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The Use of Preventive Services by the Elderly

January 1989

NTIS order #PB91-192880

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FOREWORD

Interest in health promotion and disease prevention strategies for the elderly has grown inthe last ten years, partly as a result of advancing knowledge in these areas and partly due to the

search for ways to moderate the rising cost of health care in this growing segment of the popu-lation. Reflecting this interest, the House Committee on Ways and Means requested that OTAanalyze the effectiveness and costs of providing selected preventive health services to the elderlyunder the Medicare program. The Senate Labor and Human Resources Committee has also re-quested that OTA provide information on the value of preventive services for the Americanpeople.

This Staff Paper, The Use of Preventive Services by the Elderly, is the second in a series of papers being prepared in response to these requests. Understanding the use of preventive ser-vices by the elderly is an important component of assessing their effectiveness as Medicarebenefits. In this paper we review both new and previously published data on the proportions of elderly currently receiving a variety of preventive health services; we examine factors associatedwith whether the elderly receive these services; and we analyze the likely implications for

Medicare if preventive health services were offered as covered benefits.

The first paper in this series on “Preventive Health Services Under Medicare” examinedglaucoma screening as a potential- Medicare benefit. Subsequent papers will assess screening forcholesterol, cervical cancer, and colorectal cancer, and will analyze broad issues related toMedicare financing of preventive services for the elderly.

u JOHN H. GIBBONSDirector

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The Use of Prevent ive Servic es by the Elderly

by

Michael E. Gluck

Judith L. WagnerBrigitte M. Duffy

Health ProgramOffice of Technology Assessment

Congress of the United StatesWashington, D.C. 20510-8025

January 1989

A Staff Paperin OTA’s Series on

Preventive Health Services Under Medicare

Carol Guntow prepared this Staff Paper for publication.

The views expressed in this Staff Paper do notnecessarily represent those of the TechnologyAssessment Board, the Technology AssessmentAdvisory Council, or their individual members.

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CONTENTS

Chapter Page1. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....... .

1

2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 5

Types of Preventive Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Preventive Services and Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3. Recommendations of Professional and Expert Groups for the Use of Preventive Services by Older Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

4. What Percentage of the Elderly Use Preventive Services? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Sources of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Estimates of Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

Use of Multiple Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Time Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

5. What Factors Promote or Inhibit Elderly People’s Use of Preventive Services?q. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Theoretical Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Evidence on Patient Behavior. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Evidence From Studies of Health Care Provider Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

6. Implications for Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Potential Medicare Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Delivery of Preventive Services for the Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

AppendixA. Advisory Panel-- Project on Preventive Health Services Under Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

B. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34

C. Empirical Studies of the Use and/or Determinants of Use of PreventiveServices by the Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

D. Empirical Studies of the Use and/or Determinants of Use of Preventive

Services by the Non-elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

38E. OTA Analysis of Preventive Service Use By the Elderly Using Data from

the 1982 National Health Interview Survey. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

F. Analysis of Preventive Service Use By Older Adults in a HealthMaintenance Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......... 59

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .........60

TablesTable Page

1. Selected Potential Clinical Preventive Services for the Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2. Published Recommendations for the Use of Selected Preventive Services

by Older Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83. Percent of Elderly People Receiving Preventive Services Within Specified

Periods of Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4. Percent of Persons Over 65 Using Multiple Preventive Services fromthe 1982 National Health Interview Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

ii

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CONTENTS (cent’d)

5.

6.

7.

8.

9.

10.

11.12.

13.

14.

Trends in the Percent of Adults or Older Adults Ever HavingReceived Selected Preventive Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Selected Factors Hypothesized to Affect Use of Preventive Services bythe Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Significant Predictors of Use from OTA Multivariate Logit Analysis of 1982 National Health Interview Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Periods of Time Used by OTA and Two Studies to Measure Older Adults’ Useof Preventive Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471982 National Health Interview Survey: Selected Descriptive Statisticsfor Persons Over 65 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Elderly Use of Five Screening Services: Logistic Regression Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Correlation Matrix for Variables in Logistic Regression Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Effect of Statistically Significant Binary Variables in LogisticRegressions on Elderly Use of Five Screening Services: PredictedProbabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Sample Sizes for Each Measurement Period in OTA’s Analysis of PreventiveService Use in One HMO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Percents of Continuously Enrolled HMO Members Receiving Eight PreventiveServices During Specified Periods of Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Figure1. Effect of 2. Effect of 3. Effect of 4. Effect of

PageAge on Use: Predicted Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , 54Income on Use: Predicted Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Education on Use: Predicted Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Bed Days on Use: Predicted Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

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1. SUMMARY

In recent years, clinicians, academics,and policy makers have begun to examine thepotential benefits of services to promotehealth or to prevent disease, disability, ordeath in the elderly. Although Medicare, theFederal program responsible for paying the

bulk of the noninstitutionalized elderly’shealth care bills, currently pays for few pre-ventive services, Congress has severalproposals pending to expand Medicarecoverage of these procedures. In this paper,OTA examines the implications of potentialMedicare coverage for the use of preventiveservices by analyzing current use and thedeterminants of that use.

How Many Elderly Use PreventiveServ ices?

OTA found few sources that measure theuse of preventive services by the elderly.The data that are available (summarized intable 3 in the text of the paper) suggest twomain

s

•

conclusions:

The use of preventive services by theelderly varies according to the type of service from a low of 20 to 30 percentfor routine fecal occult blood testing insome sites to a high of 93 percent forblood pressure measurement. These dif-ferences cannot be explained by dif-

ferences in the periods of time overwhich use is measured.Rates of use of specific services show ahigh level of consistency across studies,despite differences in methods.

Trends in available data suggest that theuse of these procedures has increased over thelast 15 years. Data also indicate that if anelderly person receives any preventive ser-vices, he or she is likely to receive multipleservices.

Whic h Elderly Use Prevent iveServices?

Studies to isolate factors associated withthe use of preventive services fall into twocategories:

those that focus on the behavior of patients, and

q those that focus on the behavior of health care providers and organizations.

Most of the studies in both of these categori-es examine preventive service use among thenonelderly. An analysis of data for the over-65 population in the 1982 National Health In-terview Survey (NHIS) found that, controllingfor other factors, the probability that anelderly person used each of five selected pre-

ventive services--glaucoma screening, eye ex-ams,ares,to:

q

s

•s

s

s

blood pressure measurement, breast ex-and Pap smears-- was consistently related

being male (for the three services avail-able for both men and women),being younger (although still over-65),having more education,having greater family income,having some health insurance in additionto Medicare,living in a metropolitan area, and

having spent more days in bed duringthe previous year.

OTA found that receiving health care througha prepaid health plan was not related to theuse of any preventive service. However, sofew people in the study sample belonged toprepaid plans that it may not have been pos-sible to find a statistically significant effect.Race, living alone, and having some limita-tion in activity had no clear or consistent ef-fect on the use of the five services studied.

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2 • The Use of Preventive Services by the Elderly

Other studies of the relationship betweenpatient characteristics and the use of pre-ventive services have had similar findings.

Among health care providers, physiciansplay a key role in the provision of preventiveservices. The evidence suggests that gaps ex-ist between physicians’ knowledge and ex-perts’ recommendations on the use of pre-v e n t i v e s e r v i c e s a s w e l l a s b e t w e e nphysicians’ knowledge or beliefs and actualpractice. These gaps may be more prominentin relation to elderly patients. While theymay suggest a shortcoming in physicians’ per-formance, they could also indicate thatphysicians take individual patients’ situationsinto account when ordering preventive ser-vices.

Other insights into the importance of health care providers in determining whetherthe elderly receive preventive services comefrom trials designed to improve compliancewith expert recommendations. These studiesindicate that health care organizations canorganize themselves to affect the percentageof individuals receiving such services.Strategies suggested in the literature worthyof further study include:

targeting groups in need of prevention,using non-physician medical profes-sionals to deliver services, andgenerating reminders to physicians and

patients about the periodic need for pre-ventive services (especially with the aidof computerized record-keeping sys-tems).

Although OTA’s analysis of preventive ser-vice use showed that health maintenance or-ganizations (HMOs) had no discernible effecton elderly enrollees’ preventive activities, thereview of the literature on provider behaviorindicates that HMOs and other group prac-tices with centralized administration andrecord-keeping may have potential for in-creasing the use of such services.

Implicat ions of MedicareCoverage for t he Use ofPreventive Servic es by the Elderly

The findings of this study have threemain implications for potential Medicarecoverage of preventive services:

s Reducing patients’ out-of-pocket ex-penses for preventive services throughMedicare would probably increase thepercentage of elderly receiving pre-ventive care. For four of the five ser-vices examined in detail by OTA, hav-ing some insurance coverage beyondMedicare is associated with about a 10percent increase in thereceiving each service.

However, there are threefinding:

(1) OTA’s analysis measured the

likelihood of

caveats to this

(2)

(3)

p r e s e n c e o f i n s u r a n c e t h a treduced patients’ total out-of-pocket health care expenditures,not direct coverage of preventiveservices. The effect of directcoverage on use may be differentf rom the e f fec t observed inOTA’s analysis.

The association between insuranceand use may not always reflect adirect cause and effect. Rather,some people may be likely both tobuy supplemental insurance anduse preventive services out of concern for their own health.

OTA’s analysis suggests that insur-ance coverage alone would not besufficient to induce many elderlyto avail themselves of preventiveservices.

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The Use of Preventive Services by the Elderly Ž 3

Medicare coverage of preventive servicesmay indirectly increase the use of pre-ventive services by raising interest inpreventive care among non-Medicarehealth care consumers, providers, andpayers. Such coverage would, in effect,place the authority of the Federal Gov-ernment behind the covered services.

OTA found no existing data to estimatethe existence or magnitude of thispotential effect.Because large numbers of elderly peoplealready use preventive services, expan-sion of Medicare to cover preventiveprocedures will represent an immediateboost in the program’s financial obliga-tions even if increases in use are mini-mal or nonexistent. While Medicaremay already pay for some screening ser-vices incorrectly labeled as diagnosticprocedures, Medicare coverage would

still transfer a large portion of the cur-rent costs of preventive services frompatients or other payers to the FederalGovernment.

Other Im pl icat ions for Pol icy

Among o ther fac tors impor tant indetermining whether the elderly receive pre-ventive services, a few such as gender, age,education, income, rural or urban residence,and bed days could be useful in helpingpolicy makers target educational efforts on the

need for preventive services to those elderlyat highest risk of not complying with expertrecommendations. The relationship betweenuse and educational level suggests thatpolicy makers should carefully consider themedia they employ to promote preventiveservice recommendations, benefits, and otherprograms they undertake. Pamphlets or other

materials that rely heavily on the writtenword are not as effective for the less well-educated who also have a relatively higherrisk of not receiving preventive procedures.Policy makers could consider using visualmedia to communicate their messages to suchgroups.

Some of the factors important to theelderly’s use of preventive services, such asincome or educational level, are unlikely tobe the focus of policy efforts designed solelyto increase the use of preventive services.

However, changing these factors for someother purpose might result in increases in use.

The analysis in this paper concentrateson those services most often raised in con-gressional discussions of prevention underMedicare--screening and immunizations. Theconclusions presented above may have limitedapplicability to consideration of other pre-ventive services such as health risk appraisals,health education, counseling services, or pre-vention of disability among elderly sufferingfrom chronic disease.

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2. INTRODUCTION

In 1984, personal health care expendi-tures for the 28 million Americans over theage of 65 totaled $120 billion, nearly all of which went toward the treatment of existingconditions rather than to screening for orpreventing health problems (85). Recently,

however, policy makers, health advocates, andmedical practitioners have begun to focusgreater attention upon the potential of pre-ventive medicine for the e lderly. As theelderly population has grown, physicians anddecisionmakers have looked to preventive ser-vices as a possible means of extending life,reducing morbidity and disability, and con-trolling health care costs (67,50). Congresshas recently mandated studies of community-based preventive health service programs forthe elderly and expanded Medicare coverageof certain services, including screening mam-mography and some immunizations (34).

This paper has three purposes:

to summarize existing professionalrecommendations for older adults’ use of preventive health services,to estimate the percentage of elderlywho currently use such services, andto identify the factors related to elderlyindividuals’ use of preventive care withparticular attention to the potential ef-

fects of Medicare coverage.The information brought together in this

paper has two major policy implications.First, in order to estimate the impact of Medicare coverage of preventive services onMedicare program expenditures, one mustknow the number of potential users. Whilecurrent rates of use alone may not adequatelypredict use under expanded third-partyfinancing of preventive services, examinationof existing literature and data provides in-sight into factors associated with use. In par-

ticular, such analysis reveals the relative im-portance of Medicare coverage in removing

barriers to use for elderly Americans.

Planners and administrators of diseaseprevention for the elderly also benefit froman analysis of current use. By understandingthose factors that affect whether older people

accept and receive preventive services, Con-gress may be able to target initiatives wherethey will be most effective or most needed.Where supported by the evidence, this paperpoints out such implications for public policy.

Types of Prevent ive Services

The traditional taxonomy of preventiondistinguishes among primary, secondary, andtertiary prevention (38,56). Primary pre-vention refers to activities designed to avoiddisease or other conditions that adversely af-fect health. Immunizations are one exampleof primary prevention. Secondary preventionincludes efforts to identify existing conditionsthat could cause illness and disability beforethe appearance of clinical symptoms, or tominimize the progression of disease. Diseasescreening is one form of secondary pre-vention. Tertiary prevention refers to effortsto control irreversible chronic conditions inorder to avoid disability or death. Kane, etal., have suggested that this typology does notadequately distinguish among preventive ser-

vices, especially those targeted toward thechronic conditions common among the elder-ly. For example, while diet change can be ameans of primary prevention of hypertension,treatment of existing hypertension is also pri-mary prevention of stroke.

To avoid such ambiguities, this papersimply distinguishes among immunizations,disease screening, and educational or counsel-ing services. Table 1 lists specific examplesof each category of prevention. While the listof services in table 1 is not exhaustive of all

preventive services applicable, it does includethe procedures examined in this paper.

5

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6 s The Use of Preventive Services by the Elderly

Table 1. --Selected Potential ClinicalPreventive Services for the Elderly

Immunizationss I n f l u e n z as Tetanuss Pneunococcuas

Hepat i t i s B

b

Screenings

s

s

s

s

s

s

s

s

s

s

s

s

s

Cancer screening:- B r e a s t c a n c e r ( c l i n i c a l e x a m i n a t i o n ;

mammography)-Colorec ta l cancer (occul t b lood s tool ;

s igmoidoscopy)- C e r v i c a l a n d u t e r i n e c a n c e r ( c l i n i c a l

examinat ion; Pap smear ; endometr ia l b iopsy)- P r o s t a t e c a n c e r ( c l i n i c a l e x a m i n a t i o n ;

u l t r a s o u n d )- S k i n c a n c e r ( c l i n i c a l e x a m i n a t i o n )

Blood pressure measurementVis ion examinat ionGlaucoma screeningH e a r i n g t e s tCholesterol measurement

Menta l s tatus /dement iaOsteoporos is (s tandard x - ray ; quant i ta t ive CT;o t h e r r a d i o l o g i c a l t e c h n i q u e s )Diabetes screeningA s y m p t o m a t i c c o r o n a r y a r t e r y d i s e a s e ( e x e r c i s es t r e s s t e s t )Dental health assessmentM u l t i p l e h e a l t h r i s k s a p p r a i s a l / a s s e s s m e n tFunc t ional s tatus assessmentDepress ion sc reeningScreening for hyper thy ro id ism

Education and Counselings N u t r i t i o ns Weight cont ro lm Sink ing cessat ions Home safety / in jury prevent ions Stress management

s Appropr iate use of medicat ionss Alcohol uses Ex erc i s e

Abbrev i a t i on : CT =c omputed tomography .aCurrent ly covered by Medicare.Current ly covered by Medicare for h igh r iskp a t i e n t s .

SOURCE: Off ice of Technology Assessment , 1989.

Preventive Services and Medicare

In defining preventive services andmeasuring their use, this paper focuses on the

implications for their potential coverage un-der Medicare.

This perspective limits the preventive inter-ventions analyzed to personal health servicesoffered to individuals. This review does notexamine mass media education programstargeted toward the elderly.

As enacted in 1965, Medicare covered nopreventive services. It paid for procedures ona “diagnostic” basis only--that is, when thepatient has a symptom or a previous diagnosisfor a condition. However, because treatmentof most diagnosed conditions is covered,Medicare does pay for much tertiary pre-vention designed to control existing chronicconditions. In addition, some physiciansprobably receive payment for screening ser-vices they incorrectly label as “diagnostic.”The extent of this de facto coverage of pre-vention has gone unmeasured.

In recent years, however, Congress hasincrementally added coverage of some im-munizations and screening services. Theseinclude hepatitis B immunizations for benefi-ciaries at high risk of contracting the diseaseand pneumococcal pneumonia vaccinationsf o r a l l b e n e f i c i a r i e s . T h e M e d i c a r eCatastrophic Coverage Act of 1988 (PublicLaw 100-360) includes coverage of up to $50for biannual screening mammographies be-ginning in 1990. In addition, Congress hasmandated that the Health Care Financing Ad-

ministration (HCFA) fund demonstrations of influenza immunization coverage, and of therapeutic shoes for diabetics, and severalcommunity-based demonstration projects toanalyze health outcomes and costs associatedwith the provision of screening, health riskappraisals, education, and counseling toMedicare beneficiaries,

Additional proposals brought before the100th Congress included coverage of Papsmear screening for cervical cancer and aphysical examination with medical history

upon enrollment in Medicare or on a periodicbasis.

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3. RECOMMENDAT IONS OF PROFESSIONA L A ND EXPERTGROUPS FOR THE USE OF PREVENTIVE SERVICES

BY OLDER ADULTS

One way to measure the use of pre-ventive services is to compare the actual be-havior of individuals with the frequency of u s e r e c o m m e n d e d b y e x p e r t g r o u p s .

Numerous groups have provided recom-mendations about the periodicity with whichthe elderly should receive particular im-munizations and screening services. In inter-preting the medical evidence on frequency of use, these expert groups vary in the criteriathey employ in developing recommendations.

Table 2 summarizes several selected setsof recommendations made by professional orexpert groups for older adults, primarily forthose over 65 years old. The summary is notcomprehensive; rather it includes a range of

views on the use of preventive services ana-lyzed in this paper.

The most comprehensive guidelines comefrom the two governmental task forces. Overthe last ten years, the Canadian Task Forceon the Periodic Health Examination has ana-lyzed medical evidence about the effective-ness of preventive services and made recom-mendations for Canadian citizens ( 18). TheU.S. Preventive Services Task Force hasengaged in a similar exercise and recentlypublished some of its findings. The task

force will publish its full report in 1989(39,43,79).

Among other U.S. governmental organi-zations, individual institutes within the Na-tional Institutes of Health (NIH) have maderecommendations for cancer and coronary

heart disease screening (37,77,78). Some of these recommendations result from intramuralefforts within NIH, while others are the pro-duct of consensus development conferencesthat bring together experts and interested or-ganizations. Additional guidelines come fromprofessional societies such as the AmericanCollege of Physicians (4,5), the AmericanMedical Association (68), the AmericanAcademy of Ophthalmology (2), the Amer-ican Optometric Association (9), the Amer-ican College of Obstetrics and Gynecology(42), and the American College of Radiology

(6) as well as health consumer organizationssuch as the American Cancer Society (3), theAmerican Society to Prevent Blindness (10),and the American Heart Association (8). Astable 2 indicates, there is nearly completeagreement among the included groups makingrecommendations for immunizations for theelderly. For screening services there is a highdegree of consistency among groups, butsome disagreement does exist.

7

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T ab l e 2 . - - P u bl i s h e d R e co mme n d a t i o n s f o r t h e Us e of S el e c t e d Pr e v e n t i v e Se r v i c e s by Ol d e r Ad u l t s

Pr e v e nt i v e P r o f e s s i o n als e r v i c e CD C a

C o n s u m e rA CP

bNI H

cCT F d

USPST F e s oc i e t i e sf

o r g an i z a t i o n s 9

T e t a n u s B oo s t e r e v e r y 1 0 B oo s t e r e v e r y 1 0 B o o s t e r ev e r y 10 B o os t e r e v e r yi mmu n i z a t i o n y e a r s i f p r i ma r y y e a r s y e a r s 1 0 y e a r s

s e r i e s h a s b e end o n e

- - - - - - - - - - - - - - - - - - - - - - - - - - - - . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . - - - -

P n e u m o c o c c a l Ov e r ag e 6 5 - - o nc e Ov e r a ge 65 - - o n c e Hi g h r i s k O v e r age 65--i mmu n i z a t i o n p a t i e n t s - - o n c e o n c e- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

I n f l u en z a Ov e r a g e 65-- Ov e r a g e 6 5 - - O v e r age 65--i mmu n i z a t i o n e v e r y y e a r e v e r y y e a r e v e r y y e a r- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - , . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Oc c u l t b l o o d i n NCI : o v e r a g e A CS : o v e r a g es t o o l 5 0 - - e v e r y y e a r 5 0 - - e v e r y y ea r- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

S i g mo i d o s c o p y NCI : o v e r a g e A CS : o v e r a g e5 0 - - e v e r y 3-5 50--every 3-5y e a r s y e a r s a f t e r 2

n eg a t i v e t e s t s- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Di g i t a l r e c t a l NCI : o v e r a g e N o t r e c o mme n d e d A CS : o v e r a g ee x a m 4 0 - - e v e r y y e a r f o r p r o s t a t e 4 0 - - e v e r y y e a r

c a nc e r ; n or e c o m me n d a t i o nf o r e n l a r g e dp r o s t a t e

s c r e e n i n g- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . . . - - - - - - - - - - -

Cl i n i c a l b r e a s t Co n s i d e r ed i n NCI : o v e r a g e E v e r y y e a r f r o m O v e r a g e 4 0 - - A CR: o v e r ag e 3 5- - A CS : o v e r a g ee x a mi n a t i o n c o n j u n c t i o n w i t h 5 0 - - ev e r y y e a r a g e 5 0 t o 5 9 e v e r y y e a r e v er y y e a r ( w i t h 4 0 - - e v e r y y e ar

m a mmo g r a p h y mo n t h l y b r e a s t s e l f - ( w i t h mo n t h l ye x a mi n a t i o n ) b r e as t s e l f -A COG : a d v i s e s e x a mi n a t i o n )

f o l l o wi n g ACSg u i d e l i n es

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . - . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

M a mm o g r a p h y S ay s s c r e e n i n g NCI: o v e r a g e B e t w e e n a g e s 5 0 O v e r a g e 5 0 - - A CR: o v e r a g e 5 0 - - A CS : o v e r a g ewi t h ma mmo gr a p h y 5 0- - e v e r y y e ar a n d 5 9- - e v e r y e v e r y y e a r e v e r y y e a r 5 0 - - e v e r y y e a ri s e f f e c t i v e ; y e a r A COG : a d v i s e sd o es n o t s p e c i f y f o l l o wi n g ACSf r e q u e n c y o r w h en g u i d e l i n est o s t a r t ; s a y s A MA : b e t w e e n a g e s 4 0s c r e e n i n g w o me n a n d 49 - - e v e r y o n e t oa g e d 5 0 t o 5 9 t w o y e a r s ; a g e 50s a v es l i v e s a n d ov e r - - e v e r y y e a r

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T a b l e 2 . - - P u bl i s h e d R ec o mme n d a tions f o r t h e Use o f S e l e c t e d Pr e v e n t i v e Se r v i c e s b y Ol d e r Ad u l t s ( C o nt i n u ed )

P r e v e nt i v e P r o f e s s i o n a l C o n s u m e r

s e r v i c e CD Ca

A CPb

NI Hc CT F d U S P S T F

e

s o c i e t i e sf o r g a ni z a t i o ns

P a p s m e a r MCI : o ve r ag e 1 8 E v er y 5 y e a r s A C O G, A M A , A N A , A CS : s u p p o r t s

o r i f s e x u a l l y f r o m ag e 3 5 t o A A F P , A N D A WJ A : NCI g u i d e l i n e s

a c t i v e - - 3 a g e 6 0 ; s c r e e n i ng s u p p o r t N CIc o n s e c u t i ve s h o u l d c o n t i nu e g u i d e l i n e sa n n u a l P a p s me a r s i f p r i o r s me a r sa n d pe l v i c e x a ms h a v e b e e n

wi t h n e g at i v e a b n o r ma lr e s u l t s , t h enl e s s f r e q ue n t l ya t d i s c r e t i o n o f

p hy s i c i a n- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . - - - -

Ch o l e s t e r o l NH LB I : o v e r a g es c r e e n i n g 2 0 - - e v e r y 5 y e a r s

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . . - - - - - - - - - - - - - - - - . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . . . . - - - - - - - - - -

S e r u m g l u c o s e N o t r e c o mme n d e dwi t h o u t f a mi l yh i s t o r y o f

d i a b e t e s o rp r e v i o u sc i r c u l a t o r yp r o b l e ms

---- ----- ----- . . . . . ----- ----- ----- . . . . . ----- ----- ----- ----- ----- ----- . . . . . ----- ----- ----- ----- ----- ----- -

B l o o d p r e s s u r e N HL B I : o v e r a g e Ov e r a g e 6 5 - -1 8 - - a t l e as t e v e r y 2 y e a r se v e r y 2 y e a r s ,d e p e nd i n g

p r e v i o u s r e a d i n g

---- ----- ----- ----- . . . . . ----- -.

A HA : s u p p o r t sN H L B Ir e c o m me n d a t i o n s

- - - - - - - - - - - - - - . . . . . - - - - - - - - - - - .

A DA : p e o p l e a tr i s k s h ou l d b es c r e e n e d ( n o

f r e q u e nc ys p ec i f i e d )A HA : e v e r y 5y e a r s f r o m a g e2 0 t o 7 5 ;o pt i o n a l a f t e ra g e 7 5 i fb a s e l i n e s a r eu e l l - d o c u me n t e d

---- ----- ----- ----- ----- ----- ----- ----- ----- -----A HA : e v e r y 5y e ar s s t a r t i n ga t a g e 2 0

---- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- ----- . . . . . ----- ----- ----- ----- ----- .

EK G R e c o m me n d e d f o r A HA : a t a g e s 2 0 ,

s y mp t o m a t i c 4 0 , a n d 6 0

a d u l t s o nl y- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

V i s i o n No t r e c o mme n d e d A OA : o v e r a g e A S P B : o v e r a g ee x a mi n a t i o n 4 0 - - e v e r y y e a r 3 5 - - e v e r y 2 y e a r si n c l u d i n g MO: o v e r a g eg l a u c o ma 4 0 - - e v e r y 2 t o 5s c r e e n i n g b y

t o n ome t r yy e a r s

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

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10 H The Use of Preventive Services by the Elderly

,,

II

aL

0

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4. WHAT PERCENTAGE OF THE ELDERLY USEPREVENTI VE SERVICES?

While a large empirical literature existson the use of medical services in general, fewstudies concentrate on preventive services andfewer still analyze use of these services bythe elderly .1 Apart from the analyses pre-

sented for the first time in this paper, onlynine studies offer empirical evidence aboutthe use of preventive services among olderadults. Appendix C summarizes the scopeand methods of each of these studies.

Because of the small volume of researchexamining preventive service use by theelderly, this paper also draws upon empiricalinvestigations of use by the non-elderly. Ap-pendix D describes 35 studies in thiscategory. Several of these studies examinehow age affects the use of preventive services

and offer insight into the behavior of olderpatients in seeking out such care.

Sources of Dat a

Table 3 presents comparative estimates of the percentages of elderly people using 17preventive services within specified periodsof time. Three of the seven sources containnational estimates. OTA analyzed data fromthe 1982 National Health Interview Survey(NHIS). (See appendix E for a description of the NHIS.) Results of this analysis, showingthe percentage of the elderly who havereceived five preventive services--glaucomas c r e e n i n g , eye exams, b lood pressuremeasurement, breast exams, and Pap smears --within periods of time roughly similar to theintervals suggested by expert groups areshown in the sixth column of the table.

1 Many studies have been carried out on the use andc o r r e l a t e s o f u s e o f n o n - p r e v e n t i v e medica[ s e r -v i c e s a n d de n t a l c a r e b y t h e e l d er l y . H o we v e r ,

b e c a u s e t h e p u r p o s e , n a t u r e , a n d l i k e l yd e t e r m i n a n t s o f u s e o f t h e s e s e r v i c e s d i f f e rm a r k e d l y f r o m t h o s e o f p r e v e n t i v e h e a l t h s e r v i c e s ,such studies are not reviewed i n t h i s p a p e r .

The second source of national estimatesin table 3 comes from a survey conducted bythe Gallup Organization every 3 or 4 yearsfor the American Cancer Society (ACS). Thishousehold, mail survey examines individuals’

knowledge of cancer risk factors and the fre-quency with which they receive certainscreening tests (28). Gallup publishes resultsby gender, age, and selected demographicvariables. Although the study does not pre-sent findings for Medicare-eligible respon-dents as a separate group, it does give resultsfor individuals over 50 years old.

These two studies rely on respondents’self-reported behavior, which may affect theaccuracy of the estimates. The direction of this potential bias is unclear. On the one

hand, lack of familiarity with medical ser-vices may cause respondents not to know thatthey had received a given service, and hence,to underreport use. On the other hand,respondents may perceive preventive behaviorto be socially desirable and may inflate theuse they report to the interviewer. The rela-tive importance of each of these biases in af-fecting the estimates is unknown.

The third national data source is the U.S.Immunization Survey conducted annually bythe Centers for Disease Control (CDC) until1985. A household survey, it provides dataon the percentages of individuals immu-nized against influenza and pneumococcalpneumonia, broken down by age (includingpeople over 65)(26).

Another set of estimates, found in theseventh column of table 3, comes from alarge, urban “closed-panel”* health main-tenance organization (HMO). This HMO pro-

2 In a ‘c losed panel” H M O , e n r o l l e e s m u s t r e c e i v eh e a l t h c a r e f r o m a p h y s i c i a n e m p l o y e d d i r e c t l y b yt h e HMO u s u a l l y i n a c l i n i c r u n b y t h e o r g a n i z a -t i o n .

1 1

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12 Ž The Use of Preventive Services by the Elderly

Table 3--- Percent of Elderly People Receiving PreventiveServices Within Specified Periods of Time

Studya

Ser v i c e ACSb Brown c CDCd Chao e Lazaro f OTA g OTA h Runda l l i Winawer j

Blood pressureMen 93 91

Women 93 92

- - - - - - - - - - - - - - - - - - - - - - - - - - . . . . . . . . . . . . . . . wk . . . . . . . . - . . . . . . :2 . ! : ? . . . . . . . . . . . - - - - - - - - -. . . . . . . . . . . . . . . . . . . . . . . .

Breast examWomen 48 53

( I < y r ) ( <2 y r ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . . . . . . . . .

B r eas t se l f - examWomen

Month ly o r more f requent ly 3 7L e s s f r e q u e n t l y 39

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cho les te r o lMen 75

Women 73( 5 y r )

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Complete check-up By age, not sex:Men 62 60-74=45 49Women 67 75+=24 51

( < l y r ) ( W A ) ( 1 y r ).--... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Eye examinat ionMen 73 72

Women 76 75(<3 yr) (2 yr)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Feca l occu l t b loodMen 20 30 49

Women 19 29 52 70-80

.. ......-...............!!. !!?.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... .. -:: -![!...: N ! A ? . . . - - - - - - -To ta l

. .

Glaucoma screeningMen 64Women 70

( <3 y r ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

I n f l u e n z a v a c c i n eMen 23 58Women (both sexes; 57

1 y r ) ( 1 y r ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

MammographyWomen 6 11

( e v e r ) ( 1 y r ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Pap smearWomen 60 63 50 71

( <=3 y r ) ( 1 y r ) (<4 y r ) ( 3 y r ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .-

Pneumococca l vacc ineMen 11 3 8

Women (both sexes; 301 y r ) ( ev e r )

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

(Cont’d)

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vialed OTA with data on the percentages of adults in various age categories who receivedeach of nine preventive services within peri-ods of time specified in table 8. (See appen-dix F for a more complete discussion of thedata and estimation methods.)

Unlike the three national surveys, these

estimates come directly from the provider’srecords, thus avoiding the potential in-accuracies of self-reported data. However,the population from which the HMO data aredrawn is probably not representative of thenational experience or even of other HMOs.The elderly enrolled in this single prepaidplan may be different from the total elderlypopulation in the HMO’s market area as wellas the elderly population of other areas. Inaddition, HMOs in general tend to providebetter coverage of preventive services than doother insurance plans (46). ‘ This HMO inparticular engaged in activities to promote theuse of some preventive procedures. All of these potentia l distor t ions suggest thatestimates from this HMO are probably in-dicative of the upper bound of use attainableunder Medicare coverage rather than nationalestimates of current use.

In the four remaining sets of data pre-sented in table 3, estimating use was not theauthors’ primary objective. One paper was acase-control study of breast cancer in elderly

women (15). Another looked at the rela-tionship between screening and disease prog-nos is for co lorec ta l cancer . The th i rdexamined factors associated with swine fluvaccination during the predicted epidemic of 1977 and 1978 (59), and the fourth presentsself-reported data from a retirement com-munity about respondents’ most recent use of five preventive services (19).

Estim ates of Use

Because of some overlap in the services

examined in the seven studies discussedabove, one can compare different estimates of use of the same services. These proceduresare general examinations, fecal occult blood

screening, mammography, breast examina-tions, Pap smears, eye examinations, andblood pressure checks. For four services, theestimates of use are consistent across datasources. About 92 percent of the elderlyreport having their blood pressure checkedwithin a l-year period and 74 percent reporteye examinations within the previous 2 years.

Although estimates for Pap smear use show abit more variation across studies, the rangeruns only from about 50 percent of elderlypeople in the NHIS sample to 71 percent inthe HMO data.

Differences in the periods of time overwhich researchers measure use do not accountfor the variation in estimates that does exist.For example, the ACS estimate of Pap smearuse within a 3-year period is actually higherthan the NHIS estimate that examines a peri-od of up to 4 years. Hence, these differencesreflect either different populations or dif-ferent survey methods.

Despite some consistency across studiesfor the same service, there is little similarityin rates of use across different services. Forexample, while less than 15 percent of theelderly report having had annual rectal ex-ams, 92 percent report an annual blood pres-sure check. Estimates for the remaining ser-vices fall within this wide range. Thesedrastic differences in rates of use suggest that

preventive services are more different fromone another than they are alike. Severalstudies discussed later in this paper have ex-amined these differences.

Use of Multiple Services

Measuring the percentage of elderly in-dividuals who receive multiple preventiveservices provides a slightly different profileof individuals’ preventive behavior than isrevealed by examining one service at a time.As indicated in table 4, a majority of elderly

persons report receiving all three services thatboth sexes can receive (glaucoma screening,eye exams, and blood pressure measurement).One-quarter of men and one-fifth of women

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report receiving one or fewer of the threeservices. The extremely small percentageswho report using no services reflect the al -

most universal measurement of blood pres-sure. Looking only at women and includingthe two additional services they can receive(Pap smears and breast exams) reveals thatonly 13 percent report using none or one ser-vice. However, only 30 percent report usingall five services. These data indicate a greatdeal of variation in the number of serviceselderly people receive. In the only otherstudy to examine multiple preventive serviceuse, Calnan found that among middle-agedwomen, the probability of using one servicedoes not predict whether an individual usesothers (17).

T ime Trends

The differences in trends between theACSsible

q

s

and NHIS data sources have several pos-explanations:

Only Pap smears and breast exams over-lap the NHIS and ACS surveys. Thedifferences between the two data sourcescould be due to different trends in the

particular services each survey exam-ined.NHIS estimates are for individuals over65 years old, while the ACS data are forwider age ranges. If the trend in theNHIS applies only to the elderly, the in-clusion of non-elderly people in theACS samples might obscure this trend.

Table 4--- Percent of Persons Over 65 UsingMultiple Preventive Services (From the 1982

National Health Interview Survey)a

The ACS and NHIS data allow examina-tion of time trends in self-reported use of several services over the period from 1973through 1987. As shown in table 5, the per-centage of older Americans who report ever having received these preventive servicesgrew over the periods measured. Usingidentical questionnaires, the NHIS showedsubstantial increases in the use of seven ser-vices between 1973 and 1982 (72,75).

The trends in the ACS data are not quite

as dramatic (28). Some procedures show littlechange between 1980 and 1983 with five ser-vices showing a decline in use. The declinesbetween 1980 and 1983 most likely reflectsampling error. While all of the tests exceptdigital rectal exams for women increased be-tween 1980 and 1987, the jumps are lessdramatic than those suggested by the NHISdata.

Gl au co ma, B reas t ex am , Pa p s meareye exam and glaucoma, eye examNumber of b lo od P ressu rea and blood pressures e r v i c e s Me n Wo me n Wo me n

Zero 4 3 3One 22 19 10Two 16 13 11

T h r e e 5 8 6 5 2 6

F o u r N/ A N/ A 2 1

F i v e N/ A N/ A 30

Tot al 100 100 100

A b b r e v i a t i o n : N /A = N o t a p p l i c ab l e .a F o r men an d wo men , t a b l e p r e s e n t s p r o p o r t i o n s o f

the noninstitutionalized, civilian, over-65 pop-

u l a t i o n u s i n g n o n e , o n e , t w o , o r t h r e e o f t h ef o l l o w i n g s e r v i c e s - - g l a u c o m a s c r e e n i n g , e y e e x -aminat ion, and b lood pressure measurement- -w i th in

~ t h e p e r i o d s o f t i m e l i s t e d i n t a b l e 8 .Fo r w om en o nl y , t h e t a b l e a l s o p r e s e n t s t h e p r o -por t i ons o f t h i s s am e popu la t i on us ing none , one ,t wo , t h r e e , f o u r , o r f i v e o f t h e f o l l o w i n gs e r v i c e s - - g l a u c o m a s c r e e n i n g , e y e e x a m i n a t i o n ,blood pressure measurement, Pap smears, and breaste x a m i n a t i o n - - w i t h i n t h e p e r i o d s o f t i m e l i s t e d i ntab le 8 .


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Table 5.--Some Trends in the Percent of Adults or Older AdultsEver Having Received Selected Preventive Servicesa

Nat iona l Hea l th b Amer ican Cancer Soc iety /Gal lupInterview S u r v e y Or g a n i z a t i o n s u r v e y

Y e a r Y e a r

Ser v i c e 1973 1982 1976 1980 1983 1987

Check-up 45 42 4 6 4 7(annual)

a( A l l a d u l t s )

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ----

Breast exam(Women 58 74 79 89 81

o n l y ) (Ages 65+ ) (All adult women). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------ ------ ------ -Pap smear 54 79 8 6 84 8 7

(women ( A g e s 6 5+ ) (A l l adul t women)o n l y )

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------ ------ ------ ------ ------ ----- . . . . . . . . . . . . . .

EKG 6 7 82(Ages 65+)

. . . . . ------ . . . . . . ------ . . . . . . . . . . . . ------ . . . . . . . . . . . . ------ . . . . . . ------ ------ ------ ------ ------ ------ ------ -

Eye exam 94

( A g e s 6 5 + ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ----

Glaucoma 56(Ages 65+ )

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- ------- ------- ----

Fecal occult b l o o dMen 17 29 43

Women 20 27 4 7(Ages 50+)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- .

Mammography 43 41 62(women only) (Ages 50+)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- ----

ProctosigmoidoscopyMen 3 7 32 43Women 35 31 42

\ (Ages 50+)

------ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Rectal examMen 54 56 53Women 52 4 7 5 8

(Ages 40+)

Abbrev ia t i on : E K G = e l e c t r o c a r d i o g r a m

W i t h t h e e x c e p t i o n o f t h e m e d i c a l c h e c k - u p , t h i s t a b l e p r e s e n t s d a t a o n t h e p r o p o r t i o n o f i n d i v i d u a l s w h oh a v i n g r e c e i v e d e a c h s e r v i c e . F or me d i ca l c h ec k -u p s , t h e s t a t i s t i c s r e f e r t o t h e p r o p o r t i o n

~who repor t hav ing a regular , annual exam.N a t i o n a l C e n t e r f o r H e a l t h S t a t i s t i c s , U . S . D e p a r t m e n t o f H e a l t h , E d u c a t i o n , a n d Uelfare, Wse o f Se lec tedP r e v e n t i v e S e r v i c e s U.S--- 1973,N Vital and Health Statistics, Series 10, No. 110 (Washington, DC: U.S. Gov-ermnent P r i n t i n g O f f i c e , M a r c h 1 9 7 7 ) ; a n d N a t i o n a l C e n t e r f o r H e a l t h S t a t i s t i c s , U . S . D e p a r t m e n t o f H e a l t had Human S e r v i c e s , Wse o f S e l e c t e d P r e v e n t i v e S e r v i c e s U.S--- 1982,11 Vital and Health Statistics, S e r i e s 1 0 ,No . 1 5 7 ( Wa s h i n g t o n , DC: U. S . G o v e m n e n t P r i n t i n g Of f i c e , A u g u s t 1 9 8 6 ) .

c Ga l l u p Or g a n i z a t i o n , l l T h e 1 9 8 7 survey of publ ic Awareness and Use of Cancer Detec t ion Tes ts : SLm’Iary ofFindings,ll conducted for the Amer ican Cancer Soc iety (Pr inceton, NJ : Gal lup Organizat ion, January 1988) .


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5. WHAT FACTORS PROMOTE OR INHIBITELDERLY PEOPLE’S USE OF PREVENTIV E SERVI CES?

Theoretical Approaches

In addition to providing estimates of thepercentage of the population receiving pre-ventive services, the literature laid out in ap-

pendixes C and D offers insight into factorsassociated with use. These studies representat least two theoretical approaches to explain-ing the use of preventive services: 1) anpreach that emphasizes patient behavior,2) an approach that emphasizes providerhavior.

Patient Behavior

ap-andbe-

Underlying this approach is the assump-tion that the decision to use a preventivehealth service is made by the recipient.

Receipt of these services results from factorsthat influence the decision to seek preventivecare and the patient’s ability to carry out thatdecision. There are two main versions of thisapproach: 1) a model of medical serviceutilization first proposed by Andersen and hiscolleagues (11,12,36), and 2) the Health Belief Model (57,58).

The Andersen Model. --According to thismodel, three types of factors determine anindividual’s probability of using medical ser-vices as well as the volume of use:

P r e d i s p o s i n g v a r i a b l e s i n c l u d edemographic factors and the individual’sbeliefs about the services.Enabl ing var iables that affect thepatient’s ability to gain access to servicesinc lude the indiv idua l ’ s f inanc ia lresources, the availability of the servicesin the individual’s community, and in-surance coverage. Need variables include practitioners’ andpatients’ own perceptions of the patient’shealth status. Poor health status may in-dicate a need for better health care, in-cluding preventive services. Alterna-tively, variables that measure healthstatus may actually be proxies for theneed for nonpreventive health services.

To the extent that the need for theseother services increases contact with thehealth care system, individuals may bemore likely to receive preventive ser-vices that require some health care in-

tervention. Hence, health status vari-ables may enable or predispose individ-uals to receive preventive services byincreasing their contact with the healthcare system.

The Health Belief Model. --This behav-ioral model arose from an attempt by medicalsociologists during the early 1970s to under-stand patterns of preventive health and healthmaintenance (48). It is similar to Andersen’smodel in its focus on the patient. However,it posits that patient beliefs and attitudes are

the most direct determinants of the decisionto receive preventive care. Sociodemographicfactors, characteristics of the health care sys-tem, and other exogenous variables (such aspublic education or illness of a family mem-ber) all indirectly affect preventive behaviorby influencing the individual’s beliefs and at-titudes (57,58).

These attitudinal factors include:

s

s

s

s

the patient’s perceived susceptibility to agiven disease or condition;

the perceived potential severity of thatdisease;the perceived benefit of preventive actionin reducing susceptibility or severity;cues to taking the action such as publiceducation programs, reminders andphysician recommendations; andthe perceived barriers to taking the ac-tion including cost, inconvenience, andembarrassment.

One major limitation of the Health Belief Model in explaining the use of preventiveservices is the lack of data measuring indi-vidual attitudes and perceptions. Only datasets constructed specifically for Health Belief Model analyses are likely to contain the req-uisite information (23,31 ,54).

17

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However, some researchers have used the un-derlying relationships suggested by the HealthBelief Model to design experiments to im-prove preventive behavior among patients(70).

Provider Behavior

While patient behavior models focus onthe consumers of health, provider behaviormodels focus upon providers of such services(86). They suggest that patients receive pre-ventive services as the result of their pro-viders’ decisions to offer, encourage, andenable their uptake. While the patient behav-ior models see patients as active decision-makers, the provider behavior approach seespatients as more passive, less important thantheir providers.

Explanatory studies that use the provider

behavior approach examine the effects on useof health care organization, patient contactwith the health care system, or with differenttypes of health personnel, and providers’knowledge of preventive services (55,92).This approach also underlies experiments anddemonstration projects that try to determinehow the manner in which services are pro-vided can maximize their use. Mass screen-ing programs or trials that employ physicianeducation are examples of these types of studies (20,24,62,74).

Combining the Patient and ProviderApproaches

The patient and provider approachesneed not be mutually exclusive. At leastthree studies have attempted to combine theprovider and patient approaches into a singlemodel (21,29,86). Although each approachplaces emphasis upon different groups of potential determinants of preventive behavior,they may be valid in explaining differentparts of the variation in use. In addition,there is some overlap among the two ap-proaches. Andersen’s enabling var iablesrepresent the same basic ideas that the pro-vider behavior models focus upon. However,in the patient behavior models, characteristics

of the health care system affect individualpatient decisionmaking. Provider behaviorstudies implicitly assume a more passive rolefor patients who respond largely to actions of health providers.

Evidence on Pati ent Behavior

This section describes the results of OTA’s analysis of the 1982 NHIS data set (seeappendix E for detailed discussion of meth-ods) and examines how these results comparewith results of studies listed in appendixes Cand D. While many of the studies in appen-dix D are limited in their implications forelderly use of prevention, they provide ageneral context within which studies of elderly populations can be interpreted.

OTA’s Analysis of the 1982 NHIS

Although the 1982 NHIS does not containall of the variables described in Andersen’sapproach and in the Health Belief Model, itis the most comprehensive existing source of information about the determinants of pre-ventive behavior among the noninstitutional-ized elderly. Table 6 lists potential explana-tory variables included in the NHIS data set.

Table 6. --Selected Factors HypothesizedTo Affect Use of Preventive Services

by the Elderly

P r e d i s p o s i n g f a c t o r s

s G e n d e r

s Ag es Race ( w h i t e / n o n - w h i t e )

s E d u c a t i o n

E n a b l i n g f a c t o r ss F a mi l y i n c o me

s H a v i n g h e a l t h i n s u r a n c e i n a d d i t i o n t o

Me d i c a r e a

s Re c e i v i n g h e a l t h c ar e t h r o u g h a p r e p a i d p l a n

s L i v i n g a l o n es L i v i n g i n a me t r o p o l i t a n a r e a

Me a s u r e s o f h e a l t h s t a t u s

s B e d d ay s i n t h e p r e v i o u s 1 2 mo n t h s

s Ha v i n g s o me l i mi t a t i o n o n a c t i v i t y

aPotent ia l insurance coverage f o r t h e e l d e r l y i n

a d d i t i o n t o M e d i c a r e i n c l u d e s p r i v a t e l y p u r c h a s e dh e a l t h i n s u r a n c e , V e t e r a n s A d m i n i s t r a t i o n o r m i l -i t a r y h e a l t h i n s u r a n c e , o r m e a n s t e s t e d p u b l i ca s s i s t a n c e h e a l t h b e n e f i t s i n c l u d i n g M e d i c a i d .

SOURCE : Off ice of Technology Assessment , 1989.

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The major category of variables missing fromthese data are the health belief variables:patient perceptions of disease threat, per-ceived benefits of preventive services, andperceived barriers to their use.

OTA used weighted logit models toestimate the independent effects of each of

Table 7--- Significant Predictors of Use FromOTA Multivariate Logit Analysis of 1982

National Health Interview Surveya

Glaucoma Eye Blood Pap B reas tV a r i a b l e sc reen i ng exam pressure smear exam

P r e d i s p o s i n g f a c t o r s

1 . S ex ( ma l e )

2 . A g e

3 . Ra c e ( n o n - wh i t e )

4 . E d u c a t i o n

E n a b l i n g f a c t o r s

5 . F ami l y i n c o me

6 . Ha v i n g h ea l t h

i n s ur a n c e i na d d i t i o n t o

Me d i c a r e

7 . R ec e i v i n g h e a l t h

c a r e t h r o u gh

a p r e p a i d p l a n

8 . L i v i n g i n a

me t r o p o l i t a n a r e a

9 . L i v i n g a l o n e

. .

. .

++

++

++

NS

++

NS

Me a s u r e s o f h e a l t h s t a t u s

1 0 . B e d d a y s i n

the prev ious12 months ++

11. Having sanel i m i t a t i o no n a c t i v i t y NS

. .

NS

NS

++

+

++

NS

++

NS

++

. .

++

NS

+

NS

++

NS

NS

NS

++

+

N/A N/A. . . .

NS NS++ ++

++ ++

++ ++

NS NS

+ ++

NS ++

++ ++

NS NS

A b b r e v i a t i o n s : N S = E s t i m a t e d c o e f f i c i e n t o n v a r i -a b l e n o t s t at i s t i c a l l y s i g n i f i c a n t ;N/A = N o t a p p l i c a b l e ; v a r i a b l e n o ti n c l u d e d in model.

aU s e m e a s u r e d a c c o r d i n g t o s t a n d a r d s d e s c r i b e d i nappendix E and in table 8.

Key to symbols:+ = D i f f e r e n c e i n p r o p o r t i o n s u s i n g s e r v i c e s i g -

n i f i c a n t a t 0 . 0 5 l e v e l ( 2 t a i l e d ) , v a r i a b l ep o s i t i v e l y a s s o c i a t e d w i t h u s e

++ = D i f f e r e n c e i n p r o p o r t i o n s u s i n g s e r v i c e s i g -n i f i c a n t a t 0 . 0 1 l e v e l ( 2 t a i l e d ) , v a r i a b l epos i t ive ly assoc iated ~wth use

. = D i f f e r e n c e i n p r o p o r t i o n s u s i n g s e r v i c e s i g -n i f i c a n t a t 0 . 0 5 l e v e l ( 2 t a i l e d ) , v a r i a b l enegat ive ly assoc iated wi th use

. . = D i f f e r e n c e i n p r o p o r t i o n s u s i n g s e r v i c e s i g -

n i f i c a n t a t 0 . 0 1 l e v e l ( 2 t a i l e d ) , v a r i a b l enegat ive ly assoc iated wi th use

S OURCE : Of f i c e o f T ec h n o l o g y As s e s s me n t , 1 9 8 9 .

the variables listed in table 6 on the use of each screening test or examination includedin the NHIS. These models posit that theprobability that an individual uses a pre-ventive service within a specified period of time is a function of the variables listed inthe table. Appendix E describes each modelspecification in greater detail and presents

actual estimates. Table 7 summarizes thestatistically significant predictors of use.

Despite the substantial variation that ex-ists across the five services in the percentageof elderly receiving the specified levels of prevention, the estimated models show a greatdeal of consistency across services in the sig-nificant predictors. Only the use of bloodpressure checks appears different. The anal-ysis suggests that fewer variables are impor-tant in predicting blood pressure checks thanin predicting the other services. This is con-sistent with the relative lack of variation inthe use of this service; over 90 percent of theelderly report having had their blood pressuremeasured within the previous 2-year period.Almost every medical visit includes bloodpressure measurement, and individuals canuse machines found in many supermarketsand restaurants to screen themselves for hy-pertension.

As expected, OTA’s analysis found thatyounger age, more education, and higher in-

come are all consistently associated with ahigher probability of using the five pre-ventive services measured in the NHIS. Forthe three services applicable to both genders,men over 65 are less likely than women of similar age to receive them.

More bed days are consistently related touse of the five services, suggesting that sickerindividuals have greater contact with thehealth care system, and hence, a greater op-portunity to be offered preventive services.The analysis showed no relationship between

limitation in activity and the use of any of the preventive services except for eye exams,where the direction of the association is neg-

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ative, and blood pressure measurement, wherethe direction is positive.l

For all services except blood pressuremeasurement, living in one of the CensusBureau’s Standard Metropolitan StatisticalAreas (SMSAs), which are defined by geog-raphy and population density, is positively

and significantly related to the use of pre-ventive services. In urban communities witha large number of health facilities and per-sonnel, individuals are likely to live closerand have more ways to get to appropriatehealth facilities than their rural counterparts.

Having some health insurance in additionto Medicare is also associated with use. Al-though such “Medigap” coverage (held by 71percent of the elderly in the NHIS sample) isunlikely to pay for preventive services, itdoes lower patients’ out-of-pocket expensesfor medical care, thus making preventive ser-v i c es mo r e a f fo r da b l e. I n a dd it io n, apatient’s willingness to buy such insurancemay indicate a certain concern for his or herown health also found in individuals likely touse preventive services.

Among variables not associated with theuse of preventive services, membership in anHMO or other prepaid health plan is the mostunexpected. Published literature indicatesthat such health care providers are more like-

ly than others to offer preventive services to

] I t i s p o s s i b l e t h a t b e d d a y s a n d l i m i t a t i o n s a r emeasur ing heal th s tatus i n t h e s a me w a y . I f t h e

t wo v a r i a b l e s a r e me a s u r i n g t h e e x a c t s a me i d e a,

t h e l o g i t e s t i ma t i o n p r o c e d u r e wo u l d n o t b e a b l e t o

d i s t i n g u i s h t h e i n d e p e n d e n t e f f e c t s o f e a c h v a r i -

a b l e . T h i s c o u l d l e a d t o t h e i n s i g n i f i c a n t c o e f -f ic ients found f o r t h e l i mi t a t i o n v a r i a b l e . T o

t e s t f o r t h i s p o t e n t i a l p r o b l e m ( mu l t i -

c o l l i n e ar i t y ) , we e x a mi n e d t h e c o r r e l a t i o n b e t w e e n

t h e be d da y s a n d l i mi t a t i o n s v a r i a b l e s . Ue f o u n d a

c o r r e l a t i o n c o e f f i c i e n t o f 0 . 3 1 s u g g e s t i n g t h a t

u h i l e t h e e s t i ma t e d standardemm o f t h e t w o l o g i t

c o e f f i c i e n t s ma y b e s o me wh a t b i a s e d d o wn wa r d ( t h u sc r e a t i n g p ot e nt i a l n on - s i g n i f i c a n c e ) , t h e t wo v ar i -

a b l e s l a r g e l y me a s u r e d i f f e r e n t n o t i o n s o f h e a l t h

s t a t u s .

their patients in hopes of lowering treatmentexpenses (46,54). While OTA’s analysis sug-gest that this relationship may not exist, it isalso possible that the small number of elderlyNHIS respondents enrolled in HMOs did notprovide enough statistical power to detect anactual effect of prepaid membership. In 1982only 2.3 percent (or about 573,000) of the

elderly belonged to HMOS,2 and the NHISsample reflects this relatively small number.

The remaining two variables in the logitmodels are not consistently associated withuse: race is positively associated with glau-coma screening; living alone is positively as-sociated with breast examinations.

Summary of Evidence on the Determinants of Use of Preventive Services

Age. --Age has generally been found tobe a negative predictor of the elderly’s use of preventive services (16,19,69). Studies of younger adult populations have also foundsuch an association (32,44,80,81,81,88). Inthe OTA analysis, all services except bloodpressure followed this pattern.

Two studies have examined the rela-tionship between age and immunization be-havior; neither found any strong associationbetween age and swine flu immunization(22,59). Of the other studies that look at age,

one found a positive correlation with thelikelihood and volume of preventive visits toa single HMO (40). Another study thatlooked only at fecal occult blood screeningwithin a well-defined trial also found no agee f f e c t .

2 Since 1982, the number of Medicare beneficiarieshas g r o wn d u e t o r i s k - a n d c o s t - b a s e d Me d i c a r e

d e mo n s t r a t i o n p r o g r a ms . Un d e r c o n t r a c t wi t h t h eHe a l t h Ca r e F i n a n c i n g A d mi n i s t r a t i o n , e a c h H MO

p a r t i c i p a t i n g i n t h e s e p r o g r a ms a g r e e s t o p r o v i d e

Me d i c a r e b e n e f i t s t o e l i g i b l e e n r o l l e e s . A s o fJ a n u a r y 1 9 8 8 , o v e r 1 . 7 m i l l i o n e l d e r l y w e r e p a r t i c -i p a t i n g i n M e d i c a r e / H M O d e m o n s t r a t i o n p r o g r a m s( 7 1 ) .

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The Use of Preventive Services by the Elderly s 21

Despite these exceptions, the bulk of available evidence suggests that use of pre-ventive services falls with age, especiallyamong the elderly. There are at least threeexplanations for this observation:

As an individual gets older, he or shemay perceive fewer benefits and more

barriers to receiving commonly recom-mended levels of prevention.The observed difference may reflect atendency of individuals who were elder-ly in the early 1980s not to use pre-vention -- a tendency that will disappearamong future groups of elderly. 3 T h ebenefits and availability of most pre-ventive services emphasized today havebeen known for only the past genera-tion. By the time that these services be-came widespread, older individuals mayalready have established patterns of

health care that did not include pre-vent ion. According to this reasoning,succeeding generations may have moreuniform rates of preventive care overthe adult age spectrum.As individuals age, they are more likelyto visit the doctor for diagnostic andtherapeutic services. While they stillmay receive preventive services, theymay not remember that the clinicianperformed these procedures. Preventionbecomes obscured by treatment.

Education .- - All studies of use that have

examined education as an explanatory vari-able have found it to be a statistically sig-nificant predictor of the use of preventiveservices (22,40,6 1,8 1). The more education aperson has, the more likely he or she is to usepreventive services. OTA’s analysis of theNHIS data set conforms to this observation.There are two possible explanations for theassociation between education and use:

s Education may affect the decision to usepreventive services by altering patients’

3 This i s sometimes cat led a “ c o h o r t e f f e c t . ” T h et r e n d d a t a p r e s e nt e d e a r 1 i e r i n t h i s p a p er a r e

c o n s i s t e n t w i t h t h i s h y p o t h e s i s .

perceptions about disease and potentialservices. It increases their generalknowledge and ability to evaluate healthrisks and the net benefits of prevention.In addition, it may increase their knowl-edge of specific diseases, recommenda-t ions fo r p reven t ive serv ices , andsources of care.

Education and prevention are both in-vestments with expected future payoffs(27). Individuals with more educationmay be more oriented toward the futurethan less educated people. Hence, thesepeople tend to seek both education andprevention.

Gender. - - The evidence on the effect of gender on the use of preventive health ser-vices is conflicting. Several studies, includingOTA’s analysis, found a strong significant as-sociation between being female and engaging

in preventive health measures (31,40,41). Ananalysis of swine flu vaccinations, however,indicates only a weak correlation betweenbeing a woman and use (22). On the basis of two services for the elderly (from OTA’sqanalysis) and a few other studies of the wholeadult population, one cannot conclude thatelderly women have a consistently greaterpredisposition toward the use of preventiveservices than do their male counterparts.Even if such a conclusion were empirically

justified, no explanation for this finding isreadily apparent.

Race .- - The relationship between raceand the use of preventive services by theelderly or other adults is ambiguous. OTA’smultivariate logit analysis revealed that elder-ly whites are more likely to receive glaucomascreening than are elderly members of otherracial groups. However, race was not a sig-nificant predictor of any of the other servicesstudied.

Other studies that have looked at the re-lationship between race and the use of pre-ventive services by the non-elderly presentinconsistent results. Four studies found astatistically significant negative association

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between being black or non-white and usingpreventive services (60,62,66,82), but threeother studies found no significant relationship(15,31,44). In one study, the results variedaccording to the preventive service (91). In areview of studies of participation in fecal oc-cult blood screening, Blalock and colleaguesreport similarly inconsistent results of the ef-

fect of ethnicity on the use of this one cancerscreening test and draw no conclusions (14).

Income--- Income is a reflection of theavailability of financial resources to purchasehealth services. Economic theory suggeststhat the consumption of most goods rises withincome. Preventive health services for theelderly may be particularly sensitive to in-come for two reasons. First, unlike acute ill-ness care and even some types of chronic ill-ness care, preventive care can be put off without short-term consequences. Thus, pre-

ventive care may receive a lower prioritythan other types of health care or othernecessary consumption. Second, Medicare,the primary health insurer for the elderly,does not cover most preventive services.Hence, to use such services, the elderly musthave private health insurance (discussed be-10W), wealth, or income to pay the out-of-pocket expenses.

Almost all multivariate studies of pre-ventive use, including the OTA analysis,found that income has a significant positiveeffect in predicting the use of preventive ser-

vices (17,22,31,32,40,41,44). Studies examin-ing only the bivariate relationship betweenprevention and income have also consistentlyfound such an association between preventionand income (54,81,91).

Using Michigan survey data, Rundall andWheeler examined the relationship betweenincome and the use of preventive visits ingreater detail. Their analysis indicated thatalthough income has little direct effect onpreventive use, it indirectly increases thelikelihood of use by altering perceptionsabout health and susceptibility to illness, andby increasing the probability that individualshave a regular source of care (60).

Insurance and Price--- Except for OTA’sanalysis, which found that insurance coveragebeyond Medicare had a consistently positivesignificant effect on the use of preventiveservices, the effect of insurance has not beenstudied in elderly populations. The publishedliterature on adults’ use of preventive servicesgenerally supports the contention that the

out-of-pocket price is a significant negativepredictor of use (16,32,47,61,63,86,91).However, no study has examined the rela-tionship between actual cost to the patientand the use of services.

The po ten t ia l impact o f insurancecoverage on use has important policy implica-tions for consideration of Medicare coverageof preventive services. In assessing the bene-fits and costs of such a decision, one wouldwant to know the number of new users of

covered services as well as the total numberof users. The OTA analysis and otherstudies (16,45) suggest that while insurancecoverage does increase use, a substantial per-centage of individuals do not receive recom-mended levels of preventive care, even in thepresence of generous health insurance. Arecent study that compared the use of threepreventive services-- blood pressure measure-ment, breast exams, and Pap smears--in Can-ada, where preventive services are covered bynational health insurance, and in the UnitedStates found little difference in rates of use

by elderly individuals in the two countries(76). Only breast exams were used withstatistically significantly greater frequency inCanada.

Enrollment in Prepaid Plans.--Exceptfor OTA’s analysis, which found no evidencethat enrollment in HMOs increases the use of preventive services by the elderly, only oneother study has compared preventive care inHMOs with that of traditional insurance plans(66). The researchers in that study foundthat employed adults in a prepaid grouppractice had utilization rates for preventiveservices no different from those of similarindividuals in a Blue Cross plan.

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Living Arrangements and Logistical Bar-riers. --In addition to the financial costs of preventive services, these procedures alsoentail time and transportation costs. Onewould expect the use of preventive servicesto decline as the distance between servicesand an individual’s home or job increases.Two analyses of adult demand for preventive

care in an HMO found that distance to asource of medical care was negatively (butnonsignificantly) related to the probability of use (40,41 ). Two other multivariate analysesthat included indexes of time, transportation,and perceived difficulties in obtaining pre-ventive procedures also found no significantrelationship between these logistical barriersand the likelihood of using preventive ser-vices (16,22).

A less perfect measure of logistical bar-riers to access that may be especially relevant

for the elderly is whether or not the individ-ual lives alone. Living with another personcould either raise or lower the logistical bar-riers to preventive services. An additionalhousehold member could assist an individualin overcoming immobility or distance; on theother hand, i f the addi t ional householdmember is in some way limited in mobility orfunction, the effect on the healthy member’suse of preventive services may be negativesince it may be difficult to leave a dependentpartner to receive preventive care. In OTA'sanalysis of the NHIS data, living alone was a

statistically significant, positive predictor of use for breast exams only.

Geographical Location. --The communityin which an older person lives may affect hisor her access to prevention. In a multivariateanalysis of the effect of geographic locationon use based on the same data set that OTAused (i.e., the 1982 NHIS), Woolhandler andcolleagues found that among middle-agedwomen, nonrural residence had a negative ef-fect on the likelihood of having a glaucomatest but had no effect on the use of hyper-

tension screening, Pap smears, and clinicalbreast examinations (91 ). These results con-flict with OTA’s analysis which found that

people in urban communities use more pre-ventive care than do those in non-urbancommunities. The differences between thetwo studies may be due to several factors:

s

s

Woolhandler, et al., estimated a logitmodel with fewer explanatory variablesand a slightly different distinction be-

tween urban and rural residence fromthat used by OTA;Woolhandler, et al., used a less sophisti-cated method of estimating variancesfrom the complex NHIS sample designthan OTA did;living in a rural area may be less of abarrier for middle-aged women than forthe elderly population in obtaining pre-ventive services.

Health Status. --The evidence on the ef-fect of health status on preventive health ser-

vice use is equivocal. Most multivariateanalyses have found no significant effect of health status on use (19,40,41,44,91 ).4 Exceptfor OTA’s analysis, which found a strongpositive significant relationship betweennumber of bed disability days and use, onlyRundall and Wheeler found that reportingrelatively poor health has a direct positive ef-fect on the likelihood of receiving preventivecare (60). However, variation in measures of heal th s ta tus , model specif icat ions , andsamples make it difficult to draw conclusionsfrom these studies.

A few other researchers have measuredhealth status by the presence of chronic dis-ease. Blalock, et al., reported that having achronic condition increases the likelihood of receiving fecal occult blood screening forcolorectal cancer ( 14). Warnecke, et al.,found a similar association with the probabil-ity of a regular check-up in Illinois adults(86).

d In their multi variate models o f t h e u s e o f p r e -

v e n t i v e s e r v i c e sby

mi d d l e - a g e d w o m e n u s i n g t h e

1 9 8 2 NH I S data, Wool handl er, et a 1., found thatb e i n g h e a l t h y wa s s i g n i f i c a n t l y a n d p os i t i v e l y r e -

l a t e d o n l y t o blood pressure screening.

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Limitations of the Patient Behavior Analysesof Preventive Service Use

The literature and analysis reviewed inthis section suggest at least two major limita-tions of the patient behavior approach to un-derstanding the use of preventive services:

s

s

Existing studies do not account for manyfactors specific to a particular pre-ventive intervention such as patients’perceptions of pain, discomfort, embar-rassment, or complexity of administra-tion that may impinge on the willingnessto use of a particular procedure. Inclu-sion of variables that measure these per-ceptions would be consistent with theHealth Belief Model.The models of use examined in this sec-tion assume that patients themselves de-cide whether to receive preventive care.

OTA’s analysis and most of the pub-lished patient behavior literature do notdirectly examine the role of the primarycare physician and the health care orga-nization in the decision to use services.

Evidenc e From Studies of Heal t hCare Provider Behavior

The Physician

Physicians must perform, supervise, orprescribe most preventive services in orderfor a patient to receive them. In fact, manyadults may depend on their primary carephysician to tell them what types of pre-vention they should receive and how often(92). The literature examining the role of physicians in determining the use of pre-ventive services includes three types of anal-ysis:

s

s

s

comparisons of physicians’ knowledgeabout appropriate prevention with pub-lished sets of recommendations;

analyses of actual physician perfor-mance; andexperiments to increase physician com-pliance with recommended procedures.

Because almost all of the trials designed tonarrow the gap between published recom-mendations and actual practice focus onchanges in health care organization or man-agement rather than just physician behavior,this paper considers studies that fall into thethird category in the section on health careorganization below. None of the published

studies analyzed the elderly as a group sepa-rate from the general patient population.

Physician Knowledge and Actual Prac-tice. -- Woo and her colleagues asked 83physicians in a hospital-based teaching am-bulatory care practice about the frequencywith which they recommend 16 screeningprocedures to different age groups (92).Across all patient age groups and procedures,physicians with less training recommendedwith greater frequency. Doctors with a his-tory of cancer in their families recommended

more frequent sigmoidoscopies and mam-mograms. The mean physician recommenda-tion for preventive use was more frequentthan the mean of published guidelines in 48situations and less frequent in 18 situations.The researchers found close agreement amongthe respondents on Pap smears, blood pres-sure checks, physical exams, and medical his-tories, but wide variation in glucose andcholesterol measurement and mammography.

Almost half the physicians reported thatthey knew they recommended preventive ser-v ices more f requent ly than publ ishedguidelines and cited as reasons patient desiresand the belief that the guidelines are insuffi-cient. Woo suggests that despite recom-mendations published by the Canadian TaskForce and others, the physicians in this studymay believe it better to err on the conserva-tive side by recommending services for whichthe supporting medical evidence of effective-ness is inconclusive.

5 A llsi tuationll is a p a r t i c u l a r screening s e r v i c e

f o r a p a r t i c u l a r a g e g r o u p .

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An analysis of patient records in thesame study found a higher level of physiciancompliance with recommended guidelines forthose services that doctors could order otherhealth personnel to perform, such as labora-tory or radiological tests, than with servicesthat require labor by the primary carephysician, such as sigmoidoscopy and breast

exams. Woo and her colleagues infer that be-cause the patients they surveyed desirescreening with appropriate regularity, the gapin performance must be due to doctors failingto offer prevention according to their own orpublished recommendations. They also sug-gest that rates of use are partially related tothe ease with which physicians can providethem. Other studies support this hypothesisthat variation in the use of different pre-ventive services is a function of character-istics of the services themselves (e.g., patients’pain, discomfort, and embarrassment) (57,

63,65).Another study compared the preventive

care recommendations of 31 physicians prac-ticing general internal medicine in NorthCaro l ina wi th th ree se t s o f pub l i shedguidelines (55). The participating doctorslisted procedures they considered essential toa periodic examination for three age groups(30-39; ages 40-49; and ages 50-59). Amongthe procedures recommended in publishedguidelines but not chosen as essential orroutinely recorded in the medical record by

at least two-thirds of the sample physicianswere hearing exams, vision exams, fecal oc-cult blood tests, lipid profiles, mammographyfor women over 50, immunizations, and ex-ams for hypothyroidism. The North Carolinaphysicians also recommended services notrecommended in the published guidelines, in-cluding thorough examinations of the majororgan systems, measurement of blood ureanitrogen, white blood counts, chest x-rays,and microscopic urinalysis.

Examining the records of 334 patients

visiting the 31 North Carolina internists forgeneral examinations, the researchers foundthat, on average, 59 percent of the procedures

recommended by expert groups were found inthe record. Compliance was greater foryounger patients, a result consistent with theestimates of use of several services reviewedearlier in this paper. The researchers alsofound that compliance was greater forlaboratory and physical examination proce-dures than for medical history and counseling

services and was inversely related to thenumber of expert groups recommending eachprocedure.

Noting that the lowest compliance oc-curred with procedures identified by the Ca-nadian Task Force on the Period Health Ex-amination, one of the recommending bodies,as having strong scientific validity, Rommand colleagues suggest that improving com-pliance requires physician education. In dis-cussing ways to improve compliance, they didnot consider the possibility that physicians

may take into account individual patientcharacteristics and circumstances in decidingnot to provide recommended preventive ser-vices.

In another study, McPhee, et al., foundthat discrepancies exist between AmericanCancer Society (ACS) recommendations forthe use of seven preventive services andphysician performance and that physicianstend to overestimate their own provision of these procedures (51 ). The researchers reportthat physicians cite four reasons most fre-

quently for not providing recommended ser-vices: f o rg e tf u ln es s, l ac k o f t im e, i n-convenience or logistical difficulties, andpatient discomfort or refusal.

One study suggests that physicians maydiffer by specialty in their performance of some preventive services. In a study of Papsmear use by physicians in Maryland, Teitel-baum, et al., found that specialists in ob-stetrics and gynecology (OB/GYN) were morelikely than general practitioners and interniststo encourage patients to receive Pap smears,

to remind patients by mail or telephone to geta Pap smear, and to achieve compliance withtheir recommendations (69).

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Finally, one study currently underwaymay shed additional light on the role andmotivations of the physician in providingpreventive services. Schwartz and Lewis incooperation with the American College of Physicians (ACP) recently surveyed ACPmembers about preventive practices (64). Inaddition to examining the frequency with

which physicians say they perform a numberof services, Schwartz and Lewis will look forrelationships between preventive practices forpatients and demographic characteristics, thephysicians’ experience, and the physicians’preventive practices for themselves.

Health Care Organization

Because physicians work within a largerhealth care system with other practitionersand administrators, it is possible that healthpersonnel and characteristics of the office,

hospital, clinic, group practice, or HMOproviding patients’ care could affect whetheror not older individuals receive preventiveservices. This section considers the rela-tionship between the use of preventive proce-dures and the health care organizations thatprovide them.

Heal th Main tenance Organ iza t ions(HMOs) and Other Prepaid Plans. --Some re-searchers have claimed that HMOs, in gener-al, may promote the use of preventive ser-vices (46). To the extent that HMOs stand to

gain from potential savings in health carecosts resulting from preventive services, theseorganizations would have an economic incen-tive to offer more preventive services. In ad-dition, since visits to HMOs are either free orvery inexpensive, HMO patients may demandmore such visits.

Data from a single HMO that providedOTA with estimates of preventive service usesuggests that these health care providers mayhave the ability to organize themselves toprovide more preventive services than is now

generally received by patients. As table 3above indicates, the rates of use in the HMOwere at least as high as or higher than com-

parable rates of use reported in other studies.Not only has this HMO made preventive carea stated organizational goal, but it has devel-oped management tools to achieve compliancewith some preventive recommendations, in-cluding computer-generated reminders toboth patients and physicians for immuniza-tions. However, these relatively high rates of

use may be achieved by recruiting patientswho already have characteristics that makethem more likely to use preventive care. If the high levels of use found in the singleHMO for which OTA obtained data are re-lated to its organization, it is not clearwhether less centralized prepaid health planssuch as independent practice associations(IPAs) would be able to do the same.

OTA’s multivariate analysis of the 1982NHIS found that the elderly enrolled in anHMO are no more likely to use prevention

than their unenrolled counterparts. Given thesmall number of elderly in HMOsq, however,the NHIS sample may not have been largeenough to detect an actual difference. Withrespect to preventive services other thanscreening, Riddiough, et al., reported mixedevidence about the relative likelihood of HMOs to provide immunizations (54).

Organizational Factors Related to Use---Other characteristics of health providers mayalso affect the use of preventive procedures.For example, the use of non-physician per-

sonnel, cues to compliance such as remindersand media, or health fairs are all organiza-tional strategies that have been employed toincrease the use of preventive services.

One potential mechanism for increasingthe use of preventive services is the healthscreening fair in which participants canreceive selected procedures at a publicizedtime and place. In an analysis of the cost-effectiveness of this screening method, Ber-wick concluded that fairs work best when thetarget population is clearly defined, the

screening tests are appropriately chosen, reli-able and accurate, and the fair provides ap-propriate guidelines for abnormal results,

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follow-up, referral, and treatment (13). Al-though fairs may increase the ability to detectand prevent illness, significant risks may existif screening in the fair setting is relativelyinsensitive or unspecific or does not provideadequate follow-up.

Among interventions designed to increase

patient compliance with recommended ser-vices, Thompson, et al., studied the value of combining talks by physicians and nurses,postcard reminders to patients, and phonecalls to comply with a fecal occult blood test(70). While those receiving any one of theseinterventions had an average compliance rateof 89 percent versus 68 percent among thecontrol group, the reminder postcard was es-pecially cost-effective, raising complianceabout 25 percent to an overall rate of 93 per-cent at a relatively small cost. The talk byhealth personnel, which was somewhat morelabor intensive, increased compliance about13 percent.

McDonald and colleagues found similarresults in another randomized trial. Internsand resident physicians who received com-puter-generated reminders provided 49 per-cent of the preventive services suggested tothem, while physicians in the control groupprovided only 29 percent of the services (49).Among physicians who received the reminderintervention, the researchers found that over-

all attitudes toward the reminder system andwhether the physician read and signed thereminder were statistically significant predic-tors of use, while years of training and facul-ty assessments of the physicians were not.The researchers conclude that noncompliancewith recommendations is an error of omissionthat can be mitigated by technological aids.

In another study, Satarino and colleaguesretrospectively asked patients receiving freebreast cancer screening at two clinics in NewYork City how they learned of the service

and their need to be screened (62). Mostblack screenees with less than a high schooleducation learned of the clinic through tele-vision ads followed by word-of-mouth and

private physician referrals. While this papersuggests that television may be a useful cuein promoting use, it does not indicate howone might reach individuals who were n o t screened at one of the two clinics.

Two studies have tested strategies to in-duce the provision of preventive services to

patients. In one study, four clinics were ran-domly assigned either to participate in a pro-gram that combined physician education witha checklist of services due each patient on themedical record or to a control group. Over a4-month period, the researchers measuredrates of mammography and influenza andpneumococcal immunizations among eligiblepatients in each group. The interventiongroup had significant increases in the use of these services, ranging from 2 to 40 percentover the control group. The researchers alsofound signif icant increases in tests of physician knowledge and attitudes about pre-vention among physicians (20).

In another randomized trial, nurses whoalready routinely reviewed patient charts in auniversity-based internal medicine practicereminded physicians when a patient was duefor particular screening services and im-munizations (24). For patients receiving thenurse-reminder intervention, the researchersfound statistically significant increases inrates of use for fecal occult blood screening

(32 to 47 percent), breast exams (29 to 46percent) and influenza immunizations (18 to40 percent), but not for Pap smears (13 to 14percent). The study represents the only ran-domized experiment to analyze the role of non-physician personnel in providing orboosting the use of preventive services.

Physicians believe that such organiza-tional strategies would improve the use of prevent ive se rv ices . In two s tudies of physician attitudes, researchers conclude thatwhile most physicians see themselves as in-

effective in improving patient compliancewith their recommendations for preventivecare, they believe that they could be muchmore effective if they had more resources at

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their disposal including better training forthemselves and their support staff, improvedreimbursement for preventive services, andbetter educational materials for patients(84,87).

Other research currently underway mayenhance our understanding of the impact of organization on use. The Health Services Re-search Center at the University of NorthCarolina, with funds from the National Cen-ter for Health Services Research and HealthCare Technology Assessment (NCHSR), hasrecently surveyed administrators, medicaldirectors, and staff physicians in 150 largemedical practices of different types (25).While most of the study seeks to identify or-ganizational characteristics that contribute tophysician satisfaction with his or her workenvironment, it will also focus on the partici-pating organizations’ preventive care prac-tices.

Limitations of Evidence About ProviderBehavior

Compared to studies of patient behavior,there are relatively few studies of the struc-ture of the health care system or the role of physicians in the use of preventive services(54), and none focuses exclusively on pre-vention for an elderly population. A newstudy of preventive practices among physi-

cians currently underway may shed morelight on these issues. However, no cur-rent or completed studies to date have exam-ined the role of other potentially importantfactors, including:

potential revenue obtainable from pre-ventive services,potential liability associated with offer-ing or withholding preventive services,andthe degree of management control withinthe health care organization.

The evidence about whether or notHMOs provide greater levels of prevention isambiguous. While HMO enrollees may re-ceive more preventive care than enrollees of other health plans, other predisposing andenabling factors such as gender, education,and income may explain this differential.Controlling for these factors, OTA’s analysisof the NHIS data revealed no effect of HMOmembership on the probability of using fivepreventive services. The data gathered byOTA from one closed-panel HMO suggestthat prepaid health plans may have thepotential to increase the use of preventiveservices among older adults. No data existabout whether other prepaid plans achieve alevel of preventive care comparable to theone OTA examined.

The literature contains several studies of interventions within clinics, ambulatory carepractices, and HMOs designed to promote theuse of preventive services. They suggest thatprovider-based strategies can increase the useof preventive strategies. However, the nar-rowness of these studies indicates the needfor more research. In particular, the existingliterature does not adequately address:

the generalizability of particular inter-ventions to other settings,the most effective means of informingthe public about the need for and

availability of screening programs,the role of non-physician personnel inaffecting patient use of preventive ser-vices, andthe potential of technological advances(e.g., the introduction of computerizedmedical records and new screening tech-nology for the physicians’ offices) in af-fecting patient use of preventive ser-vices.

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6. IMPLICATIONS FOR POLICY

Potential Medicare Coverage

Medicare represents the Federal Govern-ment’s major financial and policy commit-ment to health care . In 1986, Medicarerepresented 58 cents of each Federal dollar

spent on health care and was the source of payment for 29 percent of all expendituresfor hospital care and 21 percent of expendi-tures for physician services (73). The use andcorrelates of use of preventive services forthe elderly have several important implica-tions for the Medicare program.

First, covering preventive services underthe Medicare program would probably bring

about increases in the percentage of elderly

receiving preventive care. However, current

e v id e n c e su g g e s t s th a t r e d u c in g o u t -o f -

pocket expenses for patients is not sufficientto assure compliance with published pre-

ventive recommendations. OTA’s analysis of five preventive services suggested thepresence of insurance beyond Medicare is as-sociated with about a 10-percent increase inthe percentage of elderly receiving each ser-vice during the period of time examined.With the except ion of b lood pressuremeasurement, which almost all elderly alreadyreceive on a routine basis, substantial portionsof the elderly with additional coverage thatdefrays out-of-pocket expenses do not use

each of the preventive services OTA exam-ined. In addition, because the additional in-surance coverage held by Medicare recipientsin most instances excludes preventive ser-vices, the OTA analysis is not a direct test of the impact of coverage of specific procedureson the rates of use of these services.

Other factors enter into the physician’sdecision about whether to offer or providethe service and the patient’s decision aboutwhether to seek or use it. Some of these fac-tors may be amenable to change through pub-

lic policy, while other characteristics describegroups of elderly patients at relatively high orlow risk of not receiving adequate preventivecare.

Second, coverage of preventive services

for Medicare beneficiaries could affect pre-

ventive use beyond the Medicare population

itself. Medicare payment may raise interest

in preventive care among health care pro-

viders and payers by placing the authority of

the Federal Government behind it. In addi-tion, consumers of health care may put more

weight on preventive services in managing

their own health because of the public dis-

cussion and attention focused on Medicare

coverage. None of the data or literature cur-rently available allows OTA to estimate theexistence or magnitude of this potential in-direct effect. A recent analysis of preventiveservices in Canada where such procedures arepaid for by the government revealed rates of use comparable to those in the United States,suggesting that both the direct and indirect

effects of government coverage may be small(76). The Medicare Catastrophic CoverageAct of 1988 (Public Law 100-360) may offeran opportunity to assess the full impact of Medicare coverage of breast cancer screeningfor the elderly by “analyzing trends if the useof this service is monitored.

Third, expansion of Medicare to cover

preventive procedures will represent an im-

mediate boost in the program’s financial ob-

ligations even if increases in use are minimal

or nonexistent. Although gaps exist between

experts’ recommendations and current levelsof use, substantial numbers of elderly stillreceive a variety of preventive services atrecommended frequencies. OTA’s analysisindicated that at least one-half of the non-institutionalized elderly receives each of thefive services examined on a regular basis.For three of these services (glaucoma screen-ing, eye examinations, and blood pressuremeasurement), rates of use were even higher.Estimates of costs attributable to expandedMedicare coverage of preventive servicesmust take account of the program’s obligation

to pay for procedures whose costs are cur-rently borne by other payers. However, someportion of these services are for patients witha related medical history or symptoms and are

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“diagnostic” and already reimbursable underMedicare. It is also probable that somephysicians may categorize some examinationsand screening services as “diagnostic” so thatthe procedure will be covered by Medicare.No existing data from published literature orthe records of the Health Care Financing Ad-ministration (HCFA), the Federal agency that

administers Medicare, indicate what portionof all procedures reimbursed by Medicare areactually for screening purposes.

Fourth, the conclusions of this paperabout the use of medical services such as

sc r e e n in g a n d immu n iz a t io n s ma y h a v e

limited applicability for policymakers consid-

ering Medicare coverage of other preventive

services such as health risk appraisals, edu-

cation, counseling services, or tertiary pre-

vention of disability among elderly suffering

from chronic disease. Many of the services

listed in table 1 could rely on non-physicianpersonnel to a greater degree than do screen-ing and immunization, and patients couldreceive them in a wider array of settings thanthey receive most medical services. Thesecharacteristics suggest that use of preventiveservices not examined in this paper may bemarkedly different from those explored here.Hence, an understanding of the implicationsof Medicare coverage of services other thanscreening and immunizations use would re-quire additional study.

Delivery of Preventive Servicesfor the Elderly

Although one of the major focuses of this paper is the potential impact of insurancecoverage on the use of preventive services bythe elderly, the data and literature reviewedin this paper suggest that other factors arestrongly related to use. This informationwould be useful to public policy makers whoseek strategies for altering the elderly’s use of preventive services. Of the patient and pro-vider characteristics related to use, a few areimmutable, some are amenable to changethrough policy, and others are theoreticallyamenable to change, although the policy in-

terventions to accomplish these changes areunlikely to prove cost-effective.

Public policy cannot affect age, gender,rural versus urban residence, and usually,days spent in bed during the previous year,three factors correlated with the use of pre-ventive services. However , these demo-

graphic and health status characteristics doidentify segments of the population particu-larly at risk of not receiving adequate screen-ing or immunizations. Knowing that onaverage more women than men receive suchcare or that recommended prevention appearsto decline with age and good health may helppolicy makers target some of their preventivecare efforts toward the more vulnerablegroups. Because Medicare is an entitlementprogram available to all persons over 65 whoreceive Social Security, it is an unlikelymeans of focusing efforts on demographically

defined subsets of the elderly population.Nevertheless, other government investmentsin prevention such as mass media campaignsand screening fairs may be able to narrowtheir target. Policy makers who want to bol-ster use among elderly groups unlikely toreceive preventive services may wish to studythe potential costs and effectiveness of suchprograms in detail.

Other factors related to the elderly’s useof preventive care do seem amenable topolicy interventions. Studies that examine

influences on physician behavior suggest thatbetter or more frequent physician educationmay bring about better compliance with pre-ventive recommendations. In addition, evi-dence suggests that record-keeping systemsand reminders to physicians (possibly aidedby computer technology) have positive effectson use. This paper has discussed the poten-tial for insurance coverage to increase some-what the percentage of elderly receiving pre-vention. Government and providers coulddesign policies to bring about these changeswhere they do not already exist.

The relationship between use and pro-vider characteristics is not clear. For exam-

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pie, conflicting published literature and thesmall number of elderly enrolled in HMOsmakes it difficult to determine if the enroll-ment of older adults in prepaid health plansincreases the amount of preventive care theyreceive. Additional research is also needed toestablish the potential of nurses and othernon-physician health professionals in provid-

ing or promoting the appropriate use of pre-ventive services. Previous research suggeststhe substantial contact they have with patientsin an ambulatory care setting, the availabilityof new screening technologies (e.g., instru-ments that can measure cholesterol in aphysician’s office from a finger prick), andthe growth in “health fairs” that provide somepreventive services in alternative settings mayenhance the role of these professionals.

The remaining variables affecting olderindividuals’ use of screening and immun-izations - -educational level and familyincome --are also potentially susceptible togovernment interventions. However, publicpolicies designed to change these character-istics are so much more broadly construedthat they would never be implemented simply

to affect the use of preventive care. If, how-ever, the government decides for some otherreason to promote education or supplementincome among the elderly, long-term in-creases in the use of preventive proceduresmay be an additional benefit.

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Appendix A: ADVISORY PANEL

Marianne C. FahsDepartment of Health EconomicsMt. Sinai Medical CenterNew York, NY

Gordon De Friese, Panel Chair Health Services Research Center

University of North Carolina, Chapel Hill, NC

John FrankDepartment of Preventive Medicine &Biostatistics

University of TorontoOntario, Canada

Gary D. FriedmanEpidemiology and Biostatistics DivisionPermanence Medical Group, Inc.Oakland, CA

Lawrence Gottlieb

Clinical Guidelines ProgramHarvard Community Health PlanBrookline Village, MA

Mary KnappJohn Whitman and AssociatesPhiladelphia, PA

Risa Lavizzo-MoureyGeriatrics ProgramUniversity of PennsylvaniaPhiladelphia, PA

M. Cristina LeskeDepartment of Preventive MedicineSUNY at Stony BrookStony Brook, NY

Donald LogsdonINSURE ProjectNew York, NY

Mildred B. McCauleyAmerican Association of Retired Persons

Washington, DC

Peter McMenaminChevy Chase, MD

Meredith Minkler

Center on AgingUniversity of California, BerkeleyBerkeley, CA

Marilyn MoonPublic Policy InstituteAmerican Associationof Retired Persons

Washington, DC

George MorleyDepartment of Obstetrics/GynecologyUniversity of Michigan Medical Center

Ann Arbor, MI

Gilbert OmennDean, School of Public Health &Community Medicine

University of WashingtonSeattle, WA

George PickettDepartment of Public Health PolicySchool of Public HealthUniversity of MichiganAnn Arbor, MI

Donald ShepardDepartment of Health Policyand Management

Harvard School of Public HealthBoston, MA

Barry StultsDivision of General Internal MedicineUniversity of Utah Medical CenterSalt Lake City, UT

Advisory Panel members provide valuable guidance during the preparation of OTA reports.However, the presence of an individual on the Advisory Panel does not mean that individualagrees with or endorses the conclusions of this particular paper.

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Appendix B: ACKNOWLEDGMENTS

The OTA staff would like to express our appreciation of the following people for theirvaluable guidance. This acknowledgment should not be construed in any way to imply that theindividuals agree with or endorse the conclusions of this paper.

Ronald M. Andersen Charlotte MullerThe University of Chicago Mt. Sinai Medical Center

Chicago, IL New York, NY

Robert Burack Annlia Pajanini-HillWayne State University University of Southern CaliforniaDetroit, MI

Morris F. CohenKaiser- PermananteOakland, CA

Alan GarberNational Bureau of Stanford, CA

Pearl S. GermanThe Johns HopkinsBaltimore, MD

Robert L. Kane

Los Angeles, CA

Penelope PollardMedical Care Program National Health Policy Forum

The George Washington UniversityWashington, DC

Economic Research, Inc. John A. SawyerUniversity of TexasHealth Science CenterSan Antonio, TX

UniversityF. Douglas ScutchfieldAmerican College of Preventive

MedicineUniversity of MinnesotaMinneapolis, MN

Mary Grace KovarNational Center for Health StatisticsWashington, DC

David R. LairsonHealth Science CenterHouston, TX

Angela MickalideU.S. Preventive Services Task ForceWashington, DC

Washington, DC

Stephen J. WilliamsSan Diego State UniversitySan Diego, CA

Steven H. Woolf U.S. Preventive Services Task ForcWashington, DC

Steffie WoolhandlerThe Cambridge HospitalCambridge, MA

Steven MooreOffice of the Surgeon GeneralRockville, MD

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Appendix C: EMPIRICAL STUDIES-DETERMINANTS OFBY THE ELDERLY

OF THE USE AND/ORUSE OF PREVENTIVE SERVICES

35

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Appe ndix D: EMPIRICAL STUDIES OF THE USE AND/ORDETERMINAN TS OF USE OF PREVENTIV ESERVICES BY THE NON-ELDERLY

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wi t h i n f i n i t e h o u se h o l d s i n Oakland City, r e g r e s s i o n a n d p a t h a n a l y s e sp e r i o d ) Mi c h i g a n

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C e n t e r p r e v en t i v e c a r e ; b i v a r i a t e r e l a t i o n s h i p sb et w e en a t t i t u d e s a n d s oc i a l p o s i t i o n

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B r e a s t e x a m 1 y e a r g e n e r a l i n t e r n a l m e d i c i n e me a s ur e i s t h e d i f f e r en c e i n r at e o fI n f l u e n z a i mmu n i z a t i o n 1 y e ar ( f o r 6 5 +) p r a c t i c e d u r i n g t w o l - y e a r c omp l i a n c e wi t h r ec omme n d a t i o n s be t w e en

( o r 1 y e a r f o r p er i o d s ; r a n d o mi z e d t r i a l ; n =4 5 0 e x p er i me n t a l a n d c o n t r o l p e r i o d sa l l s e r v i c e s :n o t c l e a r )

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r e g u l a r me d i c a l a n d de n t a l Oh i o a r e a B e l i e f Mo d e l v a r i a b l e s ( b i v a r i a t e )c h e c k u p s

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p r e v en t i v e p h y s i c i a n v i s i t s i n d i v i d u a l s e nr o l l e d in l a r g e preventive andnonpreventive visits in an

p r e p a i d p l a n ( K ai s e r Po r t l a nd ) HMO a s a f u n c t i o n o f h e a l t h s t a t u s ,d e mo g r a p h i c , i n s u r a n c e, a n d o t h e re c o no mi c v a r i a b l e s

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a n d we i g h t r e d u c t i o n me d i c i n e p r a c t i c e ( 6 1 s t ud y a n d c o mp l i a n c e wi t h me d i c a l i nd i c a t i o n s f or5 4 c on t r o l , r a n d o ml y a s s i g n e d ) p r e v e n t i v e a nd o t h e r p r o c e d u r e s ;

s t u di e d o v e r a 2 - y e a r pe r i o d a na l y z e d t h e co r r e l a t e s o f p h ys i c i a n u sea n d r e a s o n s f o r n o n u s e

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44 The Use O f Preventive Services by the Elderly

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Appendix E: OTA ANALYSIS OF PREVENTIVE SERVICE USE BY. .THE ELDERLY WITH DATA FROM THE 1982NATIONAL HEALTH INTERVIEW SURVEY

Methods

The Data

The National Health Interview Survey

(NHIS) is a representative household surveyconducted annually since 1957 by the U.S.Department of Health and Human Service’sNational Center for Health Statistics (NCHS).In addition to a core questionnaire thatmeasures the self-reported prevalence of var-ious medical conditions, the use of healthservices, general health status, disability, anddemographic characteristics, NCHS adds sup-plemental questionnaires on specific topicsthat vary from year to year. In 1982, theNHIS contained supplemental questionnaireson the use of preventive health services and

the types and degree of health insurancecoverage. Although NCHS has publishedsome data from the preventive services sup-plement in tabular form (75), no publishedwork to date has attempted to use these datato understand what factors are associated withthe use of preventive services by the elderly.OTA decided to conduct such an analysis.

OTA obtained magnetic tapes of the coreand supplemental questionnaire data for the1982 NHIS from NCHS. These data filescontained 103,923 observations reflecting

respondents of all ages with 11,434 observa-tions for individuals 65 years or older. Inaddition to responses to survey questionnaires,e a c h o b s e r v a t i o n c o n t a i n e d a u n i q u eidentifier, variables identifying a stratum andcluster from which it was drawn, and theweights necessary to produce representativeestimates.

Among the variables on the data set,OTA was interested in:

s the amount of time elapsed since therespondent last received each of five

screening services (glaucoma screening,blood pressure measurement, eye exam-ination, breast examination, and Papsmear); and

s factors potentially associated with theuse or nonuse of these five services.

OTA converted each of the five variables

measuring elapsed time since use of pre-ventive services to a binary variable thatmeasures whether or not the individual usedthe service within a specified period of time.

These periods of time are based on therecommendations of expert groups presentedin table 2 in the text of this paper. Becausethere is some variation across the differentsets of expert guidelines listed in table 2,OTA summarized the published recommenda-tions in the composite measures presented intable 8. These composite measures do not

represent a set of recommendations them-selves; rather, they are merely one benchmarkfor comparing actual use to what is generallycons idered adequa te by recommendinggroups. Where there is disagreement amongr e c o m m e n d i n g g r o u p s , t h e c o m p o s i t emeasures tend toward longer intervals be-tween screenings in order to measure com-pliance with minimal recommended levels of prevention. These composites of expertrecommendations pertain only to the primaryanalyses conducted by OTA. As a source of comparison, table 8 also includes the periods

used by two other studies of the use of pre-ventive procedures. In one of these papers,the authors measured recommended peri-odicity as the mean of published recom-mendations (92). The other paper formed aconsensus based on their own review of relevant literature (45).

Because of the coding scheme of theNHIS, use within an ‘x” year period reallymeans that the individual had used the ser-vice within a period of less than but not in-cluding “x+1” years. For example, consider

the case of breast examinations. Table 2 sug-gests that one should measure use within theprevious year. However, under the NHIScoding scheme, one would consider an elderly

46

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woman who had her last breast examination on the data set:21 months ago to have been adequatelyscreened; a woman whose last breast exam-

s

ination was 24 months ago would not. Table9 lists all variables used in the analysis andalso includes appropriately weighted de-scriptive statistics. s

Methods of Analysis

OTA used PC-CARPR software (on an80286 personal computer) to analyze the data.PC-CARPR was developed by the StatisticalLaboratory at Iowa State University especiallyfor analyzing data from surveys with complexdesigns like the NHIS. It makes use of thesampling information in the data files to pro-duce appropriate point and variance esti-mates. OTA performed two separate analyses

a descriptive summary of the percent-ages of elderly individuals who reportedusing each of the five screening serviceswithin the specified time; and

a multivariate weighted logistic regres-sion analysis of the use or nonuse of these services.

In addition, OTA:

s examined whether observations droppedfrom the multivariate analysis becausethey contained some missing informationdiffer in any important ways from ob-servations included in the analysis,potentially biasing our estimated para-meters;

Table 8-- - Periods of Time Used by OTA and Two Studies to MeasureOlder Adults’ Use of Preventive Services

P e r i o d o f t i me t o me a s u r e u s e employed b y :

S e r v i c e O T A a L i l l a r d , e t a l . , 1 9 8 6 b wo o , e t a l . , 1 9 8 5 C

s I n i t i a l o r p e r i o d i c p h y s i c a l e x a m 1 y e a r . . . . 1 . 4 y e a r s

s B l o o d c h o l e s t e r o l l e v e l 5 y e ar s . . . . 4 . 5 y e a r s

s F e c a l o c c u l t b l o o d t e s t 1 y e a r 1 y e a r 1 . 0 y e a r

s P a p s m e a r 3 y e a r s * 3 y e a r s 4 . 1 y e a r s

s Gl a u c o ma s c r e e n i n g 2 y e a r s * . . . . - - - -

s Op t o me t r y / o p h t h a l mo l o g y e x a m 2 y e a r s * - - - - - - - -

s P n e u mo c o c c a l i mmu n i z a t i o n L i f e t i me L i f e t i me - - - -

s I n f l u e n z a i mmu n i z a t i o n 1 y e a r 1 y e a r . . . .

s T e t a n u s i mmu n i z a t i o n 1 0 y e a r s 1 0 y e ar s - . . .

s Hy p e r t e n s i o n s c r e e n i n g 1 y e a r * . . - . 1 . 4 y e a r s

s

B r e a s t e x a mi n a t i o n1 y e ar * . . - . . . . -

A b b r e v i a t i o n : H MO= h e a l t h ma i n t e n a n c e o r g a n i z a t i o n .

~ I n t e r v a l s l i s t e d in this colum represent compos i tes of the exper t recommendat ions surrnarized in table 2.

L . A . L i [ l a r d , W. G . Ma n n i n g , C. P e t e r s o n , e t a l . , Preventive Medical Care: Standards Usa~e and Efficacy (SantaMo ni c a, C A: T h e Ra n d Co r p o r at i o n , 1 98 6) .

CB. Woo, B. Woo, E.F. Cook, et a l . , IIScreening procedures in the Asymptomatic Adult: C o mp a r i s o n s o f

P hy s i c i a n s ’ Re c o mme n d a t i o n s , P a t i e n t s ’ De s i r e s , P u b l i s h e d Gu i d e l i n e s , a n d Ac t u a l P r a c t i c e , t i J.A.M.A.

254(11):1480-1484, 1985.

*As descr ibed in greater detai[ in a p p e n d i c e s E a n d F, OTA e S t i I M t d the U s e O f p r e Ve f l t i V e S er V i Ce S aMOn9

t h e e l d e r l y w i t h two d i f f e r e n t d a t a s o u r c e s - - a single HMO and the 1982 Nat ional Heal th In terv iew Survey(NHIS). T h e a s t e r i s k i n d i c a t e s s e r v i c e s i n c l u d e d i n t h e NHIS analysis. Because of the coding scheme of

t he NHIS, use within an ‘xM year per iod really means that t h e i nd i v idua l has us ed the s e rv i c e w i th in aper iod o f l es s than bu t no t i nc lud ing ‘X+lU years . Under this scheme, we would consider an elderly woman

who had her last breast examination 21 months ago to have been adequately screened; a woman whose lastbreast examination was 24 months ago would not. For the HMO data, use wi th in ‘xM years car r ies a l i tera l

d e f i n i t i o n .

So ur ces : Of f i c e o f T ec h n o l og y A s s es s me n t , 19 89 .

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s considered whether multicollinearity inthe models might reduce precision; and

s examined how the probabilities of usepredicted by the models varied witheach significant variable.

The multivariate analysis uses Taylor

series techniques to estimate a weightedlogistic regression model of the form:

is the probability of elderly person iusing service j. Use is measured bybinary variable Y ij (=1 if person ihad service j within the specifiedperiod of time; Yij O otherwise).

is a vector of predisposing charac-teristics describing elderly person i.

E i is a vector of enabling characteristics.

H i

U j

& j

describing elderly person i.

is a vector of health status charac-teristics describing elderly person i.

is an estimated parameter, and 6 j,8 j* Y j

are vectors of estimatedparameters for service j.

is an individual, service specific er-ror term.

PC-CARPR produces estimated coefficientstha t a re cons is ten t and appropr ia te lyweighted. Estimates of asymptotic variancesalso appropriately reflect the complex surveydesign.

PC-CARPR requires that no observationin the data matrix contain missing values.For the logistic regression analysis, OTA used

SPSS-PC+ to create two data files. OTApurged both files in a listwise fashion of ob-servations containing missing data on any

variable in the models. 1 OTA used one of the data sets to estimate models for pre-ventive services potentially used by bothsexes--glaucoma screening, eye examinations,and blood pressure measurement. OTA usedthe other data set, which contained only theobservations for women, to estimate modelsfor breast examinations and Pap smears.

The data set for both sexes contained ex-actly 9,000 out of the original 11,434 obser-vations. The remaining 2,434 observations,which had missing data, represented aweighted 21.5 percent of the over-65 popula-tion. The single variable with the most miss-ing observations was family income. Thisvariable alone had missing observationsrepresenting 15.3 weighted percent of theelderly population. Of each of the other var-iables containing missing values, none lackeddata on observations representing more than 4

weighted percent of individuals over-65. Thedata set containing only women had 5,040observations out of a possible 6,655. The1,615 observa t ions wi th miss ing da tarepresented 19.6 weighted percent of allwomen over 65.

Results

The estimates of the national proportionsof elderly using each of the five screeningservices within the specified time are pre-sented in table 3 in the text of the paper.Additional descriptive statistics are presentedin table 9. Table 10 below presents the para-meters of the estimated logistic regressionsthat attempt to explain the use or nonuse of each service . Table 7 summarizes theseresults, and the text of the paper discussestheir significance.

1 T o e s t i m a t e t h e d e s c r i p t i v e s t a t i s t i c s p r e s e n t e di n t a b l e 9 a n d t h e n a t i o n a l p e r c e n t a g e s o f e l d e r l yr e c e i v i n g t h e f i v e s c r e e n i n g s e r v i c e s , O T A u s e ddata sets that conta ined al l o b s e r v a t i o n s f o r w h i c h

a n y d a t a i s a v a i l a b l e f o r t h e p a r t i c u l a r v a r i a b l ei n q u e s t i o n . The Listwise deletion of missing valuesd e s c r i b e d h e r e o n l y a p p l i e s t o t h e l o g i s t i cr e g r e s s i o n a n a l y s i s .

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Table 9--- 1982 National Health Interview Survey:

Selected Descriptive Statistics for Persons Over 65

Nu mb e r o f o b s er v a t i o n s : 1 1 , 4 3 4

We i g h t e d n umb er o f o bser vat io ns: 2 5, 39 1, 02 3

Weighted Means and Standard Deviations for Continuous Variables

Var i ab l e Mean St andard dev i at i on..--.. . . . . . . . . . . . . . . ------- ------- . . . . . . . - . . . . . . .AGE -73.39 6 . 6 3..--.. . . . . . . . ------- ------- ------- ------- ------- -

INCOME 15,217.97 13,853.56

We i g h t e d F r e q u e n c y Di s t r i b u t i o n s f o r C a t e g o r i c a l V ar i a b l e s

V a r i a b l e Propor t ion Var i ab l e Pr o p o r t i o n

GL AUCOMA E DL E V E L Hi g h e s t e d u c a t i o n a l l e v e l a t t a i n e d :

l = s c r e e n e d for glaucoma within O=none or kindergarten 0.02

prev i ous 2 years , 11 months 0 . 66O= o t h e r wi s e 0 . 3 4

----- ------ ------ ------ ------ . . . . . . . . . . . . . . . .

E Y E

1 = r e c e i v e d ey e e x a mi n a t i o n wi t h i n

p r e v i o u s 2 y e a r s , 1 1 mo n t h s 0 . 7 5

O= o t h e r wi s e 0 . 2 5----- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

BLOODP

l = h ad b l o o d p r e s s u r e me a s u r e d wi t h i n

p r e v i o u s 1 y e a r , 1 1 mo n t h s 0 . 9 3

O= o t h e r wi s e 0 . 0 7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ----

BREAST

l = ha d c l i n i c a l b r e a s t e x a mi n a t i o nwi t h i n p r e v i o u s 1 y e a r , 1 1 mo n t h s 0 . 5 0

O= o t h e r wi s e 0 . 5 0

--.... ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PA P

1 = ha d Pa p s me a r w i t h i n p r e v i o u s 3

y e a r s , 1 1 mo n t h s 0 . 5 2O= o t h e r wi s e 0 . 4 8

- - - - . . . . . . . . . . . . . . . . . . . . - - - - - . . . . . . . . . . . . . . . .

1=1 to 8 years ( e lem enta ry ) 0 . 3 82=9 to 11 years (some high school) 0 . 1 63=12 years (h igh schoo l g raduate) 0 . 2 64=1 to 3 years c o l l e g e 0.09

5=college graduate 0.05

6=pos t -graduate educat ion 0.04. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . .

SMSA1=resides in a Census Bureau Standard

M e t r o p o l i t a n S t a t i s t i c a l A r e a ( u r b a n a r e a ) 0 . 6 40 = o t h e r u i s e 0 . 3 6

.-.-.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PREPAID1=enrolled in HMO or sane other prepaid

hea l th p lan 0.02

0=otherwise 0 . 9 8. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

HLTHINSR1=has some health insurance coverage

or heal th benef i ts beyond Medicarei n c l u d i n g p r e p a i d , V e t e r a n si, m i l i t a r y ,or means tes ted publ ic ass is tance

h e a l t h b e n e f i t 0 . 7 80=otherwise 0 . 2 2

------ . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . ---

ALONE

1 = l i v e s a l o n e 0.30

0=otherwise 0.70

. . . . . . . . . . . . . . . . . . . . ------- --- . . . . . . . . . . . . . ------- .

0.410=female 0.59

BEDDAYS days in bed during previous12 months:

O=none 0 . 6 51=1 to 7 days 0 . 1 62=8 to 30 days 0 . 1 23=31 to 180 days 0 . 0 54=181 to 365 days 0 . 0 2

- - - - - - . ------ ...-.-. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

NONWHI TE

l = n o n wh i t e0 = wh i t e

LIMITED

0. 1 0 1=l i m i t ed i n s o m e ac t i v i t y0 . 9 0 0=otherwi se

0.700.30

S O U R C E : Of f i c e o f T e c h n o l o g y As s e s s me n t , 1 9 89 .

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Table 10. --Elderly Use of Five Screening Services: Logistic Regression Results

GLA UCOMA BLOOOP EY E - B RE A ST P AP

I n d e pe n d e nt Me a n E s t i ma t e d E s t i ma t e d E s t i ma t e d

v a r i a b l e v a l u e c o e f f i c i e n t s c o e f f i c i e n t s c o e f f i c i e n t s

I N T E RC E P T 1 . 0 0 0 0 0 0 0 0.4160073 -0.3433352 0.8399042

P r e d i s p o s e n g f a c t o r s :M A L E 0 . 4 1 6 24 9 0

AG E 7 3 . 2 1 3 7 0 0 0

NONWHI T E 0 . 0 9 4 5 1 0 6

E D L E V E L 2.3429000

E n a b l i n g f a c t o r s :I N C OME 1 5 2 7 6 . 8 0 0 0 0 0 0

SMSA 0 . 6 3 3 65 1 0

P R EP A I D 0 . 0 2 2 9 56 1

H L T H I N S R 0 . 7 8 9 6 0 4 0

A L O N E 0 . 3 0 6 71 9 0

He a l t h s t a t u s me a s u r e s :B E DDA Y S 0 . 6 3 1 6 6 0 0

L I MI T ED 0 . 2 9 9 20 7 0

------ . . . . . . . . . . . . . . ---

(0.2927390) (0.7538013) (O.296341O)**

-0.3009192 -0.3259628 -0.2439690(0.0534922)** (0.0957841)** (0.5874069)**-0.0091917 0.0264826 -0.0061867(0.0038157)* (0.0095720)” (0.0039844)-0.3735570 -0.0368144 -0.0887188(0.0838741)** (0.1647689) (0.0923361)0.1601070 0.1038493 0.1147214

(0.0223536)** (0.0436750)* (0.0229877)**

0.0000114 0.0000106 0.0000066(0.0000026)** (0.0000058) (0.0000028)*0.2167839 0.0064913 0.2054843

(0.0571966)** (0.1049219) (0.0589708)**0.2349249 0.6391572 0.1612398

(0.2200813) (0.5023571) (0.2554439)0.4306881 0.5616778 0.3853976

( 0. 06 25 02 7) ** ( 0 .1 2 48 5 33 ) ** ( 0 .0 6 28 2 22 ) **0.0062441 -0.1136007 0.0406232

(0.0589261) (0.0944282) (0.0638674)

0.1227310 0.8908110 0.0776005(0.0304799)** (O.1O5O414)** (0.0281800)**0.0003354 0.3276151 -0.1233437

(0.0585122) ( 0. 13 17 94 8) * ( 0. 59 09 52 2) *. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Model s t a t i s t i c s :N 9 0 0 0 . 0 9 0 0 0 . 0 9 0 0 0. 0

De p e n d e n t v a r i a b l e me a n 0 . 6 6 3 5 0 . 9 3 1 9 0 . 7 4 3 2F - s t a t i s t i c 3 2 . 4 1 * * 1 5 . 1 4 * * 1 5 . 1 2 * *

A v e r a g e d e s i g n e f f e c t=

1 . 3 2 1 . 5 3 1 . 2 8

M e a n E s t i ma t e d E s t i ma t e d

v a l u e c o e f f i c i e n t s coef f ic ients

1.0000000 -0.0166337 2.1542170(0.39609n) (0.3889979)**

. . - . . .

. . . . . .73.4815000 -0.0167258 -0.0400128

(0.0051317)** (0.0049593)**0.0937475 0.0263338 0.1506788

(0.0982817) (0.1056188)2.3367600 0.1132536 0.0962961

(0.0255863)** (0.0249885)**

4059000000 0.0000119 0.0000102(0.0000027)**(0.0000028)** (0.0000028)**0.6364580 0.3110662 0.1555873

(0.0694007)** (0.0700830)*0.0199337 0.3845290 0.4433711

(0.2405225) (0.2723756) (0.2723756)0.7834470 0.3761862 0.3581028

(0.0884009)**(0.0861343)** (0.0861346)**0.4099680 0.1971576 - 0. 0397508

(O.O74391O)**(O.O665113)** (0.0651125)

0.6405870 0.3337425 0.1943092(0.0327194)**(0.0335717)** (0.0333572)**O.3O8W1O 0.0448802 0.0331326

(0.0703522) (0.0762676) (0.0762676)------ .-.-... . . . . . . . ------- ------- ------

5040.0 5040.00.4985 0.5243

23.09** 25.87**1.20 1.23

aAs y t o t i c s t a n da r d e r r o r s a r e i n p a r e n t h e s e s b e l o u e a c h e s t i ma t e d c o e f f i c i e n t .V a r i a b l e me a n s u e r e c a l c u l a t d f r o m d a t a ma t r i c e s u s ed t o e s t i ma t e l o g i t mo d e l s ( i . e . , p u r g e d o fo b s e r v a t i o n s ~ i t h mi s s i n g v a l u e s ) .

c A v e r a g e “ e f f e c t U o f c o a p l e x s u r v e y d e s i g n o n v a r i a n c e s o f e s t i ma t e d c o e f f i c i e n t s . T h i s ‘ e f f e c t ” i s me a s u r e da s t h e n u n b e r o f t i me s g r e a t e r t h e v ar i a n c e f r o m t h e c omp l e x d e s i g n i s t h a n t h e v a r i a n c e f r o m a s i mp l er a n d o m de s i g n .

* E s t i ma t e d p a r a me t e r s i g n i f i c a nt a t t h e 0 . 0 5 l e v e l , t ~ o - t a i l e d t e s t .* * E s t i ~ t e d ~ r ~ t e r s i g n i f i c a n t a t t h e 0 . 0 1 l e v e l , t W- t a i l Sd t e s t .

V a r i a b l e K e y :

~ ~ v ~GLAUCOMA - - l = s c ~e e ne d f o r g l a u c o ma wi t h i n p r e v i o u s 2 y e ar s , 1 1 mo n t h s ; O= o t h e r u i s e

EY E - - l = r e c e i v e d e y e e x a mi n a t i o n wi t h i n p r e v i o u s 2 y e a r s , 1 1 mo n t h s ; O= o t h e r w i s e

B L O CX ) P - - l = h a d b l o o d p r e s s u r e me a s u r e d u i t h i n p r e v i o u s 1 y e a r , 1 1 mo n t h s ; O= o t h e r u i s e

B R E A S T - - l = h a d c l i n i c a l b r e a s t e x a mi n a t i o n w i t h i n p r e v i o u s 1 y ea r , 1 1 mo n t h s ; O= o t h e r u i s e

P A P - - l = h a d P a p s me a r wi t h i n p r e v i o u s 3 y e a r s , 1 1 mo n t h s ; O= o t h e r w i s e

~ t v ~

M A L E - - l = ma l e ~ O= f e ma l eA GE - - r e s p o n de n t ’ s a g e i n y e a r sN O N WH I T E - - l = n o n wh i t e ; O= wh i t eE D L E V E L - - h i g h es t e d u c a t i o n a l l e v e l a t t a i n e d ; O= n o n e o r k i n d e r g a r t e n ; 1 = 1 t o 8 y e a r s ( e l e me n t a r y ) ; 2 = 9

t o 1 1 y e a r s ( s p , e h i g h s c h o o l ) ; 3 = 1 2 y e a r s ( h i g h s c h o ol g r a d u at e ) ; 4 = 1 t o 3 y e ar s c o l l e g e;5=college graduate; 6=post-graduate education

I N C OM E - - f a mi l y i n c o me i n d o l l a r sSMSA - - l = r e s i d e s i n a Ce n s u s Bu r e a u S t a n da r d Me t r o p o l i t a n S t a t i s t i c a l A r e a ( u r b a n a r e a ) ; O = o t h e r wi s eP R EP A I D - - l = e n r o l l e d i n H MO o r s o me o t h e r p r e p a i d h e a l t h p l a n ; O= o t h e r wi s e

H L T H I N S R - - l = h a s s o me h e a l t h i n s u r a n c e c o v e r a g e o r h e a l t h b e n e f i t s b e y on d Me d i c a r e i n c l u d i n g p r e p a i d ,V e t e r a n s ’ , mi l i t a r y , o r me a n s t e s t e d p u b l i c a s s i s t a n c e h ea l t h b e n e f i t ; O= ot h e r w i s e

A L ONE - - l = l i v e s a l o n e ; O= o t h e r wi s eB E DDA Y S - - d a y s i n b ed d u r i n g pr e v i e ws 1 2 mo n t h s ; O = n o n e ; 1 = 1 t o 7 d a y s ; 2 = 8 t o 3 0 d a y s ; 3 = 3 1 t o 1 80

d a y s ; 4 = 1 8 1 t o 3 6 5 d a y sL I MI T ED - - l = l i mi t e d i n s o me a c t i v i t y ; O= o t h e r w i s e

SOURCE: Of f i c e o f T e c h n ol o g y As s e s s me n t , 1 9 8 9 .

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Table 11. --Correlation Matrix for Variables in Logistic Regression Modelsa

N ON - E D - HL T H -

GLAUCOMA BLOODP EYE BREAST P A P MA L E AG E WH I T E L E V E L I N CO ME S MS A PR E PA I D I N S R A L O NE B ED DA Y S L I MI T E D

GL AUCOMA 1 . 0 0x x

BLOODP 0 . 1 9 1 . 0 0x x x x

EY E 0 . 6 9 0 . 1 8 1 . 0 0x x x x x x

BREAST x x x x x x x xx x x x x x 1 . 0 0

PA P x x x x x x x x x xx x x x x x 0 . 4 9 1 . 0 0

MALE

AG E

N O NWH I T E

E D L E V E L

I N C OME

SMSA

P R EP A I D

H L T HI N SR

A L O N E

B E D D A Y S

- 0 . 0 6x x

- 0 . 0 5x x

- 0 . 0 9x x

0 . 1 5x x

0 . 1 2x x

0 . 0 7x x

0 . 0 3x x

0 . 1 2x x

- 0 . 0 1

x x

0 . 0 4x x

- 0 . 0 4x x

0 . 0 3x x

- 0 . 0 2x x

0 . 0 5x x

- 0 . 0 5 x x x x 1 . 0 0x x x x x x 1 . 0 0

- 0 . 0 3 x x X X - 0 . 0 6X X - 0 . 0 6 - 0 . 1 5 XX

- 0 . 0 3 x x x x 0 . 0 0x x - 0 . 0 2 0 . 0 0 x x

0 . 1 0 x x x x 0 . 0 1x x 0 . 1 1 0 . 1 1 x x

0 . 0 4 0 . 0 7 x x x x 0 . 1 0x x x x 0 . 0 9 0 . 1 0 x x

0 . 0 1 0 . 0 6 XX x x - 0 . 0 1x x x x 0 . 0 9 0 . 0 5 x x

0 . 0 2 0 . 0 2 x x x x 0 . 0 3x x x x 0 . 0 4 0 . 0 4 x x

0 . 0 7 0 . 0 9 x x x x 0 . 0 2x x x x 0 . 1 0 0 . 0 9 x x

- 0 . 0 1 0 . 0 1 x x X X - 0 . 2 6x x X X 0 . 0 1 - 0 . 0 6 XX

0 . 1 3 0 . 0 2 x x x x - 0 . 0 2x x X X 0 . 1 5 0 . 0 8 XX

1 . 0 01 . 0 0

- 0 . 0 1- 0 . 0 1

- 0 . 1 4- 0 . 1 4

“ 0 . 1 1

- 0 . 0 9

- 0 . 0 00 . 0 1

- 0 . 0 3- 0 . 0 3

- 0 . 0 9- 0 . 0 8

0 . 1 80 . 2 1

0 . 0 60 . 0 6

1 . 0 01 . 0 0

- 0 . 1 6 1 . 0 0- 0 . 1 8 1 . 0 0

- 0 . 1 3 0 . 3 9 1 . 0 0“ 0 . 1 3 0 . 3 2 1 . 0 0

0 . 0 4 0 . 0 9 0 . 1 2 1 . 0 00 . 0 2 0 . 0 8 0 . 1 1 1 . 0 0

- 0 . 0 0 0 . 0 4 0 . 0 3 0 . 1 0 1 . 0 0- 0 . 0 1 0 . 0 3 0 . 0 1 0 . 0 8 1 . 0 0

- 0 . 1 2 0 . 1 8 0 . 1 1 0 . 0 1 0 . 0 8 1 . 0 0“ 0 . 1 1 0 . 1 8 0 . 0 7 0 . 0 0 0 . 0 8 1 . 0 0

0 . 0 1 - 0 . 0 2 - 0 . 3 1 - 0 . 0 0 - 0 . 0 4 - 0 . 0 1 1 . 0 0“ 0 . 0 1 - 0 . 0 0 - 0 . 3 6 - 0 . 0 1 - 0 . 0 3 0 . 0 3 1 . 0 0

0 . 0 4 - 0 . 0 5 - 0 . 0 3 - 0 . 0 1 - 0 . 0 2 - 0 . 0 1 0 . 0 1 1 . 0 00 . 0 4 - 0 . 0 5 - 0 . 0 4 - 0 . 0 0 0 . 0 0 - 0 . 0 2 0 . 0 1 1 . 0 0

L I MI T ED - 0 . 0 0 0 . 0 6 - 0 . 0 3 x x x x - 0 . 0 4 - 0 . 0 7 0 . 0 6 - 0 . 1 2 - 0 . 0 7 - 0 . 0 4 - 0 . 0 0 - 0 . 0 2 - 0 . 0 3 0 . 3 1 1 . 0 0

x x x x x x 0 . 0 4 0 . 0 3 x x - 0 . 0 4 0 . 0 7 - 0 . 1 2 “ 0 . 0 5 - 0 . 0 3 0 . 0 1 - 0 . 0 1 - 0 . 0 4 0 . 4 5 1 . 0 0

‘ P e ar s o n c o r r e l a t i o n c o ef f i c i e n t s . F i r s t r o w i n e a c h c e l l g i v e s c o r r e l a t i o n i n d a t a s e t u s e d t o e s t i ma t emo d e l s f o r GL A UC OMA , E Y E a n d BL ~ P’ ( n = 9 0 00 ) . S e c o n d r o w g i v e s c o r r e l a t i o n f o r d a t a s e t u s e d t o e s t i ma t emo d e ( s f o r B RE AS T and PA P ( n = 5 0 4 0 ) .

s y mb o l K ey : X X = No t a p p l i c a b l e ( B o t h v a r i a b l e s n o t c o n t a i n e d o n t h a t d a t a s e t )

V a r i a b l e K e y :Dependen tVar i ab les :

GLAUCOMA - - l = s c r e e n e d f o r g l a u c o ma wi t h i n p r e v i o u s 2 y e a r s , 1 1 mo n t h s ; 0 = o t h e wi s e

EY E - - l = r e c e i v e d e y e e x a mi n a t i o n wi t h i n p r e v i o u s 2 y e a r s , 1 1 mo n t h s ; O = o t h e r ~ i s eB L 0 0 D P - - l = h ad b l o o d p r e s s u r e me a s u r e d wi t h i n p r e v i o u s 1 y e a r , 1 1 mo n t h s ; O= o t h e r w i s eBREAST - - l = h a d c l i n i c a l b r e a s t e x a mi n a t i o n wi t h i n p r e v i o u s 1 y ea r , 1 1 mo n t h s ; O= o t h e r w i s ePA P - - l = h ad Pa p s me a r w i t h i n p r e v i o u s 3 y e a r s , 1 1 mo n t h s ; O= o t h e r w i s e

Independent Var iables :

MALE - - l = ma l e ; O= f e ma l eA GE - - r e s p o n de n t ’ s a g e i n y e a r sN O NWH I T E - - l = n o n wh i t e ; O = wh i t eE D L E V E L - - h i g h e s t e d u c a t i o n a l l e v e l a t t a i n e d ; O= n o n e o r k i n d e r g a r t e n ; 1 = 1 t o 8 y e a r s ( e l e me n t a r y ) ; 2 = 9 t o

1 1 y ea r s ( s o me h i g h s c h o o l ) ; 3 = 1 2 y e a r s ( h i g h s c h o o l g r a d u a t e ) ; 4 = 1 t o 3 y e a r s c o l l e g e ;5 = c o l l e g e g r a d u at e ; 6 = p o s t - g r a d u a t e e d u c at i o n

I N C OM E - - f a mi l y i n c ome i n d o l l a r sSMSA - - l = r e s i d e s i n a Ce n s u s Bu r e a u S t a n da r d Me t r o p o l i t a n St a t i s t i c a l A r e a ( u r b a n a r e a ) ; O= o t h e r w i s eP R EP A I D - - l = e n r o l l e d i n HMO o r s o me o t h e r p r e p a i d h e a l t h p l a n ; O= o t h e r wi s eH L T H I N S R - - l = h a s s o me h e a l t h i n s u r a n c e c o v e r a g e o r h e a l t h b e n e f i t s b e y on d Me d i c a r e i n c l u d i n g p r e p a i d ,

V e t e r a n s ' , mi l i t a r y , o r me a n s t e s t e d p u b l i c a s s i s t a n c e h e a l t h b e n e f i t ; O = o t h e r wi s eA L O N E - l = l i v e s a l o n e ; O= ot h e r w i s eB E D D A Y S - - d a y s i n b e d d u r i n g p r e v i e ws 1 2 mo n t h s ; O= n on e ; 1 = 1 t o 7 d a y s ; 2 = 8 t o 3 0 d a y s ; 3 = 31 t o 1 8 0 d ay s ;

4 = 1 8 1 t o 3 6 5 d a y sL I MI T ED - - l = l i mi t e d i n s o me a c t i v i t y ; O = ot h e r w i s e

SOURCE: Of f i c e o f T e c h n o l o g y A s s e s s me n t , 1 9 8 9 .

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To examine the possibility that multi-collinearity among the independent variablesin the model might preclude precise estima-tion, OTA estimated the weighted first-orderPearson correlation matrices for the two datasets. Table 11 presents the correlationstatistics. Only three pairs of independentvariables had correlations greater than 0.25

(or less than -0.25): EDLEVEL and IN-COME (0.39 in the two-gender data set and0.32 in the women only data set), ALONEand INCOME (-0.31 and -0.36 respectively),and the two measures of health status,LIMITED and BEDDAYS (0.31 and ().43respectively). In addition, ALONE and AGEhave correlations of 0.18 and 0.21 respective-ly in the two data sets. However, despite thepotential effect of this collinearity on theestimated variances, the conclusions are un-likely to change. In all models except bloodpressure measurement, EDLEVEL and IN-

COME are both already significant predictorsof preventive service use. ALONE is sig-nificant in three out the five (with bloodpressure measurement and Pap smears beingthe exceptions). Although there is a high de-gree of correlation between BEDDAYS andLIMITED, at least one of them is statisticallysignificant in all of the models except glau-coma screening, thus supporting the notionthat health status is associated with preventiveservice use among the elderly.2

OTA excluded a substantial proportion of

observations because data were missing forone or more variables in the model. In orderto examine if these exclusions could havebiased the results of the multivariate models,OTA compared the characteristics of the in-cluded and excluded groups. In both datasets, the included respondents were sig-nificantly different from those eliminated be-

Z However , because mul t icol 1 i neari ty reduces thep r e c i s i o n o f t h e e s t i m a t o r , t h e stsndard e r r o r o ft h e s e t w o v a r i a b l e s ’ e s t i m a t e d c o e f f i c i e n t s m a y b ebiased in the glaucoma screening model.

cause of missing data for only two variables:HLTHINSR (the presence of any health in-surance beyond Medicare) and INCOME. 3

For each of the other variables (including thedependent variables), the mean for the obser-vations with missing data did not differstatistically from the mean for observationsincluded in our analyses. This analysis sug-

gests that the exclusion of observations withmissing data is unlikely to introduce bias intothe multivariate models, but OTA cannot ruleout the possibility.

In order to examine the effect of eachsignificant variable in the estimated models,OTA simulated, one independent variable at atime, how the probability of using eachscreening service varied with each possiblevalue of the independent variables. In thesesimulations, all independent variables, exceptthe one whose effect was being simulated, as-

sumed their mean values.

Table 12 and figures 1 through 4 presentthe results of this analysis for each significant variable in our models. Among the indepen-dent variables, holding other factors constant,age, education, and health insurance appearto have the greatest overall effect on theprobability of receiving each of these ser-vices. This analysis also supports the notionthat blood pressure measurement is differentfrom other services. Since almost everyonereceives it, there is less variation to explain.

Hence, the variables in the model appear lessimportant in predicting its use than they dofor the other services.

3 T he g r o u p o f o b s e r v a t i o n s e x c l u d e d f r o m t h e

a n a l y s i s h a d a louer mean income ($14,475 v e r s u s

$ 1 5 , 2 7 6 i n t h e t w o ge n d e r d a t a s e t ; p c O. 0 1 ) a n d w a s

l e s s l i k e l y t o h av e a ny i n s u r a n c e c o v e r a g e b e y o n d

Me d i c a r e ( 0 . 7 0 versus 0.79 in the two gender dataset ; P<o. os) t h a n w a s t h e i n c l u d e d g r o u p . T h e i n

-

c o m e s t a t i s t i c m a y n o t a c c u r a t e l y r e f l e c t t h ee n t i r e g r o u p o f o b s e r v a t i o n s w i t h m i s s i n g d a t as i n c e t h r e e - q u a r t e r s o f t h e o b s e r v a t i o n s m i s s i n g

any data at al 1 did not have income data.

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Table 12-- - Effect of Statistically Significant Binary Variablesain Logistic Regressions on

Elderly Use of Five Screening Services: Predicted Probabilitiesb

MA L E= 0= 1

. . . . . . . . . . .

N ON WH I T E

= 0u 1

. . . . . . . . . . .

SMSA= o= 1

. . . . . . . . . . .

H L T H I N SR

= 0= 1

. . . . . . . . . . .

A L ON E

= o= 1

. . . . - - . . . . .

L I MI T ED

= 0= 1

GLA UCOMA

P r e d i c t e d

p r o b a b i l i t y

0.70

0.63. . . . . . ------

0.68

0.59- - - - - - - - - - - .

0.64

0.77. . . . . . . . . . . .

0.59

0.69----- . . . . . . .

. .

. .. . . . . . . . . . . .

. .

. .

BLOOOP

P r e d i c t e d


EY E

P r e d i c t e d


0.960.94

. . . . . . . . . . . . . .

. .

. .....-- --..... -

. .

. .. . . . . . . . . . . . . .

0.92

0.96. . . . . . . . . . . ---

. .

. .------ . . . . . . . .

0.95

0.96

0.77

0.72. . . . . . . . . . . . . .

. .--

. . . . . . . . . . . . . .

0.73

0.77. . . . . . . . . . . . . .

0.69

0.77. . . . . . . . . . . . . -

. .

. .. . . . . . . . . . . . . .

0.76

0.74

B R E A S T

P r e d i c t e d


xx

xx. . . . . . . . . . . . .

. .

. .. . . . . . . . . . . . .

0.45

0.53. . . . . . . . . . . . .

0.43

0.52----- . . . . . . . .

0.480.53

. . . . . . . . . . . . .

. .

. .

P AP

P r e d i c t e d


xx

xx. . . . . . . . . . . . .

. .

. . . . . . . . . . . . .

0.50

0.54. . . . . . . . . . . . .

0.46

0.55. . . . . . . . . . . . .

. .

. .. . . . . . . . . . . . .

. .

. .

. . .

. . .

. . .

. . .

. . .

a E f f e c t o f s i g n i f i c a n t n o n- b i n a r y v a r i a b l e s s h o wn i n f i g u r e s 1 t h r o u g h 4 .b P r e d i c t e d p r o b a b i l i t y i s e s t i m a t e d as 1/[1 + e-x~l where ~is the vector of

e s t i m a t e d c o e f f i c i e n t s a n d X i s t h e v e c t o r o f i n d i v i d u a l c h a r a c t e r i s t i c s . Of thesecharac ter is t ics (a[l i ndependen t v a r iab les i nc luded in t he es t im a ted m o d e l ) , e a c htakes on i ts mean value except the one des ignated in that row of the table above;i t takes on the va(ue shown in the row header .

S y mb o l K e y :

X X = I n d e pe n de n t v a r i a b l e n o t i n c l u d ed i n mo d e l

- - = E s t i ma t e d c o ef f i c i e n t o n i n d e pe n d en t v a r i a b l e n o t s i g n i f i c a n t a t 0 . 0 5 l e v e l , t wo - t a i l e d t e s t

V a r i a b l e K e y :

De p e n d e n t V ar i a b l e s :GL A UCOMA - - l = s c r e e n e d for glaucoma within previous 2 years, 11 months; O=otherwiseEY E - - l = r e c e i v e d e y e e x a mi n a t i o n wi t h i n p r e v i o u s 2 y ea r s , 1 1 mo n t h s ; O= o t h e r wi s e

B L OOOP - - l = h a d blood pressure me a s u r e d wi t h i n p r e v i o u s 1 y e a r , 1 1 mo n t h s ; O= o t h e r wi s e

B RE A S T - - l = ha d c l i n i c a l b r e as t e x a mi n a t i o n wi t h i n p r e v i o us 1 y e a r , 1 1 mo nt h s ; O= o t h e r w i s e

P A P - - l = h a d Pa p s me a r wi t h i n p r e v i o u s 3 y e a r s , 1 1 mo n t h s ; O= o t h e r wi s e

Independent Variables:

MA L E -- l=male; O=femaleN ON WH I T E - - l = no n wh i t e ; O= wh i t e

S MS A - - l = r e s i d e s i n a Ce ns u s Bu r e a u S t a nd ar d Me t r o p o l i t a n S t a t i s t i c a l A r e a ( u r b a n a r e a) ; O= ot h er w i s e

P RE P A I D - - l = e n r o l l e d i n HMO o r s o me o t h e r p r e p a i d h e a l t h p l a n ; O= o t h e r wi s e

H L T HI N SR - - l = h a s s o me h ea l t h i n s u r a n c e c o v e r a g e or h e a l t h b en e f i t s b e y o n d Me d i c a r e including prepaid,Veterans ! , m i l i tary , or means tes ted publ ic ass is tance heal th benef i t ; O=otherwise

A L ONE - - l = l i v e s a l o n e O= o t h er wi s e

L I MI T E D - - l = l i m i t e d in some activity; O=otherwise

S O U R C E : Of f i c e o f T e c h no l o g y A s s es s me n t , 1 9 8 9 .

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54 The Use of Preventive Services by the Elderly

00*w

000

z

E.*w

4

’ +

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APPENDIX F: ANALYSIS OF PREVENTIVE SERVICE USEBY OLDER ADULTS IN A HEALTH

MAINTENANCE ORGANIZATION

Methods

The Data

OTA contracted with a health main-tenance organization (HMO) to provide dataon the use of eight preventive services bytheir

s

s

s

s

s

s

s

s

over-65 year old enrollees:

Check-up visit,Cholesterol measurement,Eye examination,Fecal occult blood test,Pap smear,Influenza immunization,Pneumococcal immunization, andTetanus immunization.

OTA chose these services in consultation withthe HMO to meet the following criteria:

they are services often included amongdiscussions or recommendations forelderly preventive health; andthe HMO’s data system routinely recordstheir use as distinct services.

To examine how use varies with age, theHMO also provided comparable data for en-rollees between the ages of 40 and 64. TheHMO measured the proportions of enrollees

using each service within the periods of timepresented in table 8.

The HMO is a large, urban, staff modelhealth maintenance organization located inthe Northeastern United States. It serves en-rollees through private employers, govern-ment agencies, and individual accounts.Since January 1976, the HMO has servedMedicare beneficiaries, initially under a planw h e r e t h e H M O b i l l e d M e d i c a r e f o rMedicare-covered procedures on a fee-for-service basis. The HMO provided non-

covered procedures, including the preventiveservices examined in this study, through a“wraparound” or “Medi-gap” policy purchasedby or for the enrollee.

Beginning in July 1985, the HMO enter-ed into a Medicare demonstration risk con-tract with over 80 percent of its 2500 existingMedicare enrollees transferring into this plan

within the first three months. All of the ser-vices covered under the HMO’s basic benefitpackage, including preventive services, wereincluded in the risk contract plan.

The HMO has traditionally encouragedthe use of preventive services by at-risk pop-ulations through clinical guidelines for pre-ventive care and coverage of regular check-ups. Before October 1987, the monitoring of compliance with these guidelines was limitedto pediatric screening and immunization,prenatal screening, and influenza immuniza-

tion. Since that date, the HMO has adopted aprogram to monitor and inform clinicians ateach visit of a patient’s compliance with theHMO’s preventive guidelines. Since OTAbelieved that this program is not typical of most HMOs, this HMO used October 1987 asthe endpoint for measuring rates of use foreach preventive services studied. Hence,during the periods of time examined, onlyinfluenza immunizations reflect any monitor-ing by the HMO, and for that service,clinicians only received information on ag-gregate rates of compliance among all enrol-lees.

Methods of Analysis

The base population for this study is allpresent and former HMO enrollees who wereage 40 or older as of October 1, 1987. TheHMO identified the base population througha computerized search of enrollment recordsand separated the population into four sub-groups on the basis of age:

s 40 to 49 years old, 50 to 64 years old,s 65 to 74 years old, ands 75 years and older.

55

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Because the HMO calculated age at the endof the observation period, some of the enroll-ees in each group fell below the low agethreshold at the time they actually used aspecific service.

Through computer searches of this basepopulation, the HMO defined a “denominatorpopulation” for each age group and observa-tion period over which the use of a specificpreventive service was to be measured. Each“denominator poplation” consisted of all per-sons of appropriate age continuously enrolledin the HMO during the observation period.Since two of the HMO’s ten clinics did nothave computerized records at the level of specific clinical services, enrollees from thesesites were excluded from the analysis. Enroll-ees excluded from the denominator files be-cause they came from one of the non-computerized sites or because they were notcontinuous members represented 20 percentof the base population in each age group.

The “denominator” file for the over-65age groups consists of all continuously en-rolled individuals from the eight sites. Thedenominator population for the 40 to 64 agegroups were so large that the HMO used arandom sample of these groups for the analy-sis. They chose a 10-percent random samplefor all but the 10-year observation period,where they chose a 20-percent random

sample. Table 13 presents the number of ob-servations in each “denominator” file used tocalculate the rates of use.

In order to measure the use of each ser-vice for each age group, the HMO searchedthe base population to form “numerator” files

consisting of persons who met both of thefollowing criteria:

s the individual was enrolled in one of theeight sites at the time the analysis wasconducted (June through September1988); and

s the individual received the specific pre-

ventive service within the observationperiod.

To calculate rates of use, each “numer-ator” file was compared to its corresponding“denominator” file. Individuals in the numer-ator file who did not appear in the denomi-nator file were discarded. Stratifying bygender, the HMO tallied the number of indi-viduals remaining in each “numerator” fileand divided that number by the number inthe corresponding “denominator” file to calcu-late a rate of use for each service and age-gender group. Table 14 presents the resultsof this analysis.

It is possible that a few continuously en-rolled members transferred from one of thetwo excluded sites to one of the eight in-cluded sites before October 1, 1987. Whilesuch individuals would be included in the“denominator” files, they would not appear inthe “numerator” file if they received a pre-ventive service at the excluded site. Thiswould deflate the use rate. However, because

the two excluded sites serve geographicallydistinct communities with most membersliving in close proximity to the clinic, trans-fer to another site is relatively rare. There-fore, OTA and the HMO concluded that thepotential undercounting in the use rates isminimal.

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T ab l e 1 3 - - - S a mp l e Si z e s f o r E a c h Me a s u r e m e n t P e r i o d i n O TA ’ S A n a l y s i s o fP r e v e n t i v e S e r v i c e U s e i n On e HMO

3 y r . a n d 2 y r . * *1 0 y r . p e r i o d 5 y r . p er i o d* * ( 1 0 / 8 4 - 1 0 / 8 7 ) 1 yr . p e r i o d * *

Ag e ( 1 0 / 7 7 - 1 0 / 8 8 ) ( 1 0 / 8 2 - 1 0 / 8 7 ) a n d ( 1 0 / 8 5 - 1 0 / 8 7 ) ( 1 0 / 8 6 - 1 0 / 8 7 )I I 1 1

Ma l e F e ma l e T o t a l Ma l e F e ma l e T o t a l Ma l e F e ma l e T o t a l Ma l e F e ma l e T o t a l

4 0 - 4 P 2 5 0 2 6 0 5 1 0 4 5 5 5 0 7 9 6 2 72 5 7 9 7 1 5 2 2 9 9 5 1 0 6 8 2 0 6 35 0 - 6 4 ’ 2 4 6 2 2 7 4 7 3 2 8 2 3 3 1 6 1 3 4 6 6 5 1 8 9 8 4 6 5 4 7 8 4 1 4 3 8

6 5 - 7 4 * * 3 2 9 3 0 7 6 3 6 8 4 9 , 9 5 6 1 8 0 5 1 2 6 5 1 4 4 0 2 7 0 5 1 9 0 2 2 2 1 9 4 1 2 87 5 + * * 11 3 14 5 2 5 8 2 0 4 3 1 3 5 1 7 2 7 1 3 95 6 6 6 5 1 4 7 5 2 1 2 6 6

\ I I I Iq T h e n f o r 4 0 - 4 9 a n d 5 0 - 6 4 a g e g r o u p a r e p r e s e n t a 2 0 p e r c e n t s q l e o f m e n b e r s c o nt i n u o u s l y e nr o l l e d du r i n g ea c h pe r i o d a t t h e e i g h t s i t e s

s t u d i e d . T h e 6 5 - 7 4 and 75+ age g r o u p s r e p r e s e n t a l l mw b e r s .q * T h e n f o r 40-49 ad SO-64 age groups represent a F p e r c e n t s a n p ~ e o f me n b e r s c o nt i n u o u s l y e nr o l l e d d u r i r w e a c h p e r i o d a t t h e e i g h t s i t e s

s t u d i e d . T h e 6 5 - 7 4 a n d 7 5 + age g r o u p s r e p r e s e n t a l l me r b e r s . —

T ab l e 1 4 - - - P er c e n t s o f C o n t i n u o u sl y En r o l l e d Me mb e r s R ec e i v i n g Ei g h t P r e v e n t i v e Se r v i c e sDu r i n g Sp e c i f i e d Pe r i o d s of T i me

P n e u n o c o c c a lCh e ck - u p v i s i t C ho l e s t e r o l E y e e x a m F e c a l o c c u l t b l o o d P a p s me a r I nf l u e n z a v a c c i n e v a c c i n e T e t an u s v a c c i ne

Ag e ( 1 y e a r p e r i o d ) ( 5 y e a r p e r i o d ) ( 2 y ea r p e r i o d) ( 1 y e a r p e r i o d) ( 3 y ea r p e r i o d) ( 1 y ea r p e r i o d ) ( l i f e t i me ) ( 1 0 y e a r p e r i o d )

Ma l e F e ma l e T o t a l Ma l e F e ma l e To t a l Ma l e Female Tota l Ma l e F e ma l e T o t a l Ma l e F ema l e T ot a l Ma l e F e ma l e T o t a l Ma l e F e ma l e T o t a l Ma l e F ema l e T ot a l

4 0 - 4 9 y r s . 2 4 % 3 9 % 3 2 X 6 8 % 6 7 % 6 7 % 3 9 % 5 0 % 4 4 % 2 1 % 3 2% 27 % N/ A 8 0 % N/ A 4 % 5 % 4 % 1 % 1 % 2 0 % 1 7 1 8 %5 0 - 64 y r s . 3 8 4 9 4 4 8 0 7 7 7 8 5 1 5 5 5 3 3 6 4 6 4 1 N/ A 7 3 N/ A 1 4 1 2 1 3 7 5 6 1 3 1 3 1 3S u b t o t a l

4 0 - 6 4 2 9 4 3 3 7 7 3 7 1 7 2 4 4 5 2 4 8 2 7 38 33 N / A 7 7 N/ A 8 8 8 3 2 3 1 7 1 5 1 6

6 5 - 74 y r s . 4 8 5 2 5 0 7 7 7 6 7 6 7 0 7 4 7 2 4 9 5 3 5 1 N / A 7 5 N/ A 5 5 5 5 5 5 2 9 2 7 2 8 4 7 4 0 4 47 5 + y rs . 5 2 4 7 4 9 6 9 6 4 6 6 8 0 7 9 7 9 5 1 46 48 N/ A 6 0 N/ A 6 7 63 64 4 7 4 2 4 4 40 35 37S u b t o t a l

6 5 + 4 9 5 1 50 75 73 74 72 75 73 49 52 5 0 N/ A 7 1 N/ A 5 8 5 7 5 7 3 3 30 31 45 38 42

,

A b br e v i a t i o n : N/ A = No t a p p l i c a bl e .

SOURCE: Of f i c e o f T e c hn o l o g y A s s e s s me n t , 1 9 8 9.

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1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

60

Adams, M., and Kerner, J. F., “Evaluation of Promotional Strategies To Solve the Problemof Underutilization of Breast Examination/Education Center in a New York City BlackCommunity, “ in Issues in Cancer Screening and Communications (New York, NY: Alan R.Liss, Inc., 1982).

American Academy of Ophthalmology, Policy Statement, “Frequency of Ocular Examina-tions,” approved Feb. 6, 1983.

American Cancer Society, Summary of Current Guidelines for the Cancer-Related Check-up: Recommendations (New York, NY: ACS Professional Education Publication, 1988).

American College of Physicians, Committee on Immunizations, Guide for Adult Immuniza-tion, Philadelphia, PA, 1985.

American College of Physicians, Health and Public Policy Committee, “The Use of Diag-nostic Tests for Screening and Evaluating Breast Lesions,” Annals of Internal Medicine103:143-146, 1985.

American College of Radiology, Policy Statement, “Guidelines for Mammography,” adoptedSept. 22, 1982.

American Diabetes Association, ‘f A.D.A. Policy on Screening for Hyperglycemia,” June1983.

American Heart Association, “Public Screening Strategies for Measuring Blood Cholesterolin Adults--Issues for Special Concern,” October 1987.

American Optometric Association, National Health Division, “Optometry and the Nation’sHealth: Recommendations for the Implementation of Congress’ National Health Priorities,”February 1978.

American Society for the Prevention of Blindness, “Facts on Blindness and Prevention,”February 1988.

Andersen, R., and Aday, L. A., “Access to Medical Care in the U. S.: Realized and Poten-tial,” Medical Care 16:533-546, 1978.

Andersen, R., and Newman, J., “Societal and Individual Determinants of Medical CareUtilization,” Milbank Mere. Fund Q. 51:95-125, 1973.

Berwick, D., “Screening in Health Fairs: A Critical Review of Benefits, Risks and Costs,”Office of Disease Prevention and Health Promotion Monograph Series (Washington, DC:U.S. Government Printing Office, 1985).

Blalock, S. J., De Vellis, B. M., and Sandier, R. S., “Participation in Fecal Occult BloodScreening: A Critical Review,” Preventive Medicine 16:9-18, 1987.

Brown, J. T., and Hulka, B. S., “Screening Mammography in the Elderly: A Case-ControlStudy,” J. Gen. Intern. Medicine 3:126-131, 1988.

8/14/2019 8933



16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

Burack, R. C., and Liang, J., “The Early Detection of Cancer in the Primary-Care Setting:Factors Associated With the Acceptance and Completion of Recommended Procedures,”Preventive Medicine 16:739-751, 1987.

Calnan, M., “Patterns in Preventive Behaviour: A Study of Women in Middle Age,” Soc.Sci. Med. 20(3):263-268, 1985.

Canadian Periodic Health Examination Task Force, “The Periodic Health Examination,”Can. Med. Assoc. J. 121(9):1 193-1254, 1979; 130(10):1276-1292, 1984; 134(7):724-727,1986; 138(7):618-626, 1988.

Chao, A., Paganini-Hill, A., Ross, R. K., et al., “Use of Preventive Care by the Elderly,”Preventive Medicine 16:710-722, 1987.

Cohen, D. I., Littenberg, B., Wetzel, C., et al., “Improving Physician Compliance With Pre-ventive Medicine Guidelines,” Medical Care 20(10):1040-1045, 1982.

Cummings, K. M., Becker, M. H., and Maile, M. C., “Bringing the Models Together: AnEmpirical Approach to Combining Variables Used to Explain Health Actions,” Journal of Behavioral Medicine 3(2):123-145, 1980.

Cummings, K. M., Jette, A. M., Brock, B. M., et al., “Psychosocial Determinants of Im-munization Behavior in a Swine Influenza Campaign,” Medical Care 17(6):639-649, 1979.

David, A. K., and Boldt, J. S., “A Study of Preventive Health Attitudes and Behaviors in aFamily Practice Setting,” The Journal of Family Practice 11(1):77-84, 1980.

Davidson, R. A., Fletcher, S. W., Retchin, S., et al., “A Nurse-Initiated Reminder System forthe Periodic Health Examination,” Arch. Intern. Med. 144:2167-2170, 1984.

DeFriese, G., Director, Health Services Research Center, University of North Carolina atChapel Hill, personal communication, Washington, DC, May 20, 1988.

Fedson, D. S., “Influenza and Pneumococcal Immunization Strategies for Physicians,” Chest91:436-443, 1987.

Fuchs, V., How We Live (Cambridge, MA: Harvard University Press, 1983).

Gallup Organization, “The 1987 Survey of Public Awareness and Use of Cancer DetectionTests: Summary of Findings,” conducted for the American Cancer Society (Princeton, NJ:Gallup Organization, January 1988).

Green, L. W., Kreuter, M. W., Deeds, S. G., et al., “Health Education Today and thePRECEDE Framework,n in Health Education Planning: A Diagnostic Approach (Palo Alto,CA: Mayfield Publishing Company, 1980).

Grundy, S. M., Greenland, P., Herd, A., et al., “Cardiovascular and Risk Factor Evaluationof Healthy American Adults,” Circulation 75(6):1340A-1362A, 1987.

Harris, D. M., and Guten, S., “Health-Protective Behavior: An Exploratory Study,” Journalof Health and Social Behavior 20:17-29, 1979.

Hayward, R. A., Shapiro, M. F., Freeman, H. E., et al., “Who Gets Screened for Cervical andBreast Cancer?” Arch. Intern. Med. 148:1177-1181, 1988.

8/14/2019 8933


62 The Use of Preventive Services by the Elderly

33.

34 .

35 .

36 .

37 .

38 .

39 .

40.

41.

42.

43.

44.

45.

46.

47.

48.

Health Policy and Biomedical News of the Week, “Annual Pap Tests for at Least ThreeYears Advised by NCI; Guidelines Developed by Cancer Society,” Health Policy andBiomedical News of the Week 31(3):6-7, 1988.

Herdman, R., Behney, C. J., and Gluck, M.G., “Legislative Interests in Geriatric HealthPromotion,” in Proceeding of the Surgeon General’s Workshop on Health Promotion andAging (Washington, DC: U.S. Government Printing Office, 1988).

Howard, J., “Using Mammography for Cancer Control: An Unrealized Potential,” CA-ACancer Journal for Clinicians 37(1):33-48, 1987.

Hulka, B. S., and Wheat, J. R., “Patterns of Utilization: The Patient Perspective,” MedicalCare 23(5):438-460, 1985.

Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure,“The 1988 Report of the Joint National Committee on Detection, Evaluation, and Treat-ment of High Blood Pressure,” Arch. Intern. Med. 148(5):1023-1038, 1988.

Kane, R. L., Kane, R. A., and Arnold, S. B., “Prevention in the Elderly: Risk Factors,”Health Services Research 19(6,II):946-1006, 1985.

LaForce, F. M., “U.S. Preventive Services Task Force: Immunizations, Immunoprophylaxis,and Chemoprophylaxis To Prevent Selected Infections,” J. A.M.A. 257:2464-2470, 1987.

Lairson, D. R., and Swint, J. M., “A Multivariate Analysis of the Likelihood and Volume of Preventive Visit Demand in a Prepaid Group Practice,” Medical Care 16(9):730-739, 1978.

Lairson, D. R., and Swint, J. M., “Estimates of Preventive Versus Nonpreventive MedicalCare Demand in an HMO,” Health Services Research 14(1):33-43, 1979.

Lawrence, L., Government Relations Representative, American College of Obstetriciansand Gynecologists, personal communication, Washington, DC, Oct. 31, 1988.

Lawrence, R. S., and Mickelide, A., “Preventive Services in Clinical Practice: Designing thePeriodic Health Examination,” J. A.M.A. 257:2205-2207, 1987.

Lazaro, C. M., Logsdon, D. N., and Meier, R., “Utilization of Preventive Health Services bythe Elderly,” Insure Project, Lifecycle Preventive Health Services, New York, NY,presentation to the American Psychological Association Convention, Aug. 31, 1987.

Lillard, L. A., Manning, W. G., Peterson, C., et al., Preventive Medical Care: Standards.Usage, and Efficacy (Santa Monica, CA: The Rand Corporation, 1986).

Luft, M. S., Health Maintenance Organizations: Dimensions of Performance (New York,NY: John Wiley & Sons, Inc., 1981).

Lurie, N., Manning, W. G., Peterson, C., et al. “Preventive Care: Do We Practice What WePreach,” Am. J. Public Health 77(7):801-804, 1987.

Maiman, L. A., and Becker, M. H., “The Health Belief Model: Origins and Correlates,” inThe Health Belief Model and Personal Health Behavior, M.H. Becker (cd.), Health Educa-tion Monograph, vol. 2, No. 4 (Baltimore, MD: Johns Hopkins University, winter 1974).

8/14/2019 8933


The Use of Preventive Services by the Elderly 63

49.

50.

51.

52.

53 .

54 .

55 .

56.

57.

58.

59.

60.

61.

62.

63.

McDonald, C. J., Hui, S. L., Smith, D. M., et al., “Reminders to Physicians From an Intro-spective Computer Medical Record,” Annals of Internal Medicine 100:130-138, 1984.

McGinnis, M., “The Tithonus Syndrome: Health and Aging in America,” in Health Promo-tion and Disease Prevention in the Elderly, R. Chernoff and D.A. Lipschitz (eds.) (NewYork, NY: Raven Press, Ltd., 1988).

McPhee, S. J., Richard, R. J., and Solkowitz, S. N., “Performance of Cancer Screening in aUniversity General Internal Medicine Practice: Comparison With the 1980 Cancer SocietyGuidelines,” Journal of General Internal Medicine 1:275-281, 1986.

National Society for the Prevention of Blindness, “Glaucoma Patient Guide” (New York,NY: April 1984).

Radecki, S. E., Kane, R. L., Solomon, D. H., et al., “Are Physicians Sensitive to the SpecialProblems of Older Patients?” Journal of the American Geriatric Society 36:719-725, 1988.

Riddiough, M. A., Willems, J. S., Sanders, C. R., et al., “Factors Affecting the Use of Vac-cines: Considerations for Immunization Program Planners,” Public Health Reports96(6):528-535, 1981.

Romm, F. J., Fletcher, S. W., and Hulka, B., “The Periodic Health Examination: Comparisonof Recommendations and Internists’ Performance,” Southern Medical Journal 74(3):265-271,1981.

Rosenau, M. J., and Maxey, K. F., Maxcy-Rosenau Public Health and Preventive Medicine,1lth cd., J.M. Last (cd.) (New York, NY: Appleton-Century-Crofts, 1980).

Rosenstock, I. M., “Historical Origins of the Health Belief Model,” in The Health Belief Model and Personal Health Behavior, M.H. Becker (cd.), Health Education Monograph, vol.2, No. 4 (Baltimore, MD: Johns Hopkins University, winter 1974),

Rosenstock, I. M., “The Health Belief Model and Preventive Health Behavior,” in The

Health Belief Model and Personal Health Behavior, M.H. Becker (cd.), Health EducationMonograph, vol. 2, No. 4 (Baltimore, MD: Johns Hopkins University, winter 1974).

Rundall, T. G., and Wheeler, J. R. C., “Factors Associated With Utilization of the Swine FluVaccination Program Among Senior Citizens in Tompkins County, w Medical Care 17:191-200, 1979.

Rundall, T. G., and Wheeler, J. R. C., “The Effect of Income on Use of Preventive Care: AnEvaluation of Alternative Explanations,” Journal of Health and Social Behavior 20:397-406,1979.

Salkever, D. S., “Accessibility and the Demand for Preventive Care,” Social Science andMedicine 10:469-475, 1976.

Satariano, W. A., Schwartz, A. G., and Swanson, G. M., “Screening for Cervical Cancer:Results From Several Intervention Strategies, “ in Issues in Cancer Screening and Communi-cations (New York, NY: Alan R. Liss, Inc., 1982).

Sawyer, J. A., Earp, J., Fletcher, R. H., et al., “Pap Smears in Rural Black Women,” fromthe Department of Medicine and School of Public Health, University of North Carolina atChapel Hill, Chapel Hill, NC, unpublished manuscript.

8/14/2019 8933



64.

65.

66.

67.

68.

69.

70.

71.

72 .

73.

74.

75 .

76.

77.

Schwartz, S., University of Pennsylvania School of Medicine, personal communication,Philadelphia, PA, Mar. 16, 1988.

Selby, J. V., and G.B. Friedman, “Sigmoidoscopy in the Periodic Health Examination of Asymptomatic Adults,” report for the U.S. Preventive Services Task Force, Oct. 7, 1987.

Slesinger, D. P., Tessler, R. C., and Mechanic, D., “The Effects of Social Characteristics onthe Utilization of Preventive Medical Services in Contrasting Health Care Programs,”Medical Care 14(5):392-404, 1976.

Stults, B., “Preventive Care for the Elderly,” Western Journal of Medicine 141(6):832-845,1984.

Technology Reimbursement Reports, “Women Age 40 toEvery One to Two Years, AMA Delegates Recommend,”Reports 4(28):6, 1988.

49 Should Receive a MammogramTechnology Reimbursement

Teitelbaum, M. A., Weisman, C. S., Klassen, A. C., et al., “Pap Testing Intervals: SpecialtyDifferences in Physicians’ Recommendations in Relation to Women’s Pap Testing Behav-

ior,” Medical Care 26(6):607-618, 1988.Thompson, R. S., Michnich, M. E., Gray, J., et al., “Maximizing Compliance With Hemoc-cult Screening for Colon Cancer in Clinical Practice,” Medical Care 24(10):904-914, 1986.

U.S. Congress, Congressional Research Service, “Medicare: Risk Contracts With HealthMaintenance Organizations and Competitive Medical Plans,” 88-138 EPW, 1988.

U.S. Department of Health, Education, and Welfare, National Center for Health Statistics,“Use of Selected Preventive Services U.S--- 1973,” Vital and Health Statistics, Series 10, No.110 (Washington, DC: U.S. Government Printing Office, March 1977).

U.S. Department of Health and Human Services, Health Care Financing Administration,

Office of the Actuary, Division of National Cost Estimates, “National Health Expenditures,1986 -2000,” Health Care Financing Review 8(4):1-36, 1987.

U.S. Department of Health and Human Services, National Center for Health Statistics, “TheNational Health Interview Survey Design, 1973-1984, and Procedures, 1975 -1983,” Vitaland Health Statistics, Series 1, No. 18 (Washington, DC: U.S. Government Printing Office,August 1985).

U.S. Department of Health and Human Services, National Center for Health Statistics, “Useof Selected Preventive Services U. S--- 1982,” Vital and Health Statistics, Series 10, No. 157(Washington, DC: U.S. Government Printing Office, August 1986).

U.S. Department of Health and Human Services, National Center for Health Statistics,

“Adult Health Practices in the United States and Canada,” Vital and Health Statistics, Series5, No. 3 (Washington, DC: U.S. Government Printing Office, May 1988).

U.S. Department of Health and Human Services, National Institutes of Health, NationalCancer Institute, Division of Cancer Prevention and Control, Early Detection Branch,“Working Guidelines for Early Cancer Detection: Rationale and Supporting Evidence toDecrease Mortality” (Bethesda, MD: December 1987).

8/14/2019 8933


The Use of Preventive Services by the Elderly 65

78.

79.

80.

81.

82.

83.

84 .

85.

86.

87 .

88.

89 .

90.

91.

U.S. Department of Health and Human Services, National Institutes of Health, NationalHeart, Lung and Blood Institute, National Cholesterol Education Program, “Report of theExpert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults”(Bethesda, MD: October 1987).

U.S. Department of Health and Human Services, Preventive Services Task Force, “Recom-mendations for Breast Cancer Screening,” J. A.M.A. 257:2196, 1987.

U.S. Department of Health and Human Services, Public Health Service, “Screening for Cer-vical and Breast Cancer -- Southeastern Kentucky,” Morbidity and Mortality WeeklyReport 36(52):845-849, 1988.

U.S. Department of Health and Human Services, Public Health Service, “Use of Mam-mography for Breast Cancer Screening -- Rhode Island, 1987,” Morbidity and MortalityWeekly Report 37(23):357-360, 1988.

U.S. Department of Health and Human Services, Public Health Service, “ProvisionalEstimates From the National Health Interview Survey Supplement on Cancer Control --United States, January-March 1987,” Morbidity and Mortality Weekly Report 37(27):417-425, 1988.

U.S. Department of Health and Human Services, Public Health Service, Centers for DiseaseControl, Adult Immunizations: Recommendations of the Immunization Practices Com-mittee, undated.

Valente, C. M., Sobal, J., Muncie, H. L., et al., “Health Promotion: Physicians’ Beliefs, Atti-tudes, and Practices,” Am. J. Preventive Medicine 2(2):82-88, 1986.

Waldo, D. R., and Lazenby H. C., “Demographic Characteristics and Health Care Use andExpenditures by the Aged in the U. S.: 1977 -1984,” Health Care Financing Review 6(1):1-29, fall 1984.

Warnecke, R. B., Havlicek, P. L., and Manfredi, C., “Awareness and Use of Screening byOlder-Age Persons,” in Prospectives on Prevention and Treatment of Cancer in the Elderly,

R. Yancik (cd.) (New York, NY: Raven Press, 1983).

Wechsler, H., Levine, S., Idelson, R. K., et al., “The Physician’s Role in Health Promotion- - A Survey of Primary-Care Practitioners,” N. Engl. J. Med. 308(2):97-100, 1983.

Williamson, P. S., Driscoll, C. E., Dvorak, L. D., et al., “Health Screening Examinations: ThePatient’s Perspective,” The Journal of Family Practice 27(2):187-192, 1988.

Winawer, S. J., Baldwin, M., Herbert, E., et al., “Screening Experience With Fecal OccultBlood Testing as a Function of Age,” in Prospectives on Prevention and Treatment of Can-cer in the Elderly, R. Yancik (cd.) (New York, NY: Raven Press, 1983).

Windsor, R. A., Morris, J., “Consumer Participation and Payment for Health Promotion

Programs at an Urban Primary Care Center,” The Alabama Journal of Medical Sciences21(2):209-213, 1984.

Woolhandler, S., and Himmelstein, D. U., “Reverse Targeting of Preventive Care Due toLack of Health Insurance,” J. A.M.A. 259(19):2872-2874, 1988.

8/14/2019 8933



92. Woo, B., Woo, B., Cook, E. F., et al., “Screening Procedures in the Asymptomatic Adult:Comparisons of Physicians’ Recommendations, Patients’ Desires, Published Guidelines, andActual Practice,” J. A.M.A. 254(11):1480-1484, 1985.

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