An EC-FP7 Action -Research Project · · 2016-06-09Exit Interview – Medical Expenditures ......

Developing efficient and responsive community based micro health insurance in India

Developing Efficient & Responsive Community Based Micro Health

Insurance in India:

An EC-FP7 Action-Research Project

Pradeep Panda, PhDSenior Researcher, Micro Insurance Academy

&Conor Doyle, M.Sc, Sachin Shinde,M.S., Shikha Dixit, PhD

Researchers, Micro Insurance Academy

August 18th, Delhi Seminar Series, 3ie, Global Development Network


Project Overview

• The EC-FP7 project is a five year researchproject on the effectiveness of CommunityBased Health Insurance (CBHI) schemes

• Comprises three separate Randomized ControlTrials (RCTs)

• Each trial will establish an independent,community-based and community-run CBHIscheme• Performance of the three schemes will becritically evaluated


Research & implementation sites

Uttar Pradesh Bihar

Kanpur Dehat

PratapgarhVaishali

Source: www.MapsofIndia.com


Core Hypotheses (1)

1. Membership in a CBHI scheme causes a decrease in thehousehold Out-of-Pocket Healthcare Spending (OOPS).

“With the replacement of point-of-service user fees with prepaymentfor insurance, members' OOPS on healthcare decrease andbecome more predictable and manageable”

2. Insured households are less likely to rely on welfare-threatening health financing strategies than uninsured households.

“Reducing the risk of unexpected high health care costs will result inreduced risk of households that are obliged to borrow, sellassets or liquidate savings to finance their unexpectedhealthcare needs”


Core Hypotheses (2)

3. Households covered by CBHI face less financial exposure tohealth care expenditure.

Financial Exposure Index = (A x B) / CA = % of cases / insureds incurring expenditure above the CBHI capB = Average OOPS on cases incurring expenditure above the CBHI

capC = Income per capita in insured cohort

4. Insured households have a lower risk that their TotalHealthcare Expenditure (for which they are liable) will be“catastrophic”.

“CBHI schemes reduce the instances of sudden illness forcingpeople to expend a catastrophically high percentage of theirincome/assets to finance health care.”


Core Hypotheses (3)

5. Utilization of available healthcare is increased bymembership in the CBHI (for the benefit types whichare covered by the insurance package).

“Through prepayment, CBHIs lessen the financial barriers to

health care utilization, leading members to seek more

care from health providers”

6. Increase in solvent demand for healthcare due to CBHI will increase the quantity of services provided.

“The increase in solvent demand would in turn have animpact on the quantity of health care available to thesecommunities.”


Core Hypotheses (4)

7. Community based health insurance schemes (CBHI) would improve the physical accessibility of health care facilities.

“Increase in demand for health care may lead people to adopt faster modes of transportation or development of new health facilities”


Ongoing Research

Key Hypotheses

Quantitative(Surveys)

Qualitative (Interviews & Group

Discussions)

Peer reviewed articles on impact of CBHI

Roll-out of insurance to 29,880 persons by 2014

Spatial(Mapping)


• Our partners have been organizing SHG activities for between 1,000 and 1,500 members at each of our three sites.

• These members are scattered over 15, 34 and 42 villages.

• The SHG members will be encouraged to join a community based health insurance scheme.

• Community Based Health Insurance is operated by and for communities, not for individuals at random, (for reasons of rating, inclusion etc).

• We also need to generate a control group to the insured cohort.

• Our solution is the Step-Wedge Cluster RCT........

Methodology: Step-Wedge RCT


First: Revenue villages are grouped into clusters.Each cluster is geographically contiguous androughly equal in numbers of SHG members.

Methodology: Clustering


Methodology: Random SelectionSecond: Clusters of villages are randomly assignedto treatment (insurance) or control groups:


• Third: Insurance is implemented using a “Step-wedge” design:

• 1/3 of villages are selected this year• 1/3 join next year• 1/3 the year after that

• This design is used to encourage community acceptance and enthusiasm

• Over 24 months, the entire community is offered the chance to join the scheme.

Methodology: Step-Wedge Implementation


1. Household Survey – Healthcare Seeking Behaviour– Medical Expenditure– Financing of Medical Expenditure – Other details....

2. Exit Interview – Medical Expenditures– Financing of Medical Expenditure

3. Income Survey

4. Insurance Understanding Survey

Quantitative Tools


Income Survey (10%)

Insurance Understanding

(20%)

HH survey (100%)

Income Survey (10%)

Insurance Understanding

(20%)

HH survey (100%)

4000 SHG Members 1200 Non-SHG Members

5200 HH Surveys over 3 Sites

Exit Interviews

Sampling Methodology


Tool Data Type Obs Vars

HH Survey

By Health Event: health seekingbehaviour, spending andfinancing patterns

12248 311

By Individual: Socio-economicstatus, and current health status

29880 94

By Household: Perceptions ofhealthcare availability,household spending, assets, andstatus

5214 411

Exit Intervie

w

Medical Expenditures, Financingof Medical Expenditure

1664 85

Income Survey

Household income levels, bysource

566 60

Insurance Survey

Understanding of basicinsurance concepts among SHG

1013 13

Quantitative Data Output


Qualitative InvestigationFocus on FOUR Areas:• Healthcare: Health and illness, health

seeking behavior, and healthcare cost• Social capital: Socio-economic structure of

the village, trust and cooperation, rules and norms of the day to day village life, and issues of conflict, etc.

• Risk protection: Perceived risks, strategies to manage risks, interlinks between social capital and risk management

• Impact Assessment of awareness campaign and CHAT tool


Tools of investigation

• Focus group discussion with the SHG members

• Focus group discussion with the Head of SHG households

• Key Informant interviews with village leaders

• Key informant interviews with various healthcare providers

• Case studies


Qualitative Data Output

Sr. No.

InterventionsPlanned (Completed)

NIDAN BAIF SB

1 FGD - Healthcare 36 (36) 36 (32) 36 (36)

2 FGD - Social Cap. & Risk Protection

24 (24) 24 (24) 24(24)

3 KII - Healthcare 30 (36) 30 (25) 30 (30)

4 KII - Social Cap. & Risk Protection 6 (6) 6 (6) 6 (6)

5. Data Collection: Impact assessment for awareness

Upcoming Upcoming Upcoming


Qualitative Data Analysis

Analysis of Healthcare data:

• All the FGDs and KIIs are transcribed, thentranslated from Hindi into English.

• Coding work with NVivo (version 8) inprogress.

• Next steps: Picking up the themes foranalysis, extracting data and developingmodels

• Data collection after the awarenesscampaign and CHAT process


Spatial Research

Overview • Spatial research analyzes geographical attributes using

various mapping tools. • Baseline spatial research will analyze physical access

to health among target communities. • Following waves of spatial data collection will analyze

affect of CBHI on parameters associated with accessibility and utilization.

Hypothesis

• Accessibility is a major factor affecting the utilization of health care facilities. (Location of a facility and its distance from the community governs its utilization.)


Goals & Data Goals• To analyze physical access to health care among the

target communities.• To identify areas characterized by shortage of health

care facilities.• To analyze how introduction of CBHI affects the

parameters associated with accessibility and utilization of health care facilities.

Data• Block Level Data on Villages – smallest geographical

unit of analysis.• Existing Road Network – for conducting network

analysis. • Health Care Facilities – number, type, range of

services and facility size.


Tools

1. GPS Mapping – Global Positioning System(GPS) mapping will be utilized to giveprecise locations of the healthcare facilities,villages, etc.

2. Remote Sensing – Satellite Imagery will beused for precise mapping of access routes,etc.

3. Provider Survey Tool – captures supplyside details at local providers i.e. Servicesoffered, physical infrastructure, facility staff,costs & charges

4. Geographical Information System – GISsynthesizes GPS, Remote sensing andProvider survey data


Measuring Impact

LocationSupply

GPS

HCP Tool

Availability

Accessibility

RoadRail

GPSMapsSatellite data

Data synthesis

(Integration of RS & Quantitative data in the GIS platform)

Input Tools OutputSpatial Analysis

Village wise Health care Index


ILLUSTRATIONS


Household mapping & listing

Unused land *Target Household

Household Mapping

èSpatial Mapping helped in developing sampling framesfor survey.


Mapping helped in randomization

èClusters form unit ofrandomization. village polygons mapshelped in demarcation of clusters.

Before looking at village polygons

After looking at village polygons


Urbancity VariableDistance from urban centresDistance from metalled roads

Buffer distance 2 km

GoodAverageBad

èSpatial mapping helped in generating access variable (urbancity). This helped in ensuring treatment & control similarity in terms of access to metalled roads and town.

Buffer distance 1 km


Health Care Supply –Rasulabad Site

Supply mapclearly depicted implementation challenges.


Health Care Supply- Mahua-Vaishali

Provider mapdepicts large number of local medical practitioners.


Distribution of Population & Health Care Supply

Mahua Block-District Vaishali

Provider map overlaid on populationdistribution mapgives insights about health supply.


Research Challenges

• Villages are remote - access is difficult

• Participation: Unavailability and / or unwillingness ofthe participants at some locations

• Some external researchers are unfamiliar with usingthe tools effectively. This requires us to trainresearchers in using tools and applying our methods.

• Inadequacy of data in some qualitative questions /Inaccuracy of data in some quantitative questions.

• Monitoring research and standardizing proceduresacross three very separate sites.


Implementation Challenges

• Generating support among our NGO partners for therandomization of insurance access

• Explaining research needs to implementers /Explaining implementation needs to researchers.

• Integrating the timetables for research &implementation procedures – each team requiresinputs from the other


• Experimental design (RCT) allows for robust assessment of results

• Implementation program designed to optimise validity of impact assessment

• Replication of trials allows for more confidence in generalisability of findings

• Multiple evaluation methodologies (quali, quanti, spatial) capture both the “size and “source” of impact

Distinctive Elements of Project


Thank You!

An EC-FP7 Action -Research Project · · 2016-06-09Exit Interview – Medical Expenditures ......

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