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Assessing sustainable effectiveness of the adjustment mechanism of a ubiquitous clinic recommendation system

Author

Listed:
  • Min-Chi Chiu

    (National Chin-Yi University of Technology)

  • Tin-Chih Toly Chen

    (National Chiao Tung University)

Abstract

Advances in computer and communication technologies have engendered opportunities for developing an improved ubiquitous health care environment. One of the crucial applications is a ubiquitous clinic recommendation system, which entails recommending a suitable clinic to a mobile patient based on his/her location, hospital department, and preferences. However, patients may not be willing or able to express their preferences. To overcome this problem, some ubiquitous clinic recommendation systems mine the historical data of patients to learn their preferences, and they apply an algorithm to adjust the recommendation algorithm after receiving more patient data. Such an adjustment mechanism may operate for several periods; however, this raises a question regarding the sustainability (i.e., long-term effectiveness) of such an adjustment mechanism. To address this question, this study modeled the improvement in the successful recommendation rate of a ubiquitous clinic recommendation system that adopts an adjustment mechanism as a learning process. Both the asymptotic value and learning speed of the learning process provide valuable information regarding the long-term effectiveness of the adjustment mechanism. The proposed methodology was applied in a regional study to a ubiquitous clinic recommendation system that adjusts the recommendation mechanism by solving an integer nonlinear programming problem on a rolling basis. The experimental results revealed that the proposed method exhibited a considerably higher level of accuracy in forecasting the successful recommendation rate compared with several existing methods. Although the adjustment mechanism exhibits long-term effectiveness, the learning speed requires improvement.

Suggested Citation

  • Min-Chi Chiu & Tin-Chih Toly Chen, 2020. "Assessing sustainable effectiveness of the adjustment mechanism of a ubiquitous clinic recommendation system," Health Care Management Science, Springer, vol. 23(2), pages 239-248, June.
    • Handle: RePEc:kap:hcarem:v:23:y:2020:i:2:d:10.1007_s10729-019-09473-5
    DOI: 10.1007/s10729-019-09473-5
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    References listed on IDEAS

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    1. Daniel Gartner & Yiye Zhang & Rema Padman, 2018. "Cognitive workload reduction in hospital information systems," Health Care Management Science, Springer, vol. 21(2), pages 224-243, June.
    2. Abbas Al-Refaie & Toly Chen & Mays Judeh, 2018. "Optimal operating room scheduling for normal and unexpected events in a smart hospital," Operational Research, Springer, vol. 18(3), pages 579-602, October.
    3. Daniel M. Walker, 2018. "Does participation in health information exchange improve hospital efficiency?," Health Care Management Science, Springer, vol. 21(3), pages 426-438, September.
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