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Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices

BACKGROUND: Few studies have comprehensively reported intracluster correlation coefficient (ICC) estimates for outcomes collected in primary care settings. Using data from a large primary care study, we aimed to: a) report ICCs for process-of-care and clinical outcome measures related to cardiovascu...

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Autores principales: Singh, Jatinderpreet, Liddy, Clare, Hogg, William, Taljaard, Monica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4369059/
https://www.ncbi.nlm.nih.gov/pubmed/25888958
http://dx.doi.org/10.1186/s13104-015-1042-y
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author Singh, Jatinderpreet
Liddy, Clare
Hogg, William
Taljaard, Monica
author_facet Singh, Jatinderpreet
Liddy, Clare
Hogg, William
Taljaard, Monica
author_sort Singh, Jatinderpreet
collection PubMed
description BACKGROUND: Few studies have comprehensively reported intracluster correlation coefficient (ICC) estimates for outcomes collected in primary care settings. Using data from a large primary care study, we aimed to: a) report ICCs for process-of-care and clinical outcome measures related to cardiovascular disease management and prevention, and b) investigate the impact of practice structure and rurality on ICC estimates. METHODS: We used baseline data from the Improved Delivery of Cardiovascular Care (IDOCC) trial to estimate ICC values. Data on 5,140 patients from 84 primary care practices across Eastern Ontario, Canada were collected through chart abstraction. ICC estimates were calculated using an ANOVA approach and were calculated for all patients and separately for patient subgroups defined by condition (i.e., coronary artery disease, diabetes, chronic kidney disease, hypertension, dyslipidemia, and smoking). We compared ICC estimates between practices in which data were collected from a single physician versus those that had multiple participating physicians and between urban versus rural practices. RESULTS: ICC estimates ranged from 0 to 0.173, with a median of 0.056. The median ICC estimate for dichotomous process outcomes (0.088) was higher than that for continuous clinical outcomes (0.035). ICC estimates calculated for single physician practices were higher than those for practices with multiple physicians for both process (average 3.9-times higher) and clinical measures (average 1.9-times higher). Urban practices tended to have higher process-of-care ICC estimates than rural practices, particularly for measuring lipid profiles and estimated glomerular filtration rates. CONCLUSION: To our knowledge, this is the most comprehensive summary of cardiovascular-related ICCs to be reported from Canadian primary care practices. Differences in ICC estimates based on practice structure and location highlight the importance of understanding the context in which external ICC estimates were determined prior to their use in sample size calculations. Failure to choose appropriate ICC estimates can have substantial implications for the design of a cluster randomized trial.
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spelling pubmed-43690592015-03-22 Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices Singh, Jatinderpreet Liddy, Clare Hogg, William Taljaard, Monica BMC Res Notes Research Article BACKGROUND: Few studies have comprehensively reported intracluster correlation coefficient (ICC) estimates for outcomes collected in primary care settings. Using data from a large primary care study, we aimed to: a) report ICCs for process-of-care and clinical outcome measures related to cardiovascular disease management and prevention, and b) investigate the impact of practice structure and rurality on ICC estimates. METHODS: We used baseline data from the Improved Delivery of Cardiovascular Care (IDOCC) trial to estimate ICC values. Data on 5,140 patients from 84 primary care practices across Eastern Ontario, Canada were collected through chart abstraction. ICC estimates were calculated using an ANOVA approach and were calculated for all patients and separately for patient subgroups defined by condition (i.e., coronary artery disease, diabetes, chronic kidney disease, hypertension, dyslipidemia, and smoking). We compared ICC estimates between practices in which data were collected from a single physician versus those that had multiple participating physicians and between urban versus rural practices. RESULTS: ICC estimates ranged from 0 to 0.173, with a median of 0.056. The median ICC estimate for dichotomous process outcomes (0.088) was higher than that for continuous clinical outcomes (0.035). ICC estimates calculated for single physician practices were higher than those for practices with multiple physicians for both process (average 3.9-times higher) and clinical measures (average 1.9-times higher). Urban practices tended to have higher process-of-care ICC estimates than rural practices, particularly for measuring lipid profiles and estimated glomerular filtration rates. CONCLUSION: To our knowledge, this is the most comprehensive summary of cardiovascular-related ICCs to be reported from Canadian primary care practices. Differences in ICC estimates based on practice structure and location highlight the importance of understanding the context in which external ICC estimates were determined prior to their use in sample size calculations. Failure to choose appropriate ICC estimates can have substantial implications for the design of a cluster randomized trial. BioMed Central 2015-03-20 /pmc/articles/PMC4369059/ /pubmed/25888958 http://dx.doi.org/10.1186/s13104-015-1042-y Text en © Singh et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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.
spellingShingle Research Article
Singh, Jatinderpreet
Liddy, Clare
Hogg, William
Taljaard, Monica
Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
title Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
title_full Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
title_fullStr Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
title_full_unstemmed Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
title_short Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
title_sort intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4369059/
https://www.ncbi.nlm.nih.gov/pubmed/25888958
http://dx.doi.org/10.1186/s13104-015-1042-y
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