Evaluating treatment effectiveness: Complementing RCTs with real-world data
Abstract
PURPOSE: While randomized controlled trials remain the gold standard for assessing treatment efficacy, studies using real-world data (RWD) offer valuable insights into treatment effectiveness across broader, more diverse patient populations. This commentary explores the importance of using fit-for-purpose data and emphasizes the need for rigorous evaluation of RWD quality to support valid and actionable evidence generation. SUMMARY: The utility of RWD-based studies depends heavily on the fitness-for-purpose of the data source, which requires careful assessment of 5 key quality dimensions: relevance, extensiveness, timeliness, coherence, and reliability. Practical examples from coronavirus disease 2019 (COVID-19) comparative effectiveness research are used to illustrate each data quality domain. CONCLUSIONS: As the need for RWD increases, especially for post-COVID-19 pandemic decision-making, ensuring high data quality and appropriate study design is critical. Proper evaluation of RWD sources enhances the credibility of findings and supports their use in meta-analyses, clinical guidelines, and healthcare policy.
Fields of Study & Subjects
Advanced Causal Inference Techniques
Medical Coding and Health Information
Electronic Health Records Systems
Publication details
- Journal / source
- American Journal of Health-System Pharmacy
- Volume
- 83
- Issue
- Supplement_3
- Pages
- S2909–S2914
- Publication date
- 5 February 2026
- Language
- EN