University of Hertfordshire

From the same journal

By the same authors

Patient Pathway Modelling Using Discrete Event Simulation to Improve the Management of COPD

Research output: Contribution to journalArticlepeer-review

View graph of relations
Original languageEnglish
JournalJournal of the Operational Research Society
Early online date30 Dec 2020
DOIs
Publication statusE-pub ahead of print - 30 Dec 2020

Abstract

The number of people affected by chronic obstructive pulmonary disease (COPD) is increasing and the hospital readmission rate is remarkably high. Therefore, healthcare professionals and managers have financial and workforce-related pressures. A decision support toolkit (DST) for improving the management and efficiency of COPD care is needed to respond to the needs of patients now and in the future. In collaboration with the COPD team of a hospital and community service in London, we conceptualised the pathway for COPD patients and developed a discrete event simulation model (DES) incorporating the dynamics of patient readmissions. A DES model or operational model at this scale has never been previously developed, despite many studies using other modelling and simulation techniques in COPD. Our model is the first of its kind to include COPD readmissions as well as assessing the quantifiable impact of re-designing COPD services. We demonstrate the impact of post-exacerbation pulmonary rehabilitation (PEPR) policy and observe that PEPR would be cost-effective with improvements in quality-adjusted life years (QALYs), reduction in emergency readmissions and occupied bed days. The DST improves the understanding of the impact of scenarios (activities, resources, financial implications etc.) for key decision makers and supports commissioners in implementing the interventions.

Notes

This is an Accepted Manuscript version of 'Usame Yakutcan, Eren Demir, John R. Hurst & Paul C. Taylor (2020) Patient pathway modelling using discrete event simulation to improve the management of COPD, Journal of the Operational Research Society, DOI: 10.1080/01605682.2020.1854626'. It is deposited under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.” Publisher Copyright: © Operational Research Society 2020.

ID: 23008515