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Financial early warning system model for hospitals

A.S. Koyuncugil1, N. Ozgulbas2

Research Department Capital Markets Board of Turkey Ankara, Turkey
Department of Healthcare Management Baskent University Ankara, Turkey

The International Conference on Computational & Experimental Engineering and Sciences 2009, 11(3), 79-80.


The aim of this study is to present the Hospital Early Warning System (HEWS) that developed for determining financial performance and risk indicators of Ministry of Health Hospitals based on automation and in an objective manner with usage of data mining.
HEWS is an automation system based on Data Mining that hospital manager, Hospital Unions Managers in case of the constitute of hospital unions, Ministry of Health and the other needing ones will use for:
• determining financial performance of hospitals,
• detecting financial risks of hospitals,
• determining financial performance indicators objectively,
• determining early warning signals for financial risks,
• identifying the positions of the hospitals by financial performance,
• classifyingthe Ministry of Health Hospitals by financial performance
• developing road maps for improving the financial performance of hospitals,
• getting access to theoretically and technically simple reports.
HEWS was developed by using one of the Data Mining Decision Tree method called CHAID. The process of HEWS and application results of a study made for showingthe success of the HEWS were presented in this study.

Cite This Article

APA Style
Koyuncugil, A., Ozgulbas, N. (2009). Financial early warning system model for hospitals. The International Conference on Computational & Experimental Engineering and Sciences, 11(3), 79-80.
Vancouver Style
Koyuncugil A, Ozgulbas N. Financial early warning system model for hospitals. Int Conf Comput Exp Eng Sciences . 2009;11(3):79-80
IEEE Style
A. Koyuncugil and N. Ozgulbas, "Financial early warning system model for hospitals," Int. Conf. Comput. Exp. Eng. Sciences , vol. 11, no. 3, pp. 79-80. 2009.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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