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An Analysis of the Operational Efficiency of Regional Public Hospitals Using the DEA Model

  • Studies in Humanities and Social Sciences
  • Abbr :
  • 2018, (61), pp.47-70
  • DOI : 10.17939/hushss.2018..61.003
  • Publisher : Institute of Humanities and Social Sciences
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Received : October 5, 2015
  • Accepted : October 23, 2018
  • Published : November 30, 2018

Hong, Kwan-Pyo 1 Won Sik Suh 2

1가톨릭대학교 부천성모병원
2가천대학교

Accredited

ABSTRACT

This paper aims to provide policy and strategic implications for improving efficiency by measuring operational efficiency and analyzing factors affecting hospital efficiency in 33 regional public hospitals in South Korea from 2012 to 2016. Efficiency measurement analysis was conducted by using DEA Excel Solver1.0 and EnPAS1.0, while efficiency impact analysis used clipped Tobit regression. Inputs and outputs used in the DEA model were selected by using ExpertChoice11, an AHP technique. According to DEA Efficiency Analysis, the overall annual efficiency index trend of entire agency was elevated. This result also implies existence of operational efficiency, by increasing the number of adjustment patients and profit or loss of regional public hospitals, such as the number of medians controlled by regional public hospitals, the number of operating cases, and the cost of medical care. According to Tobit Regression for Efficiency Factor Analysis, the number of mediation physicians and the cost of medical care have a significant effect on the efficiency index of regional public hospitals. As a result of verification of differences in profitability and efficiency, there was no difference between the efficiency index of profit- and loss-making hospitals. In this study, we identified each regional hospital’s efficiency and inefficiency factors, and also presented benchmarking points as well. Also meaningful is the implication that local medical institutions should consider public and for-profit issues at the same time by demonstrating the relationship between profit- and loss-making hospitals.

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