Forecasting the number of outpatient visits using a new fuzzy time series based on weighted-transitional matrix

Authors:
Ching-Hsue Cheng;Jia-Wen Wang;Chen-Hsun Li
Affiliations:
Department of Information Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan, ROC;Department of Electronic Commerce Management, Nanhua University, No. 32, Chungkeng, Dalin, Chiayi, 62248, Taiwan, ROC;Department of Information Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

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Abstract

Forecasting the number of outpatient visits can help the expert of healthcare administration to make a strategic decision. If the number of outpatient visits could be forecast accurately, it would provide the administrators of healthcare with a basis to manage hospitals effectively, to make up a schedule for human resources and finances reasonably, and distribute hospital material resources suitably. This paper proposes a new fuzzy time series method, which is based on weighted-transitional matrix, also proposes two new forecasting methods: the Expectation Method and the Grade-Selection Method. From the verification and results, the proposed methods exhibit a relatively lower error rate in comparison to the listing methods, and could be more stable in facing the ever-changing future trends. The characteristics of the proposed methods could overcome the drawback of the insufficient handling of information to construct a forecasting rule in previous researches.