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Comparisons of multi-morbidity in family practice—issues and biases

BACKGROUND. As the population ages, practice and policy need to be guided by accurate estimates of chronic disease burden in primary care. OBJECTIVE. To produce a preliminary set of methodological considerations for cross-sectional and retrospective cohort studies of multi-morbidity in primary care...

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Autores principales: Stewart, Moira, Fortin, Martin, Britt, Helena C, Harrison, Christopher M, Maddocks, Heather L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722508/
https://www.ncbi.nlm.nih.gov/pubmed/23666805
http://dx.doi.org/10.1093/fampra/cmt012
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author Stewart, Moira
Fortin, Martin
Britt, Helena C
Harrison, Christopher M
Maddocks, Heather L
author_facet Stewart, Moira
Fortin, Martin
Britt, Helena C
Harrison, Christopher M
Maddocks, Heather L
author_sort Stewart, Moira
collection PubMed
description BACKGROUND. As the population ages, practice and policy need to be guided by accurate estimates of chronic disease burden in primary care. OBJECTIVE. To produce a preliminary set of methodological considerations for cross-sectional and retrospective cohort studies of multi-morbidity in primary care using three studies as examples. Prevalence rate results from the three studies were re-estimated using identical age–sex groups. METHODS. We compared the methods and results of three separate studies in primary care: (i) patients in the Saguenay region of Quebec, Canada (2005); (ii) a substudy of the BEACH (Bettering the Evaluation and Care of Health) programme in Australia (2008); and (iii) the DELPHI (Deliver Primary Health Care Information) project in South-western Ontario, Canada (2009). Areas where the methods of multi-morbidity studies may differ were identified. The percentage of patients with two or more chronic conditions was compared by age–sex groups. RESULTS. Multi-morbidity prevalence varied by as much as 61%, where reported prevalence was 95% among females aged 45–64 in the Saguenay study, 46% in the BEACH substudy and 34% in the DELPHI study. Several aspects of the methods and study designs were identified as differing among the studies, including the sampling of frequent attenders, sampling period, source of data, and both the definition and count of chronic conditions. CONCLUSIONS. Understanding the differences among the methods used to produce prevalence data on multi-morbidity in primary care can help explain the varying results. Standardization of methods would allow for more valid inter-study comparisons.
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spelling pubmed-37225082014-08-01 Comparisons of multi-morbidity in family practice—issues and biases Stewart, Moira Fortin, Martin Britt, Helena C Harrison, Christopher M Maddocks, Heather L Fam Pract Original Article BACKGROUND. As the population ages, practice and policy need to be guided by accurate estimates of chronic disease burden in primary care. OBJECTIVE. To produce a preliminary set of methodological considerations for cross-sectional and retrospective cohort studies of multi-morbidity in primary care using three studies as examples. Prevalence rate results from the three studies were re-estimated using identical age–sex groups. METHODS. We compared the methods and results of three separate studies in primary care: (i) patients in the Saguenay region of Quebec, Canada (2005); (ii) a substudy of the BEACH (Bettering the Evaluation and Care of Health) programme in Australia (2008); and (iii) the DELPHI (Deliver Primary Health Care Information) project in South-western Ontario, Canada (2009). Areas where the methods of multi-morbidity studies may differ were identified. The percentage of patients with two or more chronic conditions was compared by age–sex groups. RESULTS. Multi-morbidity prevalence varied by as much as 61%, where reported prevalence was 95% among females aged 45–64 in the Saguenay study, 46% in the BEACH substudy and 34% in the DELPHI study. Several aspects of the methods and study designs were identified as differing among the studies, including the sampling of frequent attenders, sampling period, source of data, and both the definition and count of chronic conditions. CONCLUSIONS. Understanding the differences among the methods used to produce prevalence data on multi-morbidity in primary care can help explain the varying results. Standardization of methods would allow for more valid inter-study comparisons. Oxford University Press 2013-08 2013-05-10 /pmc/articles/PMC3722508/ /pubmed/23666805 http://dx.doi.org/10.1093/fampra/cmt012 Text en © The Author 2013. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Stewart, Moira
Fortin, Martin
Britt, Helena C
Harrison, Christopher M
Maddocks, Heather L
Comparisons of multi-morbidity in family practice—issues and biases
title Comparisons of multi-morbidity in family practice—issues and biases
title_full Comparisons of multi-morbidity in family practice—issues and biases
title_fullStr Comparisons of multi-morbidity in family practice—issues and biases
title_full_unstemmed Comparisons of multi-morbidity in family practice—issues and biases
title_short Comparisons of multi-morbidity in family practice—issues and biases
title_sort comparisons of multi-morbidity in family practice—issues and biases
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722508/
https://www.ncbi.nlm.nih.gov/pubmed/23666805
http://dx.doi.org/10.1093/fampra/cmt012
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