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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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Detalles Bibliográficos
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
Descripción
Sumario: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.