Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: cross-sectional study in a Mediterranean population.

ABSTRACT:

Objectives

The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population ≥65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.

Design

A cross-sectional study was conducted based on data from electronic health records.

Setting

284 primary healthcare centres in Catalonia, Spain (2012).

Participants

916 619 eligible individuals were included (women: 57.7%).

Primary and secondary outcome measures

We extracted data on demographics, In

SUBMITTER: Violan C 

PROVIDER: S-EPMC6719769 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature