From prediction to decision: Optimizing long‐term care placements among older delayed discharge patients

Ya‐Tang Chuang, Manaf Zargoush, Somayeh Ghazalbash, Saied Samiedaluie, Kerry Kuluski and Sara Guilcher

Production and Operations Management, 2023, vol. 32, issue 4, 1041-1058

Abstract: This study examines long‐term care (LTC) discharge planning among older delayed discharge patients. While awaiting placements in alternate care such as LTC, these patients occupy hospital beds despite not requiring an intensive level of care. This study proposes a novel discharge decision model based on the Markov decision process (MDP) framework, which incorporates predictions regarding the patients' health trajectory and the associated hospital costs. Our machine learning (ML)‐based predictive analytics allow for considering heterogeneous health transitions, hence personalized decision making, leading to valuable information for reducing hospital costs. We also develop data‐driven cost functions using patient characteristics to estimate the person‐level costs associated with the decisions in the optimization model, that is, whether or not to discharge a patient to LTC. The data analyses and cost estimations are based on large historical data collected over 13 years in Ontario, Canada. To solve the resulting high‐dimensional MDP models, we develop an index policy, where each patient's index value is calculated using their health complexity (comorbidity), sex, age, and acute length of stay in the hospital. Using extensive numerical experiments, we illustrate the superior performance of the proposed index policy against some benchmarking policies and demonstrate the significance of predictive information in optimizing discharge decisions. Our results also indicate that the value of predictive information increases with LTC bed availability and decreases with hospital capacity. We also demonstrate that with the anticipated exacerbating mismatch between supply and demand, targeted prediction‐driven discharge policies, such as the proposed index policy, become even more critical.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/poms.13910

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:32:y:2023:i:4:p:1041-1058

Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1937-5956

Access Statistics for this article

Production and Operations Management is currently edited by Kalyan Singhal

More articles in Production and Operations Management from Production and Operations Management Society
Bibliographic data for series maintained by Wiley Content Delivery ().