Optimizing ICU Discharge Decisions with Patient Readmissions

41 Pages Posted: 1 Sep 2011 Last revised: 5 Oct 2011

See all articles by Carri Chan

Carri Chan

Columbia University - Columbia Business School

Vivek F. Farias

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Nicholas Bambos

Stanford University

Gabriel J. Escobar

Kaiser Permanente

Date Written: August 30, 2011

Abstract

This work examines the impact of discharge decisions under uncertainty in a capacity-constrained high risk setting: the intensive care unit (ICU). New arrivals to an ICU are typically very high priority patients and, should the ICU be full upon their arrival, discharging a patient currently residing in the ICU may be required to accommodate a newly admitted patient. Patients so discharged risk physiologic deterioration which might ultimately require readmission; models of these risks are currently unavailable to providers.

These readmissions in turn impose an additional load on the capacity-limited ICU resources. We study the impact of several different ICU discharge strategies on patient mortality and total readmis-sion load. We focus on discharge rules that prioritize patients based on some measure of criticality assuming the availability of a model of readmission risk. We use empirical data from over 5000 actual ICU patient flows to calibrate our model. The empirical study suggests that a predictive model of the readmission risks associated with discharge decisions, in tandem with simple index policies of the type proposed can provide very meaningful throughput gains in actual ICUs while at the same time maintaining, or even improving upon, mortality rates. We explicitly provide a discharge policy that accomplishes this. In addition to our empirical work, we conduct a rigorous performance analysis for the family of discharge policies we consider.

We show that our policy is optimal in certain regimes, and is otherwise guaranteed to incur readmission related costs no larger than a factor of (ˆp 1) of an optimal discharge strategy, where ˆp is a certain natural measure of system utilization.

Suggested Citation

Chan, Carri and Farias, Vivek F. and Bambos, Nicholas and Escobar, Gabriel J., Optimizing ICU Discharge Decisions with Patient Readmissions (August 30, 2011). Columbia Business School Research Paper No. 11-12, Available at SSRN: https://ssrn.com/abstract=1920416 or http://dx.doi.org/10.2139/ssrn.1920416

Carri Chan (Contact Author)

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

Vivek F. Farias

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

Nicholas Bambos

Stanford University ( email )

Stanford, CA 94305
United States

Gabriel J. Escobar

Kaiser Permanente ( email )

CA
United States

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