46
Government-Sponsored Health Insurance in India
However, undercoverage was found for hard-to-reach groups such as Scheduled Castes (12 percent of beneficiaries compared with 16 percent of the population) and Scheduled Tribes (3 percent of beneficiaries compared with 6 percent of the population). Also, 7 percent and 42 percent of beneficiaries were classified as of high and middle socioeconomic status, respectively, and 17 percent reported 10 or more years of schooling. These data appear to reflect the apparent targeting errors in state BPL lists. In the case of AP, other factors may come into play. The state has expanded its BPL lists to include non-poor but vulnerable populations.17 For example, AP uses a different poverty line (from the one used for the GOI Planning Commission estimates of BPL in AP) in which more than 70 percent of the state’s population is deemed BPL. This broader definition has resulted in eligibility for more than 80 percent of the population. However, a relatively well-off, non-BPL family can easily seek a waiver to secure the same benefits in times of need for tertiary care through an alternative mechanism (such as petitioning the chief minister’s office), which practically results in universal access to Rajiv Aarogyasri benefits. Yeshasvini in Karnataka is aimed at rural farmers, both below and above the poverty line.18 An evaluation conducted by the scheme found that some ineligible members had also joined the scheme (Nabard Consultancy Services 2007). The study also found that the members did not understand the scheme fully, especially exclusions and recent revisions. Aggarwal (forthcoming) analyzed the equity effects of enrolment in Yeshasvini. In general, the scheme tends to favor the well off members of cooperative societies. Higher levels of income and education, membership in self-help groups, and access to information19 were found to increase the probability of enrolment. Scheduled tribes were also underrepresented after controlling for household and location effects. The probability of enrolment (and renewal) was negatively correlated with distance from health facilities. Gender, however, was not found to be a determinant of enrolment. The flat premium rate, truncated benefits,20 and no coverage of transportation costs to access empaneled facilities probably contribute to curtail demand for enrolment from lower-income cooperative members. In sum, the recent wave of GSHISs has targeted BPL populations across the country. Many have introduced innovative technologies to facilitate and lower the cost of enrolment. Insurers under contract with the schemes have an incentive to enroll as many families as possible