GINA LAGOMARSINO SAPNA SINGH KUNDRA

Transcription

1 RISK-POOLING: CHALLENGES AND OPPORTUNITIES GINA LAGOMARSINO SAPNA SINGH KUNDRA RESULTS FOR DEVELOPMENT Healthcare Systems in Africa October 23, 2008 Health Insurance Fund Conference, Amsterdam

2 Today s Presentation Our methodology and focus Risk-pooling contribution to health systems Key dimensions of design for risk-pooling programs Case studies of innovative models

3 Our methodology and focus Methodology Identify innovative risk-pooling programs Categorize them by various design dimensions Describe various mechanisms currently being used to address scale-up hurdles Identify core outstanding questions Focus Smaller-scale private programs with potential to be scaled-up statewide or nationally South Asia and Sub-Saharan Africa

4 Many developing country health systems are characterized by: Numerous private providers (formal and informal) operating in parallel to public systems Lack of incentives for quality and to serve the poor Weak government regulatory regimes Asymmetries of information that can lead to inappropriate care, unnecessary care, and over-priced services High out-of pocket payments

5 How can risk-pooling improve health systems? Improvement s in health and financial status Increase utilization of beneficial services Improve health status Improve financial protection Catalyst for health systems development Platform for pooled strategic purchasing Source of steady revenue streams for providers Mechanism to funnel subsidies to the poor

6 Key risk-pooling design dimensions Key Design Dimensions: Building Health Insurance Programs in the Developing World Leverage existing community organizations MFIs Retail sales Primarily inpatient benefits Primarily outpatient benefits Comprehensive benefits Create a network from existing providers Build proprietary delivery system Fully funded by insured Subsidized by a third party Crosssubsidized Community Third Party Administrator Insurer/ HMO

7 Risk-Pooling Model: Uplift Health Maharashtra, India 35,000 lives insured Local community groups or micro finance institutions Inpatient surgical, some outpatient, and primary care consultations Wage loss benefit Leverages public providers Private network to fill gaps Hotline and navigators Premiums funded by insured No 3 rd party premium supplements Grants to Uplift Community - most administration, bears risk Uplift - TA and hotline

8 Risk-Pooling Model: Uplift Health Key design features Significant community control Supported by Uplift NGO Three-prong, low-cost delivery system 24 hour physician hotline Leverages free public providers w/ navigator Private providers, when necessary Community bears risk and borrows from other communities funds, if necessary Effectively offers comprehensive benefits

9 Risk-Pooling Model: Hygeia/Health Insurance Fund/PharmAccess Lagos, Nigeria 40,000 market women and 30,000 ICT workers insured Kwara, Nigeria 71,000 farmers insured * Shonga: 75,000 insured Farmer s Cooperative in Kwara Market women cooperative in Lagos Comprehensive benefits (e.g., labs, preventive, inpatient) Network of public and private, some proprietary providers Quality monitoring, incentives Premium subsidized by Health Insurance Fund Kwara state will help finance in 5 years Community - awareness Hygeia admin, network, risk PharmAccess M&E HIF -Subsidy

10 Risk-Pooling Model: Hygeia Community Health Plan Key design features Network delivery side enhancements that, in effect, combine franchising and risk-pooling Direct investment in network infrastructure Protocols, training, and monitoring Branding Comprehensive benefits - highly subsidized through Dutch Health Insurance Fund Plan to transition to state support in Kwara State with other third party subsidies Relationship with PharmAccess M&E and oversight

11 Risk-Pooling Model: Arogya Raksha Yojana Karnataka, India 64,000 lives insured Retail sales through existing wellknown organizations and proprietary clinics Nearly comprehensive benefits (inpatient and outpatient) Includes drug and transport benefits Narayana Hrudayalaya and other private hospitals Proprietary branded clinics Premiums funded by the insured Subsidized drugs through Biocon ICICI Lombard admin and risk Biocon discounted drugs Narayana Hrudayalaya - hospitals

12 Risk-Pooling Model: Arogya Raksha Yojana Key design features Urban, retail model Partnership ICICI Lombard bears risk and does administration Biocon Foundation provides subsidized drugs Narayana Hrudayalaya high quality network hub Leveraging Indian hospital and insurance regulations Proprietary clinics in slums marketing presence, lower cost care, revenue-generator High marketing costs ~ 40%

13 Risk-Pooling Model: MicroCare Uganda 100,000 lives insured Retail sales (formal) Community organizations (informal) Varies Primarily inpatient, some outpt. services, and primary care consultations Network of private hospitals and clinics Sophisticated IT infrastructure Informal sector premiums subsidized 25% through cross-subsidy MicroCare does all marketing, enrollment, admin, and bears risk

14 Risk-Pooling Model: MicroCare Key design features Started as NGO 7 years ago Now pursuing a corporate model of traditional insurer Leverages commercial market - cross-subsidies between formal and informal sector Sophisticated IT platform fraud prevention, quality management, review claims against treatment protocols Provides free or discounted preventive products Business plan to enter more markets

15 Risk-Pooling Model: Society for the Elimination of Rural Poverty (SERP) Andhra Pradesh, India 630,000 lives insured Village-based women s selfhelp groups (in all villages in AP) Surgical/ inpatient Complements public services and gov tsponsored insurance Network of underutilized quality hospitals Navigators, exit interviews Premiums fully funded by insured Some donor/gov t money for operations Community enrollment, premiumcollection, and risk SERP back office and network dev.

16 Risk-Pooling Model: Society for the Elimination of Rural Poverty (SERP) Key design features SERP Umbrella organization leveraging existing women s self-help groups to introduce programs Identifies high-quality excess delivery capacity and creates network Organize local districts into health insurance pools Most administration done centrally by SERP Navigators conduct exit interviews assist patients, prevent fraud, check quality

17 Risk-Pooling Model: Aarogyasri Andhra Pradesh, India 37,500,000 lives insured (All 48M BPL residents eligible) Women s self health groups (in each village in AP) Primarily inpatient surgical benefits (e.g., cancer, kidney, heart) Expanding now Network of 180 hospitals (160 private and 20 public) Case workers Health camps by network providers Cost fully funded by state government No premium for the insured Community - information dissemination Star and Allied - administration Aarogyasri Trust - governance

18 Risk-Pooling Model: Aarogyasri Key design features Huge, state-sponsored program for all BPL in AP, India Government has embraced programs that were piloted on smaller scale Offering access to quality providers and inpatient/surgical benefits Network of 180 hospitals 160 private Competitively bid out administration to Star and Allied; Munich Re is reinsuring Benefits becoming more comprehensive subsuming SERP Network providers conduct health camps to build awareness

19 Key outstanding questions Key Design Dimensions: Building Health Insurance Programs in the Developing World

20 Key outstanding questions Introduction Benefits Delivery What is the long-term effectiveness of community-based schemes? What are effective introduction methods in urban populations? What are the trade-offs between outpatient vs. catastrophic benefits packages? Can insurance improve quality of fragmented, private providers? Public providers? What types of delivery systems work in various contexts? Funding What should be the role of subsidies? Who should provide them? To what extent can you reduce a subsidy over time? Admin Which administrative functions are best managed locally vs. aggregated across a larger population? What are the relative advantages of various types of partners?

21 Concluding thoughts Going forward, need to: Measure the effectiveness and scalability of various risk-pooling models Determine which designs work best in different country contexts Explore potential paths to more comprehensive national reforms

22 Thank you!