Multimorbidity Patterns in Elderly Primary Health Care Patients in a South Mediterranean European Region: A Cluster Analysis.
Foguet-Boreu, Q; Violán, C; Rodriguez-Blanco, T; et al.Roso-Llorach, A; Pons-Vigués, M; Pujol-Ribera, E; Cossio Gil, Y; Valderas, JM
Date: 2 November 2015
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PLoS One
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Public Library of Science
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Abstract
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: ...
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.
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