Multimorbidity patterns in elderly primary health care patients in a South Mediterranean European region: A cluster analysis

Quintí Foguet-Boreu, Concepción Violán, Teresa Rodriguez-Blanco, Albert Roso-Llorach, Mariona Pons-Vigués, Enriqueta Pujol-Ribera, Yolima Cossio Gil, Jose M. Valderas

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    Abstract

    © 2015 Foguet-Boreu et al.This is an open access article distributed under the terms of the Creative Commons Attribution License ,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbidity, attended in primary care. Design Cross-sectional study. Setting 251 primary care centres in Catalonia, Spain. Participants Individuals older than 64 years registered with participating practices. Main outcome measures Multimorbidity, defined as the coexistence of 2 or more ICD-10 disease categories in the electronic health record. Using hierarchical cluster analysis, multimorbidity clusters were identified by sex and age group (65-79 and ≥80 years). Results 322,328 patients with multimorbidity were included in the analysis (mean age, 75.4 years [Standard deviation, SD: 7.4], 57.4% women; mean of 7.9 diagnoses [SD: 3.9]). For both men and women, the first cluster in both age groups included the same two diagnoses: Hypertensive diseases and Metabolic disorders. The second cluster contained three diagnoses of the musculoskeletal system in the 65- to 79-year-old group, and five diseases coincided in the ≥80 age group: varicose veins of the lower limbs, senile cataract, dorsalgia, functional intestinal disorders and shoulder lesions. The greatest overlap (54.5%) between the three most common diagnoses was observed in women aged 65-79 years. Conclusion This cluster analysis of elderly primary care patients with multimorbidity, revealed a single cluster of circulatory-metabolic diseases that were the most prevalent in both age groups and sex, and a cluster of second-most prevalent diagnoses that included musculoskeletal diseases. Clusters unknown to date have been identified. The clusters identified should be considered when developing clinical guidance for this population.
    Original languageEnglish
    Article numbere0141155
    JournalPLoS ONE
    Volume10
    Issue number11
    DOIs
    Publication statusPublished - 2 Nov 2015

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