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Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study
BACKGROUND: Multimorbidity is associated with mortality and service use, with specific types of multimorbidity having differential effects. Additionally, multimorbidity is often negatively associated with participation in research cohorts. Therefore, we set out to identify clusters of multimorbidity...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7147068/ https://www.ncbi.nlm.nih.gov/pubmed/32272927 http://dx.doi.org/10.1186/s12916-020-01543-8 |
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author | Zhu, Yajing Edwards, Duncan Mant, Jonathan Payne, Rupert A. Kiddle, Steven |
author_facet | Zhu, Yajing Edwards, Duncan Mant, Jonathan Payne, Rupert A. Kiddle, Steven |
author_sort | Zhu, Yajing |
collection | PubMed |
description | BACKGROUND: Multimorbidity is associated with mortality and service use, with specific types of multimorbidity having differential effects. Additionally, multimorbidity is often negatively associated with participation in research cohorts. Therefore, we set out to identify clusters of multimorbidity patients and how they are differentially associated with mortality and service use across age groups in a population-representative sample. METHODS: Linked primary and secondary care electronic health records contributed by 382 general practices in England to the Clinical Practice Research Datalink (CPRD) were used. The study included a representative set of multimorbid adults (18 years old or more, N = 113,211) with two or more long-term conditions (a total of 38 conditions were included). A random set of 80% of the multimorbid patients (N = 90,571) were stratified by age groups and clustered using latent class analysis. Consistency between obtained multimorbidity phenotypes, classification quality and associations with demographic characteristics and primary outcomes (GP consultations, hospitalisations, regular medications and mortality) was validated in the remaining 20% of multimorbid patients (N = 22,640). RESULTS: We identified 20 patient clusters across four age strata. The clusters with the highest mortality comprised psychoactive substance and alcohol misuse (aged 18–64); coronary heart disease, depression and pain (aged 65–84); and coronary heart disease, heart failure and atrial fibrillation (aged 85+). The clusters with the highest service use coincided with those with the highest mortality for people aged over 65. For people aged 18–64, the cluster with the highest service use comprised depression, anxiety and pain. The majority of 85+-year-old multimorbid patients belonged to the cluster with the lowest service use and mortality for that age range. Pain featured in 13 clusters. CONCLUSIONS: This work has highlighted patterns of multimorbidity that have implications for health services. These include the importance of psychoactive substance and alcohol misuse in people under the age of 65, of co-morbid depression and coronary heart disease in people aged 65–84 and of cardiovascular disease in people aged 85+. |
format | Online Article Text |
id | pubmed-7147068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71470682020-04-18 Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study Zhu, Yajing Edwards, Duncan Mant, Jonathan Payne, Rupert A. Kiddle, Steven BMC Med Research Article BACKGROUND: Multimorbidity is associated with mortality and service use, with specific types of multimorbidity having differential effects. Additionally, multimorbidity is often negatively associated with participation in research cohorts. Therefore, we set out to identify clusters of multimorbidity patients and how they are differentially associated with mortality and service use across age groups in a population-representative sample. METHODS: Linked primary and secondary care electronic health records contributed by 382 general practices in England to the Clinical Practice Research Datalink (CPRD) were used. The study included a representative set of multimorbid adults (18 years old or more, N = 113,211) with two or more long-term conditions (a total of 38 conditions were included). A random set of 80% of the multimorbid patients (N = 90,571) were stratified by age groups and clustered using latent class analysis. Consistency between obtained multimorbidity phenotypes, classification quality and associations with demographic characteristics and primary outcomes (GP consultations, hospitalisations, regular medications and mortality) was validated in the remaining 20% of multimorbid patients (N = 22,640). RESULTS: We identified 20 patient clusters across four age strata. The clusters with the highest mortality comprised psychoactive substance and alcohol misuse (aged 18–64); coronary heart disease, depression and pain (aged 65–84); and coronary heart disease, heart failure and atrial fibrillation (aged 85+). The clusters with the highest service use coincided with those with the highest mortality for people aged over 65. For people aged 18–64, the cluster with the highest service use comprised depression, anxiety and pain. The majority of 85+-year-old multimorbid patients belonged to the cluster with the lowest service use and mortality for that age range. Pain featured in 13 clusters. CONCLUSIONS: This work has highlighted patterns of multimorbidity that have implications for health services. These include the importance of psychoactive substance and alcohol misuse in people under the age of 65, of co-morbid depression and coronary heart disease in people aged 65–84 and of cardiovascular disease in people aged 85+. BioMed Central 2020-04-10 /pmc/articles/PMC7147068/ /pubmed/32272927 http://dx.doi.org/10.1186/s12916-020-01543-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Zhu, Yajing Edwards, Duncan Mant, Jonathan Payne, Rupert A. Kiddle, Steven Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study |
title | Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study |
title_full | Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study |
title_fullStr | Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study |
title_full_unstemmed | Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study |
title_short | Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study |
title_sort | characteristics, service use and mortality of clusters of multimorbid patients in england: a population-based study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7147068/ https://www.ncbi.nlm.nih.gov/pubmed/32272927 http://dx.doi.org/10.1186/s12916-020-01543-8 |
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