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A decision support system for real-time scheduling of multiple patient classes in outpatient services

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Abstract

We propose a methodology to provide real-time assistance for outpatient scheduling involving multiple patient types. Schedulers are shown how each prospective placement in the appointment book would impact a day’s operational performance for patients and providers. Rooted in prior literature and analytical findings, the information provided to schedulers about vacant slots is based on the probabilities that the calling patient, the already-existing appointments, and the session-end time will be unduly delayed. The information is updated in real-time before and after every new booking; calculations are driven by each patient type’s historical consultation times and no-show data, and implemented via a simulation tool based on the underlying analytical methodology. Our findings lead to practical guidelines for dynamically constructing templates that provide allowances for different consultation durations, service time variability, no-show rates, and provider-driven performance targets for patient waiting and provider overtime. Extensions to healthcare batch scheduling applications such as radiology, surgery, or chemotherapy—where patient mixes may be known in advance—are suggested as future research opportunities since avoiding session overtime and procedures’ completion time delays involve similar considerations.

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Acknowledgements

The authors are grateful to Mr. Harshad Rokade, M.S., for DSS prototype development and coding support.

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Authors and Affiliations

  1. Department of Management, Zicklin School of Business Baruch College, The City University of New York, One Bernard Baruch Way, Box B9-240, New York, NY, 10010, USA

    William P. Millhiser & Emre A. Veral

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  1. William P. Millhiser
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  2. Emre A. Veral
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Correspondence to William P. Millhiser.

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Millhiser, W.P., Veral, E.A. A decision support system for real-time scheduling of multiple patient classes in outpatient services. Health Care Manag Sci 22, 180–195 (2019). https://doi.org/10.1007/s10729-018-9430-1

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