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# Randomized Clinical Trial Alternatives Explored
- URL: https://www.fdaweb.com/randomized-clinical-trial-alternatives-explored/
- Published: 2017-08-03T12:00:00.000Z
- Updated: 2026-09-14T22:38:46.000Z
- Author: David McFarland
- Tags: Drugs, #legacy-id-D5139302

Former CDC director **Thomas Frieden** says that while randomized clinical trials have been considered the “gold standard” of medical research, they can have significant limitations, and other means of collecting and analyzing data can be better in some situations. Writing in *The New England Journal of Medicine*, Frieden [says](http://www.nejm.org/doi/full/10.1056/NEJMra1614394?rss=searchAndBrowse&&ref=fdaweb.com) there is no single, best approach to the study of health interventions, as clinical and public health decisions are almost always made with imperfect data.

“Promoting transparency in study methods, ensuring standardized data collection for key outcomes, and using new approaches to improve data synthesis are critical steps in the interpretation of findings and in the identification of data for action, and it must be recognized that conclusions may change over time,” Frieden writes. “There will always be an argument for more research and for better data, but waiting for more data is often an implicit decision not to act or to act on the basis of past practice rather than best available evidence. The goal must be actionable data — data that are sufficient for clinical and public health action that have been derived openly and objectively and that enable us to say, ‘Here’s what we recommend and why.’”

The article outlines some of the limitations of randomized clinical trials and identifies some other potential data sources, including observational studies and analysis of aggregate clinical or epidemiologic data. “No study design is flawless, and conflicting findings can emerge from all types of studies,” Frieden writes. He then discusses several examples showing the importance of recognizing the strengths and limitations in all data sources and finding ways to obtain the most useful data for health decision making.