Patient flow within UK emergency departments: a systematic review of the use of computer simulation modelling methods

Background: Overcrowding in the emergency department (ED) is common in the UK as in other countries worldwide. Computer simulation is one approach used for understanding the causes of ED overcrowding and assessing the likely impact of changes to the delivery of emergency care. However, little is known about the usefulness of computer simulation for analysis of ED patient flow. We undertook a systematic review to investigate the different computer simulation methods and their contribution for analysis of patient flow within EDs in the UK.

Methods: We searched eight bibliographic databases (MEDLINE; EMBASE; COCHRANE; WEB OF SCIENCE; CINAHL; INSPEC; MATHSCINET; and ACM DIGITAL LIBRARY) from date of inception until 31 March 2016. Studies were included if they used a computer simulation method to capture patient progression within the ED of an established UK NHS hospital. Studies were summarised in terms of simulation method, key assumptions, input and output data, conclusions drawn, and implementation of results.

Results: Twenty one studies met the inclusion criteria. Of these, 19 used discrete event simulation and 2 used system dynamics models. The purpose of many of these studies (n=16; 76%) centred on service redesign. Seven studies (33%) provided no details about the ED being investigated. Most studies (n=18; 86%) used specific hospital models of ED patient flow. Overall, the reporting of underlying modelling assumptions was poor. Nineteen studies (90%) considered patient waiting or throughput times as the key outcome measure. Twelve studies (57%) reported some involvement of stakeholders in the simulation study. However, only 3 studies (14%) reported on the implementation of changes supported by the simulation.

Conclusions: We found that computer simulation can provide a means to pre-test changes to ED care delivery before implementation in a safe and efficient manner. However, there are some methodological, data, stakeholder, implementation, and reporting issues, which must be addressed by future studies.