Impact of community-based health insurance in rural India on self-medication & financial protection of the insured.

Background & objectives: The evidence-base of the impact of community-based health insurance (CBHI) on access to healthcare and financial protection in India is weak. We investigated the impact of CBHI in rural Uttar Pradesh and Bihar States of India on insured households’ self-medication and financial position. Methods: Data originated from (i) household surveys, and (ii) the Management Information System of each CBHI. Study design was “staggered implementation” cluster randomized controlled trial with enrollment of one-third of the treatment group in each of the years 2011, 2012 and 2013. Around 40-50 per cent of the households that were offered to enroll joined. The benefits-packages covered outpatient care in all three locations and in-patient care in two locations. To overcome self-selection enrollment bias, we constructed comparable control and treatment groups using Kernel Propensity Score Matching (K-PSM). To quantify impact, both difference-in-difference (DiD), and conditional-DiD (combined K-PSM with DiD) were used to assess robustness of results. Results: Post-intervention (2013), self-medication was less practiced by insured HHs. Fewer insured households than uninsured households reported borrowing to finance care for non-hospitalization events. Being insured for two years also improved the HH’s location along the income distribution, namely insured HHs were more likely to experience income quintile-upgrade in one location, and less likely to experience a quintile-downgrade in two locations. Interpretation & conclusions: The realized benefits of insurance included better access to healthcare, reduced financial risks and improved economic mobility, suggesting that in our context health insurance creates welfare gains. These findings have implications for theoretical, ethical, policy and practice considerations.

‘First we go to the small doctor’: First contact for curative health care sought by rural communities in Andhra Pradesh & Orissa, India.

Background & objectives: Against the backdrop of insufficient public supply of primary care and reports of informal providers, the present study sought to collect descriptive evidence on 1st contact curative health care seeking choices among rural communities in two States of India - Andhra Pradesh (AP) and Orissa. Methods: The cross-sectional study design combined a Household Survey (1,810 households in AP; 5,342 in Orissa), 48 Focus Group Discussions (19 in AP; 29 in Orissa), and 61 Key Informant Interviews with healthcare providers (22 in AP; 39 in Orissa). Results: In AP, 69.5 per cent of respondents accessed non-degree allopathic practitioners (NDAPs) practicing in or near their village; in Orissa, 40.2 per cent chose first curative contact with NDAPs and 36.2 per cent with traditional healers. In AP, all NDAPs were private practitioners, in Orissa some pharmacists and nurses employed in health facilities, also practiced privately. Respondents explained their choice by proximity and providers’ readiness to make house-calls when needed. Less than a quarter of respondents chose qualified doctors as their first point of call: mostly private practitioners in AP, and public practitioners in Orissa. Amongst those who chose a qualified practitioner, the most frequent reason was doctors’ quality rather than proximity. Interpretation & conclusions: The results of this study show that most rural persons seek first level of curative healthcare close to home, and pay for a composite convenient service of consulting-cum-dispensing of medicines. NDAPs fill a huge demand for primary curative care which the public system does not satisfy, and are the de facto first level access in most cases.

Incidence of illness among resource-poor households: Evidence from five locations in India.

Background & objectives: This study examines the association between household attributes and perceived morbidity within resource-poor house holds (HHs) in India at five locations. This presents an innovation compared to most epidemiological studies, which focus on associations between the incidence of an illness and characteristics of the ill person. Methods: Perceived morbidity was represented by a variable called “Incidence of illness in a HH” (IIH) = the number of self reported illness episodes during three months preceding the survey, divided by household size. Variables were analyzed through bivariate correlation and multivariate linear regression. The evidence was based on a HH survey conducted in 2005 in Maharashtra, Bihar, and Tamil Nadu. Data yield reflected responses of 3,531 HHs, representing 17,323 individuals and 4,316 illness episodes. Results: Analysis showed that incidence of illness among women was higher; the under 5 yr olds and elderly (+55) were particularly vulnerable. However, in the multivariate linear regression model, gender ratio within HHs became an insignificant explanatory variable. Age distribution had a small but significant effect. Household size and the level of education in the HH were negatively and significantly associated with IIH. The regression analysis showed that income had a modest positive effect, but improved housing was associated with reduced IIH. Large differences were noted in IIH across locations. Interpretation & conclusions: Our findings showed that attributes of the unit household, including type of house, income, education and size, have significant effects on IIH; variability in IIH cannot solely be explained by age and gender of HH members.

Cost of illness: evidence from a study in five resource-poor locations in India.

BACKGROUND & OBJECTIVE: In India, health services are funded largely through out-of-pocket spendings (OOPS). We carried out this study to collect data on the cost of an illness episode and parameters affecting cost in five locations in India. METHODS: The data were obtained through a household survey carried out in 2005 in five locations among resource-poor persons in rural India. The analysis was based on self-reported illness episodes and their costs. The study was based on 3,531 households (representing 17,323 persons) and 4,316 illness episodes. RESULTS: The median cost of one illness episode was INR 340. When costs were calculated as per cent of monthly income per person, the median value was 73 per cent of that monthly income, and could reach as much as 780 per cent among the 10 per cent most exposed households. The estimated median per-capita cost of illness was 6 per cent of annual per-capita income. The ratio of direct costs to indirect costs was 67:30. The cost of illness was lower among females in all age groups, due to lower indirect costs. 61 per cent of total illnesses, costing 37.4 per cent of total OOPS, were due to acute illnesses; chronic diseases represented 17.7 per cent of illnesses but 32 per cent of costs. Our study showed that hospitalizations were the single most costly component on average, yet accounted for only 11 per cent of total on an aggregated basis, compared to drugs that accounted for 49 per cent of total aggregated costs. Locations differed from each other in the absolute cost of care, in distribution of items composing the total cost of care, and in supply. INTERPRETATION & CONCLUSION: Interventions to reduce the cost of illness should be context-specific, as there is no "one-size-fits-all" model to establish the cost of healthcare for the entire sub-continent. Aggregated expenses, rather than only hospitalizations, can cause catastrophic consequences of illness.