ICU Admission Control: An Empirical Study of Capacity Allocation and Its Implication on Patient Outcomes
Columbia University - Columbia Business School
Columbia University - Columbia Business School - Decision Risk and Operations; University of Chile - Departamento de Ingenieria Industrial
Gabriel J. Escobar
September 7, 2013
Columbia Business School Research Paper No. 12/34
This work examines admission control of the Intensive Care Unit (ICU) which provides care for a hospital's most critically ill patients. We focus on how congestion can impact ICU admission decisions and ultimately patient outcomes. We build an econometric framework to explain how ICU admission decisions are made in practice, which captures key trade-offs in allocating beds to patients with heterogeneous medical needs and stochastic arrival patterns. In addition to describing the actual admission policy used by hospitals, this econometric model provides instrumental variables that can be used to identify the effect of endogenous ICU admission decisions on patient outcomes. We estimate these models using patient data from an integrated healthcare delivery system with nearly 200,000 hospitalizations. We show that busy ICUs -- defined as exceeding the 95th percentile value of the observed bed occupancy distribution -- are associated with lower chance of admission (a 53% decrease on average) which can further lead to significant health implications. In turn, providing ICU care can improve patient outcomes substantially: hospital length of stay decreases by 1.2 days and the likelihood of readmission drops by 3.4%. Using our empirical results, we study the performance of an admission policy that minimizes adverse outcomes based solely on objective metrics available to all patients admitted from the ED and compare it with the current policy used by hospitals in our study. Because the current policy also uses the discretion of physicians (which is not captured in the available objective metrics), we see that the policy based on objective criteria can sometimes underperform, but not always. Additionally, we find that slight adjustments to the current hospital's policy, which account for the dynamic nature of the admission control problem while still exploiting physician discretion in the admission decisions, can improve outcomes without increasing costs.
Number of Pages in PDF File: 37
Keywords: service operations, healthcare operations management, empirical research, dynamic programming, capacity allocation, admission control, occupancy level, quality of serviceworking papers series
Date posted: May 19, 2012 ; Last revised: October 20, 2013
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