 627 9,817 1.1 3.0 (2.5–3.6) 2.3 (1.8–2.7)

Diphenhydramine 745 9,112 1.1 2.8 (2.2–3.4) 2.1 (1.6–2.5)

Expectorants, excl. combinations with cough suppressants

1,832 22,078 2.6 6.8 (6.0–7.5) 5.1 (4.5–5.7)

Bromhexine 1,055 12,368 1.4 3.8 (3.2–4.4) 2.8 (2.4–3.3)

Nasal decongestants for systemic use 826 12,993 1.5 4.0 (3.2–4.8) 3.0 (2.3–3.6)

Pseudoephedrine, combinations 797 12,677 1.5 3.9 (3.1–4.7) 2.9 (2.3–3.6)

Throat preparations 677 12,339 1.4 3.8 (3.0–4.6) 2.8 (2.2–3.4)

Cough suppressants,

excl. combinations with expectorants

716 11,590 1.3 3.6 (2.9–4.2) 2.7 (2.2–3.2)

Combinations 349 5,556 0.6 1.7 (1.3–2.2) 1.3 (0.9–1.6)

Adrenergics, inhalants 592 7,241 0.8 2.2 (1.7–2.8) 1.7 (1.3–2.0)

Salbutamol 469 5,355 0.6 1.6 (1.2–2.1) 1.2 (0.9–1.5)

Adrenergics for

systemic use 534 6,843 0.8 2.1 (1.7–2.5) 1.6 (1.3–1.9)

Salbutamol 454 5,861 0.7 1.8 (1.4–2.2) 1.3 (1.1–1.6)

Alimentary tract and metabolism 14,875 174,469 20.2 53.6 (50.7–56.4) 40.0 (38.3–41.6)

Blood glucose lowering drugs, excl. insulins 4,758 46,613 5.4 14.3 (11.5–17.1) 10.7 (8.8–12.6)

Metformin 2,666 25,477 3.0 7.8 (6.2–9.4) 5.8 (4.7–6.9)

Gliclazide 1,285 11,964 1.4 3.7 (2.9–4.5) 2.7 (2.2–3.3)

Glibenclamide 412 4,872 0.6 1.5 (1.0–2.0) 1.1 (0.8–1.5)

Table 9.2.1 (continued): Prescribed medications by ATC levels in primary care clinics in 2014

ATC Level 1 Unweighted count

Weighted count



Rate per

100 encounters (95% CI)

(n = 325,818)


(n = 436,743)

Belladonna and derivatives, plain 965 14,710 1.7 4.5 (3.7–5.3) 3.4 (2.8–4.0)

Butylscopolamine 960 14,672 1.7 4.5 (3.7–5.3) 3.4 (2.7–4.0)

Drugs for peptic ulcer and gastro-oesophageal reflux disease (GORD)

914 13,608 1.6 4.2 (3.5–4.8) 3.1 (2.6–3.6)

Ranitidine 432 5,221 0.6 1.6 (1.4–1.9) 1.2 (1.0–1.4)

Antacids 1,037 13,066 1.5 4.0 (3.5–4.6) 3.0 (2.6–3.4)

Magnesium silicate 502 5,581 0.7 1.7 (1.4–2.0) 1.3 (1.0–1.5)

Electrolytes with carbohydrates 956 12,000 1.4 3.7 (3.3–4.1) 2.8 (2.4–3.1)

Insulins and analogues 1,159 10,860 1.3 3.3 (2.7–4.0) 2.5 (2.0–2.9)

Insulin (human) 508 4,787 0.6 1.5 (1.1–1.8) 1.1 (0.8–1.4)

Antipropulsives 690 9,841 1.1 3.0 (2.7–3.4) 2.3 (2.0–2.6)

Loperamide 325 5,137 0.6 1.6 (1.3–1.9) 1.2 (0.9–1.4)

Diphenoxylate 365 4,704 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.3)

Stomatological preparations 774 8,638 1.0 2.7 (2.2–3.1) 2.0 (1.7–2.3)

Various 543 5,831 0.7 1.8 (1.4–2.2) 1.3 (1.0–1.6)

Propulsives 484 6,880 0.8 2.1 (1.8–2.4) 1.6 (1.3–1.8)

Intestinal adsorbents 432 6,685 0.8 2.1 (1.6–2.5) 1.5 (1.2–1.9)

Medicinal charcoal 285 4,451 0.5 1.4 (1.1–1.7) 1.0 (0.8–1.3)

Vitamin B-complex, incl. combinations 473 4,837 0.6 1.5 (1.1–1.9) 1.1 (0.8–1.4)

Vitamin B1, plain and in combination with vitamin B6 and B12

360 4,756 0.6 1.5 (1.1–1.9) 1.1 (0.8–1.4)

Cardiovascular system 14,164 133,445 15.4 41.0 (35.0–46.9) 30.6 (26.8–34.3)

Lipid modifying agents, plain 3,976 37,790 4.4 11.6 (9.5–13.7) 8.7 (7.3–10.1)

Lovastatin 2,451 23,230 2.7 7.1 (5.5–8.8) 5.3 (4.2–6.4)

Simvastatin 1,102 8,507 1.0 2.6 (2.0–3.2) 2.0 (1.5–2.4)

Selective calcium channel blockers with mainly vascular effects

3,577 34,436 4.0 10.6 (9.0–12.1) 7.9 (6.9–8.9)

Amlodipine 3,215 30,846 3.6 9.5 (8.0–11.0) 7.1 (6.1–8.1)

85

Table 9.2.1: Prescribed medications by ATC levels in primary care clinics in 2014

ATC Level 1

Unweighted count

Weighted count




(95% CI) (n = 325,818)


(n = 436,743)

ATC Level 3

ATC Level 5


Antihistamines for systemic use 8,203 105,576 12.2 32.4 (30.1–34.7) 24.2 (22.2–26.2)

Diphenhydramine, combinations 2,477 30,118 3.5 9.2 (8.2–10.3) 6.9 (6.0–7.8)

Chlorphenamine 2,514 29,057 3.4 8.9 (7.6–10.3) 6.7 (5.6–7.7)

Cetirizine 757 11,290 1.3 3.5 (2.9–4.1) 2.6 (2.1–3.1)

Dexchlorpheniramine 549 9,951 1.2 3.1 (2.3–3.8) 2.3 (1.7–2.9)

Loratadine 627 9,817 1.1 3.0 (2.5–3.6) 2.3 (1.8–2.7)

Diphenhydramine 745 9,112 1.1 2.8 (2.2–3.4) 2.1 (1.6–2.5)

Expectorants, excl. combinations with cough suppressants

1,832 22,078 2.6 6.8 (6.0–7.5) 5.1 (4.5–5.7)

Bromhexine 1,055 12,368 1.4 3.8 (3.2–4.4) 2.8 (2.4–3.3)

Nasal decongestants for systemic use 826 12,993 1.5 4.0 (3.2–4.8) 3.0 (2.3–3.6)

Pseudoephedrine, combinations 797 12,677 1.5 3.9 (3.1–4.7) 2.9 (2.3–3.6)

Throat preparations 677 12,339 1.4 3.8 (3.0–4.6) 2.8 (2.2–3.4)

Cough suppressants,

excl. combinations with expectorants

716 11,590 1.3 3.6 (2.9–4.2) 2.7 (2.2–3.2)

Combinations 349 5,556 0.6 1.7 (1.3–2.2) 1.3 (0.9–1.6)

Adrenergics, inhalants 592 7,241 0.8 2.2 (1.7–2.8) 1.7 (1.3–2.0)

Salbutamol 469 5,355 0.6 1.6 (1.2–2.1) 1.2 (0.9–1.5)

Adrenergics for

systemic use 534 6,843 0.8 2.1 (1.7–2.5) 1.6 (1.3–1.9)

Salbutamol 454 5,861 0.7 1.8 (1.4–2.2) 1.3 (1.1–1.6)


Blood glucose lowering drugs, excl. insulins 4,758 46,613 5.4 14.3 (11.5–17.1) 10.7 (8.8–12.6)

Metformin 2,666 25,477 3.0 7.8 (6.2–9.4) 5.8 (4.7–6.9)

Gliclazide 1,285 11,964 1.4 3.7 (2.9–4.5) 2.7 (2.2–3.3)

Glibenclamide 412 4,872 0.6 1.5 (1.0–2.0) 1.1 (0.8–1.5)



ATC Level 1 Unweighted count

Weighted count



Rate per

100 encounters (95% CI)

(n = 325,818)


(n = 436,743)

Belladonna and derivatives, plain 965 14,710 1.7 4.5 (3.7–5.3) 3.4 (2.8–4.0)

Butylscopolamine 960 14,672 1.7 4.5 (3.7–5.3) 3.4 (2.7–4.0)

Drugs for peptic ulcer and gastro-oesophageal reflux disease (GORD)

914 13,608 1.6 4.2 (3.5–4.8) 3.1 (2.6–3.6)

Ranitidine 432 5,221 0.6 1.6 (1.4–1.9) 1.2 (1.0–1.4)

Antacids 1,037 13,066 1.5 4.0 (3.5–4.6) 3.0 (2.6–3.4)

Magnesium silicate 502 5,581 0.7 1.7 (1.4–2.0) 1.3 (1.0–1.5)

Electrolytes with carbohydrates 956 12,000 1.4 3.7 (3.3–4.1) 2.8 (2.4–3.1)

Insulins and analogues 1,159 10,860 1.3 3.3 (2.7–4.0) 2.5 (2.0–2.9)

Insulin (human) 508 4,787 0.6 1.5 (1.1–1.8) 1.1 (0.8–1.4)

Antipropulsives 690 9,841 1.1 3.0 (2.7–3.4) 2.3 (2.0–2.6)

Loperamide 325 5,137 0.6 1.6 (1.3–1.9) 1.2 (0.9–1.4)

Diphenoxylate 365 4,704 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.3)

Stomatological preparations 774 8,638 1.0 2.7 (2.2–3.1) 2.0 (1.7–2.3)

Various 543 5,831 0.7 1.8 (1.4–2.2) 1.3 (1.0–1.6)

Propulsives 484 6,880 0.8 2.1 (1.8–2.4) 1.6 (1.3–1.8)

Intestinal adsorbents 432 6,685 0.8 2.1 (1.6–2.5) 1.5 (1.2–1.9)

Medicinal charcoal 285 4,451 0.5 1.4 (1.1–1.7) 1.0 (0.8–1.3)

Vitamin B-complex, incl. combinations 473 4,837 0.6 1.5 (1.1–1.9) 1.1 (0.8–1.4)

Vitamin B1, plain and in combination with vitamin B6 and B12

360 4,756 0.6 1.5 (1.1–1.9) 1.1 (0.8–1.4)


Lipid modifying agents, plain 3,976 37,790 4.4 11.6 (9.5–13.7) 8.7 (7.3–10.1)

Lovastatin 2,451 23,230 2.7 7.1 (5.5–8.8) 5.3 (4.2–6.4)

Simvastatin 1,102 8,507 1.0 2.6 (2.0–3.2) 2.0 (1.5–2.4)

Selective calcium channel blockers with mainly vascular effects

3,577 34,436 4.0 10.6 (9.0–12.1) 7.9 (6.9–8.9)

Amlodipine 3,215 30,846 3.6 9.5 (8.0–11.0) 7.1 (6.1–8.1)



ATC Level 1 Unweighted

count Weighted

count




(95% CI) (n = 325,818)


(n = 436,743)

ACE inhibitors, plain 2,485 22,681 2.6 7.0 (5.8–8.1) 5.2 (4.4–6.0)

Perindopril 2,024 18,030 2.1 5.5 (4.6–6.5) 4.1 (3.5–4.8)

Beta blocking agents 1,648 14,752 1.7 4.5 (3.8–5.2) 3.4 (2.9–3.9)

Atenolol 818 7,076 0.8 2.2 (1.8–2.6) 1.6 (1.4–1.9)

Metoprolol 650 5,571 0.6 1.7 (1.3–2.1) 1.3 (1.0–1.6)

Low-ceiling diuretics, thiazides 1,010 8,836 1.0 2.7 (2.1–3.3) 2.0 (1.6–2.5)

Hydrochlorothiazide 1,008 8,819 1.0 2.7 (2.1–3.3) 2.0 (1.6–2.4)

Nervous system 8,661 106,751 12.4 32.8 (31.1–34.4) 24.4 (22.8–26.1)

Other analgesics and antipyretics 7,501 90,649 10.5 27.8 (26.5–29.2) 20.8 (19.4–22.1)

Paracetamol 7,413 89,591 10.4 27.5 (26.1–28.9) 20.5 (19.2–21.9)

Musculoskeletal system 6,733 99,136 11.5 30.4 (28.0–32.9) 22.7 (20.6–24.8)

Antiinflammatory and antirheumatic products, non-steroids

4,246 63,320 7.3 19.4 (17.6–21.2) 14.5 (13.0–16.0)

Diclofenac 1,714 24,928 2.9 7.7 (6.6–8.7) 5.7 (4.9–6.6)

Mefenamic Acid 1,291 17,775 2.1 5.5 (4.8–6.1) 4.1 (3.5–4.6)

Ibuprofen 398 5,707 0.7 1.8 (1.4–2.1) 1.3 (1.0–1.6)

Topical products for joint and muscular pain 1,101 14,241 1.7 4.4 (3.7–5.0) 3.3 (2.8–3.7)

Muscle relaxants, centrally acting agents 603 10,648 1.2 3.3 (2.6–3.9) 2.4 (1.9–3.0)

Orphenadrine, combinations 501 9,180 1.1 2.8 (2.2–3.5) 2.1 (1.6–2.6)

Other drugs for disorders of the musculoskeletal system

580 8,352 1.0 2.6 (2.2–2.9) 1.9 (1.6–2.2)

Antiinfectives for systemic use 5,112 76,253 8.8 23.4 (20.7–26.1) 17.5 (15.2–19.7)

Beta-lactam antibacterials, penicillins 2,057 30,007 3.5 9.2 (8.2–10.2) 6.9 (6.0–7.7)

Amoxicillin 1,100 14,729 1.7 4.5 (3.9–5.1) 3.4 (2.9–3.9)

Amoxicillin and enzyme inhibitor 416 8,046 0.9 2.5 (1.6–3.3) 1.8 (1.2–2.5)



count Weighted

count




(95% CI) (n = 325,818)


(n = 436,743)

Other beta-lactam antibacterials

1,001 16,855 2.0 5.2 (4.0–6.3) 3.9 (3.0–4.8)

Cephalexin 633 9,378 1.1 2.9 (2.3–3.4) 2.2 (1.7–2.6)

Macrolides, lincosamides and streptogramins

921 11,940 1.4 3.7 (3.2–4.2) 2.7 (2.3–3.1)

Erythromycin 638 7,167 0.8 2.2 (1.9–2.5) 1.6 (1.4–1.9)

Quinolone antibacterials

296 5,359 0.6 1.6 (1.1–2.2) 1.2 (0.8–1.7)

Dermatologicals 2,144 26,878 3.1 8.3 (7.3–9.2) 6.2 (5.4–6.9)

Corticosteroids, plain 515 7,036 0.8 2.2 (1.8–2.6) 1.6 (1.3–1.9)

Emollients and protectives

579 6,956 0.8 2.1 (1.7–2.6) 1.6 (1.3–1.9)

Blood and blood forming organs

2,079 19,347 2.2 5.9 (5.0–6.9) 4.4 (3.8–5.1)

Iron preparations 746 6,615 0.8 2.0 (1.6–2.5) 1.5 (1.2–1.9)

Antithrombotic agents 749 6,447 0.8 2.0 (1.6–2.4) 1.5 (1.2–1.8)

Acetylsalicylic acid 650 5,406 0.6 1.7 (1.3–2.0) 1.2 (1.0–1.5)

Vitamin B12 and folic acid

505 5,244 0.6 1.6 (1.2–2.0) 1.2 (0.9–1.5)

Folic acid 450 4,479 0.5 1.4 (1.0–1.8) 1.0 (0.8–1.3)

Systemic hormonal preparations

959 16,183 1.9 5.0 (3.6–6.3) 3.7 (2.7–4.7)

Corticosteroids for systemic use, plain

823 15,079 1.7 4.6 (3.3–6.0) 3.5 (2.4–4.5)

Prednisolone 618 10,950 1.3 3.4 (2.4–4.3) 2.5 (1.8–3.3)

Sensory organs 796 8,961 1.0 2.8 (2.4–3.1) 2.1 (1.8–2.3)

Antiinfectives 442 4,633 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.2)

Genitourinary system and sex hormones

418 5,787 0.7 1.7 (1.3–2.2) 1.3 (1.0–1.7)

Antiparasitic products, insecticides and repellents

235 3,278 0.4 1.0 (0.8–1.2) 0.8 (0.6–0.9)

Various 45 609 0.1 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Antineoplastic and immunomodulating agents

5 89 0.0 0.0 (0.0–0.1) 0.0 (0.0–0.0)

Total 70,711 864,552 100.0 265.4 (256.7–274.0) 198.0 (190.8–205.1)

Note: ACE – Angiotensin converting enzyme.

87Chapter 9 : Medications



count Weighted

count




(95% CI) (n = 325,818)


(n = 436,743)

Other beta-lactam antibacterials

1,001 16,855 2.0 5.2 (4.0–6.3) 3.9 (3.0–4.8)

Cephalexin 633 9,378 1.1 2.9 (2.3–3.4) 2.2 (1.7–2.6)

Macrolides, lincosamides and streptogramins

921 11,940 1.4 3.7 (3.2–4.2) 2.7 (2.3–3.1)

Erythromycin 638 7,167 0.8 2.2 (1.9–2.5) 1.6 (1.4–1.9)

Quinolone antibacterials

296 5,359 0.6 1.6 (1.1–2.2) 1.2 (0.8–1.7)


Corticosteroids, plain 515 7,036 0.8 2.2 (1.8–2.6) 1.6 (1.3–1.9)

Emollients and protectives

579 6,956 0.8 2.1 (1.7–2.6) 1.6 (1.3–1.9)

Blood and blood forming organs

2,079 19,347 2.2 5.9 (5.0–6.9) 4.4 (3.8–5.1)

Iron preparations 746 6,615 0.8 2.0 (1.6–2.5) 1.5 (1.2–1.9)

Antithrombotic agents 749 6,447 0.8 2.0 (1.6–2.4) 1.5 (1.2–1.8)

Acetylsalicylic acid 650 5,406 0.6 1.7 (1.3–2.0) 1.2 (1.0–1.5)

Vitamin B12 and folic acid

505 5,244 0.6 1.6 (1.2–2.0) 1.2 (0.9–1.5)

Folic acid 450 4,479 0.5 1.4 (1.0–1.8) 1.0 (0.8–1.3)

Systemic hormonal preparations

959 16,183 1.9 5.0 (3.6–6.3) 3.7 (2.7–4.7)

Corticosteroids for systemic use, plain

823 15,079 1.7 4.6 (3.3–6.0) 3.5 (2.4–4.5)

Prednisolone 618 10,950 1.3 3.4 (2.4–4.3) 2.5 (1.8–3.3)

Sensory organs 796 8,961 1.0 2.8 (2.4–3.1) 2.1 (1.8–2.3)

Antiinfectives 442 4,633 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.2)

Genitourinary system and sex hormones

418 5,787 0.7 1.7 (1.3–2.2) 1.3 (1.0–1.7)

Antiparasitic products, insecticides and repellents

235 3,278 0.4 1.0 (0.8–1.2) 0.8 (0.6–0.9)

Various 45 609 0.1 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Antineoplastic and immunomodulating agents

5 89 0.0 0.0 (0.0–0.1) 0.0 (0.0–0.0)

Total 70,711 864,552 100.0 265.4 (256.7–274.0) 198.0 (190.8–205.1)

Note: ACE – Angiotensin converting enzyme.


Table 9.2.2: Prescribed medications by ATC level 1 in public clinics in 2014


count Weighted

count




(95% CI) (n = 131,624)


(n = 203,868)




Nervous system 4,059 32,857 10.1 25.0 (23.1–26.8) 16.1 (14.6–17.6)


Blood and blood forming organs 1,831 15,282 4.7 11.6 (9.5–13.7) 7.5 (6.1–8.9)

Antiinfectives for

systemic use 1,220 10,917 3.3 8.3 (7.2–9.4) 5.4 (4.5–6.2)

Dermatologicals 825 5,886 1.8 4.5 (3.7–5.2) 2.9 (2.4–3.4)

Sensory organs 434 3,270 1.0 2.5 (2.1–2.9) 1.6 (1.3–1.9)

Systemic hormonal preparations 228 1,855 0.6 1.4 (1.1–1.7) 0.9 (0.7–1.1)

Genitourinary system and sex hormones 173 1,668 0.5 1.3 (0.9–1.7) 0.8 (0.6–1.1)

Antiparasitic products, insecticides and

repellents 97 1,021 0.3 0.8 (0.5–1.1) 0.5 (0.3–0.7)

Various 16 155 0.1 0.1 (0.0–0.2) 0.1 (0.0–0.1)

Total 38,296 327,087 100.0 248.5 (236.7–260.3) 160.4 (156.5–164.4)

Table 9.2.3: Prescribed medications by ATC level 1 in private clinics in 2014


count Weighted

count




(95% CI) (n = 194,194)


(n = 232,874)




Nervous system 4,602 73,894 13.8 38.1 (36.2–39.9) 31.7 (30.1–33.4)





Sensory organs 362 5,691 1.1 2.9 (2.4–3.4) 2.4 (2.0–2.9)


Blood and blood forming organs 248 4,065 0.8 2.1 (1.6–2.5) 1.8 (1.4–2.1)

Antiparasitic products, insecticides and repellents 138 2,257 0.4 1.2 (0.8–1.5) 1.0 (0.7–1.2)

Various 29 455 0.1 0.2 (0.1–0.4) 0.2 (0.1–0.3)

Antineoplastic and immunomodulating agents 5 89 0.0 0.1 (0.0–0.1) 0.0 (0.0–0.1)

Total 32,415 537,465 100.0 276.8 (265.3–288.2) 230.8 (221.7–239.9)

9.3 MOST FREQUENTLY PRESCRIBED MEDICATIONS IN PUBLIC AND PRIVATE CLINICS

The most commonly prescribed medications by ATC level 5 classification are described below. The medication topping the top 30 list for both public and private sectors was paracetamol, which accounted for 8.8% of all medications prescribed in public clinics (Table 9.3.1) and 11.3% in private clinics (Table 9.3.2).

Public clinics

• The top 30 medications contributed to 74.6 % of all medicines prescribed in public clinics. A similar observation was reported in NMCS 2012.1

• Out of the 10 most commonly prescribed medications, seven were for chronic diseases, accounting for more than one-third (35.2%) of all medications prescribed in public clinics.

• Erythromycin and amoxicillin, the most common antibiotics prescribed, represented only 1.7% of all medications prescribed in public clinics.

• Other medications in the top 30 list included respiratory system agents such as antihistamines and bronchodilators, musculoskeletal system agents such as salicylic acid preparations and nonsteroidal antiinflammatory drugs (NSAIDS), and supplements which included vitamin-B complex, folic acid and ascorbic acid (vitamin C).

89

Table 9.2.2: Prescribed medications by ATC level 1 in public clinics in 2014


count Weighted

count




(95% CI) (n = 131,624)


(n = 203,868)




Nervous system 4,059 32,857 10.1 25.0 (23.1–26.8) 16.1 (14.6–17.6)


Blood and blood forming organs 1,831 15,282 4.7 11.6 (9.5–13.7) 7.5 (6.1–8.9)

Antiinfectives for

systemic use 1,220 10,917 3.3 8.3 (7.2–9.4) 5.4 (4.5–6.2)

Dermatologicals 825 5,886 1.8 4.5 (3.7–5.2) 2.9 (2.4–3.4)

Sensory organs 434 3,270 1.0 2.5 (2.1–2.9) 1.6 (1.3–1.9)



Antiparasitic products, insecticides and

repellents 97 1,021 0.3 0.8 (0.5–1.1) 0.5 (0.3–0.7)

Various 16 155 0.1 0.1 (0.0–0.2) 0.1 (0.0–0.1)

Total 38,296 327,087 100.0 248.5 (236.7–260.3) 160.4 (156.5–164.4)


Table 9.2.3: Prescribed medications by ATC level 1 in private clinics in 2014


count Weighted

count




(95% CI) (n = 194,194)


(n = 232,874)




Nervous system 4,602 73,894 13.8 38.1 (36.2–39.9) 31.7 (30.1–33.4)





Sensory organs 362 5,691 1.1 2.9 (2.4–3.4) 2.4 (2.0–2.9)


Blood and blood forming organs 248 4,065 0.8 2.1 (1.6–2.5) 1.8 (1.4–2.1)

Antiparasitic products, insecticides and repellents 138 2,257 0.4 1.2 (0.8–1.5) 1.0 (0.7–1.2)

Various 29 455 0.1 0.2 (0.1–0.4) 0.2 (0.1–0.3)

Antineoplastic and immunomodulating agents 5 89 0.0 0.1 (0.0–0.1) 0.0 (0.0–0.1)

Total 32,415 537,465 100.0 276.8 (265.3–288.2) 230.8 (221.7–239.9)

9.3 MOST FREQUENTLY PRESCRIBED MEDICATIONS IN PUBLIC AND PRIVATE CLINICS

The most commonly prescribed medications by ATC level 5 classification are described below. The medication topping the top 30 list for both public and private sectors was paracetamol, which accounted for 8.8% of all medications prescribed in public clinics (Table 9.3.1) and 11.3% in private clinics (Table 9.3.2).

Public clinics

• The top 30 medications contributed to 74.6 % of all medicines prescribed in public clinics. A similar observation was reported in NMCS 2012.1

• Out of the 10 most commonly prescribed medications, seven were for chronic diseases, accounting for more than one-third (35.2%) of all medications prescribed in public clinics.

• Erythromycin and amoxicillin, the most common antibiotics prescribed, represented only 1.7% of all medications prescribed in public clinics.

• Other medications in the top 30 list included respiratory system agents such as antihistamines and bronchodilators, musculoskeletal system agents such as salicylic acid preparations and nonsteroidal antiinflammatory drugs (NSAIDS), and supplements which included vitamin-B complex, folic acid and ascorbic acid (vitamin C).


Private clinics

• The top 30 medications accounted for 59.3% of all medications prescribed in the private sector. • The 10 most frequently prescribed medications in private clinics were all medications for acute

conditions, including an antiinfective (amoxicillin, 2.3%) and a steroid (prednisolone, 1.9%). • The top 10 list comprised the same medications in NMCS 2012 and 2014, except for prednisolone,

which displaced loratadine from the list in 2014.1 • In addition to amoxicillin, other systemic antiinfectives among the 30 most frequently prescribed

medications included cephalexin (1.6%), amoxicillin and enzyme inhibitor (1.5%), erythromycin (0.8%), ciprofloxacin (0.8%) and cefuroxime (0.7%). Together, antiinfectives amounted to 7.7% of all medications prescribed in the private sector.

Table 9.3.1: Thirty most frequently prescribed medications in public clinics in 2014

Rank Medication Unweighted

count (n = 38,296)

Weighted count

(n = 327,087)




(95% CI) (n = 131,624)


(n = 203,868)

1 Paracetamol 3,604 28,665 8.8 21.8 (20.1–23.5) 14.1 (12.7–15.4)

2 Amlodipine 2,906 26,382 8.1 20.0 (17.4–22.7) 12.9 (11.5–14.3)

3 Lovastatin 2,434 22,981 7.0 17.5 (14.8–20.1) 11.3 (9.9–12.7)

4 Metformin 2,471 22,901 7.0 17.4 (14.4–20.4) 11.2 (9.6–12.9)

5 Perindopril 1,977 17,294 5.3 13.1 (11.5–14.8) 8.5 (7.6–9.4)

6 Chlorphenamine 1,519 12,041 3.7 9.2 (7.9–10.4) 5.9 (5.1–6.7)

7 Gliclazide 1,168 10,261 3.1 7.8 (6.1–9.5) 5.0 (4.0–6.0)

8 Diphenhydramine, combinations 1,342 9,838 3.0 7.5 (6.4–8.6) 4.8 (4.1–5.6)

9 Hydrochlorothiazidee

975 8,407 2.6 6.4 (5.2–7.6) 4.1 (3.4–4.9)

10 Simvastatin 989 7,022 2.2 5.3 (4.0–6.6) 3.4 (2.6–4.3)

11 Atenolol 720 5,563 1.7 4.2 (3.5–5.0) 2.7 (2.3–3.2)

12 Metoprolol 641 5,474 1.7 4.2 (3.4–5.0) 2.7 (2.2–3.2)

13 Acetylsalicylic acid 629 5,093 1.6 3.9 (3.2–4.6) 2.5 (2.1–2.9)

14 Preparations with salicylic acid derivatives*

602 5,054 1.6 3.8 (2.9–4.8) 2.5 (1.9–3.1)

15 Bromhexine 653 5,021 1.5 3.8 (3.0–4.6) 2.5 (1.9–3.0)

16 Insulin (human); intermediate-acting 508 4,787 1.5 3.6 (3.0–4.3) 2.4 (1.9–2.8)

17 Glibenclamide 364 4,254 1.3 3.2 (2.3–4.2) 2.1 (1.5–2.7)

18

Insulin (human); intermediate- or long-acting combined with fast-acting

414 4,063 1.2 3.1 (2.3–3.9) 2.0 (1.5–2.5)

19 Diclofenac 443 4,049 1.2 3.1 (2.2–4.0) 2.0 (1.4–2.6)

20 Salbutamol 390 3,811 1.2 2.9 (2.2–3.6) 1.9 (1.4–2.3)

21 Diphenhydramine 394 3,562 1.1 2.7 (1.7–3.7) 1.8 (1.1–2.4)

22 Other agents for local oral treatment; various

406 3,543 1.1 2.7 (1.9–3.5) 1.7 (1.2–2.2)

23 Vitamin B-complex, plain* 401 3,540 1.1 2.7 (1.8–3.6) 1.7 (1.2–2.3)

24 Oral rehydration salt formulations* 450 3,475 1.1 2.6 (2.2–3.1) 1.7 (1.4–2.0)

25 Folic acid 390 3,413 1.0 2.6 (1.7–3.5) 1.7 (1.1–2.3)

26 Mefenamic acid 381 3,058 0.9 2.3 (1.7–3.0) 1.5 (1.1–1.9)

27 Erythromycin 346 2,953 0.9 2.2 (1.8–2.7) 1.5 (1.1–1.8)

28 Enalapril 265 2,751 0.8 2.1 (1.5–2.7) 1.4 (1.0–1.7)

29 Amoxicillin 271 2,476 0.8 1.9 (1.5–2.3) 1.2 (1.0–1.5)

30 Ascorbic acid (Vitamin C) 259 2,378 0.7 1.8 (1.1–2.5) 1.2 (0.7–1.6)

* ATC level 4

91

Private clinics

• The top 30 medications accounted for 59.3% of all medications prescribed in the private sector. • The 10 most frequently prescribed medications in private clinics were all medications for acute

conditions, including an antiinfective (amoxicillin, 2.3%) and a steroid (prednisolone, 1.9%). • The top 10 list comprised the same medications in NMCS 2012 and 2014, except for prednisolone,

which displaced loratadine from the list in 2014.1 • In addition to amoxicillin, other systemic antiinfectives among the 30 most frequently prescribed

medications included cephalexin (1.6%), amoxicillin and enzyme inhibitor (1.5%), erythromycin (0.8%), ciprofloxacin (0.8%) and cefuroxime (0.7%). Together, antiinfectives amounted to 7.7% of all medications prescribed in the private sector.


Table 9.3.1: Thirty most frequently prescribed medications in public clinics in 2014


count (n = 38,296)

Weighted count

(n = 327,087)




(95% CI) (n = 131,624)


(n = 203,868)

1 Paracetamol 3,604 28,665 8.8 21.8 (20.1–23.5) 14.1 (12.7–15.4)

2 Amlodipine 2,906 26,382 8.1 20.0 (17.4–22.7) 12.9 (11.5–14.3)

3 Lovastatin 2,434 22,981 7.0 17.5 (14.8–20.1) 11.3 (9.9–12.7)

4 Metformin 2,471 22,901 7.0 17.4 (14.4–20.4) 11.2 (9.6–12.9)

5 Perindopril 1,977 17,294 5.3 13.1 (11.5–14.8) 8.5 (7.6–9.4)

6 Chlorphenamine 1,519 12,041 3.7 9.2 (7.9–10.4) 5.9 (5.1–6.7)

7 Gliclazide 1,168 10,261 3.1 7.8 (6.1–9.5) 5.0 (4.0–6.0)


9 Hydrochlorothiazidee

975 8,407 2.6 6.4 (5.2–7.6) 4.1 (3.4–4.9)

10 Simvastatin 989 7,022 2.2 5.3 (4.0–6.6) 3.4 (2.6–4.3)

11 Atenolol 720 5,563 1.7 4.2 (3.5–5.0) 2.7 (2.3–3.2)

12 Metoprolol 641 5,474 1.7 4.2 (3.4–5.0) 2.7 (2.2–3.2)

13 Acetylsalicylic acid 629 5,093 1.6 3.9 (3.2–4.6) 2.5 (2.1–2.9)


602 5,054 1.6 3.8 (2.9–4.8) 2.5 (1.9–3.1)

15 Bromhexine 653 5,021 1.5 3.8 (3.0–4.6) 2.5 (1.9–3.0)

16 Insulin (human); intermediate-acting 508 4,787 1.5 3.6 (3.0–4.3) 2.4 (1.9–2.8)

17 Glibenclamide 364 4,254 1.3 3.2 (2.3–4.2) 2.1 (1.5–2.7)

18

Insulin (human); intermediate- or long-acting combined with fast-acting

414 4,063 1.2 3.1 (2.3–3.9) 2.0 (1.5–2.5)

19 Diclofenac 443 4,049 1.2 3.1 (2.2–4.0) 2.0 (1.4–2.6)

20 Salbutamol 390 3,811 1.2 2.9 (2.2–3.6) 1.9 (1.4–2.3)


22 Other agents for local oral treatment; various

406 3,543 1.1 2.7 (1.9–3.5) 1.7 (1.2–2.2)

23 Vitamin B-complex, plain* 401 3,540 1.1 2.7 (1.8–3.6) 1.7 (1.2–2.3)

24 Oral rehydration salt formulations* 450 3,475 1.1 2.6 (2.2–3.1) 1.7 (1.4–2.0)

25 Folic acid 390 3,413 1.0 2.6 (1.7–3.5) 1.7 (1.1–2.3)

26 Mefenamic acid 381 3,058 0.9 2.3 (1.7–3.0) 1.5 (1.1–1.9)

27 Erythromycin 346 2,953 0.9 2.2 (1.8–2.7) 1.5 (1.1–1.8)

28 Enalapril 265 2,751 0.8 2.1 (1.5–2.7) 1.4 (1.0–1.7)

29 Amoxicillin 271 2,476 0.8 1.9 (1.5–2.3) 1.2 (1.0–1.5)

30 Ascorbic acid (Vitamin C) 259 2,378 0.7 1.8 (1.1–2.5) 1.2 (0.7–1.6)

* ATC level 4


Table 9.3.2: Thirty most frequently prescribed medications in private clinics in 2014


count (n = 32,415)

Weighted count

(n = 537,465)




(95% CI) (n = 194,194)


(n = 232,874)

1 Paracetamol 3,809 60,926 11.3 31.4 (29.8–33.0) 26.2 (24.7–27.6)

2 Diclofenac 1,271 20,879 3.9 10.8 (9.2–12.3) 9.0 (7.7–10.3)


4 Chlorphenamine 995 17,017 3.2 8.8 (6.6–10.9) 7.3 (5.6–9.1)

5 Mefenamic acid 910 14,717 2.7 7.6 (6.6–8.6) 6.3 (5.5–7.2)

6 Butylscopolamine 703 12,857 2.4 6.6 (5.6–7.7) 5.5 (4.6–6.4)

7 Amoxicillin 829 12,253 2.3 6.3 (5.3–7.3) 5.3 (4.4–6.1)

8 Pseudoephedrine, combinations

650 11,464 2.1 5.9 (4.7–7.1) 4.9 (4.0–5.9)

9 Cetirizine 756 11,289 2.1 5.8 (4.9–6.7) 4.9 (4.1–5.6)

10 Prednisolone 516 10,006 1.9 5.2 (3.7–6.7) 4.3 (3.1–5.5)

11 Dexchlorpheniramine 543 9,929 1.9 5.1 (4.0–6.2) 4.3 (3.3–5.2)

12 Orphenadrine, combinations

501 9,180 1.7 4.7 (3.8–5.7) 3.9 (3.2–4.7)

13 Cephalexin 540 8,668 1.6 4.5 (3.6–5.3) 3.7 (3.0–4.4)

14 Loratadine 505 8,536 1.6 4.4 (3.5–5.3) 3.7 (2.9–4.4)

15 Oral rehydration salt formulations*

506 8,524 1.6 4.4 (3.8–5.0) 3.7 (3.2–4.2)

16 Amoxicillin and enzyme inhibitor

411 7,985 1.5 4.1 (2.8–5.4) 3.4 (2.3–4.5)

17 Bromhexine 402 7,347 1.4 3.8 (3.0–4.6) 3.2 (2.5–3.8)


372 6,745 1.3 3.5 (2.7–4.2) 2.9 (2.3–3.5)

19 Enzymes* 378 6,524 1.2 3.4 (2.8–3.9) 2.8 (2.4–3.2)

20 Throat preparations** 322 6,391 1.2 3.3 (2.2–4.4) 2.7 (1.9–3.6)

21 Opium alkaloids and derivatives; combinations

349 5,556 1.0 2.9 (2.2–3.6) 2.4 (1.8–3.0)


23 Ibuprofen 340 5,275 1.0 2.7 (2.1–3.3) 2.3 (1.7–2.8)

24 Loperamide 325 5,137 1.0 2.7 (2.2–3.1) 2.2 (1.8–2.6)

25 Salbutamol 324 4,745 0.9 2.4 (1.9–3.0) 2.0 (1.6–2.5)

26 Amlodipine 309 4,464 0.8 2.3 (1.9–2.7) 1.9 (1.6–2.3)

27 Medicinal charcoal 250 4,297 0.8 2.2 (1.7–2.7) 1.9 (1.4–2.3)

28 Erythromycin 292 4,214 0.8 2.2 (1.7–2.6) 1.8 (1.4–2.2)

29 Ciprofloxacin 202 4,082 0.8 2.1 (1.4–2.9) 1.8 (1.1–2.4)

30 Cefuroxime 192 4,007 0.8 2.1 (1.2–3.0) 1.7 (1.0–2.5)

* ATC level 4 ** ATC level 3

REFERENCE

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative, 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia.

93

Table 9.3.2: Thirty most frequently prescribed medications in private clinics in 2014


count (n = 32,415)

Weighted count

(n = 537,465)




(95% CI) (n = 194,194)


(n = 232,874)

1 Paracetamol 3,809 60,926 11.3 31.4 (29.8–33.0) 26.2 (24.7–27.6)

2 Diclofenac 1,271 20,879 3.9 10.8 (9.2–12.3) 9.0 (7.7–10.3)


4 Chlorphenamine 995 17,017 3.2 8.8 (6.6–10.9) 7.3 (5.6–9.1)

5 Mefenamic acid 910 14,717 2.7 7.6 (6.6–8.6) 6.3 (5.5–7.2)

6 Butylscopolamine 703 12,857 2.4 6.6 (5.6–7.7) 5.5 (4.6–6.4)

7 Amoxicillin 829 12,253 2.3 6.3 (5.3–7.3) 5.3 (4.4–6.1)

8 Pseudoephedrine, combinations

650 11,464 2.1 5.9 (4.7–7.1) 4.9 (4.0–5.9)

9 Cetirizine 756 11,289 2.1 5.8 (4.9–6.7) 4.9 (4.1–5.6)

10 Prednisolone 516 10,006 1.9 5.2 (3.7–6.7) 4.3 (3.1–5.5)

11 Dexchlorpheniramine 543 9,929 1.9 5.1 (4.0–6.2) 4.3 (3.3–5.2)

12 Orphenadrine, combinations

501 9,180 1.7 4.7 (3.8–5.7) 3.9 (3.2–4.7)

13 Cephalexin 540 8,668 1.6 4.5 (3.6–5.3) 3.7 (3.0–4.4)

14 Loratadine 505 8,536 1.6 4.4 (3.5–5.3) 3.7 (2.9–4.4)

15 Oral rehydration salt formulations*

506 8,524 1.6 4.4 (3.8–5.0) 3.7 (3.2–4.2)

16 Amoxicillin and enzyme inhibitor

411 7,985 1.5 4.1 (2.8–5.4) 3.4 (2.3–4.5)

17 Bromhexine 402 7,347 1.4 3.8 (3.0–4.6) 3.2 (2.5–3.8)


372 6,745 1.3 3.5 (2.7–4.2) 2.9 (2.3–3.5)

19 Enzymes* 378 6,524 1.2 3.4 (2.8–3.9) 2.8 (2.4–3.2)

20 Throat preparations** 322 6,391 1.2 3.3 (2.2–4.4) 2.7 (1.9–3.6)

21 Opium alkaloids and derivatives; combinations

349 5,556 1.0 2.9 (2.2–3.6) 2.4 (1.8–3.0)


23 Ibuprofen 340 5,275 1.0 2.7 (2.1–3.3) 2.3 (1.7–2.8)

24 Loperamide 325 5,137 1.0 2.7 (2.2–3.1) 2.2 (1.8–2.6)

25 Salbutamol 324 4,745 0.9 2.4 (1.9–3.0) 2.0 (1.6–2.5)

26 Amlodipine 309 4,464 0.8 2.3 (1.9–2.7) 1.9 (1.6–2.3)

27 Medicinal charcoal 250 4,297 0.8 2.2 (1.7–2.7) 1.9 (1.4–2.3)

28 Erythromycin 292 4,214 0.8 2.2 (1.7–2.6) 1.8 (1.4–2.2)

29 Ciprofloxacin 202 4,082 0.8 2.1 (1.4–2.9) 1.8 (1.1–2.4)

30 Cefuroxime 192 4,007 0.8 2.1 (1.2–3.0) 1.7 (1.0–2.5)

* ATC level 4 ** ATC level 3

REFERENCE

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative, 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia.

CHAPTER tenInvestigations


CHAPTER 10: INVESTIGATIONS

Laboratory and other medical investigations are essential for the diagnosis and management of many conditions. In the primary care setting, the tests are generally requested to aid in diagnosis, establish a baseline before commencing treatment, monitor long-term conditions for disease control, ensure a medication dose is within the therapeutic range, detect adverse effects to treatment and monitor or predict the response to treatment.1 While these investigations can help in the management or monitoring of patients, it must also be remembered that the rates at which the investigations are ordered can directly affect the healthcare expenditure. This chapter reports the investigations ordered by primary care providers at the point of patient encounter, which include all blood and urine pathological tests, imaging studies and other diagnostic tests.

10.1 NUMBER OF INVESTIGATIONS PER ENCOUNTER

Table 10.1.1 shows the number of encounters in primary clinics during which at least one investigation was ordered. Of all 325,818 encounters recorded in primary care, 22.6% had investigations ordered. The higher proportion of investigations in public clinics (39.6%) as compared to private (11.1%) can be due to the higher proportion of chronic diseases managed in public sector.

Table 10.1.1: Number of encounters with investigations ordered in primary care clinics in 2014

Sector Unweighted


(95% CI)

Overall (n = 325,818) 7,272 73,540 22.6 (19.7–25.4)

Public (n = 131,624) 5,945 52,060 39.6 (35.4–43.7)

Private (n = 194,194) 1,327 21,480 11.1 (9.6–12.5)

The highest numbers of investigations ordered per encounter in public clinics and private clinics were 14 and 18, respectively. Investigations were ordered more frequently in the public clinics, with about one-fifth (18.7%) of the encounters had two or more investigations ordered per encounter, compared to only 2.9% in the private sector (Figure 10.1.1).

10.2 TYPES OF INVESTIGATIONS ORDERED

Table 10.2.1 shows the distribution of the most common investigations ordered in primary care in decreasing order of frequency. A total of 143,758 investigations were ordered in primary care, at a rate of 44.1 investigations per 100 encounters and 32.9 investigations per 100 diagnoses.

• More than four-fifths (82.0%) of all investigations ordered were laboratory/pathological tests. Glucose and/or glucose tolerance test constituted one fifth of these investigations.

• Imaging studies accounted for 9.3% of the total investigations. Obstetric ultrasound was the most frequently ordered imaging modality, recorded at 4.0% of all investigations ordered (1.8 per 100 encounters and 1.3 per 100 diagnoses).

Figure 10.1.1: Number of investigations ordered per encounter in primary care clinics in 2014

Table 10.2.1: Types of investigations by ICPC-2 process codes in primary care clinics in 2014

Investigations Unweighted count

Weighted count

Percent of investigations (n = 143,758)


(95% CI) (n = 325,818)


(n = 436,743)

Pathology test 12,926 117,889 82.0 36.2 (30.5–41.9) 27.0 (23.2–30.8)

Chemistry 9,210 80,153 55.8 24.6 (19.7–29.5) 18.4 (15.1–21.7)

Glucose/glucose tolerance 2,515 24,704 17.2 7.6 (5.7–9.4) 5.7 (4.4–6.9)

Electrolytes, urea & creatinine* 1,805 14,659 10.2 4.5 (3.3–5.7) 3.4 (2.5–4.2)

Lipids 1,623 14,503 10.1 4.5 (3.5–5.4) 3.3 (2.6–4.0)

Liver function* 1,191 8,853 6.2 2.7 (2.0–3.4) 2.0 (1.5–2.5)

HbA1c 961 8,227 5.7 2.5 (1.6–3.4) 1.9 (1.2–2.5)

Chemistry; other* 495 3,883 2.7 1.2 (0.8–1.6) 0.9 (0.6–1.2)

Urate/uric acid 351 2,372 1.6 0.7 (0.4–1.1) 0.5 (0.3–0.8)

Thyroid function 144 1,674 1.2 0.5 (0.4–0.7) 0.4 (0.3–0.5)


Public 60.4 20.8 8.2 3.5 7.0

Private 88.9 8.1 1.8 0.4 0.7

0

10

20

30

40

50

60

70

80

90

100

Per

cen

t o

f en

cou

nte

rs (

%)

Number of investigations per encounter

97

CHAPTER 10: INVESTIGATIONS

Laboratory and other medical investigations are essential for the diagnosis and management of many conditions. In the primary care setting, the tests are generally requested to aid in diagnosis, establish a baseline before commencing treatment, monitor long-term conditions for disease control, ensure a medication dose is within the therapeutic range, detect adverse effects to treatment and monitor or predict the response to treatment.1 While these investigations can help in the management or monitoring of patients, it must also be remembered that the rates at which the investigations are ordered can directly affect the healthcare expenditure. This chapter reports the investigations ordered by primary care providers at the point of patient encounter, which include all blood and urine pathological tests, imaging studies and other diagnostic tests.

10.1 NUMBER OF INVESTIGATIONS PER ENCOUNTER

Table 10.1.1 shows the number of encounters in primary clinics during which at least one investigation was ordered. Of all 325,818 encounters recorded in primary care, 22.6% had investigations ordered. The higher proportion of investigations in public clinics (39.6%) as compared to private (11.1%) can be due to the higher proportion of chronic diseases managed in public sector.

Table 10.1.1: Number of encounters with investigations ordered in primary care clinics in 2014

Sector Unweighted


(95% CI)

Overall (n = 325,818) 7,272 73,540 22.6 (19.7–25.4)

Public (n = 131,624) 5,945 52,060 39.6 (35.4–43.7)

Private (n = 194,194) 1,327 21,480 11.1 (9.6–12.5)

The highest numbers of investigations ordered per encounter in public clinics and private clinics were 14 and 18, respectively. Investigations were ordered more frequently in the public clinics, with about one-fifth (18.7%) of the encounters had two or more investigations ordered per encounter, compared to only 2.9% in the private sector (Figure 10.1.1).

10.2 TYPES OF INVESTIGATIONS ORDERED

Table 10.2.1 shows the distribution of the most common investigations ordered in primary care in decreasing order of frequency. A total of 143,758 investigations were ordered in primary care, at a rate of 44.1 investigations per 100 encounters and 32.9 investigations per 100 diagnoses.

• More than four-fifths (82.0%) of all investigations ordered were laboratory/pathological tests. Glucose and/or glucose tolerance test constituted one fifth of these investigations.

• Imaging studies accounted for 9.3% of the total investigations. Obstetric ultrasound was the most frequently ordered imaging modality, recorded at 4.0% of all investigations ordered (1.8 per 100 encounters and 1.3 per 100 diagnoses).

Figure 10.1.1: Number of investigations ordered per encounter in primary care clinics in 2014

Table 10.2.1: Types of investigations by ICPC-2 process codes in primary care clinics in 2014


Weighted count



(95% CI) (n = 325,818)


(n = 436,743)

Pathology test 12,926 117,889 82.0 36.2 (30.5–41.9) 27.0 (23.2–30.8)

Chemistry 9,210 80,153 55.8 24.6 (19.7–29.5) 18.4 (15.1–21.7)

Glucose/glucose tolerance 2,515 24,704 17.2 7.6 (5.7–9.4) 5.7 (4.4–6.9)

Electrolytes, urea & creatinine* 1,805 14,659 10.2 4.5 (3.3–5.7) 3.4 (2.5–4.2)

Lipids 1,623 14,503 10.1 4.5 (3.5–5.4) 3.3 (2.6–4.0)

Liver function* 1,191 8,853 6.2 2.7 (2.0–3.4) 2.0 (1.5–2.5)

HbA1c 961 8,227 5.7 2.5 (1.6–3.4) 1.9 (1.2–2.5)

Chemistry; other* 495 3,883 2.7 1.2 (0.8–1.6) 0.9 (0.6–1.2)

Urate/uric acid 351 2,372 1.6 0.7 (0.4–1.1) 0.5 (0.3–0.8)

Thyroid function 144 1,674 1.2 0.5 (0.4–0.7) 0.4 (0.3–0.5)


Public 60.4 20.8 8.2 3.5 7.0

Private 88.9 8.1 1.8 0.4 0.7

0

10

20

30

40

50

60

70

80

90

100

Per

cen

t o

f en

cou

nte

rs (

%)

Number of investigations per encounter


Table 10.2.1 (continued): Types of investigations by ICPC-2 process codes in primary care clinics in 2014


Weighted count



(95% CI) (n = 325,818)


(n = 436,743)

Other NEC 1,395 14,987 10.4 4.6 (4.0–5.2) 3.4 (3.0–3.9)

Urine test* 900 9,504 6.6 2.9 (2.4–3.4) 2.2 (1.8–2.6)

Blood test 274 2,920 2.0 0.9 (0.6–1.2) 0.7 (0.4–0.9)

Urine pregnancy test 107 1,698 1.2 0.5 (0.3–0.8) 0.4 (0.2–0.6)

Haematology 1,534 14,890 10.4 4.6 (3.7–5.5) 3.3 (3.2–3.3)

Full blood count 1,216 11,636 8.1 3.6 (2.8–4.4) 2.7 (2.1–3.2)

Blood; other* 121 941 0.7 0.3 (0.2–0.4) 0.2 (0.1–0.3)

Haemoglobin 70 702 0.5 0.2 (0.1–0.3) 0.2 (0.1–0.3)

Microbiology 716 7,143 5.0 2.2 (1.5–2.8) 1.6 (1.2–2.1)

Hepatitis serology 183 1,932 1.3 0.6 (0.3–0.9) 0.4 (0.2–0.7)

Tuberculosis* 203 1,761 1.2 0.5 (0.3–0.8) 0.4 (0.2–0.6)

HIV 129 1,187 0.8 0.4 (0.2–0.5) 0.3 (0.2–0.4)

Venereal disease 99 1,106 0.8 0.3 (0.2–0.5) 0.3 (0.1–0.4)

Imaging 1,287 13,427 9.3 4.1 (3.3–4.9) 3.1 (2.5–3.7)

Ultrasound 746 7,226 5.0 2.2 (1.7–2.7) 1.7 (1.3–2.1)

Obstetric ultrasound 612 5,715 4.0 1.8 (1.3–2.2) 1.3 (0.9–1.7)

Diagnostic radiology 533 6,097 4.2 1.9 (1.2–2.6) 1.4 (0.9–1.9)

Chest X-ray 349 4,040 2.8 1.2 (0.7–1.8) 0.9 (0.5–1.3)

Other investigation 1,286 11,070 7.7 3.4 (2.3–4.5) 2.5 (1.8–3.3)

Physical function test 454 4,552 3.2 1.4 (0.7–2.1) 1.0 (0.6–1.5)

Blood pressure* 287 3,167 2.2 1.0 (0.4–1.6) 0.7 (0.3–1.2)

Vision 101 854 0.6 0.3 (0.1–0.4) 0.2 (0.1–0.3)

Electrical tracing 538 4,179 2.9 1.3 (0.9–1.7) 1.0 (0.7–1.3)

Electrocardiogram 536 4,113 2.9 1.3 (0.8–1.7) 0.9 (0.6–1.2)

Diagnostic procedure 294 2,339 1.6 0.7 (0.4–1.0) 0.5 (0.3–0.7)

Other diagnostic procedure; NEC* 190 1,578 1.1 0.5 (0.3–0.7) 0.4 (0.2–0.5)

Medical exam 128 1,372 1.0 0.4 (0.2–0.6) 0.3 (0.2–0.5)

Medical examination/health evaluation complete/partial

128 1,372 1.0 0.4 (0.2–0.6) 0.3 (0.2–0.5)

Total 15,627 143,758 100.0 44.1 (37.4–50.8) 32.9 (28.5–37.3)

* Comprise multiple ICPC-2 codes (see Appendix 4) Note: NEC – Not elsewhere classified.

10.3 MOST FREQUENTLY ORDERED INVESTIGATIONS IN PUBLIC AND PRIVATE CLINICS

The ordering rate of investigations differed significantly between the public and private sectors. Nonetheless, the two sectors shared six of the investigations listed among their top 10 list of investigations ordered (Figure 10.3.1 and Figure 10.3.2).

Public clinics

• The most frequently ordered test in the public sector was glucose and/or glucose tolerance test (15.1 per 100 encounters).

• Electrolytes, urea and creatinine test, ordered at a rate of 10.1 tests per 100 encounters, was the second most frequently ordered test, followed by lipid profile test (8.4 per 100 encounters).

Private clinics

• Generally, the ordering rates of investigations were much lower for the private sector. Glucose and/or glucose tolerance test, the most frequently ordered test in the private sector, was ordered only at the same rate as the tenth most frequently ordered investigation in the public sector (2.5 tests per 100 encounters).

• Urine test (2.0 per 100 encounters) and lipid profile test (1.8 per 100 encounters) were the second and third most frequently ordered tests in private clinics, respectively.

Figure 10.3.1: Top 10 investigations ordered in public clinics in 2014


2.5

2.7

3.2

4.3

5.5

6.1

7.0

8.4

10.1

15.1

0 2 4 6 8 10 12 14 16 18 20 22

Chemistry; other*

Electrocardiogram

Obstetric ultrasound

Urine test*

HbA1c

Liver function*

Full blood count

Lipids

Electrolytes, urea & creatinine*

Glucose/glucose tolerance


99

Table 10.2.1 (continued): Types of investigations by ICPC-2 process codes in primary care clinics in 2014


Weighted count



(95% CI) (n = 325,818)


(n = 436,743)

Other NEC 1,395 14,987 10.4 4.6 (4.0–5.2) 3.4 (3.0–3.9)

Urine test* 900 9,504 6.6 2.9 (2.4–3.4) 2.2 (1.8–2.6)

Blood test 274 2,920 2.0 0.9 (0.6–1.2) 0.7 (0.4–0.9)

Urine pregnancy test 107 1,698 1.2 0.5 (0.3–0.8) 0.4 (0.2–0.6)

Haematology 1,534 14,890 10.4 4.6 (3.7–5.5) 3.3 (3.2–3.3)

Full blood count 1,216 11,636 8.1 3.6 (2.8–4.4) 2.7 (2.1–3.2)

Blood; other* 121 941 0.7 0.3 (0.2–0.4) 0.2 (0.1–0.3)

Haemoglobin 70 702 0.5 0.2 (0.1–0.3) 0.2 (0.1–0.3)

Microbiology 716 7,143 5.0 2.2 (1.5–2.8) 1.6 (1.2–2.1)

Hepatitis serology 183 1,932 1.3 0.6 (0.3–0.9) 0.4 (0.2–0.7)

Tuberculosis* 203 1,761 1.2 0.5 (0.3–0.8) 0.4 (0.2–0.6)

HIV 129 1,187 0.8 0.4 (0.2–0.5) 0.3 (0.2–0.4)

Venereal disease 99 1,106 0.8 0.3 (0.2–0.5) 0.3 (0.1–0.4)

Imaging 1,287 13,427 9.3 4.1 (3.3–4.9) 3.1 (2.5–3.7)

Ultrasound 746 7,226 5.0 2.2 (1.7–2.7) 1.7 (1.3–2.1)

Obstetric ultrasound 612 5,715 4.0 1.8 (1.3–2.2) 1.3 (0.9–1.7)

Diagnostic radiology 533 6,097 4.2 1.9 (1.2–2.6) 1.4 (0.9–1.9)

Chest X-ray 349 4,040 2.8 1.2 (0.7–1.8) 0.9 (0.5–1.3)

Other investigation 1,286 11,070 7.7 3.4 (2.3–4.5) 2.5 (1.8–3.3)

Physical function test 454 4,552 3.2 1.4 (0.7–2.1) 1.0 (0.6–1.5)

Blood pressure* 287 3,167 2.2 1.0 (0.4–1.6) 0.7 (0.3–1.2)

Vision 101 854 0.6 0.3 (0.1–0.4) 0.2 (0.1–0.3)

Electrical tracing 538 4,179 2.9 1.3 (0.9–1.7) 1.0 (0.7–1.3)

Electrocardiogram 536 4,113 2.9 1.3 (0.8–1.7) 0.9 (0.6–1.2)

Diagnostic procedure 294 2,339 1.6 0.7 (0.4–1.0) 0.5 (0.3–0.7)

Other diagnostic procedure; NEC* 190 1,578 1.1 0.5 (0.3–0.7) 0.4 (0.2–0.5)

Medical exam 128 1,372 1.0 0.4 (0.2–0.6) 0.3 (0.2–0.5)

Medical examination/health evaluation complete/partial

128 1,372 1.0 0.4 (0.2–0.6) 0.3 (0.2–0.5)

Total 15,627 143,758 100.0 44.1 (37.4–50.8) 32.9 (28.5–37.3)


Chapter 10 : Investigations

10.3 MOST FREQUENTLY ORDERED INVESTIGATIONS IN PUBLIC AND PRIVATE CLINICS

The ordering rate of investigations differed significantly between the public and private sectors. Nonetheless, the two sectors shared six of the investigations listed among their top 10 list of investigations ordered (Figure 10.3.1 and Figure 10.3.2).

Public clinics

• The most frequently ordered test in the public sector was glucose and/or glucose tolerance test (15.1 per 100 encounters).

• Electrolytes, urea and creatinine test, ordered at a rate of 10.1 tests per 100 encounters, was the second most frequently ordered test, followed by lipid profile test (8.4 per 100 encounters).

Private clinics

• Generally, the ordering rates of investigations were much lower for the private sector. Glucose and/or glucose tolerance test, the most frequently ordered test in the private sector, was ordered only at the same rate as the tenth most frequently ordered investigation in the public sector (2.5 tests per 100 encounters).

• Urine test (2.0 per 100 encounters) and lipid profile test (1.8 per 100 encounters) were the second and third most frequently ordered tests in private clinics, respectively.

Figure 10.3.1: Top 10 investigations ordered in public clinics in 2014


2.5

2.7

3.2

4.3

5.5

6.1

7.0

8.4

10.1

15.1

0 2 4 6 8 10 12 14 16 18 20 22

Chemistry; other*

Electrocardiogram


Urine test*

HbA1c

Liver function*

Full blood count

Lipids





Figure 10.3.2: Top 10 investigations ordered in private clinics in 2014


10.4 DIAGNOSES WITH INVESTIGATIONS ORDERED

Table 10.4.1 reports the most common diagnoses for which investigations were ordered in primary care in 2014.

• The top 10 diagnoses for which investigations were most frequently ordered accounted for 73.2% of all diagnoses accompanied by tests.

• Diabetes accounted for a quarter (24.3%) of the diagnoses with at least one investigation ordered. This corresponds with another finding in NMCS 2014 that glucose and/or glucose tolerance test was the most frequently ordered investigation in primary care (see Section 10.2).

• The second most common diagnosis for which investigations were ordered was hypertension, which amounted to 16.0% of all diagnoses accompanied by tests, followed by lipid disorder at 9.6%.

• Together, the three aforementioned chronic diseases represented half (49.9%) of all diagnoses for which investigations were ordered, a finding which could be attributed to the high burden of the three metabolic syndrome-related conditions in primary care (see Chapter 8).

0.6

0.7

0.7

0.7

0.8

1.1

1.2

1.8

2.0

2.5

0 2 4 6 8 10 12 14 16 18 20 22

Hepatitis serology

Urine pregnancy test


Chest X-ray


Blood test

Full blood count

Lipids

Urine test*



Table 10.4.1: Top 10 diagnoses for which investigations were most frequently ordered in primary care clinics in 2014


count (n = 8,599)

Weighted count

(n = 82,978)

Percent of diagnoses

with investigation (n = 82,978)

Rate per 100 contacts with

each diagnosis (95% CI)

1 Diabetes - all* 1,958 20,157 24.3 55.1 (47.9–62.3)


Gestational diabetes 74 509 0.6 44.2 (30.3–58.1)




3 Lipid disorder 938 8,004 9.6 23.1 (17.1–29.1)


5 Upper respiratory tract infection 475 3,793 4.6 5.2 (3.8–6.6)


7 Fever 213 2,311 2.8 20.5 (15.2–25.9)


9 Pregnancy 101 1,264 1.5 73.3 (62.3–84.2)

10 Blood test 56 1,204 1.5 96.8 (93.1–100.0)


REFERENCE

1. Best tests? The general principles of laboratory investigations in primary care [Internet]. Dunedin (New Zealand): Best Practice Advocacy Centre New Zealand; 2013 Feb [cited 2015 May 7];p.3-9. Available from: http://www.bpac.org.nz/BT/2013/February/docs/best_tests_feb2013_general_principles_pages_4-11.pdf

101

Figure 10.3.2: Top 10 investigations ordered in private clinics in 2014


10.4 DIAGNOSES WITH INVESTIGATIONS ORDERED

Table 10.4.1 reports the most common diagnoses for which investigations were ordered in primary care in 2014.

• The top 10 diagnoses for which investigations were most frequently ordered accounted for 73.2% of all diagnoses accompanied by tests.

• Diabetes accounted for a quarter (24.3%) of the diagnoses with at least one investigation ordered. This corresponds with another finding in NMCS 2014 that glucose and/or glucose tolerance test was the most frequently ordered investigation in primary care (see Section 10.2).

• The second most common diagnosis for which investigations were ordered was hypertension, which amounted to 16.0% of all diagnoses accompanied by tests, followed by lipid disorder at 9.6%.

• Together, the three aforementioned chronic diseases represented half (49.9%) of all diagnoses for which investigations were ordered, a finding which could be attributed to the high burden of the three metabolic syndrome-related conditions in primary care (see Chapter 8).

0.6

0.7

0.7

0.7

0.8

1.1

1.2

1.8

2.0

2.5

0 2 4 6 8 10 12 14 16 18 20 22

Hepatitis serology

Urine pregnancy test


Chest X-ray


Blood test

Full blood count

Lipids

Urine test*



Chapter 10 : Investigations

Table 10.4.1: Top 10 diagnoses for which investigations were most frequently ordered in primary care clinics in 2014


count (n = 8,599)

Weighted count

(n = 82,978)


with investigation (n = 82,978)



1 Diabetes - all* 1,958 20,157 24.3 55.1 (47.9–62.3)


Gestational diabetes 74 509 0.6 44.2 (30.3–58.1)




3 Lipid disorder 938 8,004 9.6 23.1 (17.1–29.1)


5 Upper respiratory tract infection 475 3,793 4.6 5.2 (3.8–6.6)


7 Fever 213 2,311 2.8 20.5 (15.2–25.9)


9 Pregnancy 101 1,264 1.5 73.3 (62.3–84.2)

10 Blood test 56 1,204 1.5 96.8 (93.1–100.0)


REFERENCE

1. Best tests? The general principles of laboratory investigations in primary care [Internet]. Dunedin (New Zealand): Best Practice Advocacy Centre New Zealand; 2013 Feb [cited 2015 May 7];p.3-9. Available from: http://www.bpac.org.nz/BT/2013/February/docs/best_tests_feb2013_general_principles_pages_4-11.pdf

CHAPTER elevenAdvice/Counselling

and Procedures


CHAPTER 11: ADVICE/COUNSELLING AND PROCEDURES

In this chapter, advice/counselling and procedures provided to patients in primary care clinics are reported. Advice or counselling captured in NMCS 2014 refers to any health education, advice pertaining to the presenting problem, or counselling rendered by healthcare providers at the time of presentation to bring about effective behavioural changes in patients and enhance their wellbeing. Similarly, procedures include any administrative, therapeutic or rehabilitative procedures performed during the encounters and recorded by the providers. Note that the classification of advice/counselling and procedures followed an approach which differs from that used in NMCS 2012.

11.1 NUMBER OF ADVICE/COUNSELLING AND PROCEDURES

Out of the 325,818 encounters recorded, 24.5% were managed with at least one form of advice/counselling (Table 11.1.1). A higher frequency of advice and counselling was reported in the public sector (37.5% of public clinic encounters), more than double the frequency in private clinics (15.6%).

Table 11.1.1: Number of encounters managed with advice and counselling in primary care clinics in 2014

Sector Unweighted count Weighted count Percent of encounters

(95% CI)

Overall (n = 325,818) 7,993 79,770 24.5 (21.6–27.4)

Public (n = 131,624) 6,169 49,394 37.5 (32.4–42.6)

Private (n = 194,194) 1,824 30,376 15.6 (13.1–18.2)

Table 11.1.2 shows the percentage of encounters that had some procedures performed at the time of visit. In private clinics, 8.2% of patients underwent at least one procedure during the visit, compared to 5.0% in public clinics.

Table 11.1.2: Number of encounters managed with procedures in primary care clinics in 2014

Sector Unweighted


(95% CI)

Overall (n = 325,818) 1,681 22,471 6.9 (6.1–7.7)

Public (n = 131,624) 766 6,550 5.0 (4.2–5.8)

Private (n = 194,194) 915 15,922 8.2 (7.0–9.4)

11.2 TYPES OF ADVICE/COUNSELLING

The different types of advice/counselling provided in primary care clinics are shown in Table 11.2.1.

• About one-third (32.7%) of advice and counselling provided in primary care clinics were general advice/counselling.

• Advices on nutrition/weight (21.7%) and lifestyle advices (18.5 %) were the second and third most common advice/counselling given, respectively.

Table 11.2.1: Types of advice and counselling provided in primary care clinics in 2014

Advice/counselling Unweighted

count Weighted

count

Percent of advice and counselling (n = 111,707)


(95% CI) (n = 325,818)

Rate per 100 diagnoses

(95%CI) (n = 436,743)

Advice/counselling; NEC* 3,457 36,524 32.7 11.2 (9.4–13.1) 8.4 (7.1–9.6)

Advice/counselling; nutrition/weight* 2,666 24,269 21.7 7.4 (6.2–8.7) 5.6 (4.6–6.5)

Advice/counselling; lifestyle 1,958 20,642 18.5 6.3 (4.9–7.8) 4.7 (3.7–5.7)

Advice/counselling; treatment* 983 9,269 8.3 2.8 (2.2–3.5) 2.1 (1.6–2.6)

Advice/counselling; medication* 502 4,929 4.4 1.5 (1.1–1.9) 1.1 (0.9–1.4)

Advice/counselling; exercise 394 4,286 3.8 1.3 (0.9–1.7) 1.0 (0.7–1.3)

Advice/counselling; health/body* 285 3,193 2.9 1.0 (0.7–1.3) 0.7 (0.5–1.0)

Advice/counselling; pregnancy* 328 2,853 2.6 0.9 (0.6–1.2) 0.7 (0.4–0.9)

Advice/counselling; smoking 109 1,240 1.1 0.4 (0.2–0.5) 0.3 (0.2–0.4)

Advice/counselling; other* 66 1,121 1.0 0.3 (0.1–0.6) 0.3 (0.1–0.4)

Advice/counselling; prevention* 63 858 0.8 0.3 (0.1–0.4) 0.2 (0.1–0.3)

Family planning* 66 632 0.6 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Advice/counselling; relaxation* 43 498 0.4 0.2 (0.1–0.2) 0.1 (0.1–0.2)

Reassurance/support 43 474 0.4 0.1 (0.1–0.2) 0.1 (0.0–0.2)

Advice/counselling; drug abuse 45 439 0.4 0.1 (0.0–0.3) 0.1 (0.0–0.2)

Advice/counselling; alcohol 10 296 0.3 0.1 (0.0–0.2) 0.1 (0.0–0.2)

105

CHAPTER 11: ADVICE/COUNSELLING AND PROCEDURES

In this chapter, advice/counselling and procedures provided to patients in primary care clinics are reported. Advice or counselling captured in NMCS 2014 refers to any health education, advice pertaining to the presenting problem, or counselling rendered by healthcare providers at the time of presentation to bring about effective behavioural changes in patients and enhance their wellbeing. Similarly, procedures include any administrative, therapeutic or rehabilitative procedures performed during the encounters and recorded by the providers. Note that the classification of advice/counselling and procedures followed an approach which differs from that used in NMCS 2012.

11.1 NUMBER OF ADVICE/COUNSELLING AND PROCEDURES

Out of the 325,818 encounters recorded, 24.5% were managed with at least one form of advice/counselling (Table 11.1.1). A higher frequency of advice and counselling was reported in the public sector (37.5% of public clinic encounters), more than double the frequency in private clinics (15.6%).

Table 11.1.1: Number of encounters managed with advice and counselling in primary care clinics in 2014

Sector Unweighted count Weighted count Percent of encounters

(95% CI)

Overall (n = 325,818) 7,993 79,770 24.5 (21.6–27.4)

Public (n = 131,624) 6,169 49,394 37.5 (32.4–42.6)

Private (n = 194,194) 1,824 30,376 15.6 (13.1–18.2)

Table 11.1.2 shows the percentage of encounters that had some procedures performed at the time of visit. In private clinics, 8.2% of patients underwent at least one procedure during the visit, compared to 5.0% in public clinics.

Table 11.1.2: Number of encounters managed with procedures in primary care clinics in 2014

Sector Unweighted


(95% CI)

Overall (n = 325,818) 1,681 22,471 6.9 (6.1–7.7)

Public (n = 131,624) 766 6,550 5.0 (4.2–5.8)

Private (n = 194,194) 915 15,922 8.2 (7.0–9.4)

Chapter 11 : Advice/Counselling and Procedures

11.2 TYPES OF ADVICE/COUNSELLING

The different types of advice/counselling provided in primary care clinics are shown in Table 11.2.1.

• About one-third (32.7%) of advice and counselling provided in primary care clinics were general advice/counselling.

• Advices on nutrition/weight (21.7%) and lifestyle advices (18.5 %) were the second and third most common advice/counselling given, respectively.

Table 11.2.1: Types of advice and counselling provided in primary care clinics in 2014


count Weighted

count



(95% CI) (n = 325,818)


(95%CI) (n = 436,743)

Advice/counselling; NEC* 3,457 36,524 32.7 11.2 (9.4–13.1) 8.4 (7.1–9.6)

Advice/counselling; nutrition/weight* 2,666 24,269 21.7 7.4 (6.2–8.7) 5.6 (4.6–6.5)

Advice/counselling; lifestyle 1,958 20,642 18.5 6.3 (4.9–7.8) 4.7 (3.7–5.7)

Advice/counselling; treatment* 983 9,269 8.3 2.8 (2.2–3.5) 2.1 (1.6–2.6)

Advice/counselling; medication* 502 4,929 4.4 1.5 (1.1–1.9) 1.1 (0.9–1.4)

Advice/counselling; exercise 394 4,286 3.8 1.3 (0.9–1.7) 1.0 (0.7–1.3)

Advice/counselling; health/body* 285 3,193 2.9 1.0 (0.7–1.3) 0.7 (0.5–1.0)

Advice/counselling; pregnancy* 328 2,853 2.6 0.9 (0.6–1.2) 0.7 (0.4–0.9)

Advice/counselling; smoking 109 1,240 1.1 0.4 (0.2–0.5) 0.3 (0.2–0.4)

Advice/counselling; other* 66 1,121 1.0 0.3 (0.1–0.6) 0.3 (0.1–0.4)

Advice/counselling; prevention* 63 858 0.8 0.3 (0.1–0.4) 0.2 (0.1–0.3)

Family planning* 66 632 0.6 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Advice/counselling; relaxation* 43 498 0.4 0.2 (0.1–0.2) 0.1 (0.1–0.2)

Reassurance/support 43 474 0.4 0.1 (0.1–0.2) 0.1 (0.0–0.2)

Advice/counselling; drug abuse 45 439 0.4 0.1 (0.0–0.3) 0.1 (0.0–0.2)

Advice/counselling; alcohol 10 296 0.3 0.1 (0.0–0.2) 0.1 (0.0–0.2)


Table 11.2.1 (continued): Types of advice and counselling provided in primary care clinics in 2014


count Weighted

count



(95% CI) (n = 325,818)


(95%CI) (n = 436,743)

Result test/procedure* 11 115 0.1 0.0 (0.0–0.1) 0.0 (0.0–0.0)

Observe/wait* 2 42 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Advice/counselling; psychological 1 16 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Referral* 2 11 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Consultation with primary care provider*

1 3 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Total 11,035 111,707 100.0 34.3 (30.0–38.6) 25.6 (22.8–28.4)


11.3 MOST COMMON ADVICE/COUNSELLING PROVIDED IN PUBLIC AND PRIVATE CLINICS

The most common advice/counselling provided in public and private clinics are presented in Figure 11.3.1 and Figure 11.3.2, respectively.

• The top four advice/counselling provided for both public and private clinics were, in descending order of frequency, general advice and counselling, advices on nutrition/weight, lifestyle education and education on treatment.

• The rates of advice/counselling provision were evidently higher in the public sector. For instance, general advice/counselling was provided at a rate of 17.9 per 100 encounters in public clinics, compared to 6.7 per encounters in private clinics.

• Other advice/counselling provided in both public and private clinics included advice and counselling on medication, pregnancy, exercise, general health and smoking.

Figure 11.3.1: Ten most common advice/counselling provided in public clinics in 2014


Figure 11.3.2: Ten most common advice/counselling provided in private clinics in 2014


0.4

0.4

0.7

1.5

1.8

2.7

4.1

11.2

11.9

17.9

0 5 10 15 20 25

Family planning*

Advice/counselling; smoking

Advice/counselling; health/body*

Advice/counselling; exercise

Advice/counselling; pregnancy*

Advice/counselling; medication*

Advice/counselling; treatment*

Advice/counselling; lifestyle

Advice/counselling; nutrition/weight*

Advice/counselling; NEC*


0.3

0.3

0.4

0.7

1.2

1.2

2.0

3.1

4.4

6.7

0 5 10 15 20 25



Advice/counselling; other*









107

Table 11.2.1 (continued): Types of advice and counselling provided in primary care clinics in 2014


count Weighted

count



(95% CI) (n = 325,818)


(95%CI) (n = 436,743)

Result test/procedure* 11 115 0.1 0.0 (0.0–0.1) 0.0 (0.0–0.0)

Observe/wait* 2 42 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Advice/counselling; psychological 1 16 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Referral* 2 11 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Consultation with primary care provider*

1 3 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0)

Total 11,035 111,707 100.0 34.3 (30.0–38.6) 25.6 (22.8–28.4)


11.3 MOST COMMON ADVICE/COUNSELLING PROVIDED IN PUBLIC AND PRIVATE CLINICS

The most common advice/counselling provided in public and private clinics are presented in Figure 11.3.1 and Figure 11.3.2, respectively.

• The top four advice/counselling provided for both public and private clinics were, in descending order of frequency, general advice and counselling, advices on nutrition/weight, lifestyle education and education on treatment.

• The rates of advice/counselling provision were evidently higher in the public sector. For instance, general advice/counselling was provided at a rate of 17.9 per 100 encounters in public clinics, compared to 6.7 per encounters in private clinics.

• Other advice/counselling provided in both public and private clinics included advice and counselling on medication, pregnancy, exercise, general health and smoking.


Figure 11.3.1: Ten most common advice/counselling provided in public clinics in 2014


Figure 11.3.2: Ten most common advice/counselling provided in private clinics in 2014


0.4

0.4

0.7

1.5

1.8

2.7

4.1

11.2

11.9

17.9

0 5 10 15 20 25

Family planning*











0.3

0.3

0.4

0.7

1.2

1.2

2.0

3.1

4.4

6.7

0 5 10 15 20 25



Advice/counselling; other*










11.4 TYPES OF PROCEDURES

Table 11.4.1 shows the different types of procedures provided in primary care clinics in 2014.

• The most common procedure performed in primary care clinics was injection/infiltration, accounting for 27.9% of all procedures, followed by procedure for dressing, pressure or compression of wounds at 21.4%.

• Immunisation, an important measure for disease prevention, accounted for 10.4% of all procedures performed in primary care.

Table 11.4.1: Types of procedures provided in primary care clinics in 2014

Procedure Unweighted count

Weighted count

Percent of procedures (n = 25,001)


(95% CI) (n = 325,818)


(n = 436,743)

Injection/infiltration* 419 6,977 27.9 2.1 (1.5–2.8) 1.6 (1.1–2.1)

Dressing/pressure/ compression/tamponade*

429 5,345 21.4 1.6 (1.4–1.9) 1.2 (1.0–1.4)

Other therapeutic medication/procedures/ minor surgery*

310 3,953 15.8 1.2 (1.0–1.5) 0.9 (0.7–1.1)

Immunisation* 217 2,601 10.4 0.8 (0.6–1.0) 0.6 (0.4–0.8)

Administrative procedure* 134 1,493 6.0 0.5 (0.3–0.6) 0.3 (0.2–0.4)

Excision/removal tissue/biopsy/destruction/ debridement/cauterisation*

79 1,122 4.5 0.3 (0.2–0.4) 0.3 (0.2–0.3)

Repair/fixation - suture/cast/prosthetic device (apply/remove)*

66 1,002 4.0 0.3 (0.2–0.4) 0.2 (0.1–0.3)

Contraception procedure* 57 724 2.9 0.2 (0.1–0.3) 0.2 (0.1–0.2)

Incision/drainage/flushing/ aspiration/removal body fluid*

52 722 2.9 0.2 (0.1–0.3) 0.2 (0.1–0.2)

Medical examination complete/partial* 93 637 2.5 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Physical medicine/rehabilitation* 35 425 1.7 0.1 (0.1–0.2) 0.1 (0.0–0.1)

Total 1,891 25,001 100.0 7.7 (6.8–8.6) 5.7 (5.0–6.5)


11.5 MOST COMMON PROCEDURES PERFORMED IN PUBLIC AND PRIVATE CLINICS

• In public clinics, a total of 6,550 encounters (5.0%) had at least one procedure performed. Dressing/pressure/compression/tamponade was the most frequently performed procedure, recorded at a rate of 1.1 per 100 encounters (Figure 11.5.1).

• The same procedure was performed at rate of 2.0 per 100 encounters in private clinics (Figure 11.5.2), second to injection/infiltration (3.0 per 100 encounters).

• Immunisation was provided at similar rates in public and private clinics (0.7 versus 0.9 per 100 encounters, respectively).

Figure 11.5.1: Ten most common procedures performed in public clinics in 2014


0.1

0.2

0.2

0.3

0.3

0.7

0.8

0.9

0.9

1.1

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

Physical medicine/rehabilitation*

Incision/drainage/flushing/aspiration/removal body fluid*

Contraception procedure*


Medical examination complete/partial*

Immunisation*

Administrative procedure*


Injection/infiltration*

Dressing/pressure/compression/tamponade*


109

11.4 TYPES OF PROCEDURES

Table 11.4.1 shows the different types of procedures provided in primary care clinics in 2014.

• The most common procedure performed in primary care clinics was injection/infiltration, accounting for 27.9% of all procedures, followed by procedure for dressing, pressure or compression of wounds at 21.4%.

• Immunisation, an important measure for disease prevention, accounted for 10.4% of all procedures performed in primary care.

Table 11.4.1: Types of procedures provided in primary care clinics in 2014

Procedure Unweighted count

Weighted count

Percent of procedures (n = 25,001)


(95% CI) (n = 325,818)


(n = 436,743)

Injection/infiltration* 419 6,977 27.9 2.1 (1.5–2.8) 1.6 (1.1–2.1)

Dressing/pressure/ compression/tamponade*

429 5,345 21.4 1.6 (1.4–1.9) 1.2 (1.0–1.4)


310 3,953 15.8 1.2 (1.0–1.5) 0.9 (0.7–1.1)

Immunisation* 217 2,601 10.4 0.8 (0.6–1.0) 0.6 (0.4–0.8)

Administrative procedure* 134 1,493 6.0 0.5 (0.3–0.6) 0.3 (0.2–0.4)


79 1,122 4.5 0.3 (0.2–0.4) 0.3 (0.2–0.3)


66 1,002 4.0 0.3 (0.2–0.4) 0.2 (0.1–0.3)

Contraception procedure* 57 724 2.9 0.2 (0.1–0.3) 0.2 (0.1–0.2)

Incision/drainage/flushing/ aspiration/removal body fluid*

52 722 2.9 0.2 (0.1–0.3) 0.2 (0.1–0.2)

Medical examination complete/partial* 93 637 2.5 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Physical medicine/rehabilitation* 35 425 1.7 0.1 (0.1–0.2) 0.1 (0.0–0.1)

Total 1,891 25,001 100.0 7.7 (6.8–8.6) 5.7 (5.0–6.5)



11.5 MOST COMMON PROCEDURES PERFORMED IN PUBLIC AND PRIVATE CLINICS

• In public clinics, a total of 6,550 encounters (5.0%) had at least one procedure performed. Dressing/pressure/compression/tamponade was the most frequently performed procedure, recorded at a rate of 1.1 per 100 encounters (Figure 11.5.1).

• The same procedure was performed at rate of 2.0 per 100 encounters in private clinics (Figure 11.5.2), second to injection/infiltration (3.0 per 100 encounters).

• Immunisation was provided at similar rates in public and private clinics (0.7 versus 0.9 per 100 encounters, respectively).

Figure 11.5.1: Ten most common procedures performed in public clinics in 2014


0.1

0.2

0.2

0.3

0.3

0.7

0.8

0.9

0.9

1.1

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

Physical medicine/rehabilitation*





Immunisation*







Figure 11.5.2: Ten most common procedures performed in private clinics in 2014


11.6 DIAGNOSES WITH ADVICE/COUNSELLING AND PROCEDURES

Table 11.6.1 and Table 11.6.2 list the top 10 diagnoses managed with advice/counselling and procedures, respectively.

• The three diagnoses for which advice and counselling were provided most frequently were all chronic diseases: hypertension (20.6% of all advice/counselling provided), diabetes (18.5%) and lipid disorder (13.9%). Together, these three conditions accounted for over half (52.9%) of all advice/counselling given as part of patient management in primary care.

• Patients with asthma, for whom nebulisation forms an important part of the treatment procedure, contributed to the largest proportion (8.5%) of all diagnoses managed with a procedure.

0.1

0.2

0.2

0.3

0.3

0.5

0.9

1.4

2.0

3.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5







Immunisation*





Table 11.6.1: Ten most common diagnoses managed with advice/counselling in primary care clinics in 2014


count

(n = 10,634)

Weighted count

(n = 102,779)


with advice and

counselling (n = 102,779)


(95%CI) (n = 325,818)



1 Hypertension - all* 2,394 21,128 20.6 6.5 (5.2–7.8) 37.6 (32.6–42.6)


2,378 20,998 20.4 6.4 (5.1–7.8) 37.5 (32.5–42.5)

Hypertension in pregnancy 16 130 0.1 0.0 (0.0–0.1) 42.5 (20.4–64.7)

2 Diabetes - all* 2,014 19,018 18.5 5.8 (4.3–7.4) 52.0 (45.1–58.9)

Diabetes - non- gestational*

1,927 18,282 17.8 5.6 (4.1–7.1) 51.6 (44.5–58.6)

Gestational diabetes 87 737 0.7 0.2 (0.1–0.3) 64.0 (49.8–78.2)

3 Lipid disorder 1,562 14,286 13.9 4.4 (3.2–5.6) 41.2 (34.6–47.8)

4 Upper respiratory tract infection 879 8,290 8.1 2.5 (2.0–3.1) 11.3 (8.9–13.7)

5 Asthma 183 2,537 2.5 0.8 (0.4–1.1) 27.2 (18.1–36.2)

6 Medical examination - pregnancy* 224 2,127 2.1 0.7 (0.4–0.9) 22.5 (14.6–30.4)

7 Gastroenteritis* 197 2,106 2.0 0.6 (0.5–0.8) 16.0 (12.0–20.1)

8 Stomach function disorder 178 1,660 1.6 0.5 (0.4–0.6) 19.0 (13.9–24.1)

9 Musculoskeletal symptom/complaints* 158 1,623 1.6 0.5 (04–0.6) 12.0 (8.7–15.2)

10 Fever 169 1,569 1.5 0.5 (0.3–0.7) 13.9 (8.3–19.6)


111

Figure 11.5.2: Ten most common procedures performed in private clinics in 2014


11.6 DIAGNOSES WITH ADVICE/COUNSELLING AND PROCEDURES

Table 11.6.1 and Table 11.6.2 list the top 10 diagnoses managed with advice/counselling and procedures, respectively.

• The three diagnoses for which advice and counselling were provided most frequently were all chronic diseases: hypertension (20.6% of all advice/counselling provided), diabetes (18.5%) and lipid disorder (13.9%). Together, these three conditions accounted for over half (52.9%) of all advice/counselling given as part of patient management in primary care.

• Patients with asthma, for whom nebulisation forms an important part of the treatment procedure, contributed to the largest proportion (8.5%) of all diagnoses managed with a procedure.

0.1

0.2

0.2

0.3

0.3

0.5

0.9

1.4

2.0

3.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5







Immunisation*





Table 11.6.1: Ten most common diagnoses managed with advice/counselling in primary care clinics in 2014


count

(n = 10,634)

Weighted count

(n = 102,779)


with advice and

counselling (n = 102,779)


(95%CI) (n = 325,818)



1 Hypertension - all* 2,394 21,128 20.6 6.5 (5.2–7.8) 37.6 (32.6–42.6)


2,378 20,998 20.4 6.4 (5.1–7.8) 37.5 (32.5–42.5)

Hypertension in pregnancy 16 130 0.1 0.0 (0.0–0.1) 42.5 (20.4–64.7)

2 Diabetes - all* 2,014 19,018 18.5 5.8 (4.3–7.4) 52.0 (45.1–58.9)

Diabetes - non- gestational*

1,927 18,282 17.8 5.6 (4.1–7.1) 51.6 (44.5–58.6)


3 Lipid disorder 1,562 14,286 13.9 4.4 (3.2–5.6) 41.2 (34.6–47.8)

4 Upper respiratory tract infection 879 8,290 8.1 2.5 (2.0–3.1) 11.3 (8.9–13.7)

5 Asthma 183 2,537 2.5 0.8 (0.4–1.1) 27.2 (18.1–36.2)

6 Medical examination - pregnancy* 224 2,127 2.1 0.7 (0.4–0.9) 22.5 (14.6–30.4)

7 Gastroenteritis* 197 2,106 2.0 0.6 (0.5–0.8) 16.0 (12.0–20.1)

8 Stomach function disorder 178 1,660 1.6 0.5 (0.4–0.6) 19.0 (13.9–24.1)

9 Musculoskeletal symptom/complaints* 158 1,623 1.6 0.5 (04–0.6) 12.0 (8.7–15.2)

10 Fever 169 1,569 1.5 0.5 (0.3–0.7) 13.9 (8.3–19.6)




Table 11.6.2: Ten most common diagnoses managed with procedures in primary care clinics in 2014


count (n = 1,665)

Weighted count

(n = 21,886)


with procedure

(n = 21,886)


(95%CI) (n = 325,818)



1 Asthma 154 1,864 8.5 0.6 (0.4–0.7) 20.0 (14.5–25.4)

2 Musculoskeletal symptom/ complaints* 100 1,178 5.4 0.4 (0.3–0.5) 8.7 (6.4–11.0)

3 Injury skin (laceration/cut) 76 1,177 5.4 0.4 (0.2–0.6) 80.6 (69.1–92.1)

4 Upper respiratory tract infection 63 894 4.1 0.3 (0.2–0.4) 1.2 (0.7–1.7)

5 Preventive immunisations/ medications; NOS

46 738 3.4 0.2 (0.1–0.3) 55.2 (37.0–73.4)

6 Contraception, female 53 607 2.8 0.2 (0.1–0.3) 35.2 (25.1–45.3)

7 Dressing/pressure/ compress/ tamponade 29 579 2.6 0.2 (0.1–0.3) 64.9 (36.0–93.9)

8 Gastroenteritis 27 536 2.4 0.2 (0.0–0.3) 4.1 (1.0–7.2)

9 Skin infections 42 534 2.4 0.2 (0.1–0.2) 28.5 (18.8–38.2)

10 Trauma/injury 39 466 2.1 0.1 (0.1–0.2) 31.3 (20.0–42.7)


Table 11.6.2: Ten most common diagnoses managed with procedures in primary care clinics in 2014


count (n = 1,665)

Weighted count

(n = 21,886)


with procedure

(n = 21,886)


(95%CI) (n = 325,818)



1 Asthma 154 1,864 8.5 0.6 (0.4–0.7) 20.0 (14.5–25.4)

2 Musculoskeletal symptom/ complaints* 100 1,178 5.4 0.4 (0.3–0.5) 8.7 (6.4–11.0)

3 Injury skin (laceration/cut) 76 1,177 5.4 0.4 (0.2–0.6) 80.6 (69.1–92.1)

4 Upper respiratory tract infection 63 894 4.1 0.3 (0.2–0.4) 1.2 (0.7–1.7)

5 Preventive immunisations/ medications; NOS

46 738 3.4 0.2 (0.1–0.3) 55.2 (37.0–73.4)

6 Contraception, female 53 607 2.8 0.2 (0.1–0.3) 35.2 (25.1–45.3)

7 Dressing/pressure/ compress/ tamponade 29 579 2.6 0.2 (0.1–0.3) 64.9 (36.0–93.9)


9 Skin infections 42 534 2.4 0.2 (0.1–0.2) 28.5 (18.8–38.2)

10 Trauma/injury 39 466 2.1 0.1 (0.1–0.2) 31.3 (20.0–42.7)

*Comprise multiple ICPC-2 codes (see Appendix 4) CHAPTER twelveFollow-Ups and

Referrals


CHAPTER 12: FOLLOW-UPS AND REFERRALS

Depending on the diagnosis and patient needs, primary healthcare providers may schedule follow-up appointments for patients or refer them to other healthcare providers or services. These visit dispositions (follow-ups and referrals) and their related diagnoses were documented in NMCS 2014 and are reported here. Note that the classification of follow-ups and referrals followed a different approach than that used in NMCS 2012.

12.1 NUMBER OF FOLLOW-UPS AND REFERRALS

Table 12.1.1 shows the visit dispositions of primary care patients in 2014.

• About one-third (29.7%) of the patients presenting to primary care had a referral or follow-up appointment.

• Almost half (49.2%) of all encounters in public clinics had a follow-up appointment scheduled, compared to only 12.9% in private clinics. This finding could be attributed to the fact that the bulk of the public clinic encounters were of patients with chronic diseases (see Chapter 8), who were more likely to require some form of follow-up.

• Only 3.4% of all encounters were issued referrals. The referral rate was higher in the public sector compared to the private sector (5.8% versus 1.8%, respectively).

Table 12.1.1: Visit dispositions of primary care patients by sector in 2014

Visit disposition Unweighted

count Weighted

count Percent of encounters

(95% CI)

Overall

Follow-up 8,742 89,641 27.5 (24.4–30.8)

At least one referral 1,099 11,068 3.4 (2.8–4.0)

Follow-up or at least one referral 9,425 96,853 29.7 (26.4–33.1)

Public

Follow-up 7,224 64,737 49.2 (45.1–53.3)

At least one referral 919 7,681 5.8 (4.6–7.1)


Private

Follow-up 1,518 24,904 12.9 (10.7–15.1)



12.2 TYPES OF REFERRALS

Referrals captured in NMCS 2014 included referrals within the primary care sphere (which included referrals to family medicine specialists, non-specialist doctors, assistant medical officers, maternal and child health services, quit smoking clinics and diabetes medical therapy adherence clinics), those to medical specialists other than family medicine specialists, allied health services, hospitals, and other services (which included social welfare services for the public sector and diagnostic imaging services for the private sector). Table 12.2.1 shows the distribution of referrals by type in primary care clinics in 2014.

• Out of the 11,068 patients who had at least one referral recorded, 38.2% were referred to medical specialists (1.3 per 100 encounters and 1.0 per 100 diagnoses).

• Referrals to hospitals accounted for 27.6% of all referrals (0.9 per 100 encounters and 0.7 per 100 diagnoses), followed by those within the primary care sphere at 17.2% (0.6 per 100 encounters and 0.4 per 100 diagnoses) and those to allied health services at 13.9% (0.5 per 100 encounters and 0.4 per 100 diagnoses).

Table 12.2.1: Types of referrals in primary care in 2014

Type of referrals Unweighted

count Weighted

count

Percent of total

referrals (n = 11,068)


(95% CI) (n = 325,818)


(n = 436,743)

Specialist 386 4,229 38.2 1.3 (0.9–1.7) 1.0 (0.7–1.2)

Hospital 278 3,052 27.6 0.9 (0.7–1.1) 0.7 (0.6–0.8)

Primary care 237 1,900 17.2 0.6 (0.3–0.9) 0.4 (0.2–0.6)

Allied health services 173 1,543 13.9 0.5 (0.3–0.7) 0.4 (0.2–0.5)

Other services 25 344 3.1 0.1 (0.0–0.2) 0.1 (0.0–0.1)

Total 1,099 11,068 100.0 3.4 (2.3–4.5) 2.5 (1.7–3.4)

Table 12.2.2 and Table 12.2.3 show the distribution of referrals by type in public and private clinics, respectively.

Public clinics • Referrals in public clinics were most often to medical specialists (34.0% of referrals in the public

sector), recorded at a rate of 2.0 specialist referrals per 100 encounters (1.3 referrals per 100 diagnoses).

• Referrals within primary care accounted for 22.4% of all referrals in public clinics, followed closely by referrals to hospitals at 21.6% and allied health services at 19.3%.

Private clinics • Nearly half (47.7%) of all referrals recorded in the private sector were for medical specialists, while

hospital referrals constituted most of the other half (41.1% of total referrals). • Referrals to another primary healthcare centre, the third most common type of referrals made in

private clinics, accounted for a smaller proportion of referrals in the private sector than in the public sector (5.2% versus 22.4%, respectively).

115

CHAPTER 12: FOLLOW-UPS AND REFERRALS

Depending on the diagnosis and patient needs, primary healthcare providers may schedule follow-up appointments for patients or refer them to other healthcare providers or services. These visit dispositions (follow-ups and referrals) and their related diagnoses were documented in NMCS 2014 and are reported here. Note that the classification of follow-ups and referrals followed a different approach than that used in NMCS 2012.

12.1 NUMBER OF FOLLOW-UPS AND REFERRALS

Table 12.1.1 shows the visit dispositions of primary care patients in 2014.

• About one-third (29.7%) of the patients presenting to primary care had a referral or follow-up appointment.

• Almost half (49.2%) of all encounters in public clinics had a follow-up appointment scheduled, compared to only 12.9% in private clinics. This finding could be attributed to the fact that the bulk of the public clinic encounters were of patients with chronic diseases (see Chapter 8), who were more likely to require some form of follow-up.

• Only 3.4% of all encounters were issued referrals. The referral rate was higher in the public sector compared to the private sector (5.8% versus 1.8%, respectively).

Table 12.1.1: Visit dispositions of primary care patients by sector in 2014

Visit disposition Unweighted

count Weighted

count Percent of encounters

(95% CI)

Overall

Follow-up 8,742 89,641 27.5 (24.4–30.8)

At least one referral 1,099 11,068 3.4 (2.8–4.0)


Public

Follow-up 7,224 64,737 49.2 (45.1–53.3)



Private

Follow-up 1,518 24,904 12.9 (10.7–15.1)



Chapter 12 : Follow-Ups and Referrals

12.2 TYPES OF REFERRALS

Referrals captured in NMCS 2014 included referrals within the primary care sphere (which included referrals to family medicine specialists, non-specialist doctors, assistant medical officers, maternal and child health services, quit smoking clinics and diabetes medical therapy adherence clinics), those to medical specialists other than family medicine specialists, allied health services, hospitals, and other services (which included social welfare services for the public sector and diagnostic imaging services for the private sector). Table 12.2.1 shows the distribution of referrals by type in primary care clinics in 2014.

• Out of the 11,068 patients who had at least one referral recorded, 38.2% were referred to medical specialists (1.3 per 100 encounters and 1.0 per 100 diagnoses).

• Referrals to hospitals accounted for 27.6% of all referrals (0.9 per 100 encounters and 0.7 per 100 diagnoses), followed by those within the primary care sphere at 17.2% (0.6 per 100 encounters and 0.4 per 100 diagnoses) and those to allied health services at 13.9% (0.5 per 100 encounters and 0.4 per 100 diagnoses).

Table 12.2.1: Types of referrals in primary care in 2014


count Weighted

count

Percent of total



(95% CI) (n = 325,818)


(n = 436,743)

Specialist 386 4,229 38.2 1.3 (0.9–1.7) 1.0 (0.7–1.2)

Hospital 278 3,052 27.6 0.9 (0.7–1.1) 0.7 (0.6–0.8)

Primary care 237 1,900 17.2 0.6 (0.3–0.9) 0.4 (0.2–0.6)


Other services 25 344 3.1 0.1 (0.0–0.2) 0.1 (0.0–0.1)

Total 1,099 11,068 100.0 3.4 (2.3–4.5) 2.5 (1.7–3.4)

Table 12.2.2 and Table 12.2.3 show the distribution of referrals by type in public and private clinics, respectively.

Public clinics • Referrals in public clinics were most often to medical specialists (34.0% of referrals in the public

sector), recorded at a rate of 2.0 specialist referrals per 100 encounters (1.3 referrals per 100 diagnoses).

• Referrals within primary care accounted for 22.4% of all referrals in public clinics, followed closely by referrals to hospitals at 21.6% and allied health services at 19.3%.

Private clinics • Nearly half (47.7%) of all referrals recorded in the private sector were for medical specialists, while

hospital referrals constituted most of the other half (41.1% of total referrals). • Referrals to another primary healthcare centre, the third most common type of referrals made in

private clinics, accounted for a smaller proportion of referrals in the private sector than in the public sector (5.2% versus 22.4%, respectively).


Table 12.2.2: Types of referrals in public clinics in 2014


count Weighted

count

Percent of total



(95% CI) (n = 131,624)


(n = 203,868)

Specialist 303 2,615 34.0 2.0 (1.3–2.7) 1.3 (0.8–1.7)

Primary care 228 1,724 22.4 1.3 (0.6–2.0) 0.8 (0.4–1.3)

Hospital 205 1,662 21.6 1.3 (0.9–1.6) 0.8 (0.6–1.0)


Other services 14 195 2.5 0.1 (0.0–0.3) 0.1 (0.0–0.2)

Total 919 7,681 100.0 5.8 (3.5–8.2) 3.8 (2.2–5.3)

Table 12.2.3: Types of referrals in private clinics in 2014


count Weighted

count

Percent of total



(95% CI) (n = 194,194)


(n = 232,874)

Specialist 83 1,614 47.7 0.8 (0.6–1.1) 0.7 (0.5–0.9)

Hospital 73 1,390 41.1 0.7 (0.5–1.0) 0.6 (0.4–0.8)

Primary care 9 176 5.2 0.1 (0.0–0.2) 0.1 (0.0–0.1)

Other services 11 149 4.4 0.1 (0.0–0.1) 0.1 (0.0–0.1)

Allied health services 4 57 1.7 0.0 (0.0–0.1) 0.0 (0.0–0.1)

Total 180 3,387 100.0 1.7 (1.1–2.4) 1.5 (0.9–2.0)

12.3 MOST FREQUENTLY FOLLOWED UP DIAGNOSES

In NMCS 2014, healthcare providers could link the scheduled follow-up appointments and the referrals reported to the diagnoses for which the appointments and referrals were made. Table 12.3.1 presents the top 10 diagnoses most frequently followed up in primary care in 2014. .

• The leading diagnosis for follow-up was hypertension (including hypertension in pregnancy), which accounted for more than one-quarter (28.5%) of all diagnoses with follow-up appointments in primary care.

• The second most frequently followed up diagnosis was diabetes, which represented 20.2% of all diagnoses accompanied with follow-up appointments, followed by lipid disorder at 18.5%.

Table 12.3.1: Top 10 diagnoses for follow-up in primary care in 2014


count

(n = 13,832)

Weighted count

(n = 137,991)

Percent of diagnoses with

follow-up

(n = 137,991)


(95% CI) (n = 325,818)



1 Hypertension - all 4,132 39,319 28.5 12.1 (10.0–14.2) 70.0 (64.3–75.7)

Hypertension - cardiovascular

4,110 39,128 28.4 12.0 (9.9–14.2) 70.0 (64.3–75.7)

Hypertension in pregnancy

22 192 0.1 0.1 (0.0–0.1) 62.8 (42.7–83.0)

2 Diabetes - all 2,842 27,869 20.2 8.6 (6.6–10.6) 76.2 (70.3–82.1)

Diabetes - non-gestational

2,744 27,054 19.6 8.3 (6.4–10.3) 76.4 (70.3–82.4)

Gestational diabetes

98 816 0.6 0.3 (0.2–0.4) 70.8 (56.9–84.8)

3 Lipid disorder 2,656 25,589 18.5 7.9 (6.0–9.7) 73.8 (67.9–79.8)

4 Medical examination - pregnancy

537 4,752 3.4 1.5 (1.0–1.9) 50.3 (40.9–59.6)

5 Asthma 291 3,553 2.6 1.1 (0.7–1.5) 38.2 (29.5–46.8)

6 Upper respiratory tract infection

242 2,464 1.8 0.8 (0.6–1.0) 3.4 (2.5–4.3)

7 Medical examination 175 1,660 1.2 0.5 (0.3–0.8) 22.1 (13.0–31.3)

8 Fever 106 1,406 1.0 0.4 (0.3–0.6) 12.5 (8.5–16.6)

9 Ischaemic heart disease

153 1,291 0.9 0.4 (0.3–0.5) 59.8 (50.0–69.7)

10 Substance abuse 90 1,161 0.8 0.4 (0.0–0.7) 78.1 (57.8–98.4)

12.4 MOST FREQUENTLY REFERRED DIAGNOSES

As mentioned in the previous section, the referrals were linked to the corresponding diagnoses in NMCS 2014. Table 12.4.1 presents the top 10 diagnoses most frequently referred in primary care in 2014.

• Diabetes and hypertension were the two diagnoses for which referrals were most frequently made, accounting for 11.9% and 10.2% of all diagnoses referred, respectively.

• The third most commonly referred diagnosis was lipid disorder, representing 5.3% of all diagnoses for which referrals were made.

117

Table 12.2.2: Types of referrals in public clinics in 2014


count Weighted

count

Percent of total



(95% CI) (n = 131,624)


(n = 203,868)

Specialist 303 2,615 34.0 2.0 (1.3–2.7) 1.3 (0.8–1.7)

Primary care 228 1,724 22.4 1.3 (0.6–2.0) 0.8 (0.4–1.3)

Hospital 205 1,662 21.6 1.3 (0.9–1.6) 0.8 (0.6–1.0)


Other services 14 195 2.5 0.1 (0.0–0.3) 0.1 (0.0–0.2)

Total 919 7,681 100.0 5.8 (3.5–8.2) 3.8 (2.2–5.3)

Table 12.2.3: Types of referrals in private clinics in 2014


count Weighted

count

Percent of total



(95% CI) (n = 194,194)


(n = 232,874)

Specialist 83 1,614 47.7 0.8 (0.6–1.1) 0.7 (0.5–0.9)

Hospital 73 1,390 41.1 0.7 (0.5–1.0) 0.6 (0.4–0.8)

Primary care 9 176 5.2 0.1 (0.0–0.2) 0.1 (0.0–0.1)

Other services 11 149 4.4 0.1 (0.0–0.1) 0.1 (0.0–0.1)

Allied health services 4 57 1.7 0.0 (0.0–0.1) 0.0 (0.0–0.1)

Total 180 3,387 100.0 1.7 (1.1–2.4) 1.5 (0.9–2.0)

12.3 MOST FREQUENTLY FOLLOWED UP DIAGNOSES

In NMCS 2014, healthcare providers could link the scheduled follow-up appointments and the referrals reported to the diagnoses for which the appointments and referrals were made. Table 12.3.1 presents the top 10 diagnoses most frequently followed up in primary care in 2014. .

• The leading diagnosis for follow-up was hypertension (including hypertension in pregnancy), which accounted for more than one-quarter (28.5%) of all diagnoses with follow-up appointments in primary care.

• The second most frequently followed up diagnosis was diabetes, which represented 20.2% of all diagnoses accompanied with follow-up appointments, followed by lipid disorder at 18.5%.

Chapter 12 : Follow-Ups and Referrals

Table 12.3.1: Top 10 diagnoses for follow-up in primary care in 2014


count

(n = 13,832)

Weighted count

(n = 137,991)


follow-up

(n = 137,991)


(95% CI) (n = 325,818)



1 Hypertension - all 4,132 39,319 28.5 12.1 (10.0–14.2) 70.0 (64.3–75.7)

Hypertension - cardiovascular

4,110 39,128 28.4 12.0 (9.9–14.2) 70.0 (64.3–75.7)

Hypertension in pregnancy

22 192 0.1 0.1 (0.0–0.1) 62.8 (42.7–83.0)

2 Diabetes - all 2,842 27,869 20.2 8.6 (6.6–10.6) 76.2 (70.3–82.1)

Diabetes - non-gestational

2,744 27,054 19.6 8.3 (6.4–10.3) 76.4 (70.3–82.4)

Gestational diabetes

98 816 0.6 0.3 (0.2–0.4) 70.8 (56.9–84.8)

3 Lipid disorder 2,656 25,589 18.5 7.9 (6.0–9.7) 73.8 (67.9–79.8)

4 Medical examination - pregnancy

537 4,752 3.4 1.5 (1.0–1.9) 50.3 (40.9–59.6)

5 Asthma 291 3,553 2.6 1.1 (0.7–1.5) 38.2 (29.5–46.8)

6 Upper respiratory tract infection

242 2,464 1.8 0.8 (0.6–1.0) 3.4 (2.5–4.3)

7 Medical examination 175 1,660 1.2 0.5 (0.3–0.8) 22.1 (13.0–31.3)

8 Fever 106 1,406 1.0 0.4 (0.3–0.6) 12.5 (8.5–16.6)

9 Ischaemic heart disease

153 1,291 0.9 0.4 (0.3–0.5) 59.8 (50.0–69.7)

10 Substance abuse 90 1,161 0.8 0.4 (0.0–0.7) 78.1 (57.8–98.4)

12.4 MOST FREQUENTLY REFERRED DIAGNOSES

As mentioned in the previous section, the referrals were linked to the corresponding diagnoses in NMCS 2014. Table 12.4.1 presents the top 10 diagnoses most frequently referred in primary care in 2014.

• Diabetes and hypertension were the two diagnoses for which referrals were most frequently made, accounting for 11.9% and 10.2% of all diagnoses referred, respectively.

• The third most commonly referred diagnosis was lipid disorder, representing 5.3% of all diagnoses for which referrals were made.


Table 12.4.1: Top 10 diagnoses for referral in primary care in 2014


count

(n = 1,186)

Weighted count

(n = 12,075)


referral

(n = 12,075)


(95% CI) (n = 325,818)

Rate per 100 contacts with each

diagnosis (95% CI)

1 Diabetes - all 155 1,432 11.9 0.4 (0.3–0.6) 3.9 (2.6–5.3)

Diabetes –

Non-gestational 122 1,200 9.9 0.4 (0.2–0.5) 3.4 (2.2–4.6)


2 Hypertension - all 128 1,226 10.2 0.4 (0.2–0.6) 2.2 (1.1–3.2)

Hypertension - cardiovascular 120 1,180 10.1 0.4 (0.2–0.6) 2.1 (1.1–3.2)

3 Lipid disorder 58 645 5.3 0.2 (0.1–0.3) 1.9 (1.0–2.8)

4 Medical examination - pregnancy 34 359 2.9 0.1 (0.1–0.2) 3.8 (2.0–5.6)

5 Musculoskeletal symptom/complaints 30 333 2.7 0.1 (0.1–0.1) 2.5 (1.5–3.4)

6 High risk pregnancy 41 321 2.6 0.1 (0.0–0.2) 16.9 (6.6–27.1)

7 Fever 20 319 2.6 0.1 (0.0–0.2) 2.8 (0.9–4.8)


9 Viral disease 17 217 1.8 0.1 (0.0–0.1) 14.3 (5.6–23.1)

10 Injury eye 4 209 1.7 0.1 (0.0–0.2) 72.1 (32.3–100.0)

Table 12.4.1: Top 10 diagnoses for referral in primary care in 2014


count

(n = 1,186)

Weighted count

(n = 12,075)


referral

(n = 12,075)


(95% CI) (n = 325,818)

Rate per 100 contacts with each

diagnosis (95% CI)

1 Diabetes - all 155 1,432 11.9 0.4 (0.3–0.6) 3.9 (2.6–5.3)

Diabetes –

Non-gestational 122 1,200 9.9 0.4 (0.2–0.5) 3.4 (2.2–4.6)


2 Hypertension - all 128 1,226 10.2 0.4 (0.2–0.6) 2.2 (1.1–3.2)

Hypertension - cardiovascular 120 1,180 10.1 0.4 (0.2–0.6) 2.1 (1.1–3.2)

3 Lipid disorder 58 645 5.3 0.2 (0.1–0.3) 1.9 (1.0–2.8)

4 Medical examination - pregnancy 34 359 2.9 0.1 (0.1–0.2) 3.8 (2.0–5.6)

5 Musculoskeletal symptom/complaints 30 333 2.7 0.1 (0.1–0.1) 2.5 (1.5–3.4)

6 High risk pregnancy 41 321 2.6 0.1 (0.0–0.2) 16.9 (6.6–27.1)

7 Fever 20 319 2.6 0.1 (0.0–0.2) 2.8 (0.9–4.8)


9 Viral disease 17 217 1.8 0.1 (0.0–0.1) 14.3 (5.6–23.1)

10 Injury eye 4 209 1.7 0.1 (0.0–0.2) 72.1 (32.3–100.0)

APPENDICES


APPENDIX 1: ADDITIONAL TABLES

Table A1.1: Top 10 reasons for encounter in public clinics in 2014

Rank Reasons for encounter Unweighted count

Weighted count


(n = 252,050)


(95% CI) (n = 131,624)


Hypertension -cardiovascular* 4,737 41,236 16.4 31.3 (28.2–34.5)

2 Diabetes - all* 3,204 29,625 11.8 22.5 (19.3–25.7)

Diabetes type2 2,651 24,537 9.7 18.6 (15.4–21.9)


3 Lipid disorder 2,883 24,391 9.7 18.5 (15.8–21.3)

4 Cough 2,900 23,469 9.3 17.8 (16.3–19.4)

5 Fever 2,568 21,339 8.5 16.2 (14.5–17.9)

6 Runny nose/rhinorrhoea 2,023 15,785 6.3 12.0 (10.7–13.3)

7 Medical examination - pregnancy* 1,413 12,180 4.8 9.3 (6.9–11.6)



10 Blood test endo/metabolic 530 5,141 2.0 3.9 (2.5–5.3)


Table A1.2: Top 10 reasons for encounter in private clinics 2014

Rank Reasons for encounter

Unweighted count

Weighted count


(n = 345,513)


(95% CI) (n = 194,194)

1 Fever 3,503 54,903 15.9 28.3 (26.6–29.9)

2 Cough 3,122 51,437 14.9 26.5 (24.9–28.1)



5 Abdominal pain* 723 12,466 3.6 6.4 (5.7–7.2)


7 Pain/sore throat* 707 12,033 3.5 6.2 (4.9–7.5)

8 Diarrhoea 743 11,999 3.5 6.2 (5.6–6.8)

9 Headache - all* 646 11,948 3.5 6.2 (5.4–6.9)

Headache 612 11,120 3.2 5.7 (5.0–6.4)

10 Back problems* 491 8,668 2.5 4.5 (3.8–5.1)


APPENDIX 2: NMCS 2014 PRIMARY CARE PROVIDER’S PROFILE QUESTIONNAIRE

121

APPENDIX 1: ADDITIONAL TABLES

Table A1.1: Top 10 reasons for encounter in public clinics in 2014

Rank Reasons for encounter Unweighted count

Weighted count


(n = 252,050)


(95% CI) (n = 131,624)


Hypertension -cardiovascular* 4,737 41,236 16.4 31.3 (28.2–34.5)

2 Diabetes - all* 3,204 29,625 11.8 22.5 (19.3–25.7)

Diabetes type2 2,651 24,537 9.7 18.6 (15.4–21.9)


3 Lipid disorder 2,883 24,391 9.7 18.5 (15.8–21.3)

4 Cough 2,900 23,469 9.3 17.8 (16.3–19.4)

5 Fever 2,568 21,339 8.5 16.2 (14.5–17.9)


7 Medical examination - pregnancy* 1,413 12,180 4.8 9.3 (6.9–11.6)



10 Blood test endo/metabolic 530 5,141 2.0 3.9 (2.5–5.3)


Table A1.2: Top 10 reasons for encounter in private clinics 2014

Rank Reasons for encounter

Unweighted count

Weighted count


(n = 345,513)


(95% CI) (n = 194,194)

1 Fever 3,503 54,903 15.9 28.3 (26.6–29.9)

2 Cough 3,122 51,437 14.9 26.5 (24.9–28.1)



5 Abdominal pain* 723 12,466 3.6 6.4 (5.7–7.2)


7 Pain/sore throat* 707 12,033 3.5 6.2 (4.9–7.5)

8 Diarrhoea 743 11,999 3.5 6.2 (5.6–6.8)

9 Headache - all* 646 11,948 3.5 6.2 (5.4–6.9)

Headache 612 11,120 3.2 5.7 (5.0–6.4)

10 Back problems* 491 8,668 2.5 4.5 (3.8–5.1)


Appendices

APPENDIX 2: NMCS 2014 PRIMARY CARE PROVIDER’S PROFILE QUESTIONNAIRE


APPENDIX 3: NMCS 2014 SURVEY FORM

APPENDIX 4: ICPC-2 AND ICPC-2 PLUS GROUPS

Reasons for Encounter and Diagnoses

Group ICPC-2 ICPC-2 PLUS

Description

Abdominal pain D01 Abdominal pain/cramps, general

D02 Abdominal pain, epigastric

D06 Abdominal pain, localised, other

Arthritis – all L88 Rheumatoid/seropositive arthritis

L89 Osteoarthrosis of hip

L90 Osteoarthrosis of knee

L91 Osteoarthrosis, other

Anaemia B78 Hereditary haemolytic anaemia

B80 Iron deficiency anaemia

B82 Anaemia other/unspecified

Back problems L02 Back symptom/complaint

L03 Low back symptom/complaint

L84 Back syndrome without radiating pain

L86 Back syndrome with radiating pain

Conjunctivitis F70 Conjunctivitis, infectious

F71 Conjunctivitis, allergic

Contraception – female W11 Contraception, oral

W12 Contraception, intrauterine

W14 Contraception female, other

Dermatitis S86 Dermatitis, seborrhoeic

S87 Dermatitis, atopic eczema

S88 Dermatitis, contact/allergic

Diabetes – non-gestational T89 Diabetes, insulin dependent

T90 Diabetes, non-insulin dependent

N94012 Neuropathy; diabetic

U88011 Nephropathy; diabetic

Dressing/pressure/ compress/tamponade

A56001 Dressing

L56003 Bandage/strap

S56004 Dressing; wound

Gastroenteritis D70 Gastrointestinal infection

D73 Gastroenteritis, presumed infection

Headache – all N01 Headache

N89 Migraine

N90 Cluster headache

N95 Tension headache

123

APPENDIX 3: NMCS 2014 SURVEY FORM

Appendices

APPENDIX 4: ICPC-2 AND ICPC-2 PLUS GROUPS

Reasons for Encounter and Diagnoses


Description

Abdominal pain D01 Abdominal pain/cramps, general

D02 Abdominal pain, epigastric

D06 Abdominal pain, localised, other

Arthritis – all L88 Rheumatoid/seropositive arthritis

L89 Osteoarthrosis of hip

L90 Osteoarthrosis of knee

L91 Osteoarthrosis, other

Anaemia B78 Hereditary haemolytic anaemia

B80 Iron deficiency anaemia

B82 Anaemia other/unspecified

Back problems L02 Back symptom/complaint

L03 Low back symptom/complaint

L84 Back syndrome without radiating pain

L86 Back syndrome with radiating pain

Conjunctivitis F70 Conjunctivitis, infectious

F71 Conjunctivitis, allergic

Contraception – female W11 Contraception, oral



Dermatitis S86 Dermatitis, seborrhoeic

S87 Dermatitis, atopic eczema

S88 Dermatitis, contact/allergic

Diabetes – non-gestational T89 Diabetes, insulin dependent

T90 Diabetes, non-insulin dependent

N94012 Neuropathy; diabetic

U88011 Nephropathy; diabetic

Dressing/pressure/ compress/tamponade

A56001 Dressing

L56003 Bandage/strap

S56004 Dressing; wound

Gastroenteritis D70 Gastrointestinal infection

D73 Gastroenteritis, presumed infection

Headache – all N01 Headache

N89 Migraine

N90 Cluster headache

N95 Tension headache


Reasons for Encounter and Diagnoses (continued)


Description

High risk pregnancy W81008 Proteinuria in pregnancy

W84014 RH; iso-immunisation

W84020 Anaemia in pregnancy

Hypertension – all K86 Hypertension, uncomplicated

K87 Hypertension, complicated

W81003 Hypertension in pregnancy

Hypertension – cardiovascular

K86 Hypertension, uncomplicated


Injury skin – all S14 Burn/scald

S17 Abrasion/scratch/blister

S18 Laceration/cut

S19 Skin injury, other

Ischaemic heart disease K74 Ischaemic heart disease with angina

K75 Acute myocardial infarction

K76 Ischaemic heart disease without angina

Medical examination A30 Medical examination/health evaluation complete

A31 Medical examination/health evaluation partial

D31 Medical examination/health evaluation partial digestive

P31 Medical examination/health evaluation partial psychological

R31 Medical examination/health evaluation partial respiratory

S31 Medical examination/health evaluation partial skin

A98001 Health maintenance

Medical examination – pregnancy

W30 Medical examination/health evaluation complete pregnancy

W41 Diagnostic radiology/imaging pregnancy

W31010 Antenatal care

Menstrual problems X02 Menstrual pain

X03 Intermenstrual pain

X05 Menstruation absent/scanty

X06 Menstruation excessive

X07 Menstruation irregular/frequent

X08 Intermenstrual bleeding

X10 Postponement of menstruation

X89 Premenstrual tension syndrome



Description

Musculoskeletal symptom/complaints

L01 Neck symptom/complaint

L04 Chest symptom/complaint

L05 Flank/axilla symptom/complaint

L07 Jaw symptom/complaint

L08 Shoulder symptom/complaint

L09 Arm symptom/complaint

L10 Elbow symptom/complaint

L11 Wrist symptom/complaint

L12 Hand/finger symptom/complaint

L13 Hip symptom/complaint

L14 Leg/thigh symptom/complaint

L15 Knee symptom/complaint

L16 Ankle symptom/complaint

L17 Foot/toe symptom/complaint

L18 Muscle pain

L19 Muscle symptom/complaint NOS

L20 Joint symptom/complaint NOS

L28 Limited function/disability (limb)

L29 Musculoskeletal symptom/complaint other

S19004 Injury; soft tissue

Osteoarthritis L84004 Osteoarthritis; spine

L89001 Osteoarthritis; hip

L90001 Osteoarthritis; knee

L91003 Osteoarthritis

L91015 Osteoarthritis; wrist

L92007 Osteoarthritis; shoulder

Pain/sore throat R21004 Pain; throat

R21005 Sore throat

Rash S06 Rash localised

S07 Rash generalised

S89 Diaper rash

S92004 Rash; heat

S92006 Prickly heat

S92008 Rash; sweat

Respiratory infection R81 Pneumonia

R82 Pleurisy/pleural effusion

R83 Respiratory infection, other

125



Description

High risk pregnancy W81008 Proteinuria in pregnancy

W84014 RH; iso-immunisation

W84020 Anaemia in pregnancy

Hypertension – all K86 Hypertension, uncomplicated


W81003 Hypertension in pregnancy

Hypertension – cardiovascular

K86 Hypertension, uncomplicated


Injury skin – all S14 Burn/scald

S17 Abrasion/scratch/blister

S18 Laceration/cut


Ischaemic heart disease K74 Ischaemic heart disease with angina

K75 Acute myocardial infarction

K76 Ischaemic heart disease without angina

Medical examination A30 Medical examination/health evaluation complete


D31 Medical examination/health evaluation partial digestive

P31 Medical examination/health evaluation partial psychological

R31 Medical examination/health evaluation partial respiratory

S31 Medical examination/health evaluation partial skin

A98001 Health maintenance

Medical examination – pregnancy

W30 Medical examination/health evaluation complete pregnancy

W41 Diagnostic radiology/imaging pregnancy

W31010 Antenatal care

Menstrual problems X02 Menstrual pain

X03 Intermenstrual pain

X05 Menstruation absent/scanty

X06 Menstruation excessive

X07 Menstruation irregular/frequent

X08 Intermenstrual bleeding

X10 Postponement of menstruation

X89 Premenstrual tension syndrome

Appendices



Description

Musculoskeletal symptom/complaints

L01 Neck symptom/complaint

L04 Chest symptom/complaint

L05 Flank/axilla symptom/complaint

L07 Jaw symptom/complaint

L08 Shoulder symptom/complaint

L09 Arm symptom/complaint

L10 Elbow symptom/complaint

L11 Wrist symptom/complaint

L12 Hand/finger symptom/complaint

L13 Hip symptom/complaint

L14 Leg/thigh symptom/complaint

L15 Knee symptom/complaint

L16 Ankle symptom/complaint

L17 Foot/toe symptom/complaint

L18 Muscle pain

L19 Muscle symptom/complaint NOS

L20 Joint symptom/complaint NOS

L28 Limited function/disability (limb)

L29 Musculoskeletal symptom/complaint other

S19004 Injury; soft tissue

Osteoarthritis L84004 Osteoarthritis; spine

L89001 Osteoarthritis; hip

L90001 Osteoarthritis; knee

L91003 Osteoarthritis

L91015 Osteoarthritis; wrist

L92007 Osteoarthritis; shoulder

Pain/sore throat R21004 Pain; throat

R21005 Sore throat

Rash S06 Rash localised

S07 Rash generalised

S89 Diaper rash

S92004 Rash; heat

S92006 Prickly heat

S92008 Rash; sweat

Respiratory infection R81 Pneumonia

R82 Pleurisy/pleural effusion

R83 Respiratory infection, other




Description

Sprain/strain L77 Sprain/strain of ankle

L78 Sprain/strain of knee

L79 Sprain/strain of joint NOS

L83 Neck syndrome

Symptom/complaint eye F01 Eye pain

F02 Red eye

F03 Eye discharge

F04 Visual floaters/spots

F13 Eye sensation abnormal

F15 Eye appearance abnormal

F16 Eyelid symptom/complaint

F29 Eye symptom/complaint, other

Urinary problem U01 Dysuria/painful urination

U02 Urinary frequency/urgency

U04 Incontinence urine

U05 Urinary problems, other

U06 Haematuria

U07 Urine symptom/complaint, other

U08 Urinary retention

U13 Bladder symptom/complaint, other

Urinary tract infection U70 Pyelonephritis/pyelitis

U71 Cystitis/urinary infection, other

Note: NOS – Not otherwise specified.

Investigations, Advice/Counselling and Procedures


Description

Administrative procedure A62 Administrative procedure

A63 Follow-up encounter; unspecified

F62 Administrative procedure; eye

K62 Administrative procedure; cardiovascular

R62 Administrative procedure; respiratory

S62 Administrative procedure; skin

T62 Administrative procedure; endo/metabolic

U62 Administrative procedure; urinary

W62 Administrative procedure; pregnancy

Y62 Administrative procedure; genital (male)

Z11 Compliance/being ill problem

Advice/counselling; health/body

A45005 Advice/education; health

A45009 Health promotion

A45026 Advice/education; hygiene

D45004 Advice/education; oral health

L45 Observe/health education/advice/diet musculoskeletal

S45005 Advice/education; sun protection

Advice/counselling; medication

A45015 Advice/education; medication

A48 Clarification/discussion on RFE/demand

Advice/counselling; NEC A45 Observe/health education/advice/diet

B45 Observe/health education/advice/diet; blood

D45 Observe/health education/advice/diet; digestive

F45 Observe/health education/advice/diet; eye

H45 Observe/health education/advice/diet; ear

K45 Observe/health education/advice/diet; cardiovascular

L45002 Advice/education; musculoskeletal

N45 Observe/health education/advice/diet; neurological

P45001 Advice/education; psychological

R45 Observe/health education/advice/diet; respiratory

S45 Observe/health education/advice/diet; skin

T45 Observe/health education/advice/diet; endocrine/metabolic

U45 Observe/health education/advice/diet; urology

127



Description

Sprain/strain L77 Sprain/strain of ankle

L78 Sprain/strain of knee

L79 Sprain/strain of joint NOS

L83 Neck syndrome

Symptom/complaint eye F01 Eye pain

F02 Red eye

F03 Eye discharge

F04 Visual floaters/spots

F13 Eye sensation abnormal

F15 Eye appearance abnormal

F16 Eyelid symptom/complaint

F29 Eye symptom/complaint, other

Urinary problem U01 Dysuria/painful urination

U02 Urinary frequency/urgency

U04 Incontinence urine

U05 Urinary problems, other

U06 Haematuria

U07 Urine symptom/complaint, other

U08 Urinary retention

U13 Bladder symptom/complaint, other

Urinary tract infection U70 Pyelonephritis/pyelitis

U71 Cystitis/urinary infection, other

Note: NOS – Not otherwise specified.

Appendices

Investigations, Advice/Counselling and Procedures


Description

Administrative procedure A62 Administrative procedure

A63 Follow-up encounter; unspecified

F62 Administrative procedure; eye

K62 Administrative procedure; cardiovascular

R62 Administrative procedure; respiratory

S62 Administrative procedure; skin

T62 Administrative procedure; endo/metabolic

U62 Administrative procedure; urinary

W62 Administrative procedure; pregnancy

Y62 Administrative procedure; genital (male)

Z11 Compliance/being ill problem

Advice/counselling; health/body

A45005 Advice/education; health

A45009 Health promotion

A45026 Advice/education; hygiene

D45004 Advice/education; oral health

L45 Observe/health education/advice/diet musculoskeletal

S45005 Advice/education; sun protection

Advice/counselling; medication

A45015 Advice/education; medication

A48 Clarification/discussion on RFE/demand

Advice/counselling; NEC A45 Observe/health education/advice/diet

B45 Observe/health education/advice/diet; blood

D45 Observe/health education/advice/diet; digestive

F45 Observe/health education/advice/diet; eye

H45 Observe/health education/advice/diet; ear

K45 Observe/health education/advice/diet; cardiovascular

L45002 Advice/education; musculoskeletal

N45 Observe/health education/advice/diet; neurological

P45001 Advice/education; psychological

R45 Observe/health education/advice/diet; respiratory

S45 Observe/health education/advice/diet; skin


U45 Observe/health education/advice/diet; urology


Investigations, Advice/Counselling and Procedures (continued)


Description

Advice/counselling; NEC (continued)

W45 Observe/health education/advice/diet; reproductive (female)

X45 Observe/health education/advice/diet; genital (female)

Y45 Observe/health education/advice/diet; genital (male)

L58001 Counselling; problem; musculoskeletal

Advice/counselling; nutrition/weight

A45006 Advice/education; diet

T45005 Advice/education; nutritional

T45007 Advice/education; weight management

T45010 Weight management

T58 Counselling; weight management

Advice/counselling; other A45014 Advice/education; travel

A45022 Advice; care of sick 3rd person

A45036 Advice/education; sex

A45037 Advice/education; work practice

A58016 Consult; family member

Z45 Observe/health education/advice/diet; social

Z58 Therapeutic counselling/listening; social

Advice/counselling; pregnancy

W42 Electrical tracing; pregnancy

W45009 Advice/education; pregnancy

W45010 Advice/education; breastfeeding

Advice/counselling; prevention

A45025 Advice/education; immunisation

A58 Therapeutic counselling/listening

X45004 Advice/education; breast self-exam

X45007 Advice/education; Pap smear

Z45005 Advice/education; environment

Advice/counselling; relaxation

P45007 Advice/education; relaxation

P58 Therapeutic counselling/listening; psychological

Advice/counselling; treatment

A45016 Advice/education; treatment

A45020 Advice/education; rest/fluids

A45035 Advice/education; isolate

A45039 Advice/education; fluid intake

L45004 Advice/education; RICE

P45 Observe/health education/advice/diet; psychological




Description

Blood pressure K31001 Check-up; blood pressure

K39 Physical function test; cardiovascular

Blood; other test A33042 Lymphocyte type & count test

A34035 Blood film test

A34036 Thick blood film test

B33 Microbiological/immunological test; blood/lymph

B34 Blood test; blood/lymph

Chemistry; other test A33 Microbiological/immunological test

A34 Blood test

A35 Urine test

T34 Blood test; endocrine/metabolic

D34002 Alanine aminotransferase test

Contraception procedure W11 Contraception, oral



Dressing/pressure/ compression/tamponade

A56 Dressing/pressure/compress/tamponade

F56 Dressing/pressure/compress/tamponade; eye

S56 Dressing/pressure/compress/tamponade; skin

W56 Dressing/pressure/compress/tamponade; pregnancy

Electrolytes, urea & creatinine

A34008 Test; electrolytes

A34014 Test; potassium

U34 Blood test; urinary

U38 Other laboratory test NEC; urinary

Excision/removal tissue/biopsy/ destruction/ debridement/ cauterisation

A52 Excise/remove/biopsy/destruct/debridement/ cauterise

F52 Excise/remove/biopsy/destruct/debridement/ cauterise; eye

H52 Excise/remove/biopsy/destruct/debridement/ cauterise; ear

L52 Excise/remove/biopsy/destruct/debridement/ cauterise; musculoskeletal

R52 Excise/remove/biopsy/destruct/debridement/ cauterise; respiratory


S52 Excise/remove/biopsy/destruct/debridement/ cauterise; skin

X52 Excise/remove/biopsy/destruct/debridement/ cauterise; genital (female)

Y52 Excise/remove/biopsy/destruct/debridement/ cauterise; genital (male)

129



Description

Advice/counselling; NEC (continued)

W45 Observe/health education/advice/diet; reproductive (female)

X45 Observe/health education/advice/diet; genital (female)

Y45 Observe/health education/advice/diet; genital (male)

L58001 Counselling; problem; musculoskeletal

Advice/counselling; nutrition/weight

A45006 Advice/education; diet

T45005 Advice/education; nutritional

T45007 Advice/education; weight management

T45010 Weight management

T58 Counselling; weight management

Advice/counselling; other A45014 Advice/education; travel

A45022 Advice; care of sick 3rd person

A45036 Advice/education; sex

A45037 Advice/education; work practice

A58016 Consult; family member

Z45 Observe/health education/advice/diet; social

Z58 Therapeutic counselling/listening; social

Advice/counselling; pregnancy

W42 Electrical tracing; pregnancy

W45009 Advice/education; pregnancy

W45010 Advice/education; breastfeeding

Advice/counselling; prevention

A45025 Advice/education; immunisation

A58 Therapeutic counselling/listening

X45004 Advice/education; breast self-exam

X45007 Advice/education; Pap smear

Z45005 Advice/education; environment

Advice/counselling; relaxation

P45007 Advice/education; relaxation

P58 Therapeutic counselling/listening; psychological

Advice/counselling; treatment

A45016 Advice/education; treatment

A45020 Advice/education; rest/fluids

A45035 Advice/education; isolate

A45039 Advice/education; fluid intake

L45004 Advice/education; RICE

P45 Observe/health education/advice/diet; psychological


Appendices



Description

Blood pressure K31001 Check-up; blood pressure

K39 Physical function test; cardiovascular

Blood; other test A33042 Lymphocyte type & count test

A34035 Blood film test

A34036 Thick blood film test

B33 Microbiological/immunological test; blood/lymph

B34 Blood test; blood/lymph

Chemistry; other test A33 Microbiological/immunological test

A34 Blood test

A35 Urine test

T34 Blood test; endocrine/metabolic

D34002 Alanine aminotransferase test

Contraception procedure W11 Contraception, oral



Dressing/pressure/ compression/tamponade

A56 Dressing/pressure/compress/tamponade

F56 Dressing/pressure/compress/tamponade; eye

S56 Dressing/pressure/compress/tamponade; skin

W56 Dressing/pressure/compress/tamponade; pregnancy

Electrolytes, urea & creatinine

A34008 Test; electrolytes

A34014 Test; potassium

U34 Blood test; urinary

U38 Other laboratory test NEC; urinary

Excision/removal tissue/biopsy/ destruction/ debridement/ cauterisation

A52 Excise/remove/biopsy/destruct/debridement/ cauterise

F52 Excise/remove/biopsy/destruct/debridement/ cauterise; eye

H52 Excise/remove/biopsy/destruct/debridement/ cauterise; ear

L52 Excise/remove/biopsy/destruct/debridement/ cauterise; musculoskeletal

R52 Excise/remove/biopsy/destruct/debridement/ cauterise; respiratory


S52 Excise/remove/biopsy/destruct/debridement/ cauterise; skin

X52 Excise/remove/biopsy/destruct/debridement/ cauterise; genital (female)

Y52 Excise/remove/biopsy/destruct/debridement/ cauterise; genital (male)




Description

Family planning W45006 Advice/education; preconceptual

W45007 Advice/education; contraception (female)

W58013 Counselling; family planning (female)

Y45006 Advice/education; family plan (male)

Immunisation A44 Preventive immunisations/medications

A55004 Inject; childhood immunisation

A55005 Inject; immunisation

D44 Preventive immunisations/medications; digestive

N44 Preventive immunisations/medications; neurological

R44 Preventive immunisations/medications; respiratory

R55 Local injection/infiltration; respiratory

Incision/drainage/ flushing/aspiration/ removal body fluid

A51 Incision & drainage/flush/aspiration

F51 Incision & drainage/flush/aspiration; eye

H51 Incision & drainage/flush/aspiration; ear

S51 Incision & drainage/flush/aspiration; skin

Injection/infiltration A50 Medication/prescription/renewal/inject

A55 Local injection/infiltration

B50 Medication/prescription/renewal/inject; blood

D50 Medication/prescription/renewal/inject; digestive

F50 Medication/prescription/renewal/inject; eye

H50 Medication/prescription/renewal/inject; ear

K50 Medication/prescription/renewal/inject; cardiovascular

K55 Local injection/infiltration; cardiovascular

L50 Medication/prescription/renewal/inject; musculoskeletal

L55 Local injection/infiltration; musculoskeletal

N50 Medication/prescription/renewal/inject; neurological

N55 Local injection/infiltration; neurological

P50 Medication/prescription/renewal/inject; psychological

R50 Medication/prescription/renewal/inject; respiratory

S50 Medication/prescription/renewal/inject; skin

T50 Medication/prescription/renewal/inject; endocrine/metabolic



Description

Injection/infiltration (continued)

U50 Medication/prescription/renewal/inject; urinary

W50 Medication/prescription/renewal/inject; pregnancy

Y50 Medication/prescription/renewal/inject; genital (male)

Liver function test D34 Blood test; digestive

A34004 Albumin test

Medical examination complete/partial

A30 Medical examination/health evaluation complete


D31 Medical examination/health evaluation partial; digestive

F30 Medical examination/health evaluation complete; eye

F31 Medical examination/health evaluation partial; eye

K31 Medical examination/health evaluation partial; cardiovascular

W30 Medical examination/health evaluation complete; pregnancy

W31 Medical examination/health evaluation partial; pregnancy

X31 Medical examination/health evaluation partial; genital (female)

Observe/wait T45001 Observe/wait; endocrine/metabolic

W45003 Observe/wait; reproductive

Other diagnostic procedure; NEC

A43001 Diagnostic procedures

F43001 Diagnostic procedure; eye

W43002 Diagnostic procedure; reproductive system

X43001 Diagnostic procedure; genital system

H43001 Diagnostic procedure; ear

Other therapeutic medication/ procedures/minor surgery

A50010 Medication; given

A53 Instrument/catheter/intubate/dilate

A59 Other therapeutic procedures/minor surgery; NEC

B59 Other therapeutic procedures/minor surgery NEC; blood

D50007 Treatment; worms

D53 Instrument/catheter/intubate/dilate; digestive

F59 Other therapeutic procedures/minor surgery; eye

131



Description

Family planning W45006 Advice/education; preconceptual

W45007 Advice/education; contraception (female)

W58013 Counselling; family planning (female)

Y45006 Advice/education; family plan (male)

Immunisation A44 Preventive immunisations/medications

A55004 Inject; childhood immunisation

A55005 Inject; immunisation

D44 Preventive immunisations/medications; digestive

N44 Preventive immunisations/medications; neurological

R44 Preventive immunisations/medications; respiratory

R55 Local injection/infiltration; respiratory

Incision/drainage/ flushing/aspiration/ removal body fluid

A51 Incision & drainage/flush/aspiration

F51 Incision & drainage/flush/aspiration; eye

H51 Incision & drainage/flush/aspiration; ear

S51 Incision & drainage/flush/aspiration; skin

Injection/infiltration A50 Medication/prescription/renewal/inject

A55 Local injection/infiltration

B50 Medication/prescription/renewal/inject; blood

D50 Medication/prescription/renewal/inject; digestive

F50 Medication/prescription/renewal/inject; eye

H50 Medication/prescription/renewal/inject; ear

K50 Medication/prescription/renewal/inject; cardiovascular

K55 Local injection/infiltration; cardiovascular

L50 Medication/prescription/renewal/inject; musculoskeletal

L55 Local injection/infiltration; musculoskeletal

N50 Medication/prescription/renewal/inject; neurological

N55 Local injection/infiltration; neurological

P50 Medication/prescription/renewal/inject; psychological

R50 Medication/prescription/renewal/inject; respiratory

S50 Medication/prescription/renewal/inject; skin

T50 Medication/prescription/renewal/inject; endocrine/metabolic

Appendices



Description

Injection/infiltration (continued)

U50 Medication/prescription/renewal/inject; urinary

W50 Medication/prescription/renewal/inject; pregnancy

Y50 Medication/prescription/renewal/inject; genital (male)

Liver function test D34 Blood test; digestive

A34004 Albumin test

Medical examination complete/partial

A30 Medical examination/health evaluation complete


D31 Medical examination/health evaluation partial; digestive

F30 Medical examination/health evaluation complete; eye

F31 Medical examination/health evaluation partial; eye

K31 Medical examination/health evaluation partial; cardiovascular

W30 Medical examination/health evaluation complete; pregnancy

W31 Medical examination/health evaluation partial; pregnancy

X31 Medical examination/health evaluation partial; genital (female)

Observe/wait T45001 Observe/wait; endocrine/metabolic

W45003 Observe/wait; reproductive

Other diagnostic procedure; NEC

A43001 Diagnostic procedures

F43001 Diagnostic procedure; eye

W43002 Diagnostic procedure; reproductive system

X43001 Diagnostic procedure; genital system

H43001 Diagnostic procedure; ear

Other therapeutic medication/ procedures/minor surgery

A50010 Medication; given

A53 Instrument/catheter/intubate/dilate

A59 Other therapeutic procedures/minor surgery; NEC

B59 Other therapeutic procedures/minor surgery NEC; blood

D50007 Treatment; worms

D53 Instrument/catheter/intubate/dilate; digestive

F59 Other therapeutic procedures/minor surgery; eye




Description

Other therapeutic medication/ procedures/minor surgery (continued)

H59 Other therapeutic procedures/minor surgery; ear

L59 Other therapeutic procedures/minor surgery; musculoskeletal

R59 Other therapeutic procedures/minor surgery; respiratory

S59 Other therapeutic procedures/minor surgery; skin

U53 Instrument/catheter/intubate/dilate; urinary

U59 Other therapeutic procedures/minor surgery; urinary

W59 Other therapeutic procedures/minor surgery; pregnancy

Physical medicine/ rehabilitation

A57 Physical medicine/rehabilitation

L57 Physical medicine/rehabilitation; musculoskeletal

Referral A68 Other referral NEC

K68 Other referral NEC; cardiovascular

Repair/fixation – suture/cast/prosthetic device (apply/remove)

L54 Repair/fix – suture/cast/prosthetic device; musculoskeletal

S54 Repair/fix – suture/cast/prosthetic device; skin

T54 Repair/fix – suture/cast/prosthetic device; endo/metabolic

Result test/procedure A60 Result test/procedures

B60 Result test/procedures; blood/lymph

K60 Result test/procedures; cardiovascular

N60 Result test/procedures; neurological

Tuberculosis R32001 Mantoux test

R32002 Tuberculin test

R33001 Culture; tuberculosis

Urine test A35001 Urine test

A35002 Urinalysis

Note: NEC – Not elsewhere classified; RICE – rest, ice, compression, elevation.

APPENDIX 5: PARTICIPANTS OF NMCS 2014

Public clinics

Public Clinics (Johor)

1 Klinik Kesihatan Bukit Besar 6 Klinik Kesihatan Mahmoodiah

2 Klinik Kesihatan Jalan Mengkibol 7 Klinik Kesihatan Majidee

3 Klinik Kesihatan Kahang Batu 22 8 Klinik Kesihatan Pasir Gudang

4 Klinik Kesihatan Kulai Besar 9 Klinik Kesihatan Sungai Rengit

5 Klinik Kesihatan Larkin 10 Klinik Kesihatan Tenggaroh

Public Clinics (Kedah)

1 Klinik Kesihatan Ayer Hangat 5 Klinik Kesihatan Tunjang

2 Klinik Kesihatan Bandar Baharu 6 Klinik Kesihatan Jalan Putra

3 Klinik Kesihatan Guar Chempedak 7 Klinik Kesihatan Alor Janggus

4 Klinik Kesihatan Malau

Public Clinics (Negeri Sembilan)

1 Klinik Kesihatan Bukit Pelanduk 4 Klinik Kesihatan Pasir Panjang

2 Klinik Kesihatan Lenggeng 5 Klinik Kesihatan Terachi

3 Klinik Kesihatan Palong 9,10,11

Public Clinics (Terengganu)

1 Klinik Kesihatan Jabi 4 Klinik Kesihatan Permaisuri

2 Klinik Kesihatan Kemasek 5 Klinik Kesihatan Jabi

3 Klinik Kesihatan Kuala Kemaman

Public Clinics (Perak)

1 Klinik Kesihatan Bidor 6 Klinik Kesihatan Tronoh

2 Klinik Kesihatan Buntong 7 Klinik Kesihatan Jalan Baru

3 Klinik Kesihatan Gunung Semanggol 8 Klinik Kesihatan Sitiawan

4 Klinik Kesihatan Karai 9 Klinik Kesihatan Trolak Selatan

5 Klinik Kesihatan Lawin 10 Klinik Kesihatan Kedai Empat

133



Description

Other therapeutic medication/ procedures/minor surgery (continued)

H59 Other therapeutic procedures/minor surgery; ear

L59 Other therapeutic procedures/minor surgery; musculoskeletal

R59 Other therapeutic procedures/minor surgery; respiratory

S59 Other therapeutic procedures/minor surgery; skin

U53 Instrument/catheter/intubate/dilate; urinary

U59 Other therapeutic procedures/minor surgery; urinary

W59 Other therapeutic procedures/minor surgery; pregnancy

Physical medicine/ rehabilitation

A57 Physical medicine/rehabilitation

L57 Physical medicine/rehabilitation; musculoskeletal

Referral A68 Other referral NEC

K68 Other referral NEC; cardiovascular

Repair/fixation – suture/cast/prosthetic device (apply/remove)

L54 Repair/fix – suture/cast/prosthetic device; musculoskeletal

S54 Repair/fix – suture/cast/prosthetic device; skin

T54 Repair/fix – suture/cast/prosthetic device; endo/metabolic

Result test/procedure A60 Result test/procedures

B60 Result test/procedures; blood/lymph

K60 Result test/procedures; cardiovascular

N60 Result test/procedures; neurological

Tuberculosis R32001 Mantoux test

R32002 Tuberculin test

R33001 Culture; tuberculosis

Urine test A35001 Urine test

A35002 Urinalysis

Note: NEC – Not elsewhere classified; RICE – rest, ice, compression, elevation.

Appendices

APPENDIX 5: PARTICIPANTS OF NMCS 2014

Public clinics

Public Clinics (Johor)

1 Klinik Kesihatan Bukit Besar 6 Klinik Kesihatan Mahmoodiah

2 Klinik Kesihatan Jalan Mengkibol 7 Klinik Kesihatan Majidee

3 Klinik Kesihatan Kahang Batu 22 8 Klinik Kesihatan Pasir Gudang

4 Klinik Kesihatan Kulai Besar 9 Klinik Kesihatan Sungai Rengit

5 Klinik Kesihatan Larkin 10 Klinik Kesihatan Tenggaroh

Public Clinics (Kedah)

1 Klinik Kesihatan Ayer Hangat 5 Klinik Kesihatan Tunjang

2 Klinik Kesihatan Bandar Baharu 6 Klinik Kesihatan Jalan Putra

3 Klinik Kesihatan Guar Chempedak 7 Klinik Kesihatan Alor Janggus

4 Klinik Kesihatan Malau

Public Clinics (Negeri Sembilan)

1 Klinik Kesihatan Bukit Pelanduk 4 Klinik Kesihatan Pasir Panjang

2 Klinik Kesihatan Lenggeng 5 Klinik Kesihatan Terachi

3 Klinik Kesihatan Palong 9,10,11

Public Clinics (Terengganu)

1 Klinik Kesihatan Jabi 4 Klinik Kesihatan Permaisuri

2 Klinik Kesihatan Kemasek 5 Klinik Kesihatan Jabi

3 Klinik Kesihatan Kuala Kemaman

Public Clinics (Perak)

1 Klinik Kesihatan Bidor 6 Klinik Kesihatan Tronoh

2 Klinik Kesihatan Buntong 7 Klinik Kesihatan Jalan Baru

3 Klinik Kesihatan Gunung Semanggol 8 Klinik Kesihatan Sitiawan

4 Klinik Kesihatan Karai 9 Klinik Kesihatan Trolak Selatan

5 Klinik Kesihatan Lawin 10 Klinik Kesihatan Kedai Empat


Public Clinics (Melaka)

1 Klinik Kesihatan Ayer Keroh 13 Klinik Kesihatan Merlimau

2 Klinik Kesihatan Ayer Molek 14 Klinik Kesihatan Padang Sebang

3 Klinik Kesihatan Bukit Rambai 15 Klinik Kesihatan Peringgit

4 Klinik Kesihatan Cheng 16 Klinik Kesihatan Selandar

5 Klinik Kesihatan Durian Tunggal 17 Klinik Kesihatan Simpang Empat

6 Klinik Kesihatan Hutan Percha 18 Klinik Kesihatan Simpang Bekoh

7 Klinik Kesihatan Jalan Gereja 19 Klinik Kesihatan Sungai Rambai

8 Klinik Kesihatan Kemendor 20 Klinik Kesihatan Sungai Udang

9 Klinik Kesihatan Klebang Besar 21 Klinik Kesihatan Tanjung Kling

10 Klinik Kesihatan Kuala Sungai Baru 22 Klinik Kesihatan Ujong Pasir

11 Klinik Kesihatan Lubok China 23 Klinik Kesihatan Umbai

12 Klinik Kesihatan Macap Baru

Public Clinics (Kelantan)

1 Klinik Kesihatan Bandar Gua Musang 5 Klinik Kesihatan Pengkalan Kubor

2 Klinik Kesihatan Gual Ipoh 6 Klinik Kesihatan Peringat

3 Klinik Kesihatan Kuala Betis 7 Klinik Kesihatan Tendong

4 Klinik Kesihatan Pengkalan Chepa

Public Clinics (Pahang)

1 Klinik Kesihatan Bandar Jengka 4 Klinik Kesihatan Kuala Tahan

2 Klinik Kesihatan Chini 5 Klinik Kesihatan Pos Betau

3 Klinik Kesihatan Dong 6 Klinik Kesihatan Tanjung Gemok

Public Clinics (Selangor)

1 Klinik Kesihatan AU2 8 Klinik Kesihatan Seksyen 19 Shah Alam

2 Klinik Kesihatan Bukit Kuda 9 Klinik Kesihatan Selayang Baru

3 Klinik Kesihatan Gombak Utara (Bt. 8) 10 Klinik Kesihatan Semenyih

4 Klinik Kesihatan Kalumpang 11 Klinik Kesihatan Sijangkang

5 Klinik Kesihatan Klang 12 Klinik Kesihatan Sungai Air Tawar

6 Klinik Kesihatan Pulau Ketam 13 Klinik Kesihatan Sungai Sekamat

7 Klinik Kesihatan Rantau Panjang 14 Klinik Kesihatan Tanjung Karang

Public Clinics (Perlis)

1 Klinik Kesihatan Arau 5 Klinik Kesihatan Kuala Perlis

2 Klinik Kesihatan Beseri 6 Klinik Kesihatan Padang Besar

3 Klinik Kesihatan Kg. Gial 7 Klinik Kesihatan Simpang Empat

4 Klinik Kesihatan Kangar

Public Clinics (Pulau Pinang)

1 Klinik Kesihatan Kubang Semang 4 Klinik Kesihatan Nibong Tebal

2 Klinik Kesihatan Bandar Baru Air Itam 5 Klinik Kesihatan Prai

3 Klinik Kesihatan Mak Mandin

Public Clinics (Sabah)

1 Klinik Kesihatan Kemabong 5 Klinik Kesihatan Nangoh Rumedi

2 Klinik Kesihatan Menggatal 6 Klinik Kesihatan Taginambur

3 Klinik Kesihatan Menumbok 7 Klinik Kesihatan Tenghilan

4 Klinik Kesihatan Nabawan

Public Clinics (Sarawak)

1 Klinik Kesihatan Bako 6 Klinik Kesihatan Kota Samarahan

2 Klinik Kesihatan Bario 7 Klinik Kesihatan Kota Sentosa

3 Klinik Kesihatan Debak 8 Klinik Kesihatan Pusa

4 Klinik Kesihatan Jalan Oya 9 Klinik Kesihatan Sadong Jaya

5 Klinik Kesihatan Kabong 10 Klinik Kesihatan Sematan

Public Clinics (WP Kuala Lumpur)

1 Klinik Kesihatan Bandar Tun Razak 7 Klinik Kesihatan Kampung Pandan

2 Klinik Kesihatan Batu 8 Klinik Kesihatan Petaling Bahagia

3 Klinik Kesihatan Cheras 9 Klinik Kesihatan Sentul

4 Klinik Kesihatan Cheras Baru 10 Klinik Kesihatan Setapak

5 Klinik Kesihatan Dato Keramat 11 Klinik Kesihatan Sungai Besi

6 Klinik Kesihatan Jinjang 12 Klinik Kesihatan Tanglin

135

Public Clinics (Melaka)

1 Klinik Kesihatan Ayer Keroh 13 Klinik Kesihatan Merlimau

2 Klinik Kesihatan Ayer Molek 14 Klinik Kesihatan Padang Sebang

3 Klinik Kesihatan Bukit Rambai 15 Klinik Kesihatan Peringgit

4 Klinik Kesihatan Cheng 16 Klinik Kesihatan Selandar

5 Klinik Kesihatan Durian Tunggal 17 Klinik Kesihatan Simpang Empat

6 Klinik Kesihatan Hutan Percha 18 Klinik Kesihatan Simpang Bekoh

7 Klinik Kesihatan Jalan Gereja 19 Klinik Kesihatan Sungai Rambai

8 Klinik Kesihatan Kemendor 20 Klinik Kesihatan Sungai Udang

9 Klinik Kesihatan Klebang Besar 21 Klinik Kesihatan Tanjung Kling

10 Klinik Kesihatan Kuala Sungai Baru 22 Klinik Kesihatan Ujong Pasir

11 Klinik Kesihatan Lubok China 23 Klinik Kesihatan Umbai

12 Klinik Kesihatan Macap Baru

Public Clinics (Kelantan)

1 Klinik Kesihatan Bandar Gua Musang 5 Klinik Kesihatan Pengkalan Kubor

2 Klinik Kesihatan Gual Ipoh 6 Klinik Kesihatan Peringat

3 Klinik Kesihatan Kuala Betis 7 Klinik Kesihatan Tendong

4 Klinik Kesihatan Pengkalan Chepa

Public Clinics (Pahang)

1 Klinik Kesihatan Bandar Jengka 4 Klinik Kesihatan Kuala Tahan

2 Klinik Kesihatan Chini 5 Klinik Kesihatan Pos Betau

3 Klinik Kesihatan Dong 6 Klinik Kesihatan Tanjung Gemok

Public Clinics (Selangor)

1 Klinik Kesihatan AU2 8 Klinik Kesihatan Seksyen 19 Shah Alam

2 Klinik Kesihatan Bukit Kuda 9 Klinik Kesihatan Selayang Baru

3 Klinik Kesihatan Gombak Utara (Bt. 8) 10 Klinik Kesihatan Semenyih

4 Klinik Kesihatan Kalumpang 11 Klinik Kesihatan Sijangkang

5 Klinik Kesihatan Klang 12 Klinik Kesihatan Sungai Air Tawar

6 Klinik Kesihatan Pulau Ketam 13 Klinik Kesihatan Sungai Sekamat

7 Klinik Kesihatan Rantau Panjang 14 Klinik Kesihatan Tanjung Karang

Appendices

Public Clinics (Perlis)

1 Klinik Kesihatan Arau 5 Klinik Kesihatan Kuala Perlis

2 Klinik Kesihatan Beseri 6 Klinik Kesihatan Padang Besar

3 Klinik Kesihatan Kg. Gial 7 Klinik Kesihatan Simpang Empat

4 Klinik Kesihatan Kangar

Public Clinics (Pulau Pinang)

1 Klinik Kesihatan Kubang Semang 4 Klinik Kesihatan Nibong Tebal

2 Klinik Kesihatan Bandar Baru Air Itam 5 Klinik Kesihatan Prai

3 Klinik Kesihatan Mak Mandin

Public Clinics (Sabah)

1 Klinik Kesihatan Kemabong 5 Klinik Kesihatan Nangoh Rumedi

2 Klinik Kesihatan Menggatal 6 Klinik Kesihatan Taginambur

3 Klinik Kesihatan Menumbok 7 Klinik Kesihatan Tenghilan

4 Klinik Kesihatan Nabawan

Public Clinics (Sarawak)

1 Klinik Kesihatan Bako 6 Klinik Kesihatan Kota Samarahan

2 Klinik Kesihatan Bario 7 Klinik Kesihatan Kota Sentosa

3 Klinik Kesihatan Debak 8 Klinik Kesihatan Pusa

4 Klinik Kesihatan Jalan Oya 9 Klinik Kesihatan Sadong Jaya

5 Klinik Kesihatan Kabong 10 Klinik Kesihatan Sematan

Public Clinics (WP Kuala Lumpur)

1 Klinik Kesihatan Bandar Tun Razak 7 Klinik Kesihatan Kampung Pandan

2 Klinik Kesihatan Batu 8 Klinik Kesihatan Petaling Bahagia

3 Klinik Kesihatan Cheras 9 Klinik Kesihatan Sentul

4 Klinik Kesihatan Cheras Baru 10 Klinik Kesihatan Setapak

5 Klinik Kesihatan Dato Keramat 11 Klinik Kesihatan Sungai Besi

6 Klinik Kesihatan Jinjang 12 Klinik Kesihatan Tanglin


Private clinics

Private Clinics (Johor)

1 Kelinik Malaysia 23 Klinik Waqaf An-Nur

2 Klinik Adham Cawangan Indahpura 24 Klinik Wawasan Perdana

3 Klinik Aiswarya 25 Klinik Yeoh Dan Surgeri

4 Klinik Amir 26 Klinik Zaiton

5 Klinik Asia Rawang Sg. Mati 27 Klinik Zohar & Surgeri

6 Klinik Dan Surgeri Taman Daya 28 Kumpulan Perubatan Asia Sdn Bhd

- Klinik Asia Skudai

7 Klinik Dedap Sdn. Bhd. 29 Kumpulan Perubatan Asia Sdn Bhd

-Klinik Asia Taman Daya

8 Klinik Ilham & Surgeri 30 Poliklinik Dr. Abdullah

9 Klinik Intan 31 Poliklinik Impian

10 Klinik Jay 32 Poliklinik Khoo & Surgeri

11 Klinik Kamal 33 Poliklinik Krishna

12 Klinik Keluarga (Segamat) 34 Poliklinik Lee

13 Klinik Koh Dan Surgeri 35 Poliklinik Mustakizah

14 Klinik Kwang 36 Poliklinik Penawar

15 Klinik Medic Care 37 Poliklinik Penawar Seri Alam

16 Klinik Mohan Dan Surgeri 38 Poliklinik Rozikin

17 Klinik Pantai 39 Poliklinik Rozikin

18 Klinik Ria 40 Poliklinik Sejahtera Sdn Bhd

19 Klinik Tee 41 Poliklinik Yuslina (Taman Istimewa)

20 Klinik Teo ( Klinik Teo & Tan Sdn Bhd ) 42 Polyklinik Termuzi

21 Klinik TJ 43 Poliklinik Penawar

22 Klinik Utama

Private Clinics (Kedah)

1 Kelinik Muhibbah 12 Klinik Topcare

2 Klinik C. S. Ooi 13 Klinik Ummi

3 Klinik Cheng & Su 14 Klinik Wawasan

4 Klinik Doreen Khoo 15 Lim Poliklinik

5 Klinik Dr Chong 16 Mediklinik Ehsan Alor Setar

6 Klinik Dr Robetah 17 Poliklinik Dr. Azhar & Rakan-Rakan

7 Klinik Dr. Roslan 18 Poliklinik Dr. Azhar Dan Rakan-Rakan

8 Klinik Dr. Salina 19 Poliklinik Ihsan

9 Klinik Dr.Chua 20 Poliklinik Keluarga

10 Klinik Foong 21 Poliklinik Kenanga

11 Klinik Liew Yin Fong 22 Poliklinik Mahkota

Private Clinics (Kelantan)

1 Klinik Ariffin 12 Klinik Goh

2 Klinik Azhar 13 Klinik Ikhtiar Kota Jembal

3 Klinik Balkhis 14 Klinik Insaf

4 Klinik Bima Sakti 15 Klinik Mahmood

5 Klinik Dr. Alwani 16 Klinik Perdana

6 Klinik Dr. Haydar Ali 17 Klinik Primer Tanah Merah

7 Klinik Dr. Roshadah 18 Klinik Wakaf Siku

8 Klinik Dr. Wan 19 Klinik Zainal Aziz

9 Klinik Dr. Wan Mohd. Noor 20 Klinik Ziad Pasir Tumbuh

10 Klinik Ehsan 21 Kumpulan Klinik M.I.R

11 Klinik Fatah & Abdullah 22 Poliklinik Dr Azhar Dan Rakan-Rakan

Private Clinics (Melaka)

1 Klinik Bukit Beruang 8 Klinik Noh

2 Klinik Chin 9 Klinik Nurussyifa' Perubatan Dan Surgeri

3 Klinik Famili 10 Klinik Peringgit Point Sdn Bhd

4 Klinik Keluarga 11 Klinik Wira Medik Sdn Bhd

5 Klinik Kuan Sdn. Bhd. 12 Poliklinik & Surgeri Merlimau

6 Klinik Melaka Raya 13 Poliklinik Dan Surgeri Cosmopoint

7 Klinik Mesra 14 Poliklinik Perdana

Private Clinics (Negeri Sembilan)

1 Klinik Ang & Ang Sdn Bhd 11 Klinik Zaaba

2 Klinik An-Nur 12 Poliklinik Foo Dan Yong

3 Klinik Bistari 13 Poliklinik Hidayah Sdn Bhd (Jln Cattleya)

4 Klinik Keluarga 14 Poliklinik Hidayah Sdn. Bhd.

5 Klinik Keluarga Darul Syifa' 15 Poliklinik Ibnu Sina

6 Klinik Mediviron 16 Poliklinik Jasa

7 Klinik Mediviron (Klinik Seremban 2) 17 Poliklinik Publik

8 Klinik Mesra Bayu 18 Poliklinik Sakti

9 Klinik Pantai 19 Pusat Rawatan Dr Mahmud & Dr Zanariah (Poliklinik & Surgeri)

10 Klinik Seremban

137

Private clinics

Private Clinics (Johor)

1 Kelinik Malaysia 23 Klinik Waqaf An-Nur

2 Klinik Adham Cawangan Indahpura 24 Klinik Wawasan Perdana

3 Klinik Aiswarya 25 Klinik Yeoh Dan Surgeri

4 Klinik Amir 26 Klinik Zaiton

5 Klinik Asia Rawang Sg. Mati 27 Klinik Zohar & Surgeri

6 Klinik Dan Surgeri Taman Daya 28 Kumpulan Perubatan Asia Sdn Bhd

- Klinik Asia Skudai

7 Klinik Dedap Sdn. Bhd. 29 Kumpulan Perubatan Asia Sdn Bhd

-Klinik Asia Taman Daya

8 Klinik Ilham & Surgeri 30 Poliklinik Dr. Abdullah

9 Klinik Intan 31 Poliklinik Impian

10 Klinik Jay 32 Poliklinik Khoo & Surgeri

11 Klinik Kamal 33 Poliklinik Krishna

12 Klinik Keluarga (Segamat) 34 Poliklinik Lee

13 Klinik Koh Dan Surgeri 35 Poliklinik Mustakizah

14 Klinik Kwang 36 Poliklinik Penawar

15 Klinik Medic Care 37 Poliklinik Penawar Seri Alam

16 Klinik Mohan Dan Surgeri 38 Poliklinik Rozikin

17 Klinik Pantai 39 Poliklinik Rozikin

18 Klinik Ria 40 Poliklinik Sejahtera Sdn Bhd

19 Klinik Tee 41 Poliklinik Yuslina (Taman Istimewa)

20 Klinik Teo ( Klinik Teo & Tan Sdn Bhd ) 42 Polyklinik Termuzi

21 Klinik TJ 43 Poliklinik Penawar

22 Klinik Utama

Private Clinics (Kedah)

1 Kelinik Muhibbah 12 Klinik Topcare

2 Klinik C. S. Ooi 13 Klinik Ummi

3 Klinik Cheng & Su 14 Klinik Wawasan

4 Klinik Doreen Khoo 15 Lim Poliklinik

5 Klinik Dr Chong 16 Mediklinik Ehsan Alor Setar

6 Klinik Dr Robetah 17 Poliklinik Dr. Azhar & Rakan-Rakan

7 Klinik Dr. Roslan 18 Poliklinik Dr. Azhar Dan Rakan-Rakan

8 Klinik Dr. Salina 19 Poliklinik Ihsan

9 Klinik Dr.Chua 20 Poliklinik Keluarga

10 Klinik Foong 21 Poliklinik Kenanga

11 Klinik Liew Yin Fong 22 Poliklinik Mahkota

Appendices

Private Clinics (Kelantan)

1 Klinik Ariffin 12 Klinik Goh

2 Klinik Azhar 13 Klinik Ikhtiar Kota Jembal

3 Klinik Balkhis 14 Klinik Insaf

4 Klinik Bima Sakti 15 Klinik Mahmood

5 Klinik Dr. Alwani 16 Klinik Perdana

6 Klinik Dr. Haydar Ali 17 Klinik Primer Tanah Merah

7 Klinik Dr. Roshadah 18 Klinik Wakaf Siku

8 Klinik Dr. Wan 19 Klinik Zainal Aziz

9 Klinik Dr. Wan Mohd. Noor 20 Klinik Ziad Pasir Tumbuh

10 Klinik Ehsan 21 Kumpulan Klinik M.I.R

11 Klinik Fatah & Abdullah 22 Poliklinik Dr Azhar Dan Rakan-Rakan

Private Clinics (Melaka)

1 Klinik Bukit Beruang 8 Klinik Noh

2 Klinik Chin 9 Klinik Nurussyifa' Perubatan Dan Surgeri

3 Klinik Famili 10 Klinik Peringgit Point Sdn Bhd

4 Klinik Keluarga 11 Klinik Wira Medik Sdn Bhd

5 Klinik Kuan Sdn. Bhd. 12 Poliklinik & Surgeri Merlimau

6 Klinik Melaka Raya 13 Poliklinik Dan Surgeri Cosmopoint

7 Klinik Mesra 14 Poliklinik Perdana

Private Clinics (Negeri Sembilan)

1 Klinik Ang & Ang Sdn Bhd 11 Klinik Zaaba

2 Klinik An-Nur 12 Poliklinik Foo Dan Yong

3 Klinik Bistari 13 Poliklinik Hidayah Sdn Bhd (Jln Cattleya)

4 Klinik Keluarga 14 Poliklinik Hidayah Sdn. Bhd.

5 Klinik Keluarga Darul Syifa' 15 Poliklinik Ibnu Sina

6 Klinik Mediviron 16 Poliklinik Jasa

7 Klinik Mediviron (Klinik Seremban 2) 17 Poliklinik Publik

8 Klinik Mesra Bayu 18 Poliklinik Sakti

9 Klinik Pantai 19 Pusat Rawatan Dr Mahmud & Dr Zanariah (Poliklinik & Surgeri)

10 Klinik Seremban


Private Clinics (Pahang)

1 Ananda Klinik 10 Klinik Sulaiman

2 Kinik Ganesh & Surgery 11 Klinik Sulaiman

3 Klinik Efendi 12 Klinik Sulaiman

4 Klinik Ehsan 13 Klinik Syed Badaruddin

5 Klinik Lee 14 Klinik Syed Badaruddin

6 Klinik Low 15 Klinik Wira

7 Klinik Mutiara 16 Klinik Yu Sdn Bhd

8 Klinik Ng 17 Poliklinik & Surgeri Shankar

9 Klinik Philip Dan Rakan 18 Poliklinik Maran

Private Clinics (Perak)

1 Chua Kelinik 16 Klinik Setia

2 Kelinik Che Wan (Medan Polyclinic & Surgery) 17 New Town Poliklinik

3 Kelinik Che Wan (UTP Health Centre) 18 Klinik Teoh & Chan Sdn Bhd

4 Kelinik Majid 19 Perak Medical Centre Sdn. Bhd, Ipoh

5 Klinik Aman 20 Polikelinik Bakti

6 Klinik Berkat 21 Poliklinik & Surgeri Batu Gajah

7 Klinik C.K. Chan 22 Poliklinik & Surgeri Kumar

8 Klinik Dr. Sharul 23 Poliklinik Dr. Azhar & Rakan-Rakan

(Parit Buntar)

9 Klinik Dr. Tiong 24 Poliklinik Dr. Azhar & Rakan-Rakan (Manjung)

10 Klinik E.C. Lee 25 Poliklinik Dr. C.Y. Ong Sdn. Bhd.

11 Klinik Edina 26 Poliklinik Fitrah

12 Klinik Greentown 27 Poliklinik Gemilang (Dr. Thomas)

13 Klinik Lau & Sharon 28 Poliklinik Gomez-UTAR

14 Klinik Perubatan Zalfa 29 Poliklinik Manjit

15 Klinik Rawatan Ahsan 30 Sitiawan Surgery

Private Clinics (Perlis)

1 Klinik & Dispensari Dr. Rohimi Osman 5 Klinik Refflesia

2 Klinik Dr. Mohadzir 6 Klinik Tan & Lee

3 Klinik Faizah 7 Poliklinik Dr Azhar Dan Rakan-Rakan

4 Klinik Menon Sdn. Bhd.

Private Clinics (Pulau Pinang)

1 Glugor Klinik 18 Klinik Pillar

2 H.S. Khoo Clinic Sdn. Bhd 19 Klinik Rashidi

3 Klinik 1 Utama 20 Klinik Roberts

4 Klinik 6 21 Klinik Sentosa Sdn Bhd

5 Klinik Bersatu 16 Jam 22 Klinik Seri Pulau

6 Klinik Dr. Abd Aziz 23 Klinik Singapore

7 Klinik Dr. Lee Hock Huat 24 Klinik Syed Alwi Dan Chandran

8 Klinik England 25 Klinik Topcare (Raja Uda) Sdn Bhd

9 Klinik Gurney 26 Klinik Wong

10 Klinik Harmony 27 Poliklinik Bestari

11 Klinik Joe Fernandez 28 Poliklinik Chiah

12 Klinik Joe Fernandez (Seberang Jaya) 29 Poliiklinik Dr Azhar & Rakan- Rakan

(Kepala Batas)

13 Klinik Kenari 30 Poliklinik Dr Azhar & Rakan- Rakan (Gelugor)

14 Klinik Lee 31 Poliklinik Dr Velu

15 Klinik Malaysia 32 Poliklinik HL

16 Klinik Munnir 33 Poliklinik Pan

17 Klinik Pertama

Private Clinics (Sabah & WP Labuan)

1 Clinic Chua 14 Klinik Lo & Wah

2 Klinik BSI 15 Klinik Malaysia (Cawangan SESB)

3 Klinik Dan Surgeri Dr Gan 16 Klinik Nasir & Surgeri

4 Klinik Dr. C.H. Kong 17 Klinik Ramlee & Partners

5 Klinik Dr. Gan & Surgeri 18 Klinik S. K. Lo Sdn. Bhd.

6 Klinik Dr. Lilian Hong 19 Klinik Sabah

7 Klinik Dr. Loi Yew June 20 Klinik Surgeri Dr. Toh

8 Kelinik Ong 21 Klinik Wawasan

9 Klinik Dr. Selvam Sdn. Bhd. 22 Permai Polyclinics

10 Klinik Dr. T. L. Chaw 23 Poliklinik Mesra & Surgeri (Putatan Branch)

11 Klinik Elopura Sdn. Bhd. 24 Poliklinik Rakyat(Cawangan Putatan)

12 Klinik Keluarga Keningau 25 Putatan Klinik Dan Surgeri

13 Klinik Layong 26 Sinsuran Clinic

139

Private Clinics (Pahang)

1 Ananda Klinik 10 Klinik Sulaiman

2 Kinik Ganesh & Surgery 11 Klinik Sulaiman

3 Klinik Efendi 12 Klinik Sulaiman

4 Klinik Ehsan 13 Klinik Syed Badaruddin

5 Klinik Lee 14 Klinik Syed Badaruddin

6 Klinik Low 15 Klinik Wira

7 Klinik Mutiara 16 Klinik Yu Sdn Bhd

8 Klinik Ng 17 Poliklinik & Surgeri Shankar

9 Klinik Philip Dan Rakan 18 Poliklinik Maran

Private Clinics (Perak)

1 Chua Kelinik 16 Klinik Setia

2 Kelinik Che Wan (Medan Polyclinic & Surgery) 17 New Town Poliklinik

3 Kelinik Che Wan (UTP Health Centre) 18 Klinik Teoh & Chan Sdn Bhd

4 Kelinik Majid 19 Perak Medical Centre Sdn. Bhd, Ipoh

5 Klinik Aman 20 Polikelinik Bakti

6 Klinik Berkat 21 Poliklinik & Surgeri Batu Gajah

7 Klinik C.K. Chan 22 Poliklinik & Surgeri Kumar

8 Klinik Dr. Sharul 23 Poliklinik Dr. Azhar & Rakan-Rakan

(Parit Buntar)

9 Klinik Dr. Tiong 24 Poliklinik Dr. Azhar & Rakan-Rakan (Manjung)

10 Klinik E.C. Lee 25 Poliklinik Dr. C.Y. Ong Sdn. Bhd.

11 Klinik Edina 26 Poliklinik Fitrah

12 Klinik Greentown 27 Poliklinik Gemilang (Dr. Thomas)

13 Klinik Lau & Sharon 28 Poliklinik Gomez-UTAR

14 Klinik Perubatan Zalfa 29 Poliklinik Manjit

15 Klinik Rawatan Ahsan 30 Sitiawan Surgery

Private Clinics (Perlis)

1 Klinik & Dispensari Dr. Rohimi Osman 5 Klinik Refflesia

2 Klinik Dr. Mohadzir 6 Klinik Tan & Lee

3 Klinik Faizah 7 Poliklinik Dr Azhar Dan Rakan-Rakan

4 Klinik Menon Sdn. Bhd.

Appendices

Private Clinics (Pulau Pinang)

1 Glugor Klinik 18 Klinik Pillar

2 H.S. Khoo Clinic Sdn. Bhd 19 Klinik Rashidi

3 Klinik 1 Utama 20 Klinik Roberts

4 Klinik 6 21 Klinik Sentosa Sdn Bhd

5 Klinik Bersatu 16 Jam 22 Klinik Seri Pulau

6 Klinik Dr. Abd Aziz 23 Klinik Singapore

7 Klinik Dr. Lee Hock Huat 24 Klinik Syed Alwi Dan Chandran

8 Klinik England 25 Klinik Topcare (Raja Uda) Sdn Bhd

9 Klinik Gurney 26 Klinik Wong

10 Klinik Harmony 27 Poliklinik Bestari

11 Klinik Joe Fernandez 28 Poliklinik Chiah

12 Klinik Joe Fernandez (Seberang Jaya) 29 Poliiklinik Dr Azhar & Rakan- Rakan

(Kepala Batas)

13 Klinik Kenari 30 Poliklinik Dr Azhar & Rakan- Rakan (Gelugor)

14 Klinik Lee 31 Poliklinik Dr Velu

15 Klinik Malaysia 32 Poliklinik HL

16 Klinik Munnir 33 Poliklinik Pan

17 Klinik Pertama

Private Clinics (Sabah & WP Labuan)

1 Clinic Chua 14 Klinik Lo & Wah

2 Klinik BSI 15 Klinik Malaysia (Cawangan SESB)

3 Klinik Dan Surgeri Dr Gan 16 Klinik Nasir & Surgeri

4 Klinik Dr. C.H. Kong 17 Klinik Ramlee & Partners

5 Klinik Dr. Gan & Surgeri 18 Klinik S. K. Lo Sdn. Bhd.

6 Klinik Dr. Lilian Hong 19 Klinik Sabah

7 Klinik Dr. Loi Yew June 20 Klinik Surgeri Dr. Toh

8 Kelinik Ong 21 Klinik Wawasan

9 Klinik Dr. Selvam Sdn. Bhd. 22 Permai Polyclinics

10 Klinik Dr. T. L. Chaw 23 Poliklinik Mesra & Surgeri (Putatan Branch)

11 Klinik Elopura Sdn. Bhd. 24 Poliklinik Rakyat(Cawangan Putatan)

12 Klinik Keluarga Keningau 25 Putatan Klinik Dan Surgeri

13 Klinik Layong 26 Sinsuran Clinic


Private Clinics (Sarawak)

1 B. Teo's Child And Family Clinic 9 Klinik Kong (1980)

2 Klinik Aniza 10 Klinik L.T. Wong

3 Klinik Chai 11 Klinik Peter Lee

4 Klinik Dr. Ngui 12 Klinik Petra

5 Klinik Godwin Chan 13 Klinik Robert Wong

6 Klinik Haizam 14 Klinik Waqaf An-Nur Sarawak

7 Klinik Hasani 15 Klinik Yeo, Skin & Medical

8 Klinik Ibukota Semarak (Klinik Aishah) 16 Sulah Clinic

Private Clinics (Selangor & WP Putrajaya)

1 Dr Leela Ratos Dan Rakan-Rakan 26 Klinik Keluarga Azian & Elina

2 Drs Young Newton Dan Rakan-Rakan 27 Klinik Keluarga Dan Surgeri

3 Jacob Klinik Kundang 28 Klinik Keluarga Dr. Nora

4 Klinik & Surgeri Shah Alam 29 Klinik Kita Poliklinik & Surgeri

5 Klinik Ahmad Shah (Jalan Perbahan) 30 Klinik M L Wong

6 Klinik Ahmad Shah (Jalan Tukas) 31 Klinik Maamor

7 Klinik Aishah 32 Klinik Mani Dan Surgeri

8 Klinik Alam Medic (Putra Mahkota) 33 Klinik Maria Putrajaya

9 Klinik Alam Medic (Sri Puteri) 34 Klinik Medic Suria

10 Klinik And Surgery Equine Park 35 Klinik Medic-Plus

11 Klinik Ansar 36 Klinik Medijaya

12 Klinik Baharudin 37 Klinik Mediviron (Klang)

13 Klinik Bandaran (Taman Puchong Permai) 38 Klinik Mediviron (Petaling Jaya)

14 Klinik Bandaran, Jalan Bunga Melor 39 Klinik Mediviron (Kajang)

15 Klinik Chelliah 40 Klinik Mediviron (Bandar Baru Bangi)

16 Klinik Dharan 41 Klinik Mediviron (Petaling Jaya)

17 Klinik Dr Zaini 42 Klinik Mediviron Dr. Halim

18 Klinik Dr. Adib 43 Klinik Meena

19 Klinik Dr. Azizah 44 Klinik Metro (Metro Clinic)

20 Klinik Dr. Paramjit Kaur&Alam Medic 45 Klinik Nadia

21 Klinik Faezah 46 Klinik Nik Isahak

22 Klinik Famili 47 Klinik One Medic

23 Klinik Ganesan 48 Klinik Perdana

24 Klinik Hafiz 49 Klinik Perdana Dan Surgeri

25 Klinik Idzham 50 Klinik Perwira

51 Klinik Petaling Jaya 67 Klinik Teh

52 Klinik Popular 68 Klinik Teoh & Cheah

53 Klinik Puspanathan 69 Klinik Thomas

54 Klinik Qistina 70 Klinik Ummi Salihah

55 Klinik Raj 71 Klinik Waqaf Annur

56 Klinik Rs Khan 72 Klinik Wisma

57 Klinik Segara 73 Klinik Wong & Chye

58 Klinik Selangor 74 Klinik Wong Singh

59 Klinik Selva 75 Kumpulan Medic (Ampang)

60 Klinik Sentosa 76 Kumpulan Medic (Subang Jaya)

61 Klinik Sheela 77 Poliklinik & Surgeri Lim

62 Klinik Siti 78 Poliklinik An-Nisa

63 Klinik Sri Kinrara 79 Poliklinik Damai Emergency

64 Klinik Suntex 80 Poliklinik Gomez

65 Klinik Syifa 81 Poliklinik Harmoni

66 Klinik Tan & Mano 82 Poliklinik Ikhwan

67 Klinik Teh 83 Poliklinik Jaya

68 Klinik Teoh & Cheah 84 Poliklinik Kelana Jaya

69 Klinik Thomas 85 Poliklinik Kg Tunku

70 Klinik Ummi Salihah 86 Poliklinik Ludher Bhullar & Rakan-Rakan

51 Klinik Petaling Jaya 87 Poliklinik Mahkota

52 Klinik Popular 88 Poliklinik Medi-Nur

53 Klinik Puspanathan 89 Poliklinik Mindaku

54 Klinik Qistina 90 Poliklinik Mohan

55 Klinik Raj 91 Poliklinik Penawar

56 Klinik Rs Khan 92 Poliklinik Salehudin (Klang)

57 Klinik Segara 93 Poliklinik Salehudin (Salak Tinggi)

58 Klinik Selangor 94 Poliklinik Seri Putra

59 Klinik Selva 95 Poliklinik Sg Long

60 Klinik Sentosa 96 Poliklinik Sg. Jelok

61 Klinik Sheela 97 Poliklinik Sungai Bertek

62 Klinik Siti 98 Poliklinik Syifa & Surgeri

63 Klinik Sri Kinrara 99 Poliklinik Zain Azrai

64 Klinik Suntex 100 Pro Care Clinic

65 Klinik Syifa 101 Tan Dispensary

66 Klinik Tan & Mano 102 Y.F. Chew Klinik Sdn Bhd

141

Private Clinics (Sarawak)

1 B. Teo's Child And Family Clinic 9 Klinik Kong (1980)

2 Klinik Aniza 10 Klinik L.T. Wong

3 Klinik Chai 11 Klinik Peter Lee

4 Klinik Dr. Ngui 12 Klinik Petra

5 Klinik Godwin Chan 13 Klinik Robert Wong

6 Klinik Haizam 14 Klinik Waqaf An-Nur Sarawak

7 Klinik Hasani 15 Klinik Yeo, Skin & Medical

8 Klinik Ibukota Semarak (Klinik Aishah) 16 Sulah Clinic

Private Clinics (Selangor & WP Putrajaya)

1 Dr Leela Ratos Dan Rakan-Rakan 26 Klinik Keluarga Azian & Elina

2 Drs Young Newton Dan Rakan-Rakan 27 Klinik Keluarga Dan Surgeri

3 Jacob Klinik Kundang 28 Klinik Keluarga Dr. Nora

4 Klinik & Surgeri Shah Alam 29 Klinik Kita Poliklinik & Surgeri

5 Klinik Ahmad Shah (Jalan Perbahan) 30 Klinik M L Wong

6 Klinik Ahmad Shah (Jalan Tukas) 31 Klinik Maamor

7 Klinik Aishah 32 Klinik Mani Dan Surgeri

8 Klinik Alam Medic (Putra Mahkota) 33 Klinik Maria Putrajaya

9 Klinik Alam Medic (Sri Puteri) 34 Klinik Medic Suria

10 Klinik And Surgery Equine Park 35 Klinik Medic-Plus

11 Klinik Ansar 36 Klinik Medijaya

12 Klinik Baharudin 37 Klinik Mediviron (Klang)

13 Klinik Bandaran (Taman Puchong Permai) 38 Klinik Mediviron (Petaling Jaya)

14 Klinik Bandaran, Jalan Bunga Melor 39 Klinik Mediviron (Kajang)

15 Klinik Chelliah 40 Klinik Mediviron (Bandar Baru Bangi)

16 Klinik Dharan 41 Klinik Mediviron (Petaling Jaya)

17 Klinik Dr Zaini 42 Klinik Mediviron Dr. Halim

18 Klinik Dr. Adib 43 Klinik Meena

19 Klinik Dr. Azizah 44 Klinik Metro (Metro Clinic)

20 Klinik Dr. Paramjit Kaur&Alam Medic 45 Klinik Nadia

21 Klinik Faezah 46 Klinik Nik Isahak

22 Klinik Famili 47 Klinik One Medic

23 Klinik Ganesan 48 Klinik Perdana

24 Klinik Hafiz 49 Klinik Perdana Dan Surgeri

25 Klinik Idzham 50 Klinik Perwira

Appendices

51 Klinik Petaling Jaya 67 Klinik Teh

52 Klinik Popular 68 Klinik Teoh & Cheah

53 Klinik Puspanathan 69 Klinik Thomas

54 Klinik Qistina 70 Klinik Ummi Salihah

55 Klinik Raj 71 Klinik Waqaf Annur

56 Klinik Rs Khan 72 Klinik Wisma

57 Klinik Segara 73 Klinik Wong & Chye

58 Klinik Selangor 74 Klinik Wong Singh

59 Klinik Selva 75 Kumpulan Medic (Ampang)

60 Klinik Sentosa 76 Kumpulan Medic (Subang Jaya)

61 Klinik Sheela 77 Poliklinik & Surgeri Lim

62 Klinik Siti 78 Poliklinik An-Nisa

63 Klinik Sri Kinrara 79 Poliklinik Damai Emergency

64 Klinik Suntex 80 Poliklinik Gomez

65 Klinik Syifa 81 Poliklinik Harmoni

66 Klinik Tan & Mano 82 Poliklinik Ikhwan

67 Klinik Teh 83 Poliklinik Jaya

68 Klinik Teoh & Cheah 84 Poliklinik Kelana Jaya

69 Klinik Thomas 85 Poliklinik Kg Tunku

70 Klinik Ummi Salihah 86 Poliklinik Ludher Bhullar & Rakan-Rakan

51 Klinik Petaling Jaya 87 Poliklinik Mahkota

52 Klinik Popular 88 Poliklinik Medi-Nur

53 Klinik Puspanathan 89 Poliklinik Mindaku

54 Klinik Qistina 90 Poliklinik Mohan

55 Klinik Raj 91 Poliklinik Penawar

56 Klinik Rs Khan 92 Poliklinik Salehudin (Klang)

57 Klinik Segara 93 Poliklinik Salehudin (Salak Tinggi)

58 Klinik Selangor 94 Poliklinik Seri Putra

59 Klinik Selva 95 Poliklinik Sg Long

60 Klinik Sentosa 96 Poliklinik Sg. Jelok

61 Klinik Sheela 97 Poliklinik Sungai Bertek

62 Klinik Siti 98 Poliklinik Syifa & Surgeri

63 Klinik Sri Kinrara 99 Poliklinik Zain Azrai

64 Klinik Suntex 100 Pro Care Clinic

65 Klinik Syifa 101 Tan Dispensary

66 Klinik Tan & Mano 102 Y.F. Chew Klinik Sdn Bhd


Private Clinics (Terengganu)

1 Dr Sapiah Medical Centre 10 Klinik Mamad Sdn Bhd

2 Klinik Addeen 11 Klinik Norhazlina

3 Klinik Aishah Dan Akma 12 Klinik Pakar Perubatan Menon

4 Klinik Al Kausar 13 Klinik Rahim Hamzah Halim Razali

5 Klinik Alias 14 Klinik Sazrina

6 Klinik An-Nur 15 Klinik Syed Salleh Dan Rakan-Rakan

Sdn. Bhd

7 Klinik Darul Iman 16 Klinik Ummi Azizan

8 Klinik Ikhtiar 17 Klinik Wan Maihan

9 Klinik Leong 18 Klinik Zakaria

Private Clinics (WP Kuala Lumpur)

1 Aman Putri Dispensary 24 Klinik Medicare

2 Drs Tong, Leow, Chiam & Partners

(Chong Dispensary) 25 Klinik Mediviron (Desa Pandan)


(Chong Dispensary) 26 Klinik Mediviron (Desa Sri Hartamas)

4 Jose Clinic And Surgery 27 Klinik Mediviron (Kepong)

5 Klinik Aishah 28 Klinik Menara TM

6 Klinik Asia 29

Klinik Mitter Dan Rakan-Rakan

(Changed Name To Klinik Alam Medic)

7 Klinik Asia 30 Klinik Ng Dan Lee

8 Klinik Aun 31 Klinik Putrijaya

9 Klinik Bakti Balai Berita 32 Klinik Sannasees

10 Klinik Bintang 33 Klinik Shafi

11 Klinik Care Poliklinik Dan Surgeri 34 Klinik Sri Palar

12 Klinik Cheras Baru 35 Klinik Suria (Previously Known As Klinik TVS

Medicare)

13 Klinik Dan Surgeri Loo 36 Klinik Uni-Med

14 Klinik Dan Surgeri Mesra Sdn. Bhd. 37 Klinik Zarif

15 Klinik Dan Surgeri Thong 38 Medic Damansara

16 Klinik Famili BTS Sdn Bhd 39 Poliklinik & Dispensari Solaris Sdn. Bhd

17 Klinik Famili Dr Wan Kamariah Sdn Bhd 40 Poliklinik Dan Pembedahan Reiki Baba

18 Klinik Farrali Medicare 41 Poliklinik Kumpulan City

(Dr Chai Dan Rakan-Rakan)

19 Klinik Healthcare Dan Surgeri 42 Poliklinik Lai

20 Klinik Ian Ong 43 Poliklinik Lakshmi

21 Klinik Kaulsay 44 Poliklinik Lean

22 Klinik Keluarga 45 Poliklinik Ren Ai Bukit Maluri

23 Klinik Khor 46 Poliklinik Soo & Tan

143

Private Clinics (Terengganu)

1 Dr Sapiah Medical Centre 10 Klinik Mamad Sdn Bhd

2 Klinik Addeen 11 Klinik Norhazlina

3 Klinik Aishah Dan Akma 12 Klinik Pakar Perubatan Menon

4 Klinik Al Kausar 13 Klinik Rahim Hamzah Halim Razali

5 Klinik Alias 14 Klinik Sazrina

6 Klinik An-Nur 15 Klinik Syed Salleh Dan Rakan-Rakan

Sdn. Bhd

7 Klinik Darul Iman 16 Klinik Ummi Azizan

8 Klinik Ikhtiar 17 Klinik Wan Maihan

9 Klinik Leong 18 Klinik Zakaria

Private Clinics (WP Kuala Lumpur)

1 Aman Putri Dispensary 24 Klinik Medicare


(Chong Dispensary) 25 Klinik Mediviron (Desa Pandan)


(Chong Dispensary) 26 Klinik Mediviron (Desa Sri Hartamas)

4 Jose Clinic And Surgery 27 Klinik Mediviron (Kepong)

5 Klinik Aishah 28 Klinik Menara TM

6 Klinik Asia 29

Klinik Mitter Dan Rakan-Rakan

(Changed Name To Klinik Alam Medic)

7 Klinik Asia 30 Klinik Ng Dan Lee

8 Klinik Aun 31 Klinik Putrijaya

9 Klinik Bakti Balai Berita 32 Klinik Sannasees

10 Klinik Bintang 33 Klinik Shafi

11 Klinik Care Poliklinik Dan Surgeri 34 Klinik Sri Palar

12 Klinik Cheras Baru 35 Klinik Suria (Previously Known As Klinik TVS

Medicare)

Appendices

13 Klinik Dan Surgeri Loo 36 Klinik Uni-Med

14 Klinik Dan Surgeri Mesra Sdn. Bhd. 37 Klinik Zarif

15 Klinik Dan Surgeri Thong 38 Medic Damansara

16 Klinik Famili BTS Sdn Bhd 39 Poliklinik & Dispensari Solaris Sdn. Bhd

17 Klinik Famili Dr Wan Kamariah Sdn Bhd 40 Poliklinik Dan Pembedahan Reiki Baba

18 Klinik Farrali Medicare 41 Poliklinik Kumpulan City

(Dr Chai Dan Rakan-Rakan)

19 Klinik Healthcare Dan Surgeri 42 Poliklinik Lai

20 Klinik Ian Ong 43 Poliklinik Lakshmi

21 Klinik Kaulsay 44 Poliklinik Lean

22 Klinik Keluarga 45 Poliklinik Ren Ai Bukit Maluri

23 Klinik Khor 46 Poliklinik Soo & Tan

Sivasampu SWahab YF

Ong SMIsmail SA

Goh PPJeyaindran S

Documents

CRC - Sivasampu S Wahab YF Ong SM Ismail SA Goh PP ......Sivasampu S, Wahab YF, Ong SM, Ismail SA, Goh PP, Jeyaindran SNational Medical . Care Statistics (NMCS) 2014. Kuala Lumpur: