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Reconciling Research and Implementation Needs in Community-Level Cluster Randomised Trials: An EC-FP7 Research Project. Pradeep Panda, PhD Micro Insurance Academy, New Delhi Ellen Van de Poel Erasmus University Rotterdam. Introduction. - PowerPoint PPT Presentation
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Developing efficient and responsive community based micro health insurance in India
Reconciling Research and Implementation Needs in Community-Level Cluster
Randomised Trials:
An EC-FP7 Research Project
Pradeep Panda, PhDMicro Insurance Academy, New Delhi
Ellen Van de PoelErasmus University Rotterdam
Developing efficient and responsive community based micro health insurance in India
• Micro-Insurance Academy is an Indian charity dedicated to training, research, technical assistance and advisory services for micro-insurance units serving the poor
• With our partners, we are running 3 separate, but similar, RCTs in northern India
• Each RCT will establish a Community Based Health Insurance (CBHI) scheme – a small-scale, member-operated health insurance scheme, offering limited coverage of defined events
• Each scheme will be evaluated for its effect on healthcare utilization and healthcare financing
• Now 30 months into this 5-year project – all CBHI units went live in 2011
Introduction
Developing efficient and responsive community based micro health insurance in India
1. What do we Know about Micro Health Insurance
(MHI)?
Developing efficient and responsive community based micro health insurance in India
Limited robust evidence on causal impact of MHI schemes:• Of the 22 most robustly studied trials, only 2 use
a randomised trial methodology…• … and only 7 use any form of counterfactual!• The remaining evaluations are prone to bias• No evaluation has examined a holistic list of
outcome indicators• And comparability of results across trials may be
limited, as all kinds of different schemes have been called “MHI:” national public schemes, private for-profits products, operator run pre-payment programs, and non-profit mutual finds!
1. What do we Know about Micro Health Insurance?
Developing efficient and responsive community based micro health insurance in India
2. Overview of Trials
Developing efficient and responsive community based micro health insurance in India
These trials aim to close knowledge gaps on MHI in three ways:
1. Use the “gold standard” randomised trial methodology to boost internal validity
2. Give clear and detailed descriptions of scheme setting and operation to clarify limits of external validity
3. Evaluate a holistic range of outcome indicators to broaden the knowledge base
2.1 Motivation for Trials
Developing efficient and responsive community based micro health insurance in India
1. Kanpur Dehat
2. Pratapgarh 3.
Vaishali
Uttar Pradesh
Bihar
3 separate CRTs at 3 separate sites:
2.2 Scheme Areas & Target Populations
Developing efficient and responsive community based micro health insurance in India
At each site, a particular type of MHI scheme is set up:
Community Based Health Insurance (CBHI)
CBHI schemes are locally based, mutual, not-for-profit programs:
• All schemes are owned by members• All schemes are managed by members• All premiums and coverage types are set by
members
This is why we call it Community Based!
2.2 Scheme Areas & Target Populations
Developing efficient and responsive community based micro health insurance in India
• Implementation at each site is managed by an NGO implementing partner
• Each NGO has a network of Self Help Groups (SHGs): village level MFI groups
• At each site, there are 1400 – 1600 SHG members• Members and their families can take part in the
trial
2.2 Scheme Areas & Target Populations
Developing efficient and responsive community based micro health insurance in India
4 sequential modules create an eventual impact:
2.3 Description of Treatment Program
2. AwarenessInsurance Education
(x3)CHAT (x2)
Finalization (x1)Enrollment (x1)
1. DesignBenefit Options workshop
(x1)Awareness Tools workshop
(x1)Design workshop (x1) 3. Launching
Selection of OfficersTraining of OfficersInstallation of MIS
Stakeholder Events
4. Live SchemeSubmission of
ClaimsProcessing of Claims
Payout of Claims
Key Outcome Indicators
Developing efficient and responsive community based micro health insurance in India
3. Overview of Research Design
Developing efficient and responsive community based micro health insurance in India
1. Effects of CBHI on Healthcare Utilization LevelsKey indicators depend on coverage of insurance packages at each trial. Will be drawn from:
Maternity Care Usage Rates
Outpatient Care Usage Rates
Hospitalisation Rates
Involuntary Non-Treatment
Rates
Use of Transport
3.1 Outcome Measures & Tools
Developing efficient and responsive community based micro health insurance in India
2. Effects of CBHI on Healthcare FinancingKey Indicators include:
Total Healthcare Spending
Instance of catastrophic health expenditure (>10% HH Income)
Financial Exposure Index (Under Development)
3. Physical Accessibility of Healthcare
Village-wise Health Care Index
Instance of asset sales, savings liquidation, etc.
3.1 Outcome Measures & Tools
Developing efficient and responsive community based micro health insurance in India
Quantitative• Household
surveys• Healthcare
Provider surveys
• Exit interviews• Income
surveys• Insurance
Understanding surveys
Qualitative• FGDs - SHG
members • FGDs - Heads
of SHG households
• KIIs - SHG leaders
• KIIs - Local Healthcare Providers
3.1 Outcome Measures & Tools
Spatial• GPS Mapping • Satellite
Imaging• GIS Imaging
3 mutually supportive and integrated research streams:
This presentation shows have quantitative and spatial baseline have driven experimental design….
Developing efficient and responsive community based micro health insurance in India
3.2 Important design aspects of the RCT
• Staggered implementation– Each wave a random third of the target
population gets offered CBHI• Clustered trial
– SHGs are grouped into clusters– Clusters are randomized in 3 treatment
groups• En-bloc affiliation
– All hhs within a SHG need to join the CBHI
Developing efficient and responsive community based micro health insurance in India
3.3 Defining an Implementation Friendly Unit of Randomisation
• combine Quantitative and Spatial data, and map locations of trial participants
• “3 Rules” to integrate implementation and research needs when forming clusters:
1. Non-Divisibility: A village cannot be divided over different clusters
2. Equal Size: Clusters must contain (roughly) equal numbers of SHG members
3. Continuity: Each cluster must be geographically continuous
Developing efficient and responsive community based micro health insurance in India
3.3 Defining an Implementation Friendly Unit of Randomisation
This transforms villages into clusters….
Developing efficient and responsive community based micro health insurance in India
3.4 Generating Power with a Fixed Population Size
Then MDES is calculated: If it is too low, one of the three rules must be broken somewhere to
improve power Trial 1 -
Pratapgarh Trial 2 - Kanpur Dehat
Trial 3 - Vaishali
No. SHG Members 1557 1226 1459No HH surveys complete
1272 1042 1248
No. Villages 15 42 34No. Clusters (J) 15 17 16Average HHs per cluster
86 61 84
Minimum Detectable Effect Size
0.45 0.45 0.44
Developing efficient and responsive community based micro health insurance in India
3.5 Randomization
• Matching prior to randomization was considered (creating similar triplets of clusters) but did not improve balance on observables
• Simple randomization was chosen as it does not affect power
• Less balance on ethnicity/caste & health care supply
Developing efficient and responsive community based micro health insurance in India
3.6 Limitations
• External validity:– Only effect of CBHI on SHG– Selection of implementation partners
• Internal validity:– Self-selection of SHGs in CBHI ->
intention to treat effect• Contamination effects• (health related) attrition• Multiple treatments (through participatory
design of CBHI)
Developing efficient and responsive community based micro health insurance in India
Thank You!