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Dynamic overbooking scheduling system to improve patient access

Author

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  • Y Huang

    (New Mexico State University, Las Cruces, NM, USA)

  • P Zuniga

    (New Mexico State University, Las Cruces, NM, USA)

Abstract

Patient no-show has long been a recognized problem in modern outpatient health-care delivery systems. The common impacts are reduced clinic efficiency and provider productivity, wasted medical resources, increased health-care cost and limited patient access to care. The main goal of this research is to develop an effective dynamic overbooking policy into any scheduling system that accounts for the predictive probability of no-shows for any given patient. This policy increases the quality of patient care in terms of wait time and access to care while minimizing the clinic's costs. This proposed model is also illustrated to be more cost-effective than overbooking patients evenly throughout a clinic session. This paper also suggests that overbooking should be performed at better patient flow and higher no-show rate so that the costs are minimized. Consequently, this research improves the outpatient experience for both patients and medical providers.

Suggested Citation

  • Y Huang & P Zuniga, 2012. "Dynamic overbooking scheduling system to improve patient access," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(6), pages 810-820, June.
    • Handle: RePEc:pal:jorsoc:v:63:y:2012:i:6:p:810-820
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    Citations

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    Cited by:

    1. Samorani, Michele & LaGanga, Linda R., 2015. "Outpatient appointment scheduling given individual day-dependent no-show predictions," European Journal of Operational Research, Elsevier, vol. 240(1), pages 245-257.
    2. Murtaza Nasir & Nichalin Summerfield & Ali Dag & Asil Oztekin, 2020. "A service analytic approach to studying patient no-shows," Service Business, Springer;Pan-Pacific Business Association, vol. 14(2), pages 287-313, June.
    3. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    4. T. Meersman & B. Maenhout, 2022. "Multi-objective optimisation for constructing cyclic appointment schedules for elective and urgent patients," Annals of Operations Research, Springer, vol. 312(2), pages 909-948, May.

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