An Examination of Early Transfers to the ICU Based on a Physiologic Risk Score
Wenqi Hu, Carri W. Chan, José R. Zubizarreta, Gabriel J. Escobar
Manufacturing & Service Operations Management · 2018 · Volume 20 · Issue 3
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. The online appendix is available at https://doi.org/10.1287/msom.2017.0658 .
Keywords
intensive care units, empirical models, matching
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