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An integrated statistical model of Emergency Department length of stay informed by Resilient Health Care principles

Ross, A. J., Murrells, T., Kirby, T., Jaye, P. and Anderson, J. E. ORCID: 0000-0002-1452-8370 (2019). An integrated statistical model of Emergency Department length of stay informed by Resilient Health Care principles. Safety Science, 120, pp. 129-136. doi: 10.1016/j.ssci.2019.06.018

Abstract

Background
Hospital Emergency Departments (EDs) face variable demand and capacity issues affecting timely discharge of patients. This is due in part to a lack of integration of routine monitoring data, affecting anticipation and response.

Methods
Patient flow was modelled (four hour target breaches; time to decision-to-admit; subsequent time to admit-to-hospital) in a busy ED. Patient and organisational data were collated, screened and conceptualised using Resilient Health Care (RHC) theory. Data were collected for all patients presenting during a 24-month period (May 2014–April 2016; n = 232,920) and analysed via multivariable logistic regression for four hour target breaches, and ordinary least squares regression for time. A measure of effect size was calculated for each independent variable. Overall model fit was assessed using percent concordant.

Results
Length of stay is related to demand, capacity and process indicators including: number of patients; night shift; first location being resuscitation or major injury area(s); urgent or very urgent triage patients; patients readmitting from up to 7 days previous; bed capacity; recent ambulance arrivals; and patients where the primary presenting complaint (PPC) is related to mental health or difficult to ascertain.

Conclusions
Understanding variation in performance through RHC theory can support staff and organisations in monitoring, anticipating and responding. A set of reliable core predictors has been identified to help design future ways to facilitate resilient performance through early indicators of pressure.

Publication Type: Article
Additional Information: © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: Resilient Health Care, Data systems, Emergency department, Patient flow, Informatics
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments: School of Health Sciences > Nursing
Related URLs:
Date Deposited: 17 Sep 2020 09:05
URI: https://openaccess.city.ac.uk/id/eprint/24926
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