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Study on specialist outpatient matching appointment and the balance matching model

Author

Listed:
  • Ying Yang

    (Shanghai Polytechnic University)

  • Shoucheng Luo

    (Shanghai Polytechnic University)

  • Jing Fan

    (Shanghai Polytechnic University)

  • Xinye Zhou

    (Shanghai Polytechnic University)

  • Chunyu Fu

    (Shanghai Jiaotong University)

  • Guochun Tang

    (Shanghai Polytechnic University)

Abstract

Currently specialists’ outpatient appointments in large hospitals in China are made by patients’ one-side choice of specialists, and most are “first select first served”. A specialist cannot choose a patient according to his specialty. Because of the “worship of famous doctors” and asymmetric information between specialists and patients, the appointments are often made with certain blindness, thus it is difficult for patients to get the best diagnosis and treatment from specialists. In this paper, we apply the two-sided matching theory, from the both views of patients and specialists, we design specialists-outpatients matching appointment system, in the system, we propose the process of the appointment and the one-to-many appointment matching algorithm. In order to provide fairness to both sides, we apply the theory of balance-matching, construct the algorithm of one-to-one and one-to-many two-sided balance matching. At last, through the computational examples we prove the model is effective in hospital specialists outpatient appointment.

Suggested Citation

  • Ying Yang & Shoucheng Luo & Jing Fan & Xinye Zhou & Chunyu Fu & Guochun Tang, 2019. "Study on specialist outpatient matching appointment and the balance matching model," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 20-39, January.
    • Handle: RePEc:spr:jcomop:v:37:y:2019:i:1:d:10.1007_s10878-017-0208-z
    DOI: 10.1007/s10878-017-0208-z
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    References listed on IDEAS

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    1. Roth, Alvin E, 1986. "On the Allocation of Residents to Rural Hospitals: A General Property of Two-Sided Matching Markets," Econometrica, Econometric Society, vol. 54(2), pages 425-427, March.
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    3. Guido Kaandorp & Ger Koole, 2007. "Optimal outpatient appointment scheduling," Health Care Management Science, Springer, vol. 10(3), pages 217-229, September.
    4. Zohar Feldman & Avishai Mandelbaum & William A. Massey & Ward Whitt, 2008. "Staffing of Time-Varying Queues to Achieve Time-Stable Performance," Management Science, INFORMS, vol. 54(2), pages 324-338, February.
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    Citations

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    Cited by:

    1. Zhao, Meng & Wang, Yajun & Zhang, Xueyi & Xu, Chang, 2023. "Online doctor-patient dynamic stable matching model based on regret theory under incomplete information," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    2. J. Behnamian & Z. Gharabaghli, 2023. "Multi-objective outpatient scheduling in health centers considering resource constraints and service quality: a robust optimization approach," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-35, March.
    3. Ying Yang & Huijing Wu & Caixia Yan, 2021. "Medical consumable usage control based on Canopy_K-means clustering and WARM," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 722-739, November.
    4. Jing Fan & Hui Shi, 0. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-13.
    5. Gang Du & Xi Liang & Xiaoling Ouyang & Chunming Wang, 2021. "Risk prediction of hypertension complications based on the intelligent algorithm optimized Bayesian network," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 966-987, November.
    6. Jing Fan & Hui Shi, 2021. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 896-908, November.
    7. Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 2021. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 677-699, November.
    8. Ying Yang & Huijing Wu & Caixia Yan, 0. "Medical consumable usage control based on Canopy_K-means clustering and WARM," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-18.
    9. Jing Yu & Lining Xing & Xu Tan, 0. "The new treatment mode research of hepatitis B based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-20.
    10. Gang Du & Xi Liang & Xiaoling Ouyang & Chunming Wang, 0. "Risk prediction of hypertension complications based on the intelligent algorithm optimized Bayesian network," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-22.
    11. Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 0. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    12. Jing Yu & Lining Xing & Xu Tan, 2021. "The new treatment mode research of hepatitis B based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 740-759, November.

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