China had proposed the unification of equity and efficiency since the launch of the new round of health system reform in 2009. And the central government gave priority to the development of primary health care (PHC) whilst ensuring its availability and improving its efficiency. This study aimed to evaluate the changes of equity and efficiency in PHC resource allocation (PHCRA) and explored ways to improve the current situation. The data of this study came from the China Health Statistical Yearbook (2013–2017) and China Statistical Yearbook (2017). Three and five indicators were used to measure equity and efficiency, respectively. The Lorenz curve, Gini coefficient (G), Theil index (T) and health resource density index (HRDI) were used to assess equity in demographic and geographical dimensions. Data envelopment analysis (DEA) and the Malmquist productivity index (MPI) were chosen to measure the efficiency and productivity of PHCRA. From 2012 to 2016, the total amount of PHCR had increased year by year. The Gs by population size were below 0.2 and that by geographical area were between 0.6 and 0.7. T had the same trend with G, and intra-regional contribution rates were higher than inter-regional contribution rates, which were all beyond 60%. From 2012 to 2016, the numbers of provinces that achieved an effective DEA were 4, 3, 4, 5 and 5, respectively. The mean of the total factor productivity index was 0.994. The equity of PHCRA in terms of population size is superior in the geographical area. Intra-regional differences are the main source of inequality. The eastern region has the highest density of PHCR, whereas the western region has the lowest. In addition, PHC institutions in more than 80% of the provinces are inefficient, and the productivity of the institutions decline by 0.6% from 2012 to 2016 because of technological retrogression.

Background: Healthcare reforms in many countries have shown a movement from pure payment systems to mixed payment systems. However, there remains an insufficient understanding of how to design better mixed payment systems and how such systems, especially Diagnosis-Related-Group (DRG)-based systems, benefit patients. We therefore designed a controlled laboratory experiment to investigate the effects of fee-for-service (FFS), DRG, and mixed payment systems on physicians’ service provision.Methods: A total of 210 medical students were recruited from Capital Medical University as subjects. They, in the role of physicians, were randomly divided into seven groups and chose the quantity of medical services for different patient types under pure FFS, pure DRG, or mixed payment schemes that included two FFS-based mixed payment schemes and three DRG-based mixed payment schemes. There were five rounds of each group of experiments, and each subject made 18 decisions per round. The quantity of medical services provided by subjects were collected. And relevant statistics were computed and analyzed by nonparametric tests and random effects model.Results: The results showed that the physicians’ overprovision (underprovision) of services under FFS (DRG) schemes decreased under mixed payment schemes, resulting in higher benefit to patients under mixed payment schemes. Patients’ health conditions also affected physicians’ behavior but in different directions. Higher disease severity was associated with higher deviation of physicians’ quantity choices from the optimal quantity under DRG and DRG-based mixed payment schemes, while the opposite was found for FFS and FFS-based mixed payment schemes.Conclusions: Mixed payment systems are a better way to balance physicians’ profit and patients’ benefit. The design of mixed payment systems should be adjusted according to the patient’s health conditions. When patients are in lower disease severity and resource consumption is relatively small, prospective payments or mixed systems based on prospective payments are more suitable. While for patients in higher disease severity, retrospective payments or mixed systems based predominantly on retrospective payments are better.