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Critical Care Capacity Management: Understanding the Role of a Step Down Unit

Author

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  • Mor Armony
  • Carri W. Chan
  • Bo Zhu

Abstract

In hospitals, Step Down Units (SDUs) provide an intermediate level of care between the Intensive Care Units (ICUs) and the general medical†surgical wards. Because SDUs are less richly staffed than ICUs, they are less costly to operate; however, they also are unable to provide the level of care required by the sickest patients. There is an ongoing debate in the medical community as to whether and how SDUs should be used. On one hand, an SDU alleviates ICU congestion by providing a safe environment for post†ICU patients before they are stable enough to be transferred to the general wards. On the other hand, an SDU can take capacity away from the already over†congested ICU. In this work, we propose a queueing model of patient flow through the ICU and SDU in order to determine when an SDU is needed, what size it should be, and what are the main drivers influencing these decisions. Using first†and second†order analysis, we examine the tradeoff between reserving capacity in the ICU for the most critical patients and gaining additional capacity achieved by allocating nurses to the SDU due to the lower staffing requirement. We find that under some circumstances the optimal size of the SDU is zero, while in other cases, having a sizable SDU may be beneficial. Moreover, we identify two parameters which play a prominent role in the SDU sizing decision: p, which captures the demand for SDU beds, and ν, which captures the supply gains by moving nurses to the SDU. The insights from our work provide rigorous justification for the variation in SDU use seen in practice as well as highlight which factors should be considered when making such sizing decisions for critical care.

Suggested Citation

  • Mor Armony & Carri W. Chan & Bo Zhu, 2018. "Critical Care Capacity Management: Understanding the Role of a Step Down Unit," Production and Operations Management, Production and Operations Management Society, vol. 27(5), pages 859-883, May.
  • Handle: RePEc:bla:popmgt:v:27:y:2018:i:5:p:859-883
    DOI: 10.1111/poms.12825
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    Cited by:

    1. Zhiyuan Chen & Guangwen Kong, 2023. "Hospital admission, facility‐based isolation, and social distancing: An SEIR model with constrained medical resources," Production and Operations Management, Production and Operations Management Society, vol. 32(5), pages 1397-1414, May.
    2. Carri W. Chan & Linda V. Green & Suparerk Lekwijit & Lijian Lu & Gabriel Escobar, 2019. "Assessing the Impact of Service Level When Customer Needs Are Uncertain: An Empirical Investigation of Hospital Step-Down Units," Management Science, INFORMS, vol. 65(2), pages 751-775, February.
    3. Seokjun Youn & H. Neil Geismar & Michael Pinedo, 2022. "Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4407-4423, December.
    4. Huiyin Ouyang & Nilay Tanık Argon & Serhan Ziya, 2020. "Allocation of Intensive Care Unit Beds in Periods of High Demand," Operations Research, INFORMS, vol. 68(2), pages 591-608, March.
    5. Emily Zhu & Beste Kucukyazici & Yasmina Maizi, 2020. "Designing Observation Units for Heart Failure Patients: Capacity and Patient Flow Considerations," Service Science, INFORMS, vol. 12(1), pages 8-25, March.
    6. Jim G. Dai & Pengyi Shi, 2021. "Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1838-1862, June.
    7. Yun Fong Lim & Bingnan Lu & Rowan Wang & Wenjia Zhang, 2020. "Flexibly Serving A Finite Number of Heterogeneous Jobs in A Tandem System," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1431-1447, June.
    8. Ginger Zhe Jin & Ajin Lee & Susan Feng Lu, 2022. "Patient Routing to Skilled Nursing Facilities: The Consequences of the Medicare Reimbursement Rule," Management Science, INFORMS, vol. 68(12), pages 8722-8740, December.
    9. van Dijk, N.M. & van der Sluis, E. & Bulder, L.N. & Cui, Y., 2024. "Flexible serial capacity allocation with intensive care application," International Journal of Production Economics, Elsevier, vol. 272(C).
    10. Peng Wang & Kai Pan & Zhenzhen Yan & Yun Fong Lim, 2022. "Managing Stochastic Bucket Brigades on Discrete Work Stations," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 358-373, January.
    11. Li, Na & Zhang, Yue & Teng, De & Kong, Nan, 2021. "Pareto optimization for control agreement in patient referral coordination," Omega, Elsevier, vol. 101(C).
    12. Sandra Sülz & Andreas Fügener & Michael Becker-Peth & Bernhard Roth, 2024. "The potential of patient-based nurse staffing – a queuing theory application in the neonatal intensive care setting," Health Care Management Science, Springer, vol. 27(2), pages 239-253, June.

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