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Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice

OBJECTIVES: Prevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods. This study examines the independent effects on prevalence estimates of how ‘disease entity’ is defined—as a single chronic condition or chapters/domains in the International Classi...

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Autores principales: Harrison, Christopher, Britt, Helena, Miller, Graeme, Henderson, Joan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120329/
https://www.ncbi.nlm.nih.gov/pubmed/25015470
http://dx.doi.org/10.1136/bmjopen-2013-004694
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author Harrison, Christopher
Britt, Helena
Miller, Graeme
Henderson, Joan
author_facet Harrison, Christopher
Britt, Helena
Miller, Graeme
Henderson, Joan
author_sort Harrison, Christopher
collection PubMed
description OBJECTIVES: Prevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods. This study examines the independent effects on prevalence estimates of how ‘disease entity’ is defined—as a single chronic condition or chapters/domains in the International Classification of Primary Care (V.2; ICPC-2), International Classification of Disease (10th revision; ICD-10) or the Cumulative Illness Rating Scale (CIRS), the number of disease entities required for multimorbidity, and the number of chronic conditions studied. DESIGN: National prospective cross-sectional study. SETTING: Australian general practice. PARTICIPANTS: 8707 random consenting deidentified patient encounters with 290 randomly selected general practitioners. MAIN OUTCOME MEASURES: Prevalence estimates of multimorbidity using different definitions. RESULTS: Data classified to ICPC-2 chapters, ICD-10 chapters or CIRS domains produce similar multimorbidity prevalence estimates. When multimorbidity was defined as two or more (2+) disease entities: counting individual chronic conditions and groups of chronic conditions produced similar estimates; the 12 most prevalent chronic conditions identified about 80% of those identified using all chronic conditions. When multimorbidity was defined as 3+ disease entities: counting individual chronic conditions produced significantly higher estimates than counting groups of chronic conditions; the 12 most prevalent chronic conditions identified only two-thirds of patients identified using all chronic conditions. CONCLUSIONS: Multimorbidity defined as 2+ disease entities can be measured using different definitions of disease entity with as few as 12 prevalent chronic conditions, but lacks specificity to be useful, especially in older people. Multimorbidity, defined as 3+, requires more measurement conformity and inclusion of all chronic conditions, but provides greater specificity than the 2+ definition. The proposed concept of “complex multimorbidity”, the co-occurrence of three or more chronic conditions affecting three or more different body systems within one person without defining an index chronic condition, may be useful in identifying high-need individuals.
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spelling pubmed-41203292014-08-05 Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice Harrison, Christopher Britt, Helena Miller, Graeme Henderson, Joan BMJ Open Geriatric Medicine OBJECTIVES: Prevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods. This study examines the independent effects on prevalence estimates of how ‘disease entity’ is defined—as a single chronic condition or chapters/domains in the International Classification of Primary Care (V.2; ICPC-2), International Classification of Disease (10th revision; ICD-10) or the Cumulative Illness Rating Scale (CIRS), the number of disease entities required for multimorbidity, and the number of chronic conditions studied. DESIGN: National prospective cross-sectional study. SETTING: Australian general practice. PARTICIPANTS: 8707 random consenting deidentified patient encounters with 290 randomly selected general practitioners. MAIN OUTCOME MEASURES: Prevalence estimates of multimorbidity using different definitions. RESULTS: Data classified to ICPC-2 chapters, ICD-10 chapters or CIRS domains produce similar multimorbidity prevalence estimates. When multimorbidity was defined as two or more (2+) disease entities: counting individual chronic conditions and groups of chronic conditions produced similar estimates; the 12 most prevalent chronic conditions identified about 80% of those identified using all chronic conditions. When multimorbidity was defined as 3+ disease entities: counting individual chronic conditions produced significantly higher estimates than counting groups of chronic conditions; the 12 most prevalent chronic conditions identified only two-thirds of patients identified using all chronic conditions. CONCLUSIONS: Multimorbidity defined as 2+ disease entities can be measured using different definitions of disease entity with as few as 12 prevalent chronic conditions, but lacks specificity to be useful, especially in older people. Multimorbidity, defined as 3+, requires more measurement conformity and inclusion of all chronic conditions, but provides greater specificity than the 2+ definition. The proposed concept of “complex multimorbidity”, the co-occurrence of three or more chronic conditions affecting three or more different body systems within one person without defining an index chronic condition, may be useful in identifying high-need individuals. BMJ Publishing Group 2014-07-11 /pmc/articles/PMC4120329/ /pubmed/25015470 http://dx.doi.org/10.1136/bmjopen-2013-004694 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Geriatric Medicine
Harrison, Christopher
Britt, Helena
Miller, Graeme
Henderson, Joan
Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice
title Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice
title_full Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice
title_fullStr Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice
title_full_unstemmed Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice
title_short Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice
title_sort examining different measures of multimorbidity, using a large prospective cross-sectional study in australian general practice
topic Geriatric Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120329/
https://www.ncbi.nlm.nih.gov/pubmed/25015470
http://dx.doi.org/10.1136/bmjopen-2013-004694
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