How much is a Health Card worth? The Impact of CARE s Out-patient Health Insurance and Preventive & PromotiveProducts Intervention in rural Yavatmal

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1 How much is a Health Card worth? The Impact of CARE s Out-patient Health Insurance and Preventive & PromotiveProducts Intervention in rural Yavatmal In Preparation Ajay Mahal(Monash University) Karuna Krishnaswamy(Consultant) Rupalee Ruchismita(CIRM) September 2012

PromotiveProducts Intervention in rural Yavatmal In Preparation

2 Acknowledgments Congratulations to CARE Foundation on their work in rural health and thanks to CARE and ILO s MIF for supporting and encouraging this study.

3 The Study Design -RCT Study the impact of the insurance product and also the bundle of insurance and preventive-promotiveproducts On health seeking behaviour, morbidity, health status and health expenses We conduct a randomized controlled trial experiment Considered the gold standard Randomly assign people to two groups, so they are identical. Offer intervention to one of them only and observe differences between control and treated.

conduct a randomized controlled trial experiment Considered the gold standard Randomly assign people to two

4 The Study Design RCT (2) 30 Villages were listed and 30 households randomly drawn and assigned to one of 3 groups of ten each Group 1: 80% discount on OP insurance and preventivepromotive products Group 2: 80% discount on OP insurance only Group 3: 1 free visit to the VHC Discount to encourage take-up more in the treatment vs. control group Factors: Spillover possible understating effects Control group will have take-up as well Total sample size of 889 in baseline (2010) and 859 in endline (2011)

free visit to the VHC Discount to encourage take-up more in the treatment vs.

5 Estimation Methodology Difference in difference estimator Hosp. Exp. A CONTROL B TREATMENT Effect = B -A BEFORE HEALTH CARD LAUNCH 1 YEAR AFTER LAUNCH

6 Estimation Methodology (2) Difference in difference estimate Difference between treatment and control after the intervention and before the intervention Different from regular endline comparison Harder to interpret Triple differences studying impact on subgroups in sample Don t always see effects on the whole population Rich vs. poor; sicker vs. healthier; high vs. low access We present Intent to treat effect This understates the effect We will focus on differences between the two groups rather than absolute values for the purpose of evaluating the impact.

always see effects on the whole population Rich vs. poor; sicker vs. healthier; high vs.

7 Results Insurance substantially increases visits to VHC Both Treatment groups are visiting the VHC more (~ 0.1 visits per month per household) than the Control (0.01) Share of VHC to total provider visits is also higher (7% vs. 0.06%) Some evidence of drop in visits to other providers. (1.58 visits per month in group 1 vs of control) Perhaps other providers recommend needless visits No evidence of needless visits due to insurance (per VHC interviews) OP expenses drop as expected Drop in overall OP expenses of Rs. 250 per month in both Treatment groups While not surprising this the OP premium is subsidized, still impressive since they use other providers too Drop in 6 month recall period of expenses on top ailments (fever, diarrhea and children s sickness) in Group 1

8 Results (2) Referrals to CARE clinic and hospital are 100% higher Referrals by VHC to clinic or by doctor to hospital/other clinic Almost twice in the treatment groups vs. control group 0.43 to 0.48 referrals in treatment group vs in the control group Hospitalization expenses are lower than the insurance premium amount Total hospitalization expenses per household in a 6 month recall period Lower by Rs. 550 in Treatment group 2 compared to control No effect on Treatment Group 1 but that is likely due to random chance Some drop in number of days in bed The sicker half of Treatment group 2 spent 1.7 fewer days on a hospital bed per household per 6 months

9 Results (3) No impact on morbidity The focus of the intervention was malaria, children sickness, diarrhea However, no impact on num. of days sick, incidence of ailments, self-reported health etc. This is unexpected; need to understand why

10 Interpretation Insurance and PP sales seems to increase visits to the covered provider, the VHC Frequent visits increases number of referrals and perhaps earlier detection of serious ailments Hence people get hospitalized before condition becomes worse, leading to fewer days in hospital and less expenses

perhaps earlier detection of serious ailments Hence people get hospitalized

11 Conclusion Demonstrates the power and social benefits of pre-paid health card compared to a pay-per-use model The policy implication is that insurers and governments providing hospitalization insurance products should consider offering primary care Possible reduction in claims ratios, preventing future premiums from spiralling upwards, and hence increase in future enrolment/renewal rates, It may be more profitable for the provider to throw in prepaid primary care Will do qualitative study and one more endlineafter a year with handheld/mobile diagnostic software to dig deeper into these findings and make stronger recommendations

from spiralling upwards, and hence increase in future enrolment/renewal rates, It may be more profitable for the provider to throw in prepaid primary care

12 THANKYOU

The Impact of Out-patient Health Insurance and Preventive & Promotive Products in a Randomized Controlled Trial experiment

The Impact of Out-patient Health Insurance and Preventive & Promotive Products in a Randomized Controlled Trial experiment Ajay Mahal, * Karuna Krishnaswamy, Rupalee Ruchismita March 2012 PRELIMINARY AND