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The Impact of Discharge Decisions on Health Care Quality

Author

Listed:
  • Emre Berk

    (School of Business, Bilkent University, Ankara, Turkey)

  • Kamran Moinzadeh

    (School of Business, University of Washington, Seattle, Washington 98195)

Abstract

In this paper, we present a normative study that describes the impact of discharging decisions in the face of resource shortages. We develop a model that represents the dynamics of a health care unit. Then, to capture the essence of discharge decisions, we consider discharge policies that incorporate both the occupancy level of the unit and the status of patients measured by their stage of recovery and the time they have spent in that stage. We believe that our model can be used as an aid to physicians and administrators to better assess discharge and/or capacity decisions. In addition, we investigate the impact of discharge decisions on the measures that represent the quality of care at a facility such as average hospital stays, system accessibility, and average complication risk of discharged patients. Our findings illustrate that inclusion of early discharge option improves system accessibility significantly and does not jeopardize care equity among patients. Furthermore, introduction of early discharge option has more pronounced effects on increasing care unit capacity than addition of open beds with no early discharges.

Suggested Citation

  • Emre Berk & Kamran Moinzadeh, 1998. "The Impact of Discharge Decisions on Health Care Quality," Management Science, INFORMS, vol. 44(3), pages 400-415, March.
    • Handle: RePEc:inm:ormnsc:v:44:y:1998:i:3:p:400-415
    DOI: 10.1287/mnsc.44.3.400
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    References listed on IDEAS

    as
    1. James R. Jackson, 1957. "Networks of Waiting Lines," Operations Research, INFORMS, vol. 5(4), pages 518-521, August.
    2. Kamran Moinzadeh, 1989. "Operating Characteristics of the (S - 1, S) Inventory System with Partial Backorders and Constant Resupply Times," Management Science, INFORMS, vol. 35(4), pages 472-477, April.
    3. Charles P. Schmidt & Steven Nahmias, 1985. "(S - 1, S) Policies for Perishable Inventory," Management Science, INFORMS, vol. 31(6), pages 719-728, June.
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    Cited by:

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    2. Francis de Véricourt & Yong-Pin Zhou, 2005. "Managing Response Time in a Call-Routing Problem with Service Failure," Operations Research, INFORMS, vol. 53(6), pages 968-981, December.
    3. Thomas J. Best & Burhaneddin Sandıkçı & Donald D. Eisenstein & David O. Meltzer, 2015. "Managing Hospital Inpatient Bed Capacity Through Partitioning Care into Focused Wings," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 157-176, May.
    4. Mohammad Delasay & Armann Ingolfsson & Bora Kolfal, 2016. "Modeling Load and Overwork Effects in Queueing Systems with Adaptive Service Rates," Operations Research, INFORMS, vol. 64(4), pages 867-885, August.
    5. Ludwig Kuntz & Roman Mennicken & Stefan Scholtes, 2015. "Stress on the Ward: Evidence of Safety Tipping Points in Hospitals," Management Science, INFORMS, vol. 61(4), pages 754-771, April.
    6. Diwas S. Kc & Christian Terwiesch, 2009. "Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations," Management Science, INFORMS, vol. 55(9), pages 1486-1498, September.
    7. Yang, Xiaopeng & Zheng, Danheng & Sieminowski, Tammy & Paradi, Joseph C., 2015. "A dynamic benchmarking system for assessing the recovery of inpatients: Evidence from the neurorehabilitation process," European Journal of Operational Research, Elsevier, vol. 240(2), pages 582-591.
    8. Thanassoulis, Emmanuel & Silva Portela, Maria & Graveney, Mike, 2016. "Identifying the scope for savings at inpatient episode level: An illustration applying DEA to chronic obstructive pulmonary disease," European Journal of Operational Research, Elsevier, vol. 255(2), pages 570-582.

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