1. C OMMUNICATING F INDINGS & L INKING D ATA WITH A CTION Module 5

2. PART I: PROVIDING FEEDBACK ON DATA COLLECTED / ANALYZED

3. Part 1: Session Objectives  Understand the importance of feedback in program improvement and management  Consider how to improve feedback mechanisms in own work 3

4. “We are always giving patient forms and data to our M&E Unit, who then gives data to donors and the government. I am the head doctor and I never have the chance to look through the data before they go up. We just keep giving data up and up, and we never hear back about it…” Head of ART facility, Nigeria

5. Importance of Feedback  Information needs to be shared  At timely and regular intervals  Within, between, up, and down  Paves path between data collectors and users at all levels of the health system

6. Importance of Feedback  Leads to greater appreciation of data:  Improved data quality  Influencing collection of appropriate data  Important element of management and supervision  Creates opportunity to monitor & improve program services  Incentive for staff

7. Examples of Feedback  Sharing information within a facility or organization  Sharing aggregated service provision data from facilities within a district or between provinces  Meetings between facility and supervising agency to review and discuss information  Meetings between donor and NGO to review information and discuss challenges and opportunities

8. Working Toward a Culture of Information Use  Information becomes an integral part of decision-making processes, including planning, problem solving, choosing alternatives, feedback, etc.  Empowers people to ask questions, seek improvement, learn, and improve quality

9. Higher Levels: District, Province, National Analysts, Evaluators Service Delivery Point Feedback Managers, Government, Donors Program Compiled Data Clinical Histories, Service Statistics Reports Information Flow

10. Variety of Formats  Narratives  Summaries, bulleted items, graphs, charts  In-person discussion  One-on-one  Staff meetings, district meetings  Speeches to staff  Supervision visits

13. Quarterly Performance Indicators #IndicatorNumeratorDenominatorPercentage ART 1% of eligible clients placed on ART # of new clients on ARTSum of # of new clients on ART and clients on ART waiting list 100% 39 2% of current ART clients # of active clients on ART# of cumulative clients on ART 92% 16201765 3% of ART clients in 6 month cohort undergoing repeat CD4 testing # of clients for whom repeat CD4 testing was done at 6 months Total # of active ART clients in 6 month cohort 94% 147156 Pediatric ART 1% of children current on ART # of active children on ART# of cumulative children on ART 78% 4558 ART Care Follow-up 1% of non active ART patients who have stopped ART. # of patients who stopped ART. # of non active ART patients. 0% 0145 2% of non active ART patients who transferred out. # of patients who transferred out. # of non active ART patients. 6% 8145 3% of non active ART patients who died. # of patients who died.# of non active ART patients. 73% 106145 4% of non active ART patients who have been lost to follow- up. # of patients who have been lost to follow-up. # of non active ART patients. 16% 23145

14. When developing feedback mechanism, consider…  The information being shared  Who will benefit from feedback  The format of the feedback mechanism  The forum in which the feedback will be shared  How often the feedback will be provided  How the feedback will move to the next level  Document the process

15. Potential barriers to providing feedback  Hierarchy  Role clarification – data clerk & M&E officer  Approval requirements to distribute data  Lack of knowledge of what information stakeholders need

16. Group Participation  Discuss barriers to providing feedback that you have experienced in your work  Discuss the benefits of feedback that you have experienced in your work  Identify:  Two stakeholder groups that would benefit from receiving feedback  The ideal mechanism to provide feedback to them

17. PART 2: LINKING DECISIONS/QUESTIONS WITH POTENTIAL DATA SOURCES

18. Part 2: Session Objectives  Identify priority decisions and programmatic questions  Link decisions/questions with potential data sources  Create a time-bound plan for using data in decision making (Framework for Linking Data with Action) 18

19. Building Data Use into Your Work  PLAN PLAN PLAN !  Regularly review your data – schedule time  Use the Framework for Linking Data with Action  Engage in dialogue with stakeholders to fully understand the  decisions they make  information they need  best way to present that information

20. Elements of the Framework  Decision makers and stakeholders with potential interest in your data  Decisions / actions that the stakeholder makes (possible uses of data)  Questions to which the stakeholder requires answers  When the decision will be made

21. Elements of the Framework (cont’d)  Indicators and/or data of interest (to respond to stakeholder need)  Source of data  How will data be presented (what types of analyses, graphs, formats)?

22. F RAMEWORK FOR L INKING D ATA WITH A CTION

23. Framework for Linking Data with Action Decision / Action Program/ Policy Question Decision Maker (DM), Other Stakehold- ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel

24. Framework for Linking Data with Action Decision/ Action Program /Policy Question Decision Maker (DM), Other Stakehold- ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel

25. What Are Decisions?  Choices that lead to action  All decisions are informed by questions  All questions should be based on data

26. Decisions  Allocation of resources across IPs/ states / districts/facilities  Revising OVC program approaches to emphasize fostering and adoption  Develop and institute workplace policies on HIV/AIDS in all institutions in state X  Hire and allocate staff to facilities

27. Programmatic Questions  What percentage of HIV+ pregnant women in care actually are delivering in health facilities?  What percentage of clients starting ART are lost to follow-up?  Are the number of family planning clients decreasing?  What percentage of pregnant patients who are HIV+ actually are receiving ART?

28. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehol ders (OS) Indicator/ Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio?

29. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training

30. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training

31. Framework for Linking Data with Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training 711 form indicator s K41, B73, B 91 Service statistics; Logistics manage- ment system

32. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training 711 form indicator s K41, B73, B 91 Service statistics; Logistics manage- ment system

33. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicato r/Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training 711 form indicator s K41, B73, B 91 Service statistics; Logistics manage- ment system Dec. 2010, March 2011, June 2011, September 2011, December 2011

34. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training 711 form indicator s K41, B73, B 91 Service statistics; Logistics manage- ment system Dec. 2010

35. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training 711 form indicator s K41, B73, B 91 Service statistics; Logistics manage- ment system Dec. 2010Short summary presented to facility manager at weekly clinic meeting

36. Framework for Linking Data with Action Decision/ Action Program/ Policy Question Decision Maker (DM), Other Stakehold ers (OS) Indicator /Data Data Source Timeline (Analysis) (Decision) Commu- nication Channel DM OS Hire more PMTCT counsel- ors Are we reaching testing targets in PMTCT? Do we have sufficient test kits? What is nurse: client ratio? DM – Head of Regional Health Committee OS – Other providers, Division of Clinical Training 711 form indicator s K41, B73, B 91 Service statistics; Logistics manage- ment system Dec. 2010Short summary presented to facility manager at weekly clinic meeting

37. Framework for Linking Data with Action  Creates a time-bound plan for information- informed decision making  Encourages greater use of existing information  Monitors the use of information in decision making

38. Small Group Activity 6 – Instructions  Select a note taker  On flip chart paper, create the Framework table  Brainstorm three decisions or questions in columns 1 & 2  Complete the remaining columns  Time: 1 hour

39. Small Group Activity – Report Back  Each group will have 10 minutes to present its completed Framework  Group discussion – are there other data sources that might have been used in this decision? Were there other stakeholders who should have been considered? (10 minutes)

40. Building Data Use into Your Work  PLAN PLAN PLAN !  Regularly review your data – schedule time  Use the Framework for Linking Data with Action  Engage in dialogue with stakeholders  Consider other tools or methods related to data demand and use

41. Improving Data Demand & Use: Multifaceted Approach Applying a combination of:  Assessment of current data use, capacity building needs, and barriers to data use  Capacity building initiatives around data use concepts, use of tools, data analysis…  Tool application  Organization development (e.g., leadership, systems improvement)  Collaborative efforts between data users and producers

42. Multifaceted Approach in Nigeria  Large amount of data collected, feeding NNRIMS  Data were not being used effectively at sites or within project  Pervasive mistrust of data  Lack of understanding of how RHIS data could be used  Lack of understanding of how indicators were calculated and used for program improvement

43. Multifaceted Approach in Nigeria

47. Multifaceted Approach in Nigeria: Results  86% of respondents implemented solutions to identified barriers to data use  76% reported assisting decision makers with data interpretation

48. THANK YOU! MEASURE Evaluation is a MEASURE project funded by the U.S. Agency for International Development and implemented by the Carolina Population Center at the University of North Carolina at Chapel Hill in partnership with Futures Group International, ICF Macro, John Snow, Inc., Management Sciences for Health, and Tulane University. Views expressed in this presentation do not necessarily reflect the views of USAID or the U.S. Government. MEASURE Evaluation is the USAID Global Health Bureau's primary vehicle for supporting improvements in monitoring and evaluation in population, health and nutrition worldwide. Visit us online at http://www.cpc.unc.edu/measure