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Comorbidity Patterns in Patients with Chronic Diseases in General Practice

INTRODUCTION: Healthcare management is oriented toward single diseases, yet multimorbidity is nevertheless the rule and there is a tendency for certain diseases to occur in clusters. This study sought to identify comorbidity patterns in patients with chronic diseases, by reference to number of comor...

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Autores principales: García-Olmos, Luis, Salvador, Carlos H., Alberquilla, Ángel, Lora, David, Carmona, Montserrat, García-Sagredo, Pilar, Pascual, Mario, Muñoz, Adolfo, Monteagudo, José Luis, García-López, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3281110/
https://www.ncbi.nlm.nih.gov/pubmed/22359665
http://dx.doi.org/10.1371/journal.pone.0032141
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author García-Olmos, Luis
Salvador, Carlos H.
Alberquilla, Ángel
Lora, David
Carmona, Montserrat
García-Sagredo, Pilar
Pascual, Mario
Muñoz, Adolfo
Monteagudo, José Luis
García-López, Fernando
author_facet García-Olmos, Luis
Salvador, Carlos H.
Alberquilla, Ángel
Lora, David
Carmona, Montserrat
García-Sagredo, Pilar
Pascual, Mario
Muñoz, Adolfo
Monteagudo, José Luis
García-López, Fernando
author_sort García-Olmos, Luis
collection PubMed
description INTRODUCTION: Healthcare management is oriented toward single diseases, yet multimorbidity is nevertheless the rule and there is a tendency for certain diseases to occur in clusters. This study sought to identify comorbidity patterns in patients with chronic diseases, by reference to number of comorbidities, age and sex, in a population receiving medical care from 129 general practitioners in Spain, in 2007. METHODS: A cross-sectional study was conducted in a health-area setting of the Madrid Autonomous Region (Comunidad Autónoma), covering a population of 198,670 individuals aged over 14 years. Multiple correspondences were analyzed to identify the clustering patterns of the conditions targeted. RESULTS: Forty-two percent (95% confidence interval [CI]: 41.8–42.2) of the registered population had at least one chronic condition. In all, 24.5% (95% CI: 24.3–24.6) of the population presented with multimorbidity. In the correspondence analysis, 98.3% of the total information was accounted for by three dimensions. The following four, age- and sex-related comorbidity patterns were identified: pattern B, showing a high comorbidity rate; pattern C, showing a low comorbidity rate; and two patterns, A and D, showing intermediate comorbidity rates. CONCLUSIONS: Four comorbidity patterns could be identified which grouped diseases as follows: one showing diseases with a high comorbidity burden; one showing diseases with a low comorbidity burden; and two showing diseases with an intermediate comorbidity burden.
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spelling pubmed-32811102012-02-22 Comorbidity Patterns in Patients with Chronic Diseases in General Practice García-Olmos, Luis Salvador, Carlos H. Alberquilla, Ángel Lora, David Carmona, Montserrat García-Sagredo, Pilar Pascual, Mario Muñoz, Adolfo Monteagudo, José Luis García-López, Fernando PLoS One Research Article INTRODUCTION: Healthcare management is oriented toward single diseases, yet multimorbidity is nevertheless the rule and there is a tendency for certain diseases to occur in clusters. This study sought to identify comorbidity patterns in patients with chronic diseases, by reference to number of comorbidities, age and sex, in a population receiving medical care from 129 general practitioners in Spain, in 2007. METHODS: A cross-sectional study was conducted in a health-area setting of the Madrid Autonomous Region (Comunidad Autónoma), covering a population of 198,670 individuals aged over 14 years. Multiple correspondences were analyzed to identify the clustering patterns of the conditions targeted. RESULTS: Forty-two percent (95% confidence interval [CI]: 41.8–42.2) of the registered population had at least one chronic condition. In all, 24.5% (95% CI: 24.3–24.6) of the population presented with multimorbidity. In the correspondence analysis, 98.3% of the total information was accounted for by three dimensions. The following four, age- and sex-related comorbidity patterns were identified: pattern B, showing a high comorbidity rate; pattern C, showing a low comorbidity rate; and two patterns, A and D, showing intermediate comorbidity rates. CONCLUSIONS: Four comorbidity patterns could be identified which grouped diseases as follows: one showing diseases with a high comorbidity burden; one showing diseases with a low comorbidity burden; and two showing diseases with an intermediate comorbidity burden. Public Library of Science 2012-02-16 /pmc/articles/PMC3281110/ /pubmed/22359665 http://dx.doi.org/10.1371/journal.pone.0032141 Text en García-Olmos et al. http://creativecommons.org/licenses/by/4.0/ 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 properly credited.
spellingShingle Research Article
García-Olmos, Luis
Salvador, Carlos H.
Alberquilla, Ángel
Lora, David
Carmona, Montserrat
García-Sagredo, Pilar
Pascual, Mario
Muñoz, Adolfo
Monteagudo, José Luis
García-López, Fernando
Comorbidity Patterns in Patients with Chronic Diseases in General Practice
title Comorbidity Patterns in Patients with Chronic Diseases in General Practice
title_full Comorbidity Patterns in Patients with Chronic Diseases in General Practice
title_fullStr Comorbidity Patterns in Patients with Chronic Diseases in General Practice
title_full_unstemmed Comorbidity Patterns in Patients with Chronic Diseases in General Practice
title_short Comorbidity Patterns in Patients with Chronic Diseases in General Practice
title_sort comorbidity patterns in patients with chronic diseases in general practice
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3281110/
https://www.ncbi.nlm.nih.gov/pubmed/22359665
http://dx.doi.org/10.1371/journal.pone.0032141
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