| Summary: | Abstract:: This study aimed to develop a new junior doctor allocation plan, and evaluate its impact on the door-to-doctor time (DDT) of a specific patient population at the Accident & Emergency (A&E) department of Changi General Hospital (CGH) in Singapore. The new junior doctor allocation plan was developed by solving an integer linear programming model with the objective of matching available junior doctors with the patient arrival pattern. Compared to the period prior to the new plan’s implementation at CGH A&E, the average daily median, 95th percentile, and standard deviation of DDT of target population were observed to have been reduced by 9.7 minutes (27.3%), 24.5 minutes (21.9%), and 8.5 minutes (23.2%), respectively, in the post-implementation period. These differences remained statistically significant after adjustment for differences in patient load and other relevant patient characteristics over the pre- and post-implementation periods. Majority, if not all, of the previous work on A&E staff allocation studies relied on simulation models to project the impact of new staff allocation plans on DDT performance. They did not report the extent of DDT improvement in the new plan actualized and experienced by A&E patients. This paper addresses this gap in A&E overcrowding management research. It offers empirical evidence, from an operational A&E, on DDT improvements achieved through implementation of a new junior doctor allocation plan that better matched patient arrival pattern compared to the past. Keywords:: Optimization, Manpower allocation, Waiting time, Arrival pattern
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