基于DEA-Malmquist指数模型的云南省卫生监督效率分析OA

Objective This study aims to reveal changes in health supervision efficiency across 16 cities and prefectures in Yunnan Province,and to provide a scientific basis for health supervision decision-making.Methods Data on the basic characteristics and supervision activities of health supervision institutions in Yunnan Province between 2019 and 2023 were extracted from the National Health Supervision Information Reporting System.Input indicators included the number of supervision institutions,number of health supervision personnel,expenditure,and total floor area of supervision institutions;output indicators included the number of inspected entities,the completion rate of national random sampling inspections,and the number of cases investigated and handled.The DEA-Malmquist index model was then used to statistically analyze the efficiency of health supervision across the province.Results From 2019 to 2023,the number of health supervision organizations in Yunnan Province increased from 143 to 150.The number of health supervision personnel remained generally stable,reaching 1 758 in 2023.The total floor area of supervision institutions showed an overall decreasing trend but rebounded in 2023.The mean total factor productivity across the cities and prefectures of Yunnan Province from 2019 to 2023 was 1.115,representing an overall increase in operational efficiency of 11.5%.During this period,the total factor productivity change index exceeded 1 in 14 cities and prefectures,while it was below 1 in two prefectures,Dehong Dai and Jingpo Autonomous Prefecture and Nujiang Lisu Autonomous Prefecture.Conclusions Between 2019 and 2023,the overall efficiency of health supervision in Yunnan Province exhibited an upward trend;however,substantial variations were observed across cities and prefectures.To enhance the efficiency of health supervision and enforcement,it is necessary to dynamically address human resource shortages,establish regional coordination mechanisms to improve technical efficiency,innovate regulatory models,and strengthen institutional safeguards.