Stochastic and Deterministic Methods for Patient Flow Optimization in Care Service Networks.

Healthcare Operations Management;Industrial and Operations Engineering;Engineering;Industrial and Operations Engineering

Helm, Jonathan EugeneHancock, Walton M. ;

University of Michigan

关键词: Healthcare Operations Management;    Industrial and Operations Engineering;    Engineering;    Industrial and Operations Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/94008/jhelm_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Healthcare organizations typically lack effective enterprise-level management of care resources, contributing to workloads that are statistically ;;out of control.;; This system dysfunction manifests itself in emergency patient bed block, surgical cancelation, ambulance diversions, operational chaos, and poor service. A significant contributor to this is the scheduling/admissions process. Previous schedule improvement has been addressed in its entirety only through inexact simulation search heuristics. This work develops new analytical models for controlling patient flow to optimize workloads over complex stochastic queueing networks. The results provide the theoretical foundations for an efficient admissions management system and a practical decision support methodology to stabilize workloads across networks of care resources. Through case studies with multiple hospitals, the decision support derived from this research is shown to provide significant benefits in terms of cost and access.