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Cross-National Analysis of Opioid Prescribing Patterns: Enhancements and Insights from the OralOpioids R Package in Canada and the United States
- Source :
- BioMedInformatics, Vol 4, Iss 3, Pp 2107-2116 (2024)
- Publication Year :
- 2024
- Publisher :
- MDPI AG, 2024.
-
Abstract
- Background: The opioid crisis remains a significant public health challenge in North America, highlighted by the substantial need for tools to analyze and understand opioid potency and prescription patterns. Methods: The OralOpioids package automates the retrieval, processing, and analysis of opioid data from Health Canada’s Drug Product Database (DPD) and the U.S. Food and Drug Administration’s (FDA) National Drug Code (NDC) database. It includes functions such as load_Opioid_Table, which integrates country-specific data processing and Morphine Equivalent Dose (MED) calculations, providing a comprehensive dataset for analysis. The package facilitates a comprehensive examination of opioid prescriptions, allowing researchers to identify high-risk opioids and patterns that could inform policy and healthcare practices. Results: The integration of MED calculations with Canadian and U.S. data provides a robust tool for assessing opioid potency and prescribing practices. The OralOpioids R package is an essential tool for public health researchers, enabling a detailed analysis of North American opioid prescriptions. Conclusions: By providing easy access to opioid potency data and supporting cross-national studies, the package plays a critical role in addressing the opioid crisis. It suggests a model for similar tools that could be adapted for global use, enhancing our capacity to manage and mitigate opioid misuse effectively.
Details
- Language :
- English
- ISSN :
- 26737426
- Volume :
- 4
- Issue :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- BioMedInformatics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.684cc14637574295bd8d214325f80bd7
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/biomedinformatics4030112