Comparison of inpatient distribution amongst different medical alliances in a county: a longitudinal study on a healthcare reform in rural China - Yifan Ran; Hongxia Gao; Dan Han; Guilin Hou; Yingchun Chen; Yan Zhang (BMC, 2020)
Abstract Background China has launched the medical alliances (MAs) reform to drive the development of primary medical institutions and decrease health inequality in rural areas. Three different types of MAs were built to promote township hospitals in Y County. This study aims to evaluate the actual effect of China's MAs reform in rural areas on inpatient distribution especially amongst different types of MAs. Methods We obtain 2008-2015 claims data from the New Cooperative Medical Scheme (NCMS) in Y County, Hubei Province of China. We consider January 2008-December 2010 as the pre-reform period and January 2011-December 2015 as the post-reform period. We use independent sample t-test and single-group interrupted time series analysis (ITSA) to compare the number of inpatients per month in the three MAs, including three county and 10 township hospitals before and after the reform. We use paired t-test and multiple-group ITSA between seven township hospitals within MAs and seven township hospitals outside MAs. Results The MAs reform in Y County increased the number of inpatients in county and township hospitals within MAs. After the reform, the number of inpatients per month in county hospitals had an upward trend, with a slope of 31.01 person/month (P < 0.000). Approximately 19.99 new inpatients were admitted to township hospitals monthly after the reform (P < 0.000). Furthermore, township hospitals within MAs had a substantial increase in the number of inpatients (10.45 new inpatients monthly) compared with those outside MAs. Conclusion The MAs reform in Y County significantly improved the capability of medical institutions within MAs. After the reform, township hospitals within MAs had greater development advantages than those outside MAs. However, it also caused further imbalance in the county region, which contained the new health inequality risk.