The document discusses interoperability and data linkage in health information systems. It defines key terms like interoperability, fragmentation, integration, and data warehousing. It describes how linking data sources like RHIS, EMRs, and surveys can improve health systems by enabling analysis of relationships between different types of data and more timely monitoring. Specific examples are provided of countries that linked their LMIS, HMIS, and HRIS systems to generate new indicators and identify supply issues. Decision support systems and enterprise architecture are introduced as ways to facilitate data analysis and alignment of health IT investments.

1. Interoperability: Linking RHIS and
Other Data Sources
RHINO Forum
Michael Edwards, PhD
RHINO Forum Webinar,
September 20, 2016

2. Objectives and Topics Covered
Objectives
• Explain Interoperability and data linkage terms
• Describe the role of information and communication technology
(ICT) in integration and interoperability of the RHIS
• Introduce Forum Discussion Topics
Topics Covered
• RHIS Fragmentation
• Integration of the Health System
• Interoperability of Information Systems
• Data Linkage Terminology
• Health Information Exchange
• Data Warehouse
• Enterprise Architecture

3. Data Linkage Terminology
• Fragmentation of the Health System
• Integration
• Interoperability
• Electronic Medical Records
• Aggregate Systems
• MFL (master facility list)
• Health information exchange (HIE)
• Sharing metadata
• Triangulation
• Enterprise Architechture

4. RHIS Fragmentation
Fragmentation of RHIS refers to the
absence, or underdevelopment, of
connections among the data collected
by the various systems and
subsystems.
Source: Heywood A; Boone D. (2015). Guidelines for RHIS data management
standards. Chapel Hill, NC: MEASURE Evaluation, University of North
Carolina.

5. HISFragmentation
Source: Adapted by MEASURE Evaluation from University of Oslo presentation

6. Causes of Fragmentation
• Relating to poor governance, weak
oversight and supervision, differing
organizational and programmatic
interests, political maneuvering, donor
pressure, and/or geographic rivalry
Institutional
• Reflecting poor HIS design, lack of
technical interoperability among existing
systems, and the absence of common
metadata (i.e., data definitions, data
sources, frequency of reporting, levels of
use, targets)
Technical
• Resulting from narrow programmatic
interests, inadequate training, and the
lack of appropriate HIS skills of health
managers and providers
Behavioral

7. What is “integration” of the health system
• The act of forming, coordinating, or
blending several subsystems into a
functioning or unified whole
• The ultimate purpose is to create a health
system where integrated service delivery
leads to holistic health improvements

8. Integration of the Data Management System
A number of definitions apply to integration:
• In engineering: Bringing together of the components into a
single system and ensuring that subsystems function
together as a unit
• In information technology: Process of linking together
different computing systems and software applications
physically or functionally, to act as a coordinated whole.
Source: Heywood A; Boone D. Guidelines for RHIS Data Management
Standards. February 2015. MEASURE Evaluation

9. Best Practices
• Standard Indicators and Data Sets
o Agreeing on and developing standard indicators and related data sets is an
essential first step in developing an integrated RHIS.
• Beneficiary-Centered Integration
o Integration of Paper Records
o Integration of Electronic Records
• Facility-Level Integration
o Summary reports from different programs are combined into one integrated
monthly facility report
• System-Level Integration
o Integration of the RHIS
o Interoperability of data sources
o Integrated data warehouse

10. Linking Data Sources
Linking of data sources leads to a strengthened health
information system (HIS)
• Linking various EMR systems
• Linking EMRs to aggregate systems
• Linking various RHIS subsystems such as HMIS,
LMIS, HRIS, Laboratory, Financial, etc.
• Linking the routine health information system
(RHIS) with population census and data from the
Demographic and Health Surveys (DHS)

11. Electronic Medical Records (EMR)
• Contain data related to a single patient, such as
diagnosis, name, age, and earlier medical history
• Data typically based on a single patient/healthcare
worker interaction
• Systems used largely by clinicians for diagnosis and
treatment, but also by administrative staff for
accounting and file management
• EMR is not just one system; it may include interfaces
with multiple other systems and applications

12. Aggregate Information Systems
• Contain consolidated data relating to multiple
patients, and therefore cannot be traced back to a
specific patient. They are merely counts, such as
incidences of malaria, TB, or other diseases.
• Aggregated data are used for the generation of
routine reports and indicators, and for strategic
planning and guidance within the health system.

13. Interoperability
Ability of health information systems to work together within
and across organizational boundaries in order to advance
the effective and integrated delivery of healthcare for
individuals and communities
Ability of different information technology systems and
software applications to communicate, exchange data, and
use the information that has been exchanged for improved
service delivery and health.
Source: HMISS Interoperability and Standards Toolkit. Retrieved from
http://www.himss.org/library/interoperability-standards/toolkit.

14. Sharing Metadata
• Metadata: “data about data"
• Metadata describe how, when, and by whom a
particular set of data was collected, and how the data
are formatted
• Metadata: Essential for understanding information
stored in data warehouses; has become increasingly
important in XML-based web applications (most
recent IEP)

15. Health Information Exchange
Electronic health information exchange (HIE) allows doctors,
nurses, pharmacists, other healthcare providers, and patients to
appropriately access and securely share a patient’s vital medical
information electronically, thus improving the speed, quality, safety,
and cost of patient care.
• Directed Exchange: Ability to send and receive secure
information electronically between care providers to support
coordinated care
• Query-Based Exchange: Ability for providers to find and/or
request information on a patient from other providers, often used
for unplanned care
• Consumer Mediated Exchange: Ability for patients to
aggregate and control the use of their health information among
providers

16. Open HIE
Community of Practice (CoP) dedicated to improve the
health of the underserved through open and collaborative
development and support of country-driven, large-scale
health-information-sharing architectures.
• Enabling large-scale health information interoperability
• Offering freely available standards-based approaches
and reference technologies
• Supporting each other’s needs through peer technical
assistance communities

17. HIS Architecture and Health Information
Exchange

18. Master Facility List (MFL)
• A comprehensive, up-to-date, and accurate list of all the
health facilities (public and private, including community
services) in the country
• Each health facility is uniquely identified using a set of
identifiers (the signature domain)
• Links health services data and other core health-system
data (financing, human resources, commodities, and
infrastructure) through the unique identifiers defined in
the MFL:
o Is useful for administrative purposes
o Allows better analysis and synthesis of information
o Improves health systems reporting and planning

19. Linking Data Using Master Facility List
• Data harmonization: comparing and contrasting data
across different data sources and across time
• Data linkages and collaboration between departments
and ministries with related data
• Health facility surveys: comprehensive lists for
sampling
• Health information system strengthening: combining
data from multiple sources to generate facility,
regional, and national profiles for effective planning

20. RHIS Linkage Examples
Linking HMIS with a census
• Coverage rates
Linking logistics management information systems (LMIS)
and HMIS:
• Relationship between stockouts and services
• Composite indicators, such as couple years of
protection (CYP)
Linking human resource information systems (HRIS) and
HMIS
• Workload analysis (patient visits per doctor)

21. Linking Family Planning
Service Data with Census Data
• Intervention, restructuring maternal and child
health (MCH)/family planning (FP) facility-based
information system
• Before linking RHIS and census data, the only
contraceptive prevalence rates available to an
MOH were national estimates from DHS every 5
years
• After linkages, calculations from RHIS data
provided the needed annual district- and
national-level CPR estimates

22. 22
Routine FP data: Case Study on Morocco

23. An Example of System Interoperability in Eritrea
Linking LMIS and HMIS Data for
Improved Use of Information
• Intervention: General restructuring of the facility-based RHIS
• Before the improved RHIS, vaccine stockouts went unreported
• After linking LMIS and HMIS, vaccine stockouts could be monitored
monthly, and the relationship between stockouts and children
vaccinated could be tracked
• Evidence of an elevated stockout percentage alerted MOH to request
additional vaccines from donors

24. Linking LMIS and HMIS Data for Improved
Use of Information
Before: Vaccine stockouts went unreported
After: Tracked
relationship between
stockouts and
children vaccinated
Evidence of elevated stockout percentage and lower number of
children vaccinated alerted MOH to request additional vaccines
from donors.

25. 0 200 400 600 800 1000 1200
ANSEBA
DEBUB
DEBUBAWI KEYHI BAHRI
GASH-BARKA
MAAKEL
NATIONAL REFERRAL
SEMENAWI KEYHI BAHRI
Admissions per Doctor
Eritrea: Linking HRIS and
HMIS:
Calculation of New Indicators

26. What Is a Decision Support System (DSS)?
A computerized application allowing health
managers to visualize RHIS health indicators and
data elements in graphic and geographic
presentations
Comparison is one of the most powerful analytic
methods
• Spatial: by health facility, district, province
• Time: trends by week, month, year
• Indicators: between inputs and outputs
• Benchmark: expected versus achieved

27. Decision Support System

28. Why a Decision Support System (DSS)?
• Enables health managers to promptly and
efficiently analyze data for decision making
• Allows health managers with limited data analysis
skills to better interpret aggregate information from
the RHIS
• Is well-suited to health managers at national,
regional, district, and local levels, because is user-
friendly for lowly ICT educated health workers

29. Data Warehouse Definitions
“A data warehouse is simply a single, complete, and
consistent store of data obtained from a variety of sources
and made available to end users in a way they can
understand and use it in a business context.”
– Barry Devlin, IBM consultant
“A data warehouse is a subject-oriented, integrated,
time-variant, and non-volatile collection of data in
support of management's decision-making process.”
– W. H. Inmon, computer scientist

30. Data Warehouse Concepts
Distinction between data and information
• Data are observable and recordable facts that are
often found in operational or transactional systems
• Data only have value to end-users when they are
organized and presented as information
• Information is an integrated collection of facts and is
used as the basis for decision making

31. Data Warehouse Concepts
• Data warehouse is designed for query and analysis
rather than for transaction processing
• Data warehouse separates analysis workload from
transaction workload. This helps:
o Maintain historical records
o Analyze data to better understand the business
o Improve the business

32. Data Warehouse Architecture

33. Need for Enterprise Architecture (EA)?
To give management the big picture.
EA gives a “systems thinking” view that combines vision and strategy,
business architecture, information systems, and technology domains.
To align IT investments with business goals.
Creating a platform for business-ICT stakeholder collaboration is essential.
Effective enterprise architecture supports strategy, analysis and planning by
providing stakeholders a blueprint of the current state of the business and IT
landscape, and of the desired future state (vision).
To provide IT developers with specific requirements for software
applications
The business architecture provides the IT developer with the specific
software requirements of an application.

34. Enterprise Architecture

35. HIS Architecture Principles
35

36. HIS Architecture
• Can align and leverage investments to build stronger and better
integrated HIS supporting better health policy and local health
services management, and ultimately stronger health systems
• To be built on a coherent set of best practices for promoting data
integration
• To foster stakeholder groups to collaboratively build on common
components and a common architecture within the HIS
• Helps identify and create interoperability between the
components of the system

37. RHINO Forum
This presentation was produced with the support of the United States Agency for International
Development (USAID) under the terms of MEASURE Evaluation cooperative agreement AID-
OAA-L-14-00004. MEASURE Evaluation is implemented by the Carolina Population Center,
University of North Carolina at Chapel Hill in partnership with ICF International; John Snow,
Inc.; Management Sciences for Health; Palladium; and Tulane University. The views
expressed in this presentation do not necessarily reflect the views of USAID or the United
States government.