In this article, we present a decision support system (DSS) for improving patient flow in emergency departments (EDs). The core of the system is a discrete-event simulation (DES) model that aims to support capacity planning in the ED, in view of controlling patients' length of stay (LOS). Conceptually, it regards the patient LOS as the result of different queueing systems, the behaviour of which is influenced by different types of capacities. Taking inputs from ED patient record data, the DSS allows to analyse the impact of different capacity changes on patient flow, and to detect efficient capacity combinations using data envelopment analysis (DEA). We report on the insights obtained from a case study in a large regional hospital in Belgium.
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Carmen et al. (2015) studied this question.
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