EURO 2024 Copenhagen
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921. Optimizing Early Discharge: Trade-Offs between Capacity and Readmissions

Invited abstract in session WD-10: Admission and discharge, stream OR in Health Services (ORAHS).

Wednesday, 14:30-16:00
Room: 11 (building: 116)

Authors (first author is the speaker)

1. Jingui Xie
Technical University of Munich

Abstract

In this work, we consider the ward capacity management problem with readmissions, where the decision-maker optimizes the elective schedule and early discharge policy, so as to minimize bed shortages. Existing research has shown that early discharge can lead to higher rates of readmission, and longer readmission length-of-stay. This sets up the need to balance the temporal trade-off between the immediate capacity freed up by early discharges and increased readmissions down the road. Such re-entry structure creates challenges when modelling via traditional methods. We appeal to the Pipeline Queues (Bandi and Loke 2018) framework, and propose an optimization model where the early discharge policy is expressed as a state-dependent decision rule. The model has a reformulation, which can be solved as a sequence of convex programs with asymptotically linear constraints. In our numerical study, we identify an intermediate region of the probability of readmissions where time-invariant policies can lead to as much as 77% more shortages. Ignoring the effects of early discharge on readmissions can lead to at least 75% and 150% more bed shortages in time-homogeneous and non-time-homogeneous settings respectively, even against un-optimized elective admissions. Using optimal early discharge strategies without jointly optimizing elective admissions will lead to 20% more shortages.

Keywords

Status: accepted

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