Patient Assignment and Prioritization for Multi-Stage Care with Reentrance

TL;DR

This paper models multi-stage patient care with reentrance, analyzing priority and assignment decisions to optimize nurse scheduling, demonstrating the effectiveness of heuristics and policies through theoretical and simulation results.

Contribution

It introduces a queueing model with reentrance, proposes heuristic policies for nurse-patient assignment, and analyzes priority rules with theoretical and simulation validation.

Findings

Shortest-first policy performs well under certain conditions.

Heuristic policies outperform benchmark policies.

Policies considering queue length significantly improve patient care efficiency.

Abstract

In this paper, we study a queueing model that incorporates patient reentrance to reflect patients' recurring requests for nurse care and their rest periods between these requests. Within this framework, we address two levels of decision-making: the priority discipline decision for each nurse and the nurse-patient assignment problem. We introduce the shortest-first and longest-first rules in the priority discipline decision problem and show the condition under which each policy excels through theoretical analysis and comprehensive simulations. For the nurse-patient assignment problem, we propose two heuristic policies. We show that the policy maximizing the immediate decrease in holding costs outperforms the alternative policy, which considers the long-term aggregate holding cost. Additionally, both proposed policies significantly surpass the benchmark policy, which does not utilize queue length information.