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

Author:

Beridze Giorgi1ORCID,Abbadi Ahmad1ORCID,Ars Joan123,Remelli Francesca4,Vetrano Davide L15ORCID,Trevisan Caterina14,Pérez Laura-Mónica2,López-Rodríguez Juan A678ORCID,Calderón-Larrañaga Amaia158ORCID

Affiliation:

1. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Aging Research Center, Stockholm, Sweden

2. RE-FiT Barcelona Research group, Vall d'Hebron Institute of Research (VHIR) and Parc Sanitari Pere Virgili, Barcelona, Spain

3. Medicine Department, Universitat Autònoma de Barcelona, Barcelona, Spain

4. Department of Medical Sciences, University of Ferrara, Ferrara, Italy

5. Stockholm Gerontology Research Center, Stockholm, Sweden

6. Research Unit, Primary Health Care Management, Madrid, Spain

7. Department of Medical Specialties and Public Health, Faculty of Health Sciences Rey Juan Carlos University, Madrid, Spain

8. Research Network on Chronicity, Primary Care and Health Promotion (RICAPPS), Carlos III Health Institute, Madrid, Spain

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.

Publisher

SAGE Publications

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