Evaluating the impact of a simulation study in emergency stroke care
Operations Research for Health Care
Copyright © 2015 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Very few discrete-event simulation studies follow up on recommendations with evaluation of whether modelled benefits have been realised and the extent to which modelling contributed to any change. This paper evaluates changes made to the emergency stroke care pathway at a UK hospital informed by a simulation modelling study. The aims of the study were to increase the proportion of people with strokes that undergo a time-sensitive treatment to breakdown a blood clot within the brain and decrease the time to treatment. Evaluation involved analysis of stroke treatment pre- and post-implementation, as well as a comparison of how the research team believed the intervention would aid implementation compared to what actually happened. Two years after the care pathway was changed, treatment rates had increased in line with expectations and the hospital was treating four times as many patients than before the intervention in half the time. There is evidence that the modelling process aided implementation, but not always in line with expectations of the research team. Despite user involvement throughout the study it proved difficult to involve a representative group of clinical stakeholders in conceptual modelling and this affected model credibility. The research team also found batch experimentation more useful than visual interactive simulation to structure debate and decision making. In particular, simple charts of results focused debates on the clinical effectiveness of drugs - an emergent barrier to change. Visual interactive simulation proved more useful for engaging different hospitals and initiating new projects.
National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South West Peninsula
NIHR CLAHRC Wessex
NOTICE: this is the author’s version of a work that was accepted for publication in Operations Research for Health Care. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Operations Research for Health Care, Vol. 6 (2015). DOI: 10.1016/j.orhc.2015.09.002
Open access article
Vol. 6, pp. 40 - 49