Government Health Care Investment Model Assessment and Path Optimization
Against the background of diversified government health care investment paths,how to reasonably guide the flow of funds and evaluate the performance of different investment paths under the premise of ensuring the scale of investment is related to the structural optimization of government health care investment in the future.Utilizing panel data from the China Family Panel Survey(CFPS)from 2010 to 2020,based on a two-stage model of the Con-ditional Mixed Process(CMP),this paper examines the health performance,economic performance and medical serv-ice supply performance of government healthcare investment from three perspectives:of the"supply-side subsidy",the"demand-side subsidy"and"strengthening grass-roots level".The research results show that the governments funding in different directions is conducive to significantly improving residents'health status."Demand-side subsi-dy"is beneficial to reducing the patient's out-of-pocket medical expense and thus reducing the patient's medical burden,while"supply-side subsidy"is the opposite.Both"demand-side subsidy"and"supply-side subsidy"significantly improve patients'subjective medical evaluation,while the improvement of patients'medical services uti-lization rate mainly depends on government demand-side subsidy and grass-roots investment.Heterogeneity results show that there are differences in health performance and medical service supply performance of government health care investment between urban and rural areas and different regions.In rural areas and central and western regions,"demand-side subsidy","supply-side subsidy"and"strengthening grass-roots level"have shown stronger effects on improving health performance and medical service supply performance.Based on this,this paper proposes to increase the grassroots investment and"demand-side subsidy",optimize the allocation of medical resources,im-prove the supporting measures for the medical and health care system and other optimization paths to effectively protect residents'health rights and interests.
NETL
NSTL
万方数据
