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Efficiency and scale effect of county public hospitals in Shandong Province, China: a cross-sectional study
OBJECTIVE: To evaluate the efficiency of county public hospitals in Shandong Province following China’s new medical reform and compare the efficiency of hospitals with different bed sizes for improving efficiency. DESIGN AND SETTING: This was a cross-sectional study on the efficiency and size of 68...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299019/ https://www.ncbi.nlm.nih.gov/pubmed/32540890 http://dx.doi.org/10.1136/bmjopen-2019-035703 |
Sumario: | OBJECTIVE: To evaluate the efficiency of county public hospitals in Shandong Province following China’s new medical reform and compare the efficiency of hospitals with different bed sizes for improving efficiency. DESIGN AND SETTING: This was a cross-sectional study on the efficiency and size of 68 county public hospitals in China in 2017. OUTCOME MEASURES: Data envelopment analysis was used to calculate the efficiency scores of hospitals and to analyse the slack values of inefficient hospitals. The actual number of open beds, doctors, nurses and total expenditure were selected as inputs, and the total number of annual visits, discharges and total income were selected as outputs. The Kruskal-Wallis H test was employed to compare the efficiency of hospitals with different bed sizes. The χ(2) test was used to compare the returns to scale (RTS) of hospitals with different bed sizes. RESULTS: Twenty (29.41%) hospitals were efficient. There were 27 hospitals with increasing returns to scale, 23 hospitals with constant returns to scale and 18 hospitals with decreasing returns to scale (DRS). The differences in technical efficiency (p=0.248, p>0.05) and pure technical efficiency (p=0.073, p>0.05) were not statistically significant. However, the differences in scale efficiency (p=0.047, p<0.05) and RTS (p<0.001) were statistically significant. Hospitals with DRS began to appear at 885 beds. All sample hospitals with more than 1100 beds were already saturated and some hospitals even had a negative scale effect. CONCLUSIONS: The government and hospital managers should strictly control the bed size in hospitals and make hospitals resume operating in the interests of public welfare. Interventions that rationally allocate health resources and improve the efficiency of medical workers are conducive to solving redundant inputs and insufficient outputs. |
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