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

Wenqi Hu (), Carri W. Chan (), José R. Zubizarreta () and Gabriel J. Escobar ()
Additional contact information
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

Manufacturing & Service Operations Management, 2018, vol. 20, issue 3, 531-549

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.

Keywords: intensive care units; empirical models; matching (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://doi.org/10.1287/msom.2017.0658 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:20:y:2018:i:3:p:531-549

Access Statistics for this article

More articles in Manufacturing & Service Operations Management from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().