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Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small
Ehsan Rezaei-Darzi1,2, Parinaz Mehdipour1,3, Mariachiara Di Cesare4
1Non-Communicable Diseases Research Centre, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Insights
This study analyzed novel oral anticoagulant (NOAC) prescriptions in England, revealing spatial inequalities. The findings will guide targeted public health interventions to improve NOAC access for atrial fibrillation (AF) patients.
Area of Science:
- Pharmacoepidemiology
- Health Services Research
- Spatial Statistics
Background:
- Atrial fibrillation (AF) is a common arrhythmia affecting 1.6% of England's population.
- Novel oral anticoagulants (NOACs) are effective in reducing stroke risk for AF patients.
- Understanding NOAC prescription patterns is crucial for equitable healthcare delivery.
Purpose of the Study:
- To estimate and predict individual NOAC prescription trends with high spatial resolution across England.
- To identify and quantify inequalities in NOAC prescribing at the Clinical Commissioning Group (CCG) level.
- To develop a statistical modeling approach for analyzing pharmacoepidemiologic data.
Main Methods:
- Utilized a Bayesian spatio-temporal model (extended BYM2) with RStan.
- Employed small area analysis on the "Practice Level Prescribing in England" dataset (2014-2019).
- Adjusted for CCG-level covariates including demographics and deprivation indices, using WHO's DDD methodology.
Main Results:
- Quantified spatial and temporal variations in NOAC prescriptions across English CCGs.
- Highlighted inequalities in the utilization of NOACs among different geographical areas.
- Established a robust statistical framework for pharmacoepidemiologic analysis.
Conclusions:
- The developed statistical approach effectively links prescription data with socioeconomic factors.
- Findings enable the evaluation of NOAC prescription inequalities.
- The methodology supports the development of geographically targeted public health interventions to improve medication access and equity.
Background:
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.
Methods:
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.
Discussion:
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.
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