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Physician influence on medication adherence, evidence from a population-based cohort

BACKGROUND: The overall impact of physician prescribers on population-level adherence rates are unknown. We aimed to quantify the influence of general practitioner (GP) physician prescribers on the outcome of optimal statin medication adherence. METHODS: We conducted a retrospective cohort study usi...

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Autores principales: Yao, Shenzhen, Lix, Lisa M., Teare, Gary, Evans, Charity, Blackburn, David F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714848/
https://www.ncbi.nlm.nih.gov/pubmed/36454907
http://dx.doi.org/10.1371/journal.pone.0278470
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author Yao, Shenzhen
Lix, Lisa M.
Teare, Gary
Evans, Charity
Blackburn, David F.
author_facet Yao, Shenzhen
Lix, Lisa M.
Teare, Gary
Evans, Charity
Blackburn, David F.
author_sort Yao, Shenzhen
collection PubMed
description BACKGROUND: The overall impact of physician prescribers on population-level adherence rates are unknown. We aimed to quantify the influence of general practitioner (GP) physician prescribers on the outcome of optimal statin medication adherence. METHODS: We conducted a retrospective cohort study using health administrative databases from Saskatchewan, Canada. Participants included physician prescribers and their patients beginning a new statin medication between January 1, 2012 and December 31, 2017. We grouped prescribers based on the prevalence of optimal adherence (i.e., proportion of days covered ≥ 80%) within their patient group. Also, we constructed multivariable logistic regression analyses on optimal statin adherence using two-level non-linear mixed-effects models containing patient and prescriber-level characteristics. An intraclass correlation coefficient was used to estimate the physician effect. RESULTS: We identified 1,562 GPs prescribing to 51,874 new statin users. The median percentage of optimal statin adherence across GPs was 52.4% (inter-quartile range: 35.7% to 65.5%). GP prescribers with the highest patient adherence (versus the lowest) had patients who were older (median age 61.0 vs 55.0, p<0.0001) and sicker (prior hospitalization 39.4% vs 16.4%, p<0.001). After accounting for patient-level factors, only 6.4% of the observed variance in optimal adherence between patients could be attributed to GP prescribers (p<0.001). The majority of GP prescriber influence (5.2% out of 6.4%) was attributed to the variance unexplained by patient and prescriber variables. INTERPRETATION: The overall impact of GP prescribers on statin adherence appears to be very limited. Even “high-performing” physicians face significant levels of sub-optimal adherence among their patients.
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spelling pubmed-97148482022-12-02 Physician influence on medication adherence, evidence from a population-based cohort Yao, Shenzhen Lix, Lisa M. Teare, Gary Evans, Charity Blackburn, David F. PLoS One Research Article BACKGROUND: The overall impact of physician prescribers on population-level adherence rates are unknown. We aimed to quantify the influence of general practitioner (GP) physician prescribers on the outcome of optimal statin medication adherence. METHODS: We conducted a retrospective cohort study using health administrative databases from Saskatchewan, Canada. Participants included physician prescribers and their patients beginning a new statin medication between January 1, 2012 and December 31, 2017. We grouped prescribers based on the prevalence of optimal adherence (i.e., proportion of days covered ≥ 80%) within their patient group. Also, we constructed multivariable logistic regression analyses on optimal statin adherence using two-level non-linear mixed-effects models containing patient and prescriber-level characteristics. An intraclass correlation coefficient was used to estimate the physician effect. RESULTS: We identified 1,562 GPs prescribing to 51,874 new statin users. The median percentage of optimal statin adherence across GPs was 52.4% (inter-quartile range: 35.7% to 65.5%). GP prescribers with the highest patient adherence (versus the lowest) had patients who were older (median age 61.0 vs 55.0, p<0.0001) and sicker (prior hospitalization 39.4% vs 16.4%, p<0.001). After accounting for patient-level factors, only 6.4% of the observed variance in optimal adherence between patients could be attributed to GP prescribers (p<0.001). The majority of GP prescriber influence (5.2% out of 6.4%) was attributed to the variance unexplained by patient and prescriber variables. INTERPRETATION: The overall impact of GP prescribers on statin adherence appears to be very limited. Even “high-performing” physicians face significant levels of sub-optimal adherence among their patients. Public Library of Science 2022-12-01 /pmc/articles/PMC9714848/ /pubmed/36454907 http://dx.doi.org/10.1371/journal.pone.0278470 Text en © 2022 Yao et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yao, Shenzhen
Lix, Lisa M.
Teare, Gary
Evans, Charity
Blackburn, David F.
Physician influence on medication adherence, evidence from a population-based cohort
title Physician influence on medication adherence, evidence from a population-based cohort
title_full Physician influence on medication adherence, evidence from a population-based cohort
title_fullStr Physician influence on medication adherence, evidence from a population-based cohort
title_full_unstemmed Physician influence on medication adherence, evidence from a population-based cohort
title_short Physician influence on medication adherence, evidence from a population-based cohort
title_sort physician influence on medication adherence, evidence from a population-based cohort
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714848/
https://www.ncbi.nlm.nih.gov/pubmed/36454907
http://dx.doi.org/10.1371/journal.pone.0278470
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