Positive Synergies between Global Health Initiatives

1. Professor Rifat Atun Professor of International Health Management, Imperial College London & Director Strategy, Policy and Performance Cluster, The Global Fund to Fight AIDS, TB & Malaria Positive Synergies between Global Health Initiatives

2. Key Research Questions What are the extent and nature of integration of GHIs (programmes they finance) and health systems to achieve synergies in varied contexts? Which factors influence the extent and nature of integration? How the varied health system designs and delivery structures influence outcomes?

3. Key variables affecting the nature and extent of integration The Problem being addressed The Intervention The Adoption System The Health System characteristics The Broad Context Atun, Ohiri, Adeyi, 2008

4. Integrate or not to integrate: framework for analysis Broad Context Health System Characteristics Adoption System Intervention Problem Broad Context

5. The Problem Necessity and Urgency Burden Economic and social Perceived and real Social Narrative Transmission dynamics

6. The Intervention Complexity Scalability Simpler to more complex* Replicability * See next slide

7. Intervention: simple versus complex Single episode Less complex Multiple elements Few elements More complex Multiple episodes Atun and Kyratsis 2007

8. Intervention: simple versus complex Few stakeholders Less complex Multiple levels Few levels More complex Multiple stakeholders Atun and Kyratsis 2007

9. Intervention: simple versus complex User engagement lower Less complex Behaviour dominates Technology dominates More complex User engagement higher Atun and Kyratsis 2007

10. The Adoption System Receptivity Individual & organisational Political economy Incentives agency/provider/user incentive alignment Legitimacy Cognitive Technical Normative Economic

11. Health System Characteristics Feasibility Governance Structure and organization Financing Provider payment methods Resource availability Service delivery M&E system

12. The Context Sustainability Attributability Fiscal space Overall and health sector specific Frailty Reporting needs

13. The Context Opportunity Desirability Critical events Visibility Synergy Technology / innovation Political economy Socio-cultural factors

14. Analysing the extent and nature of integration

15. Integration into Critical Health System Functions Governance Reporting Accountability Financing Pooling Provider payment Planning Needs assessment Priority setting Resource allocation

16. Integration into Critical Health System Functions Service Delivery Structural Human resources, Shared infrastructure Operational integration Supply chain Guidelines Procurement Monitoring and Evaluation Data collection and analysis Demand Generation Financial incentives – e.g. CCT, insurance Population interventions – e.g. education and promotion

17. Some Initial Results

18. Intervention Complexity Single Dular - India Onchocerciasis - Uganda Nutrition - Peru, etc. FP/MCH - Matlab, Bangladesh STD - Mbofana FP; STD - Lafort Many Few FP/MCH - Pakistan - LHWP FP/MCH - Nepal (Tuladhar) Malaria - Colombia Dengue - Cuba Leprosy - India, Sri Lanka Schistosomiasis - Brazil, Burundi, Cameroon, China, Saudi Arabia, Uganda HIV/AIDS - Haiti ICDS IMCI Mental health - Whetten Substance abuse - Friedmann Multiple Intervention frequency/number of episodes Intervention elements

19. Extent of integration & success as documented in studies Fully integrated Most to all outcomes Partially integrated Mixed outcomes Few to no outcomes Not integrated ? ? Unknown Unknown

21. Extent of integration & success as documented in studies Governance Service delivery Monitoring & Evaluation Success Demand generation Planning Finance Dengue ? Cuba (ToledoRomani2007) Malaria Colombia (Rojas2001)

22. Extent of integration & success as documented in studies Governance Service delivery Success Monitoring & Evaluation Demand generation Planning Finance Schistosomiasis control ? ? ? Brazil (Filho1992) ? ? ? ? Burundi (Engels1993,1995) Cameroon (Bausch1995,Cline1996) China (Sleigh1998) ? Saudi Arabia (Ageel 1997) ? ? Uganda (Kabatereine 2006) ?

23. Extent of integration & success as documented in studies Stewardship/Governance Service delivery Success Monitoring & Evaluation Demand generation Planning Finance Leprosy India (Rao 2002, Thakar 2003) ? ? Sri-Lanka (Kasturiaratchi 2002)

24. Extent of integration & success as documented in studies Governance Service delivery Success Monitoring & Evaluation Demand generation Planning Finance Nutrition Peru Bangladesh (Hossain2005) ? ? Various (Deitchler2004) ?

25. Extent of integration & success as documented in studies Governance Service delivery Success Monitoring & Evaluation Demand generation Planning Finance Child health & development IMCI* ICDS - India (Agarwal2000, Kapil1999) ? ? ? Dular - India (Dubowitz2007)

26. Extent of integration & success as documented in studies Governance Service delivery Success Monitoring & Evaluation Demand generation Planning Finance Family Planning services Bangladesh – FPHSP (Philips1984, de Graff 1986) ? ? ? ? ? Pakistan – LHWP (Douthwaite 2005) ? ? ? ? Nepal (Tuladhar 1982)

27. Extent of integration & success as documented in studies Stewardship/Governance Service delivery Success Monitoring & Evaluation Demand generation Planning Finance HIV/AIDS & STD services ? ? ? Haiti (Peck 2003)

28. Conclusions Extent and nature of integration varies Context matters: complex adaptive systems at play Reductionist approaches counterproductive: aim to ‘unpack’ what is meant by integration

29. Empirical Research

30. Case Study Approach Exploratory Descriptive Explanatory

31. Design Logic of design key Russia TB Estonia PHC Africa HIV Euro PHC Tech adoption Baltic PPP Russia HIV

32. Embedded units HIV TB Malaria NTDs Regions

33. Analytic vs. Statistical Generalisation Cases not sampling units but each akin to an individual ‘experiment’ Analytic generalisation using theory developed a priori Replication logic n number of case studies support the same theory n number of case studies do not support a rival theory Statistical generalisation Sampling logic

34. Careful case selection Literal replication Each predict similar results (n=4) Theoretical replication Predict contrasting results --- but for predictable reasons (n=4)

35. Theoretical framework and propositions key State the conditions under which particular phenomena are likely to be found Allows literal replication State the conditions when particular phenomena are not likely to be found Allows theoretical replication

36. Closed vs. flexible design Closed but with inductive analysis Retain replication logic Build theory as an output Test ‘additional’ new/alternative propositions Flexible and inductive Risk of drift

37. One or two tail design Good outcome Good and poor outcome

38. Data Mixed methods Multiple sources Inductive Iterative Triangulation

39. Process Construct validity Reliability Agree theory Construct validity Internal validity Analytical tools approach & d/base Generate propositions Pilot cases Refine tools Rival propositions Propositions Case studies Case studies Literal replication Theoretical replication Explanatory theory & Evidence Internal validity External validity

40. Cases Africa Tanzania Ghana SE Asia Thailand Viet Nam Embedded units of analysis NTDs + malaria + TB + HIV NTDs + malaria + TB + HIV Malaria, TB, HIV? Malaria, TB, HIV?