Community-based health insurance in poor rural China: the distribution of net benefits

The collapse of China's Cooperative Medical System (CMS) in 1978 resulted in the lack of an organized financing scheme for health care, adversely affecting rural farmers' access to health care, especially among the poor. The Chinese government recently announced a policy to re-establish some forms of community-based insurance (CBI). Many existing schemes involve low premiums but high co-payments. We hypothesized that such benefit design leads to unequal distribution of the "net benefits" (NB)--benefits net of payment--because even though low premiums are more affordable to poor farmers, high co-payments may have a significant deterrent effect on the poor in the use of services in CBI. To test this hypothesis empirically, we estimated the probability of farmers joining a re-established CBI using logistic regression, and the utilization of health care services for those who joined the scheme using the two-part model. Based on the estimations, we predicted the distribution of NB among those who joined the CBI and for the entire population in the community. Our data came from a household survey of 4160 members of 1173 households conducted in six villages in Fengshan Township, Guizhou Province, China. Three principal findings emerged from this study. First, income is an important factor influencing farmers' decision to join a CBI despite the premium representing a very small fraction of household income. Secondly, both income and health status influence enrollees' utilization of health services: richer/sicker participants obtain greater NB from the CBI than poorer/healthier members, meaning that the poorer/healthier participants subsidize the rich/sick. Thirdly, wealthy farmers benefit the most from the CBI with low premium and high co-payment features at every level of health status. In conclusion, policy recommendations related to the improvement of the benefit distribution of CBI schemes are made based on the results from this study.