Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model

The purpose of this study was to perform an interim evaluation of the policy effect of the current reform of Japan’s municipal hospitals. We focused on efficiency improvements both within hospitals and within two separate internal hospital organizations. Hospitals have two heterogeneous internal organizations: the medical examination division and administration division. The administration division carries out business management and the medical-examination division provides medical care services. We employed a dynamic-network data envelopment analysis model (DN model) to perform the evaluation. The model makes it possible to simultaneously estimate both the efficiencies of separate organizations and the dynamic changes of the efficiencies. This study is the first empirical application of the DN model in the healthcare field. Results showed that the average overall efficiency obtained with the DN model was 0.854 for 2007. The dynamic change in efficiency scores from 2007 to 2009 was slightly lower. The average efficiency score was 0.862 for 2007 and 0.860 for 2009. The average estimated efficiency of the administration division decreased from 0.867 for 2007 to 0.8508 for 2009. In contrast, the average efficiency of the medical-examination division increased from 0.858 for 2007 to 0.870 for 2009. We were unable to find any significant improvement in efficiency despite the reform policy. Thus, there are no positive policy effects despite the increased financial support from the central government.

[1]  Herbert F. Lewis,et al.  Two-Stage DEA: An Application to Major League Baseball , 2003 .

[2]  N. Nakayama Technical Efficiency and Subsidies in Japanese Public Hospitals , 2004 .

[3]  Jesús T. Pastor,et al.  An enhanced DEA Russell graph efficiency measure , 1999, Eur. J. Oper. Res..

[4]  Magnus Tambour,et al.  Productivity and customer satisfaction in Swedish pharmacies: A DEA network model , 1999, Eur. J. Oper. Res..

[5]  Thomas R. Sexton,et al.  Network DEA: efficiency analysis of organizations with complex internal structure , 2004, Comput. Oper. Res..

[6]  Kaoru Tone,et al.  Dynamic DEA with network structure: A slacks-based measure approach , 2013 .

[7]  R. Färe,et al.  Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries , 1994 .

[8]  Noriyoshi Nakayama,et al.  A Comparison of Parametric and Non-Parametric Distance Functions , 2003 .

[9]  Kaoru Tone,et al.  Network DEA: A slacks-based measure approach , 2009, Eur. J. Oper. Res..

[10]  R. F. Rea,et al.  Network DEA , 1999 .

[11]  José Luis Zofío,et al.  Network DEA efficiency in input-output models: With an application to OECD countries , 2007, Eur. J. Oper. Res..

[12]  J. Harris The Internal Organization of Hospitals: Some Economic Implications , 1977 .

[13]  Bruce Hollingsworth,et al.  Use of ratios in data envelopment analysis , 2003 .

[14]  K. Tone,et al.  Dynamic DEA: A slacks-based measure approach , 2010 .

[15]  O. H. Brownlee,et al.  ACTIVITY ANALYSIS OF PRODUCTION AND ALLOCATION , 1952 .

[16]  B. Hollingsworth The measurement of efficiency and productivity of health care delivery. , 2008, Health economics.

[17]  Ali Emrouznejad,et al.  DEA models for ratio data:convexity consideration , 2009 .

[18]  R. Färe,et al.  Intertemporal Production Frontiers: With Dynamic DEA , 1996 .

[19]  Kaoru Tone,et al.  A slacks-based measure of efficiency in data envelopment analysis , 1997, Eur. J. Oper. Res..

[20]  S. Malmquist Index numbers and indifference surfaces , 1953 .