Methodological Challenges in Conducting Large-Scale Real-World Data Analyses on Opioid Use in Musculoskeletal Disorders
Year: 2020
Type: review
Abstract: ➢ As the United States is currently experiencing an epidemic of opioid misuse, overdose deaths, and addiction, the number of published articles on the patterns of opioid use and the safety of opioids has dramatically increased over the past decade. ➢ Most published reports have described observational studies based on large-scale real-world data (RWD) collected in real-world medical settings (i.e., not in clinical trials). Administrative claims databases, electronic medical records, and patient registries are commonly used RWD sources. ➢ Understanding the strengths and limitations of different types of data sources and applying appropriate study design and methods for each study question are essential for ensuring the validity of observational studies. ➢ Studies analyzing the association between opioid exposure following surgery and persistent use are important for understanding the risks and benefits of opioid use in this context. No widely accepted definition of the term persistent use exists, and studies have yielded highly divergent estimates of the frequency of persistent use depending on the definition employed. Careful attention to methods is needed when conducting these studies, and understanding their limitations is important when interpreting the results. ➢ The present report discusses general methodological challenges for large-scale RWD analyses on opioid use among patients with musculoskeletal disorders.
Authors: Seoyoung C. Kim, Brian T. Bateman
Institutions: Brigham and Women's Hospital, Harvard University
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W3015016582