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Patterns of multimorbidity in primary care electronic health records: A systematic review.

Authors :
Beridze, Giorgi
Abbadi, Ahmad
Ars, Joan
Remelli, Francesca
Vetrano, Davide L
Trevisan, Caterina
Pérez, Laura-Mónica
López-Rodríguez, Juan A
Calderón-Larrañaga, Amaia
Source :
Journal of Multimorbidity & Comorbidity; 1/30/2024, p1-18, 18p
Publication Year :
2024

Abstract

Background: Multimorbidity, the coexistence of multiple chronic conditions in an individual, is a complex phenomenon that is highly prevalent in primary care settings, particularly in older individuals. This systematic review summarises the current evidence on multimorbidity patterns identified in primary care electronic health record (EHR) data. Methods: Three databases were searched from inception to April 2022 to identify studies that derived original multimorbidity patterns from primary care EHR data. The quality of the included studies was assessed using a modified version of the Newcastle-Ottawa Quality Assessment Scale. Results: Sixteen studies were included in this systematic review, none of which was of low quality. Most studies were conducted in Spain, and only one study was conducted outside of Europe. The prevalence of multimorbidity (i.e. two or more conditions) ranged from 14.0% to 93.9%. The most common stratification variable in disease clustering models was sex, followed by age and calendar year. Despite significant heterogeneity in clustering methods and disease classification tools, consistent patterns of multimorbidity emerged. Mental health and cardiovascular patterns were identified in all studies, often in combination with diseases of other organ systems (e.g. neurological, endocrine). Discussion: These findings emphasise the frequent coexistence of physical and mental health conditions in primary care, and provide useful information for the development of targeted preventive and management strategies. Future research should explore mechanisms underlying multimorbidity patterns, prioritise methodological harmonisation to facilitate the comparability of findings, and promote the use of EHR data globally to enhance our understanding of multimorbidity in more diverse populations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
26335565
Database :
Complementary Index
Journal :
Journal of Multimorbidity & Comorbidity
Publication Type :
Academic Journal
Accession number :
175159094
Full Text :
https://doi.org/10.1177/26335565231223350