Webinar presentation by Eric Geers

1. Information Products
to Drive Decision
Making
Eric Geers, MPH, MA
MEASURE Evaluation
Palladium
May 9th, 2017
Webinar

2. Routine health information
system (RHIS)?
Information that is collected at regular periods
in a year to support decision making at
different levels of health system
• Service or resource records systems from facility
and community-based public, private, and
parastatal service providers

3. Types of Internet-based RHIS:
1. Health management information system (HMIS)
2. Human resources for health information system (HRHIS)
3. Logistics management information system (LMIS)
4. Disease surveillance response system (DSRS)
5. Disease-specific system
6. Don’t know
What type of internet-based
RHIS is most useful for managing health
services?

4. • Limited reach for the use of internet-based
RHIS
• Describe barriers to data use
• Information products are tools for RHIS
engagement
Presentation aims

5. Assessment overview
MEASURE Evaluation project
Kenya:
• September 2015 to April 2016
Tanzania:
• March to July 2016

6. Research aims
• Availability of information products
• Potential for improvements
• How best to use information products
Methods
Informants
• HIV/AIDS and MCH staff, national to health facility (n=57)
• Kenya (n=23): 3 counties
• Tanzania (n=34): 4 districts

7. Data sources
• Data accessed
• Data systems used
• Triangulation
Questions
User experiences
• Relevance of information
products
• Preferences to receive
information
• Data reviews
• Challenges / motivations
https://www.measureevaluation.org/
resources/publications

8. Ripple effect of data use…
“We need to change the whole
culture and practices of
information sharing to
motivate health providers.
They need to feel and see the
value of the data they collect
by sharing with them
frequently the outcome of the
work they do on the data.”
National

9. Limited work force and
technical capacity to fulfill
a triple burden of:
• Service delivery
• Data collection
• Data use
Why no data use at facility?

10. Reduce burden of
• Data collection
• Data management
Promotion of data use
Facilitate access to data through
• Preselected indicators
• Understandable presentation of analysis
• Feedback on performance

11. Who can / should produce
information products?
National & Regional District & Facility
Technical Ability &
External Support
Data Collection
& Reporting
Burden
Service
Provision
Technical
Ability &
External
Support
Data
Collection &
Reporting
Burden
Service Provision

12. Design and test new information products
• Identify information needs of service providers
• Create visuals that highlight key messages in data
• Pilot test
• Orient intended audience to product
• Disseminate prior to key planning events
Where to focus?

13. “If available, an information product would be
useful to provide feedback on performance. It
would help [us] to set new targets reasonably. It
would help [us] measure our own performance.
It would help [us] to correct ourselves where we
go wrong. It would guide us where to put more
efforts.”
Informants value feedback

14. • Performance comparisons
• Recommendations on how to improve performance
• Suggestions on where to focus resources
• Sharing of best practices
• Predictions of problems
• Recognition of good performance
• Guidance on how to access other data
• Guidance on whom to involve in the review
Brief, written feedback within
information product

15. Next level of data use:
Performance review meetings

16. Barriers:
• Specialization
• Lack awareness / access
• Differing time periods
• Conflicting data
Solutions:
• Incremental integration based on
need
• Links to other databases
• Training on multiple databases
Triangulation of data sources

17. Observations of product use

18. Observations of product use
Questions Observations
What does
this info tell
me?
“… We are looking at performance for PMTCT… We
look at the gap… We need to figure out why those
mothers who are positive are not getting the
prophylaxis.”
Any questions
about the
program?
“… Quality issues with the data… You can’t know which
health facility, or even which county.”
Next steps? “… interrogate the data… A lot of our mothers, if you go
back to the registers, actually get prophylaxis. So we
would probably do a DQA [data quality audit].”
Recommend “I would recommend that the team conduct facility-level
data analysis to identify which facility is reporting this
data.”

19. Observations of product use

20. Observations of product use
Questions Observation
What does
this info tell
me?
“…you can… kind of find out… how many of them
did get their prophylaxis, the total number of maternal
ANC patients, and the total number of those who are
positive… So you can even now try to judge: are they
doing very well or is there an area that they need to
do an intervention.”
Any questions
about the
program?
“…there are areas with more [HIV-positive pregnant
women]…is it because of population…or way of
life…”
Next steps? “This can tell you a lot…give you a lot to plan for
interventions.”
Recommend “… It will require a field visit after digging deeper…”

21. Provide regular, standardized information
products for specific target audiences
Staff value feedback
Relate routine data to service delivery with data
review opportunities
Summary

22. Questions?
www.measureevaluation.org/resources/publications/sr-17-145-en
Eric Geers, MEASURE Evaluation
Eric.Geers@thepalladiumgroup.com

23. 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. Views expressed are not
necessarily those of USAID or the United States government.
www.measureevaluation.org