public health insurance for the poor in indonesia:

Public Health Insurance for the Poor in Indonesia:

Targeting and Impact of Indonesia’s Askeskin Programme

Asep SuryahadiWenefrida Widyanti

(The SMERU Research Institute, Jakarta)

Robert Sparrow(Institute of Social Studies, The Hague)

April 2009

http://www.iss.nl/index.html


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


Objectives of this study

1) To investigate the extent and distribution of OOP, and hence the scope for public intervention in Indonesia

2) To investigate how targeting of Askeskin has addressed this problem

3) To evaluate the effectiveness of Askeskin to increase access to affordable health care for the poor


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


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


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


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


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


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Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Rural Urban Total

TargetingBy quintile and location


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Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

Actual OOP Required OOP

TargetingBy actual and required OOP


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


Evaluation design

Askeskin

Askeskin

Non Askeskin Non Askeskin

2005(Before)

2006(After)

Impact Askeskin!Initial difference?

- Health status- Poverty- Supply

Problem: shocks!- Health status- Other programs- Demographics


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


Impact estimatesOutpatient utilisation

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Total Public health centre Public hospital


Impact estimatesInpatient utilisation

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Total Public


Impact estimatesInpatient utilisation

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Total Public hospital


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


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


Descriptive statistics Balanced household panel Attrition 2005 2006 2005 Mean Stand. dev. Mean Stand. dev. Mean Stand. dev. Per capita expenditure (Indonesian Rp.) 259,168 230,920 285,947 241,692 294,079 226,354 Per capita health expenditure (Indonesian Rp.) 5,601 21,344 6,105 47,983 5,607 14,988 Age 28.28 19.43 28.92 19.78 27.11 18.51 Female 0.50 0.50 0.50 0.50 0.49 0.50 Household size 4.77 1.79 4.75 1.80 4.64 1.84 Female head of household 0.08 0.28 0.08 0.28 0.09 0.29 No education 0.45 0.50 0.45 0.50 0.41 0.49 Primary education 0.26 0.44 0.26 0.44 0.25 0.43 Junior secondary education 0.13 0.34 0.13 0.33 0.15 0.36 Senior secondary education 0.13 0.33 0.13 0.34 0.16 0.37 Higher education 0.03 0.17 0.03 0.18 0.03 0.18 Illness in last month disrupted work/schooling 0.18 0.38 0.15 0.35 0.15 0.36 Nr. of outpatient visits in last month 0.19 0.76 0.15 0.75 0.19 0.91 Nr. of outpatient visits at public health centre in last month 0.07 0.36 0.06 0.34 0.07 0.34 Nr. of inpatient days in last year 0.08 1.33 0.07 1.59 0.08 1.38 Nr. of inpatient days in public hospital in last year 0.05 1.20 0.04 1.35 0.03 0.52 Self treatment/medication in last month 0.19 0.39 0.16 0.37 0.18 0.39 Access to Askeskin 0.12 0.32 Access to health card 0.10 0.30 0.09 0.29 Participates in Askes 0.07 0.25 0.06 0.23 0.08 0.27 Participates in Jamsostek 0.03 0.16 0.02 0.15 0.03 0.16 Number of individuals 34,825 34,525 7,693 Number of households 8,582 8,582 1,993


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All providers Public health centres Private hospitals and doctors

Health care utilisationOutpatient care


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All providers Public hospital Private hospitals and doctors

Health care utilisationInpatient care


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Actual OOP Required OOP

OOP health spendingBudget shares by quintile and location


Health care utilisationNumber of outpatient visits in last month

All providers

Public health

centres

Private hospitals

and doctors

2005 2006 2005 2006 2005 2006

Quintile 1 (poorest) 0.1651 0.1237 0.0783 0.0612 0.0198 0.0134

Quintile 2 0.1671 0.1391 0.0650 0.0561 0.0374 0.0305

Quintile 3 0.2036 0.1716 0.0689 0.0564 0.0534 0.0399

Quintile 4 0.1992 0.1540 0.0652 0.0493 0.0696 0.0524

Quintile 5 (richest) 0.2067 0.1624 0.0424 0.0329 0.0985 0.0842

Urban 0.1861 0.1422 0.0568 0.0449 0.0714 0.0547

Rural 0.1861 0.1544 0.0721 0.0582 0.0367 0.0305

Male 0.1751 0.1463 0.0587 0.0512 0.0520 0.0409

Female 0.1971 0.1510 0.0719 0.0527 0.0522 0.0430

Total 0.1861 0.1486 0.0653 0.0520 0.0521 0.0420


Health care utilisationNumber of inpatient days in last year

All providers

Public hospital

Private hospitals

and doctors

2005 2006 2005 2006 2005 2006

Quintile 1 (poorest) 0.0273 0.0218 0.0109 0.0170 0.0125 0.0042

Quintile 2 0.0389 0.0550 0.0170 0.0287 0.0153 0.0196

Quintile 3 0.0630 0.0472 0.0399 0.0243 0.0176 0.0163

Quintile 4 0.1293 0.1084 0.0895 0.0660 0.0321 0.0346

Quintile 5 (richest) 0.2009 0.1388 0.1104 0.0478 0.0798 0.0875

Urban 0.0923 0.0870 0.0507 0.0389 0.0351 0.0440

Rural 0.0770 0.0561 0.0466 0.0326 0.0238 0.0179

Male 0.0801 0.0755 0.0444 0.0435 0.0297 0.0265

Female 0.0875 0.0659 0.0525 0.0275 0.0279 0.0340

Total 0.0838 0.0707 0.0484 0.0355 0.0288 0.0302


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

Acute

respiratory

infection

Influenza

Diarrhoea

Illness has

disrupted

work/schooling

Quintile 1 (poorest) 17.04 12.36 2.45 17.42

Quintile 2 17.00 12.18 2.07 18.27

Quintile 3 16.45 12.02 1.92 18.58

Quintile 4 16.18 11.70 1.49 16.37

Quintile 5 (richest) 15.41 13.66 1.35 14.18

Urban 15.36 12.21 1.77 15.51

Rural 17.40 12.46 2.02 18.38

Male 17.04 12.48 1.95 17.45

Female 15.95 12.22 1.87 16.75

Total 16.49 12.35 1.91 17.10


OOP health spendingBudget shares (percentages)

Share of total spending Share of non-food spending

2005 2006 2005 2006


Quintile 2 1.78 1.66 4.94 4.64

Quintile 3 1.94 1.93 5.06 4.77

Quintile 4 2.23 1.91 5.04 4.32


Urban 2.13 1.99 4.62 4.19

Rural 2.03 1.78 5.41 4.78

Total 2.07 1.88 5.07 4.51


Predicted health spendingExpected required budget shares (percentages)

Share of total spending Share of non-food spending

2005 2006 2005 2006


Quintile 2 7.18 6.96 22.11 21.91

Quintile 3 5.21 5.14 14.83 14.53

Quintile 4 3.63 3.56 9.49 8.93


Urban 4.51 4.36 11.66 11.24

Rural 7.27 7.15 24.07 24.27

Total 6.07 5.86 18.68 18.26

Note: Predicted per capita OOP health expenditures with per capita expenditure fixed at the 90th percentile and location at Jakarta.


TargetingBy quintile, location and gender (percentages)

Health card

(2005)

Askeskin

(2006)

Coverage Share Coverage Share


Quintile 2 10.51 24.59 15.33 27.24

Quintile 3 8.39 18.22 10.23 17.32

Quintile 4 4.61 9.01 5.44 8.58


Urban 6.37 31.15 8.64 34.71

Rural 11.26 68.85 14.55 65.29

Male 9.11 50.11 11.79 50.21

Female 9.07 49.89 11.74 49.79

Total 9.09 100.00 11.76 100.00

Note: Quintiles are based on 2005 per capita expenditure.


TargetingBy distribution of OOP health spending (percentages)

OOP a Predicted OOP b

Share of

total

spending

Share of

non-food

spending

Share of

total

spending

Share of

non-food

spending

Quintile 1 (low OOP share) 11.53 9.11 4.92 3.92

Quintile 2 10.73 10.53 6.77 6.95

Quintile 3 11.65 11.25 9.36 9.71

Quintile 4 11.54 13.01 14.11 14.47

Quintile 5 (high OOP share) 13.48 15.07 21.08 21.21

a) Quintiles reflect the distribution of actual per capita OOP health spending in 2005.

b) Quintiles reflect the distribution of predicted per capita OOP health spending for

2006, with per capita expenditure fixed at the 90th percentile and location at Jakarta.


Impact estimatesUnit of analysis: individual

Outpatient Inpatient

All Public All Public

Quintile 1 (poorest) 0.0362+ 0.0422** 0.0625 0.0548

Quintile 2 0.0296 0.0441** 0.1224** 0.0920**

Quintile 3 0.0517+ 0.0577** 0.1154** 0.1088**

Quintile 4 0.0866* 0.1036** 0.1014 0.1380

Quintile 5 (richest) 0.1536* 0.0772+ 1.4543** 0.8013**

Female 0.0621** 0.0543** 0.1139** 0.0948**

Male 0.0327+ 0.0515** 0.1961** 0.1388**

Rural 0.0450** 0.0493** 0.1323** 0.1199**

Urban 0.0557* 0.0691** 0.1881** 0.1024**

Total 0.0472** 0.0540** 0.1474** 0.1135**

Note: Outcomes are number of outpatient visits in last month and inpatient days in last year + significant at 10%; * significant at 5%; ** significant at 1%


Impact estimatesUnit of analysis: household

Outpatient Inpatient

All Public All Public

Quintile 1 (poorest) 0.0553+ 0.0358* 0.0453 0.0413

Quintile 2 0.0445+ 0.0462** 0.0794** 0.0405*

Quintile 3 0.0504 0.0656** 0.0960** 0.0997**

Quintile 4 0.0982* 0.0860** 0.1175 0.1584+

Quintile 5 (richest) 0.0880 0.0822+ 0.8815** 0.4692**

Rural 0.0485** 0.0525** 0.0857* 0.0835*

Urban 0.0872** 0.0601** 0.2066** 0.1309**

Total 0.0557** 0.0522** 0.1233** 0.0976**

Note: Outcomes are number of outpatient visits in last month and inpatient days in last year + significant at 10%; * significant at 5%; ** significant at 1%


Per capita health spending Distribution in 2005 and 2006

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sity

0 2000 4000 6000 8000 10000Per capita health expenditure (Rp.)

2005 2006


public health insurance for the poor in indonesia:

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