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Satisfied surgeon–patient matching: a model-based method

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Abstract

To support elective surgery scheduling, a surgery assignment plan often needs to be determined beforehand, while a good plan is actually a satisfied matching between surgeons and patients. How to match surgeons and patients considering constrains on the surgeons’ service ability and subjective preferences of the surgeons and patients is a noteworthy research issue, but the in-depth study on this issue is still lacking. The objective of this paper is to develop a method for satisfied matching between surgeons and patients. In the method, surgeons’ satisfaction degrees are calculated according to the preferences of surgeons concerning different types of surgeries, and meanwhile patients’ satisfaction degrees are calculated according to the preferences of patients concerning different surgeons. Then, given the constrains on the surgeons’ service ability, a bi-objective optimization model is constructed to maximize the surgeons’ total satisfaction degree and patients’ total satisfaction degree. Further, an algorithm for solving the model is given. By solving the model, the satisfied matching can be determined. Finally, a case study is given to illustrate the feasibility and validity of the proposed method.

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Acknowledgements

This work was partly supported by the National Science Foundation of China (Project Nos. 71371002, 71571039, 71571040 and 71771043) and the 111 Project (B16009).

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Authors and Affiliations

  1. Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang, 110167, China

    Yang Liu, Zhi-Ping Fan & Yan-Ping Jiang

  2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China

    Zhi-Ping Fan

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  1. Yang Liu
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  2. Zhi-Ping Fan
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Correspondence to Zhi-Ping Fan.

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Liu, Y., Fan, ZP. & Jiang, YP. Satisfied surgeon–patient matching: a model-based method. Qual Quant 52, 2871–2891 (2018). https://doi.org/10.1007/s11135-018-0714-9

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