Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.

<h4>Background</h4>Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting about 1.6% of the population in England. Novel oral anticoagulants (NOACs) are approved AF treatments that reduce stroke risk. In this study, we estimate the equality in individual NOAC prescript...

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Main Authors: Ehsan Rezaei-Darzi, Parinaz Mehdipour, Mariachiara Di Cesare, Farshad Farzadfar, Shadi Rahimzadeh, Lisa Nissen, Alireza Ahmadvand
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0246253
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spelling doaj-e87e187d1eb3466a84fb83ed3d6fe5dc2021-07-29T04:32:55ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01162e024625310.1371/journal.pone.0246253Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.Ehsan Rezaei-DarziParinaz MehdipourMariachiara Di CesareFarshad FarzadfarShadi RahimzadehLisa NissenAlireza Ahmadvand<h4>Background</h4>Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting about 1.6% of the population in England. Novel oral anticoagulants (NOACs) are approved AF treatments that reduce stroke risk. In this study, we estimate the equality in individual NOAC prescriptions with high spatial resolution in Clinical Commissioning Groups (CCGs) across England from 2014 to 2019.<h4>Methods</h4>A Bayesian spatio-temporal model will be used to estimate and predict the individual NOAC prescription trend on 'prescription data' as an indicator of health services utilisation, using a small area analysis methodology. The main dataset in this study is the "Practice Level Prescribing in England," which contains four individual NOACs prescribed by all registered GP practices in England. We will use the defined daily dose (DDD) equivalent methodology, as recommended by the World Health Organization (WHO), to compare across space and time. Four licensed NOACs datasets will be summed per 1,000 patients at the CCG-level over time. We will also adjust for CCG-level covariates, such as demographic data, Multiple Deprivation Index, and rural-urban classification. We aim to employ the extended BYM2 model (space-time model) using the RStan package.<h4>Discussion</h4>This study suggests a new statistical modelling approach to link prescription and socioeconomic data to model pharmacoepidemiologic data. Quantifying space and time differences will allow for the evaluation of inequalities in the prescription of NOACs. The methodology will help develop geographically targeted public health interventions, campaigns, audits, or guidelines to improve areas of low prescription. This approach can be used for other medications, especially those used for chronic diseases that must be monitored over time.https://doi.org/10.1371/journal.pone.0246253
collection DOAJ
language English
format Article
sources DOAJ
author Ehsan Rezaei-Darzi
Parinaz Mehdipour
Mariachiara Di Cesare
Farshad Farzadfar
Shadi Rahimzadeh
Lisa Nissen
Alireza Ahmadvand
spellingShingle Ehsan Rezaei-Darzi
Parinaz Mehdipour
Mariachiara Di Cesare
Farshad Farzadfar
Shadi Rahimzadeh
Lisa Nissen
Alireza Ahmadvand
Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.
PLoS ONE
author_facet Ehsan Rezaei-Darzi
Parinaz Mehdipour
Mariachiara Di Cesare
Farshad Farzadfar
Shadi Rahimzadeh
Lisa Nissen
Alireza Ahmadvand
author_sort Ehsan Rezaei-Darzi
title Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.
title_short Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.
title_full Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.
title_fullStr Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.
title_full_unstemmed Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis.
title_sort evaluating equality in prescribing novel oral anticoagulants (noacs) in england: the protocol of a bayesian small area analysis.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2021-01-01
description <h4>Background</h4>Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting about 1.6% of the population in England. Novel oral anticoagulants (NOACs) are approved AF treatments that reduce stroke risk. In this study, we estimate the equality in individual NOAC prescriptions with high spatial resolution in Clinical Commissioning Groups (CCGs) across England from 2014 to 2019.<h4>Methods</h4>A Bayesian spatio-temporal model will be used to estimate and predict the individual NOAC prescription trend on 'prescription data' as an indicator of health services utilisation, using a small area analysis methodology. The main dataset in this study is the "Practice Level Prescribing in England," which contains four individual NOACs prescribed by all registered GP practices in England. We will use the defined daily dose (DDD) equivalent methodology, as recommended by the World Health Organization (WHO), to compare across space and time. Four licensed NOACs datasets will be summed per 1,000 patients at the CCG-level over time. We will also adjust for CCG-level covariates, such as demographic data, Multiple Deprivation Index, and rural-urban classification. We aim to employ the extended BYM2 model (space-time model) using the RStan package.<h4>Discussion</h4>This study suggests a new statistical modelling approach to link prescription and socioeconomic data to model pharmacoepidemiologic data. Quantifying space and time differences will allow for the evaluation of inequalities in the prescription of NOACs. The methodology will help develop geographically targeted public health interventions, campaigns, audits, or guidelines to improve areas of low prescription. This approach can be used for other medications, especially those used for chronic diseases that must be monitored over time.
url https://doi.org/10.1371/journal.pone.0246253
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