Public Health Insurance for the Poor in Indonesia:

1. Public Health Insurance for the Poor in Indonesia: Targeting and Impact of Indonesia’s Askeskin Programme Asep Suryahadi Wenefrida Widyanti (The SMERU Research Institute, Jakarta) Robert Sparrow (Institute of Social Studies, The Hague) April 2009

2. Motivation • Health care utilisation and public spending falls behind its Southeast Asian neighbours, inequality in health care utilisation relatively high • Low utilisation • Low propensity to spend, low incidence of catastrophic spending • But great variation in spending: non-poor allocate larger budget shares • Public health insurance for the poor (Askeskin) in 2005

3. Objectives of this study • To investigate the extent and distribution of OOP, and hence the scope for public intervention in Indonesia • To investigate how targeting of Askeskin has addressed this problem • To evaluate the effectiveness of Askeskin to increase access to affordable health care for the poor

4. Data • Household panel (Susenas) 2005 and 2006 • 2005 provides baseline for Askeskin, 2006 reflects first year coverage • Nationally representative • Balanced panel of 8,582 households • Attrition 18.8%, but no systematic patterns in observables • Variables • Socioeconomic status of households • Self reported morbidity, health care utilisation • Participation in public and private health insurance schemes • Detailed expenditure module

5. I. Scope for InterventionHealth care utilisation and OOP spending patterns • Health care utilisation pro-non poor • Mainly due to distribution of private care utilisation • More prominent for inpatient care • OOP health spending about 2% budget share • Higher for the non poor and in urban areas • Non-food budget share distributed more evenly • Reflect differences in affordability of care and the propensity to spend between poor and rich

6. Exposure to health spending • OOP health spending does not reflect difference in exposure to adverse health shocks • Expected OOP payments one would require in order to obtain some reference level of health care • Given health status and demographic profile of households • Standardized at some level of welfare (90th percentile) and health care supply (Jakarta) • Assume that required health care is determined by demographic characteristics of households, health status and the level of income

7. II. Targeting of AskeskinProgramme design • Health insurance for the poor • Basic outpatient care • 3rd class hospital inpatient care • Includes mobile health services, special services for remote areas and islands, immunisation programs and medicines • Providers can claim compensation for delivered services • Aim to cover 60 million people; total budget USD 400 million • Decentralised targeting • Budgets allocated to districts • Districts target individuals • In practice not all barriers to access for the poor overcome • Askeskin cards not free of costs • Indirect costs not covered

8. Targeting • 11.8% of population covered in Feb 2006; ± 25 million people • Askeskin targeted pro-poor • About 70% of people covered by Askeskin are with the poorest 40% of the population • But non-trivial leakage to the non-poor: almost 12% Askeskin coverage is allocated to the richest 40% • Rural share is 65.3% • Askeskin targeted to individuals with relatively high health care spending needs

9. TargetingBy quintile and location

10. TargetingBy actual and required OOP

11. TargetingBy actual and required OOP

12. Evaluation design • Evaluation problem • What would be the situation in absence of Askeskin? • Non-Askeskin covered are not a suitable control group (selection bias!) • Targeting based on poverty, health status, etc... • Difference-in-difference estimation • Compare Askeskin and non-Askeskin insured, before and after introduction of Askeskin • Control for initial difference in (un-) observed characteristics • Problem with this approach are shocks • Selection based on health shocks: allocation based on acute need • Participation in other public programs (UCT) • Control for these shocks in regression analysis

13. Evaluation design 2005 (Before) 2006 (After) • Problem: shocks! • Health status • Other programs • Demographics Askeskin Askeskin Impact Askeskin! • Initial difference? • Health status • Poverty • Supply Non Askeskin Non Askeskin

14. Impact estimates • Askeskin increases outpatient and inpatient care • Most of increase at public hospitals and clinics • Distribution of impact non-poor, in particular for inpatient care • Impact greater in urban areas, dispersed across different providers • Capture of Askeskin benefits also confirmed by governance and decentralisation survey • Increased non-poor bed occupancy in 3rd class hospitals

15. Impact estimatesOutpatient utilisation

16. Impact estimatesOutpatient utilisation

17. Impact estimatesOutpatient utilisation

18. Impact estimatesInpatient utilisation

19. Impact estimatesInpatient utilisation

20. Conclusion • Scope for public intervention regarding health insurance • The Indonesian poor tend to underutilisation of health care services and have a lower propensity to spend relative to their needs • Askeskin is targeted pro-poor, despite non-trivial leakage • Askeskin is targeted to individuals that are expected to require relatively high OOP health care budget share to meet health care needs • Strong impact of Askeskin, for both inpatient and outpatient care • Impact particularly strong among the non-poor • Askeskin does not overcome all barriers to health care for the poor • Indirect and opportunity costs of seeking health care

21. Future research • Impact on health care expenditure and poverty • Investigate impact heterogeneity and remaining access barriers to (public) health care • Health shocks • Impact of health shocks • Smoothing effect of public health insurance • Longer term impacts health insurance • Sustainability of public health insurance

22. Descriptive statistics

23. Health care utilisationOutpatient care

24. Health care utilisationInpatient care

25. OOP health spendingBudget shares by quintile and location

26. Health care utilisationNumber of outpatient visits in last month

27. Health care utilisationNumber of inpatient days in last year

28. Self reported illnessDisease prevalence in last month (percentages), 2005

29. OOP health spendingBudget shares (percentages)

30. Predicted health spendingExpected required budget shares (percentages)

31. TargetingBy quintile, location and gender (percentages)

32. TargetingBy distribution of OOP health spending (percentages)

33. Impact estimatesUnit of analysis: individual

34. Impact estimatesUnit of analysis: household

35. Per capita health spendingDistribution in 2005 and 2006