Multimorbidity, disease count, mortality and emergency care use in persons attending the emergency department: a cross-sectional data-linkage study

McParland, C., Cooper, M. A., Lowe, D. J. , Stanley, B. and Johnston, B. (2022) Multimorbidity, disease count, mortality and emergency care use in persons attending the emergency department: a cross-sectional data-linkage study. Journal of Multimorbidity and Comorbidity, 12, p. 26335565221147417. (doi: 10.1177/26335565221147417) (PMID:36545236) (PMCID:PMC9761223)

Abstract

Background: Multimorbidity (two or more concurrent chronic conditions) is associated with poorer health outcomes and increased healthcare utilisation in primary care and general populations. Less is known about the prevalence of multimorbidity in emergency department attenders, or its association with poor outcomes in this population. Aim: This study sought to explore the relationship between multimorbidity, mortality and health-care utilisation in a large urban cohort of persons attending emergency departments. Methods: Validated algorithms for the identification of 28 chronic conditions from ICD-10 codes were deployed on a cross-sectional sample of patients attending emergency departments in Glasgow, Scotland between April 2019 and March 2020. Analysis was conducted on complete cases (n=63,328) and compared with results from data with imputed missing values (n=75,723). Models adjusted for age, sex, deprivation and ethnicity were fitted to test for the association between (i) multimorbidity, (ii) complex multimorbidity, (iii) disease count and the following outcomes: admission to hospital, reattendance at 30 and 90 days, and death during admission. Results: Multimorbidity, complex multimorbidity and disease count were significantly associated with hospital admission and emergency department reattendance. Those with 1-3 conditions were at increased risk of inpatient mortality. Conclusion: This study further evidences the impact of multimorbidity and disease burden on health-care use, and mortality to a lesser extent. Deployed algorithms were sufficiently sensitive to detect associations, despite limited access (21 months) to secondary-care data. This should allow for the construction of more robust models to prospectively identify persons at risk of poor outcomes in similar populations.

• Item Type: Articles
• Additional Information: This study was funded by NHS Greater Glasgow and Clyde as part of the first author’s clinical academic PhD fellowship.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cooper, Dr Mark and Stanley, Miss Bethany and Johnston, Professor Bridget and Lowe, Dr David and McParland, Mr Chris
• Authors: McParland, C., Cooper, M. A., Lowe, D. J., Stanley, B., and Johnston, B.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Robertson Centre; College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing; College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing > Nursing and Health Care
• Journal Name: Journal of Multimorbidity and Comorbidity
• Publisher: SAGE Publications
• ISSN: 2633-5565
• ISSN (Online): 2633-5565
• Published Online: 15 December 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Journal of Multimorbidity and Comorbidity 12: 26335565221147417
• Publisher Policy: Reproduced under a Creative Commons License