New bed configurations and discharge timing policies: A hospital-wide simulation

Abstract

Objective: Optimising patient flow is becoming an increasingly critical issue as patient demand fluctuates in healthcare systems with finite capacity. Simulation provides a powerful tool to fine-tune policies and investigate their impact before any costly intervention.

Methods: A hospital-wide discrete event simulation is developed to model incoming flow from ED and elective units in a busy metropolitan hospital. The impacts of two different policies are investigated using this simulation model: (i) varying inpatient bed configurations and a load sharing strategy among a cluster of wards within a medical department and (ii) early discharge strategies on inpatient bed access. Several clinically relevant bed configurations and early discharge scenarios are defined and their impact on key performance metrics are quantified.

Results: Sharing beds between wards reduced the average and total ED length of stay (LOS) by 21% compared to having patients queue for individual wards. The current baseline performance level could be maintained by using fewer beds when the load sharing approach was imposed. Earlier discharge of inpatients resulted in reducing average patient ED LOS by approximately 16% and average patient waiting time by 75%. Specific time-based discharge targets led to greater improvements in flow compared to blanket approaches of discharging all patients 1 or 2 hours earlier.

Conclusions: ED access performance for admitted patients can be improved by modifying downstream capacity or inpatient discharge times. The simulation model was able to quantify the potential impacts of such policies on patient flow and to provide insights for future strategic planning.

Keywords: decision making; decision support systems; discrete-event simulation; resource management; strategic planning.