Abstract
There is no known method for determining the minimum number of beds in hospital inpatient units (IPs) to achieve patient waiting-time targets. This study aims to determine the relationship between patient waiting time–related performance measures and bed utilization, so as to optimize IP capacity decisions. The researchers simulated a novel queueing model specifically developed for the IPs. The model takes into account salient features of patient-flow dynamics and was validated against hospital census data. The team used the model to evaluate inpatient capacity decisions against multiple waiting time outcomes: (1) daily average, peak-hour average, and daily maximum waiting times; and (2) proportion of patients waiting strictly more than 0, 1, and 2 hours. The results were published in a simple Microsoft Excel toolbox to allow administrators to conduct sensitivity analysis.