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Mining the preferences of patients for ubiquitous clinic recommendation

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Abstract

A challenge facing all ubiquitous clinic recommendation systems is that patients often have difficulty articulating their requirements. To overcome this problem, a ubiquitous clinic recommendation mechanism was designed in this study by mining the clinic preferences of patients. Their preferences were defined using the weights in the ubiquitous clinic recommendation mechanism. An integer nonlinear programming problem was solved to tune the values of the weights on a rolling basis. In addition, since it may take a long time to adjust the values of weights to their asymptotic values, the back propagation network (BPN)-response surface method (RSM) method is applied to estimate the asymptotic values of weights. The proposed methodology was tested in a regional study. Experimental results indicated that the ubiquitous clinic recommendation system outperformed several existing methods in improving the successful recommendation rate.

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Acknowledgments

This study was sponsored by the Ministry of Science and Technology, Taiwan.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan

    Tin-Chih Toly Chen

  2. Department of Industrial Engineering and Management, National Chin-Yi University of Technology, 57, Sec. 2, Zhongshan Rd., Taiping, Taichung City, 411, Taiwan

    Min-Chi Chiu

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  1. Tin-Chih Toly Chen
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  2. Min-Chi Chiu
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Correspondence to Min-Chi Chiu.

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Chen, TC.T., Chiu, MC. Mining the preferences of patients for ubiquitous clinic recommendation. Health Care Manag Sci 23, 173–184 (2020). https://doi.org/10.1007/s10729-018-9441-y

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  • DOI: https://doi.org/10.1007/s10729-018-9441-y

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