| BackgroundThe scale of public hospitals needs to be controlled under the background of health care reform. In our country, the health service system can’t good meet the medical demands, and the different and high cost in seeing a doctor have been major livelihood issues. At the same time, the size and the number of hospitals have been rapidly increased. In order to cope with these situations, national relevant ministries successively issued multiple files that “moderate scale”, “rational layout”, and “strictly beds control the scale of a single public hospital” acted as the key words.The “new normal” for economy required developing integrated health care. In recent years, most countries has been in slowdown based on the long-term structural adjustment transformation. President Xi also put forward that our country has entered the “new normal”, with the rapid growth slowing down. The contradiction between the rapid growth of the total health expenses and economic slowdown will be further intensified. In response to the rising health care costs caused by excessive fragmentation in health care system, “integration” and “collaboration” has been the important direction of the national medical service system reform.Shanghai urban development required further study of hospital scale development model. The city orientation of Shanghai determines the service subjects of its health service system: not only the permanent and migrant population in Shanghai, but also the population in Yangtze River delta region, Yangtze River Basin, the whole country and Asia. The health service resources in Shanghai are relative abundant. But with the change of the population structure, the contradiction between the medical service supply and demand can’t been ignore.Health services practice required the development on the angle and method in hospital scale efficiency evaluation. The hospitals are complex systems with multiple input and output characteristics. Objective, effective, and accurate assessment of the scale efficiency of public hospital is the first task of improving the efficiency of public hospital scale. Data envelopment analysis(DEA) is recognized as one of the most advanced and effective method in medical institution efficiency evaluation. It can be effective in the stage from practice to research, but not from research to practice. Artificial neural networks can approximate real system with arbitrary precision so as to make up the deficiency of DEA. At the same time, artificial neural networks can get the relative weight of the input and output indicators to guide the practice directly.ObjectiveThis study closely combined with the needs of public hospitals reform, aimed at the current reality of expanding beds scale of urban public hospital, using DEA to analyze the scale efficiency of the public hospitals in Shanghai. We combined artificial neural network with DEA to the whole process of “practice to research to practice” and get the relative weight of the input and output indicators. Drawing on the concept of integrated care, through the fact finding and typical cases analysis in a certain hospital group, we explore the optimization strategy of the hospital monomer scale efficiency.Contents and MethodsAccording to the study design and methods, the content in this study can be divided into three stages.The first stage is a retrospective study, including the second and third chapter. With the methods of literature review, historical review method, statistical description method, we determined the specific methods in the analysis of hospital scale efficiency assessment based on an overview of the related theory and empirical researches. Shanghai hospital scale development trend was analyzed in terms of environmental factors, health resources allocation and hospital scales.The second stage is the hospital scale efficiency analysis, including the forth chapter. Applying literature assemble method, statistical method, DEA, the scale efficiency of public hospitals in Shanghai were analyzed from the static and dynamic dimensions.The third stage is the hospital scale modeling and index weight analysis, including the fifth chapter. Applying BP neural network model, The SPSS software and Matlab software were used to establish 288 BP neural network models to choose the optimal models and the relative weight of the input and output indicators.The forth stage is optimization strategy research, including the sixth chapter. Drawing on the concept of integrated care, through the fact finding and typical cases analysis in a certain hospital group, we explore the optimization strategy of the hospital monomer scale efficiency.MaterialsThe first part was articles and statistics yearbooks. Through reading all kinds of professional journals and searching database, more than 200 articles were retrieved. The second part was the national family planning financial reporting system. The data of 58 second-class or third-class public general hospitals in Shanghai between 2010 and 2014 were extracted from this system. The third part was field investigation materials, including the characteristics and cases of the transferred patients of a certain hospital group.Results and conclusionsAnalysis on Shanghai public hospital development environment and trend. Large population base and high density of Shanghai will cause the health service demand further rise, with the degree of ageing and new born population increasing. Sound development in social and economic provides effective support for the satisfaction of health service demand, and also stimulates the demand of health services to a certain extent. Compared with the national and eastern developed area, the health resources allocation level and health resource utilization were high in Shanghai(for example, the bed utilization rate of medical institutions in Shanghai was 95.33%, ranking the first in our country), and all kinds of hospital beds were also obvious larger. These information suggested that the growth space of total health resources was limited, and the type of ascension in service efficiency also needs to be changed.Analysis on the scale efficiency of Shanghai public hospital based on the DEA. Descriptive analysis showed that the effect of control measures on hospitals scale expansion by the health administrative departments was not obvious. Static scale efficiency analysis showed that the scale efficiency of small scale, medium scale, medium to large scale, and large scale third-class hospitals were 0.9820, 0.9252, 0.9109, and 0.9820, respectively; the scale efficiency of small scale, medium scale, medium to large scale, and large scale secondclass hospitals were 0.9695, 0.9361, 0.9174, and 0.9695, respectively. The scale efficiency of small-size hospitals group was relatively optimal, and significantly higher than the other three groups. While the difference between other three groups was not significant. Dynamic scale efficiency analysis showed that the size of hospitals beds and the change of hospitals beds and the scale efficiency index had no statistical correlation. This study did not support the assumption that hospital scale economy would be infinite, and confirmed that different levels of hospital had its proper size.The modeling study on hospital scale efficiency based on BP neural network. Based on Matlab software, the mean square error of optimization model of third-class and secondclass hospitals were 0.0010 and 0.0004; based on SPSS software, the mean square error of optimization model of third-class and second-class hospitals were 0.0016 and 0.0006. The simulation effect of Matlab software was superior to SPSS software, but the differences was not obvious. Through the BP neural network modeling analysis, we ultimately selected "total surgical operations", "the number of inpatient", "average facility inpatient days" as key indicators for third-class hospital; "the number of inpatient", "total spending", "number of beds" as key indicators for second-class hospital.The optimization strategy study on hospital scale efficiency based on integrated care model. Firstly, arounding the key indicators and combining with the health demand and the present situation of the health service system in Shanghai, it was found that non-medical technical factors should be the main direction on improve. Secndly, Drawing on the concept of integrated care, through the fact finding and typical cases analysis in a certain hospital group, we explore the optimization strategy of the hospital monomer scale efficiency. Combined with the health demand and the present situation of the health service system in Shanghai, we explored the causes that the ideal patient flow was difficult to achieve. Through investigated a certain hospital group in Shanghai, we found that the hospital group had limited impact on initial diagnosis and supravergence, but transferring patients can obviously improve the scale efficiency of hospitals and reduce the exorbitant bed utilization rate. Based on the empirical research, optimization strategy was recommended as following: improving and implementing the policies to create the supravergence external environment; clearing the orientation of hospitals function, and paying more attention to the development of rehabilitation medical institutions; optimizing the evaluation indexes of hospitals, and guiding all levels hospitals to form collaborative mechanism. |
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