A study on the performance of medical centers in Taiwan: An application of data envelopment analysis
List of Authors
  • Yi-Horng Lai

Keyword
  • hospitals, technical efficiency, slack analysis, data envelopment analysis (DEA)

Abstract
  • Background: The hospital industry in Taiwan has become more competitive than ever before. Improving operational performance is thus an important issue for hospital managers or operators. Methods: The research data of this study is the 2019 National Health Insurance Statistics obtained from National Health Insurance Administration, Ministry of Health and Welfare (Taiwan). The efficiency and productivity of hospital performance were evaluated by input-oriented Data Envelopment Analysis (DEA). Two inputs variables (number of doctors, number of beds) and five outputs variables (number of outpatients, outpatient revenues, number of inpatients, inpatient revenues, number of admission days) were adopted in the DEA model. Results: According to the DEA analysis, 8 hospitals are considered efficient. With super-efficiency, efficiency can be detected in more detail. Conclusion: This study combines DEA results efficiency scores and total medical income into a BCG matrix. There are 6 hospitals in the super star group, 7 hospitals in the cow group, 2 in the question marks group, and 4 in the dog group.

Reference
  • 1. Hsu, M., Yamada, T. (2017). Population Aging, Health Care, and Fiscal Policy Reform: The Challenges for Japan, The Scandinavian Journal of Economics, 121(2), 547-577. https://doi.org/10.1111/sjoe.12280

    2. Chen, Y.T. (2019). An Examination of the Determination of Medical Capacity under a National Health Insurance Program. International journal of environmental research and public health, 16(7), 1206. https://doi.org/10.3390/ijerph16071206

    3. Charnes, A., Cooper, W. W., and Rhodes, E. (1978). Measuring the Efficiency of Decision Making Units. European Jour-nal of Operational Research, 2(6), 42-52. https://farapaper.com/wp-content/uploads/2019/06/Fardapaper-Measuring-the-efficiency-of-decision-making-units.pdf

    4. Banker, R. D., Charnes, A., and Cooper, W. W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078

    5. Vicente, C.S., Vicente, B., and Rafael, B. S. (2020). Conven-tional and Fuzzy Data Envelopment Analysis. https://cran.r-project.org/web/packages/deaR/index.html

    6. Hunt, D., Link, C. R. (2019). Better outcomes at lower costs? The effect of public health expenditures on hospital effi-ciency. Applied Economics, 52(4), 400-414. https://doi.org/10.1080/00036846.2019.1646405

    7. Chitnis, A., Mishra, D. K. (2019). Performance Efficiency of In-dian Private Hospitals Using Data Envelopment Analysis and Super-efficiency DEA. Journal of Health Management, 21(2), 279-293. https://doi.org/10.1177/0972063419835120

    8. National Health Insurance Administration (2022). Medical Benefits. https://www.nhi.gov.tw/Content_List.aspx?n=8A5CA04F618E3364&topn=23C660CAACAA159D

    9. Charnes, A., Cooper, W. W., and Thrall, R. M. (1991). A struc-ture for classifying and characterizing efficiency and inef-ficiency in Data Envelopment Analysis. Journal of Productivity Analysis, 2, 197-237. https://doi.org/10.1007/BF00159732