The document discusses building information systems for community programs, focusing on the role of community actors and the importance of quality data in health service delivery and management. It outlines the community health strategy in Kenya and highlights lessons learned regarding monitoring and evaluation, emphasizing that community health information systems require long-term commitment to function effectively. Additionally, it addresses challenges faced in data collection and management, particularly among community-based organizations working with vulnerable populations.

1. Building Information Systems
for Community Programs
Mary Freyder

2. Community Programs
 Definitions of community
 Geography, identity
 Setting, target, agent, resource
 Clinical and non-clinical health services
 Community actors – volunteers, civil society
orgs, government agencies
 Evidence-based impact – community
development, non-clinical services

3. MEASURE Evaluation Contributions
 M&E framework – Kenya
 Needs assessments – Kenya, Mozambique, Mali
 Case studies – Kenya, Tanzania, Zambia
 System design and training – Ethiopia, Kenya
 Data quality assessments– Tanzania, Rwanda

4. MEASURE Evaluation Contributions
 Indicator development
 Routine data quality assessment (RDQA) tool
 mhealth technologies for data quality improvement
 Child Status Index (CSI)
 Priorities for Local AIDS Control Efforts (PLACE)
 Survey tool for OVC programs

5. Lessons Learned
 Community volunteers and CBOs are collecting
and using data – Kenya dialogue days, local CBOs
serving vulnerable children
 Information systems often focus on reporting to
higher levels – not useful or sustainable at the
community level.
 M&E tools are only useful when they fit the
purpose – room for capacity building

6. Interventions for Empowering
Communities-Strengthening the
Community Health Information System
(CHIS) in Kenya
Edward Kunyanga
MEASURE Evaluation
End-of-Phase-III Event, May 22, 2014

7. Outline
 Background
 Overview of Community Health Strategy
(CHS) in Kenya
 Progress and outcomes in CHIS
strengthening
 Lessons Learned

8. Background
 Community Health Strategy (CHS) rolled out in
2006 as part of the National Health Sector
Strategic Plan (NHSSP II) 2005-2010
 NHSSP II refocuses national efforts on health
promotion of individuals and communities,
formally recognizing tier 1 services
 Tier 1 services are aimed at empowering
communities and households to take charge of
improving their health

9. Structure for Community Health
Service Delivery

10. Community Health Committee (CHC)
 Health activities taking place in the community
unit (CU) are coordinated
by the CHC:
 Dialogue days: key health indicators are reviewedin
orderto identify communityneedsto improvehealth
and developactions
 Actiondays: keyactions as determinedduring the
dialogue days are implemented

11. Typical Monthly CU Dialogue Day
 Improvingtheperformance(availability,access,qualityandutilization)ofCHISwill
beagradualprocess(lowliteracylevelsofCHWs,volunteerism,sizeofthe
coverage,stakeholderconsensusbuilding)
 Utilizationofover80%ofthecollectedcommunitydatainCUsdialogueandaction
dayshasimprovedhealthoutcomes

12. Objectives of CHIS Strengthening
 To strengthen CHIS in providing quality
data from tier 1 for use at both community
level and within the formal health sector
 Prepare CHIS for linkage with the unified
system for national health information
management (District Health Information
System – DHIS2)

13. CHIS Strengthening

14. Examples of CHIS Indicators
 # of deliveries by a skilled attendant
 # of pregnant mothers who attend at least
4 ANC visits
 # of children fully immunized
 # of fever cases managed
 # of case referred
 # of births, # of deaths by age
 # of diarrhea cases managed

15. Community Health Information System
(CHIS) – Assessment
 Case Study of the CHIS in 5 CUs conducted
in April 2011
 M&E capacity assessment of national CHS
M&E unit conducted in June 2013
 CHIS functionality assessment of 31
CUs conducted in July 2013

16. Findings
 CHISrequirescoordinatedstrengtheningeffortsaround
priorityareasin orderforittobea morecompleteand
functional systemservingbothcommunityand national-level
programmonitoring anddecisionmaking, asintended.(Case
Study, 2011)
 Capacity oftheM&E teamtoimplementCHIS requires
supportwithineachofthe12 componentsofafunctional
M&Esystemtoimprovethequality, technical, and financial
autonomy in implementingCHIS (M&ECBAssessment,2013)

17. CHIS Functionality Assessment
Key Finding: Only half of the CUs that
were sampled were fully functional as
per national guidelines.
Issues include:
 lack of infrastructure
 training gaps among CU staff
 poor reporting rates and data quality

18. Where Are We Now?
 Monitoring the collectionanduseofquality datain8CUsthat
havebeentargeted with apackageofinterventions todevelop
themas“Centers ofExcellence” forCHIS
 Currentreportingrates insupportedCUsreceiving apackage
ofinterventions hasincreasedfrom69%inJune,2013to100%
asofMarch2014
 New data collectiontoolshavebeenrolled-outtobetterfacilitate
thecollection, management, anduseofcommunityhealth data
 TheCHISM&Eteamisimplementing acapacitybuilding action
plan
 AnmHealthplatformhasbeendeveloped toincreasethe
collection ,quality, anduseofcommunityhealth data
 Structuredlearning visits have beenorganizedtosharelessons
andbestpractices inCHSprogramming.

19. Lessons Learned
1. System strengthening takes timeandlong-term commitment
andresourcesinordertoensureboth
successandsustainability
2. SuccessfulCHISstrengthening isreliant uponunderstanding
localdataneeds
3. Continuousengagement with DCHSiscritical incoordinatinga
countryownedprocessforsystem strengthening
4. Synergyamongallpartners isessential inordertoaddress allof
theneeds forstrengthening CHIS
5. Using CHWstoanswerdonor,national, andsubnational
questions abouthealth service delivery andoutcomesoften
over-burdensstaff,andresults inmissing reportsandpoor
quality data

20. Community Based Information Systems
Through an OVC Lens
Molly Cannon
End-of-Project Event
May 22, 2014

21. Volunteer
CBO

22. Types of OVC Information Gathered
Information Types Illustrative Tools
Situation Analysis PEPFAR OVC program evaluation tools
Targeting Nigeria’s Child Vulnerability Index, VAT, VI
Information to support
and monitor case
management
Child Status Index, Orphan Wellbeing Tool
Parenting Map, Child Support Index,
Household Assessment
Monitoring
Registration, Visitation/Service, Referral,
Training forms
Program Evaluation PEPFAR OVC program evaluation tools

23. MEASURE Evaluation Contributions
 Global Leadership
 National Systems
 Assessments
 Quantitative
 Qualitative
 Mixed Methods

24. MEASURE Evaluation Contributions
 Global Leadership
 National Systems
 Assessments
 Quantitative
 Qualitative
 Mixed Methods

25. MEASURE Evaluation Contributions
 Global Leadership
 National Systems
 Assessments
 Quantitative
 Qualitative
 Mixed Methods

26. MEASURE Evaluation Contributions
 Global Leadership
 National Systems
 Assessments
 Quantitative
 Qualitative
 Mixed Methods

27. OVC M&E Lessons Learned
1. Advances in OVC M&E systems
2. Data collection systems are organized for
reporting purposes
3. Design of M&E systems effects data flow
4. Ensure tools are fit for purpose

28. 1. Advances in OVC M&E Systems
 Strong M&E systems
 Emphasis on data quality and availability
 Use of information for decision making

31. OVC Tools
Database
Canned Reports
Review Data
Queries
Framework for Decision Making

32. 2. Data Collection Systems Are
Organized for Reporting Purposes

33. Consequences
 Disconnect
 Collecting information on every child at
every encounter
 Ethics
 Burden
 Data quality
I’m sorry, didn’tyou
already ask me about that
last time you were here?

34. 3. Design Of M&E Systems Effects Data Flow
Village 1
X40
Village 2
X40
SIGNATURES
80 forms per ward
X 20 wards =1,600
forms
WEO 1
CBO2
CBO3
CBO4
CBO5
CBO6
CBO7
CBO8
80 forms
CBO 1

35. X4 X4 X4
Station 1 Station 2 Station 3
11 volunteers
per station x 4
forms = 44
per station
tation
11 vol * 4 forms
District 1
OVC Focal Person
CBO 1
44 forms X 3 stations =
132 forms for a District
2 districts X 66 volunteers =
252 forms
District 2
1 volunteer
completes 40
forms per
month. 40
stay with
him/her
CBO 2 CBO 3
11 vol * 4 forms 11 vol * 4 forms

36. Consequences
Volunteer CBO
Increased
burden
More forms,
more labor
Need capacity
for tallying
Need capacity
for entry,
analysis, IT
More challenging
to assess data
quality
Is it
sustainable?
 Signatures can
impede flow and
create burden
 Aggregation task
shifting has
consequences

37. 4. Ensure Tools Are Fit for Purpose
 Consequence
 May make
decisions on
incorrect
information

38. The Way Forward
Prioritize information needs
Streamline guidance and tools
Ensureinformationsupportsvolunteers
Identify sustainable solutions

39. www.measureevaluation.org/eop