Multimorbidity Patterns in Elderly Primary Health Care Patients in a South Mediterranean European Region: A Cluster Analysis
The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbidity, attended in primary care.
Foguet-Boreu Q, Violán C, Rodriguez-Blanco T, Roso-Llorach A, Pons-Vigués M, Pujol-Ribera E, Cossio Gil Y, Valderas JM. Multimorbidity Patterns in Elderly Primary Health Care Patients in a South Mediterranean European Region: A Cluster Analysis. PLoS One. 2015 Nov 2;10(11):e0141155. Available at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141155
Article
27/11/2015
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.
Foguet-Boreu Q, Violán C, Rodriguez-Blanco T, Roso-Llorach A, Pons-Vigués M, Pujol-Ribera E, Cossio Gil Y, Valderas JM.
España