Multidimensional Evidence Generation and FDA Regulatory Decision Making – Defining and Using “Real-World” Data

JAMA
August 22/29, 2017, Vol 318, No. 8, Pages 677-764
http://jama.jamanetwork.com/issue.aspx

Viewpoint
August 22/29, 2017
Multidimensional Evidence Generation and FDA Regulatory Decision Making – Defining and Using “Real-World” Data
Jonathan P. Jarow, MD1; Lisa LaVange, PhD1; Janet Woodcock, MD1
JAMA. 2017;318(8):703-704. doi:10.1001/jama.2017.9991
Initial Text
Evidence linking interventions with health outcomes is the basis for good health care decision making. The widespread use of electronic health records, administrative claims, and social media and the ubiquity of smart devices have created “big data” that heretofore have not been widely utilized. There is substantial enthusiasm for the use of real-world data sources to generate so-called real-world evidence (RWE), but confusion remains about what RWE means. Evidence generation is multidimensional, including data source, study design, and degree of pragmatism. Real-world evidence is defined by the data source and degree of pragmatism independent of study design. Generation of RWE therefore is not limited to observational studies but also includes randomized trials conducted in clinical settings. The US Food and Drug Administration (FDA) currently uses RWE in safety surveillance and development of drugs for rare diseases, but there are other potential applications…