2011年-世界发展银行全球_Actuarial_Costing_of_Universal_Health_Insurance_and_Coverage_in_Indonesia___Options_and_Preliminary_Results_44页_3mb
报告摘要
Summary of Actuarial Costing of Universal Health Insurance Coverage in Indonesia: Options and Preliminary Results
Core Content
This document provides an actuarial costing analysis of the potential costs and implications of transitioning to universal health insurance coverage (UC) in Indonesia. It is part of a broader effort by the World Bank to support the Indonesian government in designing and financing a comprehensive health insurance system. The study is based on the 2010 Actuarial Consultant Report and consultations with key stakeholders, including government representatives and health experts.
The analysis focuses on the cost implications of various UC transition scenarios, emphasizing the importance of data quality, actuarial modeling, and the impact of policy choices on public health expenditures. It also outlines the need for better data collection, especially regarding unit costs, claims, and national health accounts, to improve the accuracy of future cost estimates.
Main Points and Key Information
1. Universal Coverage (UC) Cost Estimation Framework
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The cost of a UC program is influenced by several factors:
- Size and composition of the covered population
- Benefit package
- Cost-sharing arrangements
- Availability and distribution of health care services
- Provider payment mechanisms
- Changes in demand and disease patterns
- Technological advances
- Aging population
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The study uses the formula:
$$
\operatorname{Pop} \times [P \times Q] + A = E
$$
Where:- Pop = Population
- P = Unit price of service
- Q = Quantity of service
- A = Administrative costs
- E = Total health expenditure under UC
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The study highlights that the cost of UC is not only determined by the formula but also by the behavioral and supply-side responses, which are critical for accurate estimation.
2. Current Health Insurance Coverage in Indonesia (2008)
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51.7% of the population had health insurance coverage.
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The main health insurance programs in 2008:
- Jamkesmas: 76 million people (33%)
- Askes: 14.26 million people (6%)
- Jamsostek: 5.66 million people (2.5%)
- JPKM: 8.91 million people (4%)
- Private Insurance: 2.65 million people (1.2%)
- Self Insurance: 4.62 million people (2%)
- Other: 5.94 million people (2.6%)
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The Askes program, covering civil servants and their dependents, was used as the baseline for cost estimation due to the lack of detailed Jamkesmas data.
3. Cost per Member per Month (CMPM)
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In 2008, the average CMPM for Askes was Rp 16,000, but this was adjusted to reflect the full population and UC scenarios:
- National average CMPM (after adjustments): Rp 11,671
- Greater Jakarta average CMPM: Rp 20,724
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Adjusted CMPM values are used to estimate the potential cost of UC, but they do not account for:
- Out-of-pocket (OOP) expenses (40% of total health spending)
- Large subsidies to the public system
- Supply-side constraints
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Including these factors, the real CMPM ranges from Rp 19,258 to Rp 36,029, depending on the assumptions made.
4. Projected Expenditures for UC by 2020
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The study projects that achieving UC in Indonesia by 2020 would require total expenditures ranging from:
- Rp 127 trillion (6.66% of total public expenditures, 1.17% of GDP)
- Rp 221 trillion (11.58% of total public expenditures, 2.03% of GDP)
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The lower estimate assumes low OOP and increased supply.
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The higher estimate assumes the rest of the country reaches the same level of service access as Greater Jakarta.
5. Alternative UC Scenarios
- Gradual Expansion: A phased approach to UC, considering changes in demand, disease patterns, aging, and technology.
- 'Jamkesmas For All': Expanding the Jamkesmas program to cover the entire population, which would cost between Rp 16-30 trillion in 2020 (0.86-1.58% of public spending, 0.15-0.28% of GDP).
6. Limitations and Future Work
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The study acknowledges that the data are not robust enough to estimate:
- Costs for limited benefit packages (e.g., not covering tertiary care)
- Impacts of changes in service supply
- Effects of new technologies on service utilization
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It emphasizes the need for:
- Better data on unit costs, claims, and national health accounts
- Institutionalization of health modeling and actuarial costing capabilities in Indonesia
- Further stakeholder consultations to finalize UC design, financing, and transition options
7. Methodological Basis
- The report provides a spreadsheet model for actuarial cost estimation, which can be used by Indonesian government technicians and stakeholders.
- It outlines the methodological adjustments needed to estimate UC costs, including:
- Adjusting Askes data to represent the entire population
- Accounting for demographic, socioeconomic, and geographic differences
- Incorporating benefit package, cost-sharing, and provider payment variations
8. Conclusion
- Achieving UC in Indonesia will significantly increase public health expenditures.
- The current Askes and Jamkesmas programs are not indicative of the full cost of UC due to supply-side constraints and low utilization.
- The study serves as a modifiable tool for future cost estimates and highlights the need for data improvement and policy refinement.
Key Takeaways
- UC in Indonesia is expected to cost between Rp 127 trillion and Rp 221 trillion by 2020.
- The 'Jamkesmas For All' scenario would cost between Rp 16-30 trillion.
- The current Askes CMPM of Rp 16,000 is adjusted to Rp 11,671 for the national average and Rp 20,724 for Greater Jakarta.
- The study underscores the importance of actuarial models, data quality, and policy decisions in estimating and managing the costs of UC.
Appendices and Tables
- Appendix One provides a detailed cost summary.
- Tables include:
- Estimated current health insurance coverage (2008)
- Adjusted Askes data (2010)
- Elasticity factors
- Cost projections for different UC scenarios
- Benefit package design for maternal health and children
Final Note
This report is a preliminary analysis and is intended to inform further discussions and decisions on UC in Indonesia. It is not a final policy recommendation but rather a tool for estimation and debate.
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