ICU Admission Control: An Empirical Study of Capacity Allocation and Its Implication on Patient Outcomes
University of Southern California - Marshall school of Business
Columbia University - Columbia Business School
Columbia University - Columbia Business School - Decision Risk and Operations; University of Chile - Engineering Department
Gabriel J. Escobar
April 23, 2014
Columbia Business School Research Paper No. 12/34
This work examines the admission process to hospitals' Intensive Care Units (ICUs), which currently lacks well-defined admission criteria. A major challenge that has impeded the progress of developing ICU admission standards is that the impact of ICU admission on patient outcomes has not been well quantified, making it difficult to evaluate the performance of candidate admission strategies. Using a large patient-level dataset of over 190,000 hospitalizations across 15 hospitals, we first quantify the cost of denied ICU admission for a number of patient outcomes. We make methodological contributions in this context, improving upon previously developed instrumental variable approaches. Using the estimates from our econometric analysis, we provide a framework to evaluate the performance of various admission strategies. By simulating a hospital with 21 ICU beds, we then show that we could save about 1.9 million dollars per year by using our optimal objective policy--and hence can be used as a standard-- designed to reduce readmissions and hospital length-of-stay. We also discuss the role of physicians' discretion on the performance of alternative admission strategies.
Number of Pages in PDF File: 34
Keywords: service operations, healthcare operations management, empirical research, dynamic programming, capacity allocation, admission control, occupancy level, quality of service
Date posted: May 19, 2012 ; Last revised: August 18, 2015
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