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Analysis of the cost effectiveness in county-level public hospitals in Chongqing and relevant influencing factors

TAN Hua-wei1,2,3, ZHENG Wan-hui1,2,3, ZHANG Yun1,2,3, YAN Wei-hua1,2,3, ZHU Xiao-lin1,2,3, LIU Xian1,2,3, ZHANG Pei-lin1,2,3   

  1. 1.Hospital Cost Management Research Center of Chongqing, 2.The Ninth People's Hospital of Chongqing, 3.Health Economics Association Secretariat of Chongqing, Chongqing 400700, China
  • Online:2016-05-28 Published:2016-05-26
  • Supported by:

    National Social Sciences Fund of China, 14BGL112; Projects of medical scientific research of Health and Family Planning Commission of Chongqing, 20143044

Abstract:

Objective To investigate the cost effectiveness in county-level public hospitals in Chongqing and relevant influencing factors. Methods Data of main indexes of medical institutions in Chongqing from 2012 to 2014 were collected. The cost effectiveness was calculated with the Stochastic Frontier Approach (SFA). Factors influencing the cost effectiveness were analyzed with the Tobit regression model. Results The average score of cost effectiveness in county-level public hospitals in Chongqing was 0.8416 and increased by 0.49% annually. Tobit regression analysis revealed that cost effectiveness in county-level public hospitals was significantly influenced by four external factors, i.e. location, hospital level, reform pilot, and permanent resident population, and eight internal factors, i.e. number of beds, proportion of drug, proportion of medical technicians expenditure, number of discharged patients per employee per year, utilization rate of  beds, current ratio, income from drugs with prices less than 100 Yuan and hygiene materials, and rate of management expenses. Conclusion The cost effectiveness in county-level public hospitals in Chongqing still needs improvement. Multiple factors influence the cost effectiveness in county-level public hospitals. Managers and policymakers of county-level public hospitals should take efficient measures to improve the cost effectiveness according to relevant influencing factors.

Key words: county-level public hospitals, cost efficiency, influencing factors, stochastic frontier approach, Tobit regression model