The effects of China's three basic health insurance schemes on the equity of health-related quality of life: a cross-sectional survey using coarsened exact matching

Abstract

BackgroundFragmentation in health insurance schemes adversely affects health equity. To achieve universal health coverage by 2020, China has implemented comprehensive reforms to improve health insurance. China has three basic health insurance schemes: Urban Employee Basic Medical Insurance (UEBMI), Urban Resident Basic Medical Insurance (URBMI), and the New Rural Cooperative Medical Scheme (NRCMS). However, little research has compared the effects of different health insurance schemes on the equity of health-related quality of life. This study aimed to compare the equity of health-related quality of life of residents under any two of the schemes. MethodsOur analysis used cross-sectional survey data from the 5th National Health Services Survey of Shaanxi Province, China, with a coarsened exact matching method to control for confounding factors. We included a matched sample of 6802 respondents between UEBMI and URBMI, 34 169 respondents between UEBMI and NRCMS, and 36 928 respondents between URBMI and NRCMS. Health-related quality of life was measured by three-level EuroQol five-dimensions (EQ-5D-3L) based on the Chinese-specific value set. We adopted a concentration index to assess health equity and its contributing factors. In this study, the horizontal inequity index of health-related quality of life was obtained by removing the contributions of unavoidable variables (such as gender and age) from the overall concentration index of health-related quality of life. A positive (or negative) horizontal inequity index of health-related quality of life indicated pro-rich (or pro-poor) inequity. FindingsAfter matching, the mean EQ-5D utility scores were 0·9589 (SD 0·0036) and 0·9449 (0·0062) in UEBMI and URBMI, 0·9579 (0·0036) and 0·9473 (0·0016) in UEBMI and NRCMS, and 0·9505 (0·0055) and 0·9605 (0·0013) in URBMI and NRCMS, respectively. Horizontal inequity indexes were 0·0036 and 0·0045 in UEBMI and URBMI, 0·0035 and 0·0058 in UEBMI and NRCMS, and 0·0053 and 0·0052 in URBMI and NRCMS, respectively, which were mainly explained by age, educational and economic statuses. For example, between UEBMI and NRCMS, we found that age (52·15%), educational status (19·88%), and economic status (19·78%) made the largest contributions to explain the inequality of health-related quality of life for the insured residents of UEBMI. InterpretationOur findings highlight the need to consolidate all three schemes with uniform administration, merged funding pools, and matched benefit packages. Strategies to reduce the factors that contribute to health inequity (eg, to facilitate health conditions of elderly people, narrow the economic gap, and reduce educational inequity) are essential. This study will provide evidence-based strategies on consolidating the fragmented health schemes towards reducing health inequity in both China and other developing countries. FundingResearch Program of Shaanxi Soft Science (2015KRM117), National High-Level Talents Special Support Plan (“Thousands of People Plan”), Shaanxi Provincial Youth Star of Science and Technology in 2016, and the Basic Scientific Research Funding of Xi'an Jiaotong University (SK2015007).