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An Examination of Early Transfers to the ICU Based on a Physiologic Risk Score

Author

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  • Wenqi Hu

    (Decision, Risk, and Operations Division, Columbia Business School, Columbia University, New York, New York 10027)

  • Carri W. Chan

    (Decision, Risk, and Operations Division, Columbia Business School, Columbia University, New York, New York 10027)

  • José R. Zubizarreta

    (Decision, Risk, and Operations Division, Columbia Business School, Columbia University, New York, New York 10027)

  • Gabriel J. Escobar

    (Kaiser Permanente Division of Research, Oakland, California 94612)

Abstract

Unplanned transfers of patients from general medical-surgical wards to the intensive care unit (ICU) can occur as a result of unexpected patient deterioration. Such patients tend to have higher mortality rates and longer lengths of stay than direct admissions to the ICU. As such, the medical community has invested substantial efforts in the development of patient risk scores with the intent to identify patients at risk of deterioration. In this work, we consider how one such risk score could be used to trigger proactive transfers to the ICU. We utilize a retrospective data set from 21 Kaiser Permanente Northern California hospitals to estimate the potential benefit of transferring patients to the ICU at various levels of patient risk of deterioration. To reduce the sensitivity of our findings to key identification and modeling assumptions, we use a combination of multivariate matching and instrumental variable approaches. Using our empirical results to calibrate a simulation model, we find that proactively transferring the most severe patients could reduce mortality rates and lengths of stay without increasing other adverse events; however, proactive transfers should be used judiciously, as being too aggressive could increase ICU congestion and degrade quality of care.

Suggested Citation

  • Wenqi Hu & Carri W. Chan & José R. Zubizarreta & Gabriel J. Escobar, 2018. "An Examination of Early Transfers to the ICU Based on a Physiologic Risk Score," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 531-549, July.
  • Handle: RePEc:inm:ormsom:v:20:y:2018:i:3:p:531-549
    DOI: 10.1287/msom.2017.0658
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    References listed on IDEAS

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    2. Marquinez, José Tomás & Sauré, Antoine & Cataldo, Alejandro & Ferrer, Juan-Carlos, 2021. "Identifying proactive ICU patient admission, transfer and diversion policies in a public-private hospital network," European Journal of Operational Research, Elsevier, vol. 295(1), pages 306-320.
    3. Jie Bai & Andreas Fügener & Jochen Gönsch & Jens O. Brunner & Manfred Blobner, 2021. "Managing admission and discharge processes in intensive care units," Health Care Management Science, Springer, vol. 24(4), pages 666-685, December.
    4. Jiayi Liu & Jingui Xie & Kum Khiong Yang & Zhichao Zheng, 2019. "Effects of Rescheduling on Patient No-Show Behavior in Outpatient Clinics," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 780-797, October.
    5. Ingolfsson, Armann & Almehdawe, Eman & Pedram, Ali & Tran, Monica, 2020. "Comparison of fluid approximations for service systems with state-dependent service rates and return probabilities," European Journal of Operational Research, Elsevier, vol. 283(2), pages 562-575.
    6. Diwas Singh KC & Stefan Scholtes & Christian Terwiesch, 2020. "Empirical Research in Healthcare Operations: Past Research, Present Understanding, and Future Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 73-83, January.
    7. Luke Keele & Steve Harris & Samuel D. Pimentel & Richard Grieve, 2020. "Stronger instruments and refined covariate balance in an observational study of the effectiveness of prompt admission to intensive care units," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1501-1521, October.
    8. Muriel Perez & Martine Seville & Philippe Berthelot & Professeur En Médecine, 2019. "Proposition d'un modèle organisationnel de prévention des risques d'infections associées aux soins," Post-Print hal-02384472, HAL.

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