A hybrid approach of data mining and genetic algorithms for rehabilitation scheduling

Chen-Fu Chien, Yi-Chao Huang and Chih-Han Hu

International Journal of Manufacturing Technology and Management, 2009, vol. 16, issue 1/2, 76-100

Abstract: To enhance the medical care quality and patient satisfaction, the hospital management has received considerable attention. This research aims to develop an intelligent approach that integrates Genetic Algorithm (GA) and Data Mining (DM) approaches to resolve the physical therapy scheduling problems to reduce patient waiting time and thus enhance service quality. In particular, this approach employed the attribute-oriented induction method to extract the patterns of the solutions generated from the GA approach. Thus, the decision rules derived from the patterns can be applied to resolve similar therapy scheduling problems with much lesser computational effort. The results of an empirical study conducted in a general hospital validated the practical viability of this approach.

Keywords: service engineering; service quality; genetic algorithms; GAs; data mining; attribute-oriented induction; physical therapy scheduling; physical therapy; rehabilitation scheduling; hospital management; healthcare management; medical care quality; patient satisfaction; waiting times reduction. (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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