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“Designing” an IHIAHealth Information Systems; Integration and Scaling
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– Why IHIA?
– IHIA challenges (fragmentation++)
– three levels of standards
– why is integration important?
– integration strategies; including interoperability
– scaling of IHIA initiatives
Understanding IHIAs
IHIA: The motivation
“Global” consensus on the importance of integration
+ HIS means different things to different groups of people
+ Different technologies form parts of the infrastructure used to support various systems
+ Standards allow different systems and supporting infrastructures to “speak to each other”
= Integrated Health Information Architecture (IHIA)
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“Better information. Better decisions. Better health” - Health Metrics Network (HMN)
Conceptualizing Architecture
Architectures are not end-solutions, but approaches to manage complexity (e.g. city planning / regulation)- Tension between short term solution and long term goal
- HIS architectures provide road maps or compass for “good design”
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Standards? Prerequisite for integration and interoperability. Without shared “understanding” and meaning, no interoperability or integration, be it within social or technical systems!
IHIA/HIS: Four Challenges
Fragmentation of data sources– Different sub-systems, owned by different stakeholders
Data-led, not action-led– Focus is on collecting and reporting data, rather than using
if for decision making
Lack of Scaling (and sustainability)– Limited system coverage– Limited uses and users (functionality)
Centralization vs decentralization– Difficult to strike a balance (social & technical)
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An example of fragmentation: Mozambique
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Point of departureFragmented information & Poor data quality
1st step : Integrate data reporting Use existing data in District /National database repository
& Demonstrate integration is possible and useful Revise data reporting forms & structures
2nd Step : “Vertical Integration” Patient record system (OpenMRS) for HIV /AIDS
Export aggregate patient data to DHIS Human resource management (iHRIS)
Export aggregate HR data to DHIS
Another Example: Sierra Leone
Point of departure Sierra Leone:Fragmentation of information
National:Fragmented infoDifficult access
District:Fragmented data managementPaper-based transcription and transmissionNot fully disaggregated
Facility:Many reportsLittle feedbackLittle use at facilityNo hospital reports
Census
Surveys
NationalStatisticsOfficeEPI
All programs own systems
HIV RH/FP
Hospital
IDSR
EPIRH/FPHIVIDSR
Directorate ofPlanning & Information
District reports compiled by hand
Outpatient services & morbidity
EPIRH/FPHIVIDSR
HMIS
TB
TB
TB
Outpatient services & morbidity
Sierra Leone: 1st step- aggregate data from all programs & services (horizontal integration)
HF1 HF2 HF3 HFn…..
Harmonised paper forms
Health facilities and hospitalsreporting aggregate paper forms toHIS office at district
Nati
onal
Lev
elD
istr
ict L
evel
Faci
lity
Leve
l
HIS officeIntegrated data management
HIS officeIntegrated data entry
Information use
Information use
Information use
Feedback
Feedback
DHIS:District data repository
DHIS:National data repository
Data and tools available to allstaff
Sierra Leone: 2nd step Integration & interoperability (vertical)
DHIS
Others
OpenMRS iHRIS<... Integration ...>
Interoperability
Patient records Human Resources
IHIAs as social systems
system of systems- IHIA perspective emphasize social context in relation
to technology- multiple rationalities- various human /organizational actors (international
donors, ministry officials, vendors, infrastructure providers) and technologies
- change typically involves redefining power relations (e.g. paper gateways / gate keepers)
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Some social causes of fragmentation
- Statisticians (data people) vs Public health (action people)
- Medical (point of care) vs Public health (aggregate)- Proprietary systems vs Open source- Quick fixes vs Long term Strategy- Isolated systems vs IHIA- Donor Politics vs National Strategy
Statisticians vs Public Health
“data represents a public health event”
More is better vs Minimum Data Set & information pyramid
Treatment of outliers
Upward reporting bias (performance)
Medical vs public health
Medical focus on patient record systems
Disease based coding & classification – ICD
Isolated (e.g. Excel) systems that do not talk with others
Doctors as informaticians not as users
Systems of limited scale
Proprietary vs open source
Proprietary systems may breed corruption
Vendor lock-in & Licensing costs
Short term with respect to system evolution (package)
IT people or finance people in control
Lack of procurement guidelines
BUT even open source initiatives may breed corruption (e.g. training, consultancy)
Quick fixes vs long term strategy
Ideal: long term, build local capacity / sustainability / maintainability – linked with education process
BUT
Vendors promise short term utopias
Government officials typically short term – want to be remembered for reforms
Aid projects often short term – pilots
Hardware/software emphasized, not people
Isolated systems vs architecture
Isolated systems promoted by many; donors, vendors, health programmes
Funding scheme contribute to fragmentation
Lack of interoperability standards
Architecture thinking is still alien
Many legacy systems (e.g. Norway)
Donor politics
How does it play out?- Promoting own systems
- Expatriates/experts
- Influencing government
- Not adopting integrated health
systems framework
HISP/DHIS2 from activists to regulators?
IHIA requirements?
Existing work practices as requirements => automating inefficiencies?
Focus on “information use” – information for action
Support information needs across horizontal and vertical dimensions of the IHIA (integration)
Guiding principles
Information available at “one point” (data warehouse)
Lower levels need richer and more granular data
Higher levels need less data; more aggregated
Information for action; essential data and indicators linked to targets and real use
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HIS/HIA: Integration
– Involves data, organizational behavior, workforce, and policies
– Must be sustained over time through routine processes, and is not a one off technical process (institutionalization)
Example (DHIS2)District HIS designed to enable collection, collation, and
analysis of HMIS & disease surveillance data across different subsystems
“The process of making multiple subsystems appear as one single system”
Some benefits of integration
Value added to data– New indicators possible– Enables cross-comparison– Ease of access
Cost efficient– Professionalizing information management (e.g. cloud
computing)– Pooling of resources (financial, human)– Economies of scale– Centralized supporting activities (technical maintenance)– Decentralized core activities (public health decision making)
Number of clients per clinical worker per day, by district, 2008 and 2009
0
5
10
15
20
25
Western Area Moyamba Kono Kailahun Bonthe Port Loko Bo Kenema Kambia Koinadugu Bombali Tonkolili Pujehun
Total
PHU (All) Chiefdom (All)
Average of Clients/Clinician/Day
District
Example Integrated Human Resource & Health service data
Level 1: InformationNeeds, Users, UsageAcross Organisations
“Social System level”
Level 2: Software applications& Information Systems“Application level”
Level 3: “Data exchange level”“Technical level”
Interoperability & standards, technicalinfrastructure
OpenMRS
DHISPatientrecords
iHRIS
Data warehouseAggregate data
SDMX-HD
Institutional use of information
Applications supporting useof information
Data Standards and infrastructure supporting the applications
Enterprise architecture: 3 Layers
Data & indicator standards
Facility list
SDMX-HD
Three levels of HIA (enterprise architecture)
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Three Levels of the Health Information Architecture
Level 1: Information needs, users and usage:“Business Level/ Social System Level”Level 1 uses services from the level below (level 2)
Information needs and actual usage of information; business processes supported by the HIA. Documented through users specifications and requirements. The defining layer of the architecture!
Level 2: Software applications and information systems:“Application level”Level 2 uses services from the level below (level 3)
Applications and systems responding to the users’ needs, providing the required information and services to the users. Documented through application documentation, manuals, and actual implementations!
Level 3: Data exchange, interoperability and standards:“Technical level”
The technical level of data exchange and interoperability. Data and technical standards for interoperability between systems and applications. Documented as formal standards for data exchange, data dictionaries of data standards and semantics.
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Increasing differences between views
Three Levels of (achieving)Interoperability
--Organisational/ Political /pragmatic
--Semantic
--Syntactic /technical
Compared to a telephone conversation
Shared interests?Interested in talking?
Shared language and shared understanding?
Compatible telephones & networks?
Interoperability and integration require standards
For each level; “solutions” based on solutions at level below, and rely on agreement at level above
SDMX-HD,etc.
Shared / agreed indicators& meta data
Programs / donors /agenciesAgree to standardisation
Unique id.
Standardisation & interoperability may be seen as going on at three levels of increasing complexity
HorizontalAcross health programs, Services & agencies ateach level
VerticalLevels of aggregation;From HR /patient records, to national & global reporting (MDG indicators)
DHISOpenHealth
Other data sources –programs
NationalDistrict based
Integrated data repository
CRIS
High Granularity
Low Granularity
iHRIS
DHIS
SDMX-HD
Statistical data“numbers”
HR records“names”
Translation& aggregation
DATADICTIONARY/
CONCEPTREPOSITORY
OpenMRS
DHIS
Exchange standard
Tensions between Standards and Local Flexibility => Essential Data Set
Organisational /political level of integration
(information needs & usage)
Horizontal integration: Information from across sectors & health programs available at “one point”
Vertical Integration: “Seamless” flow of information from peripheral to central levels, from patient encounters in clinics to national M&E
Software applications& Information Systems
Horizontal integration: Data warehouse, such as DHIS, integrating & managing data from different health programs and sectors
Vertical Integration: Extracting aggregate data from Human Resource system, and patient record systems into one data warehouse (e.g. DHIS2)
Data exchange, interoperability &
standardisation
Horizontal integration: Shared data & indicator standards prerequisite for sharing data across health programs & sectors, whether from paper or computer sources. SDMX-HD data exchange format enable transfer of indicator definitions and data
Vertical Integration: Shared data standards also prerequisite for aggregating from individual human resource records in iHRIS to data according to standard loaded in DHIS using SDMX-HD
The application level of IHIA
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Data Interoperability
Data Interoperability / syntactic/ technical– Essential component to achieve integration– Interoperability; standardized data definitions for data
exchange among sub systems
Example– Shared data definitions among data collections tools (paper
or software) across different subsystems, and standards for exchanging these data (e.g. XML)
Standards to facilitate interoperability
Data standards:– Definitions and rules of use for data– Example: ”infant mortality rate” is an internationally agreed
indicator, with a clear definition
Data exchange standars:– For enabling software to process electronically sent
information– Example: HL7, SDMX-HD
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Strategies for scaling of IHIAs
Technical system, quantitative dimension:
Components of the IHIA
Social system, qualitative dimension:
Cultivation approaches
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IHIA Scaling: Technical perspective
Data warehouse for aggregate data- manage the data- integrate the various datasets and sub-systems - Interoperability and data exchange through standards- gateways between data warehouse and sources of data (paper, computer).
The data warehouse needs to be flexible- Integrate and manage data sets as they are emerging, changing and
developing- Present and make data available according to domain knowledge and
"business intelligence", as user needs are developing and emerging
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Shared data standards and indicators, are the primary building block of the IHIA
IHIA Scaling: Social Perspective
User participation; to get users’ at all levels committed, and foster learning and a sense of ownership to information and system
Scale the architecture gradually along the vertical and horizontal axes, depending on users’, and institutional readiness and learning
Focus on solving specific large problems shared by many
Flexibility; data standards, data warehouse and means of data exchange need to be flexible; to enable change according to redefinition of needs, infrastructure and overall context
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Five (uneven) processes of change From paper to computer
From stand-alone to networked computers
From paper records to electronic patient records
From paper to mobile phone
From offline to online (web-based HMIS)
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Scaling in uneven contexts:
Do we need to cover all forms? (deepen)
Do we need to cover all reproting units? (widen)
If not, useless?
Centralization, decentralization and hybrid models
Centralization versus decentralization is a historical challenge in IS/HIS design
Dimensions involved here are– Who makes decisions?– Who controls budget?– Where does the data reside? (political/technical/managerial)– Does implementation start at top, or bottom, or a hybrid?
These questions have implications on:– User involvement (not always empowering)– Sustainability of systems– Scalability of systems– Use of information for decision making
Discussion topic: HISs/IHIAs as socio-technical systems1. Form groups
2. Discuss the following proposition in your group”HISs/IHIAs can not be built from scratch, but evolve as socio-technical
systems. The introduction of new (HMIS) routines, new technology etc. takes place in a highly complex and embedded setting, and will be shaped by this”
In relation to the proposition consider:- Data / information flow & transparency - Data ownership- HIS Funding/financing- Health Data regulations & policy- Top-Down vs Bottom-up IHIA restructuring
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