Personalized Hospital Admission Control: A Contextual Learning Approach

Posted: 18 Aug 2020

See all articles by Mohammad Zhalechian

Mohammad Zhalechian

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Esmaeil Keyvanshokooh

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Cong Shi

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Mark P. Van Oyen

University of Michigan at Ann Arbor

Date Written: July 16, 2020

Abstract

Hospitals are typically uncertain about the readmission impact of a care unit placement decision for a patient. The placement decision is challenging due to the wide variety of patient characteristics, uncertain needs of patients, and the limited number of beds in critical and intermediate care units. We develop an optimization-learning algorithm, called the Personalized Admission Control (PAC) algorithm, under the presence of limited reusable hospital beds and delayed bandit feedback. The algorithm is designed to adaptively learn the readmission risk of patients and choose the best care unit placement for a patient based on the observed contextual information. The objective is to minimize patient readmissions while capturing the trade-off between the benefit of better health outcomes versus the opportunity cost of reserving high-demand beds for potentially more complex patients arriving in the future. We prove that our proposed online optimization-learning algorithm admits a sub-linear Bayesian regret bound. We also investigate and assess the effectiveness of our methodology using hospital system data. Our empirical results suggest that implementing our approach provides promising results compared to different benchmark policies and improves the current policy of our partner hospital.

Keywords: online learning, contextual bandit, regret analysis, readmission, personalized admission control

Suggested Citation

Zhalechian, Mohammad and Keyvanshokooh, Esmaeil and Shi, Cong and Van Oyen, Mark P., Personalized Hospital Admission Control: A Contextual Learning Approach (July 16, 2020). Available at SSRN: https://ssrn.com/abstract=3653433

Mohammad Zhalechian (Contact Author)

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
IOE Department
Ann Arbor, MI 48109
United States

Esmaeil Keyvanshokooh

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Cong Shi

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Mark P. Van Oyen

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
170
PlumX Metrics