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

Author
Violán, C.; Foguet Boreu, Q.; Fernández, S.; Guisado, M.; Cabrera-Bean, Margarita; Formiga, F.; Valderas, J.; Roso Llorach, Albert
Type of activity
Journal article
Journal
BMJ Open
Date of publication
2019-08-01
Volume
9
Number
8
First page
1
Last page
14
DOI
10.1136/bmjopen-2019-029594
Repository
http://hdl.handle.net/2117/169036 Open in new window
URL
https://bmjopen.bmj.com/content/9/8/e029594 Open in new window
Abstract
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.
Keywords
Chronic conditions, Cluster analysis, Epidemiology, Fuzzy C-Means, Multimorbidity
Group of research
SPCOM - Signal Processing and Communications Group

Participants

  • Violán Fors, Concepción  (author)
  • Foguet Boreu, Quintí  (author)
  • Fernández Bertolín, Sergio  (author)
  • Guisado Clavero, Marina  (author)
  • Cabrera Bean, Margarita Asuncion  (author)
  • Formiga, Francesc  (author)
  • Valderas, José Maria  (author)
  • Roso Llorach, Albert  (author)