Open Access<p>Harnessing Real-World Data for Regulatory Use and Applying Innovative Applications</p>
Author(s) -
Kelly H. Zou,
Jim Z. Li,
Joseph Imperato,
Chandrashekhar Potkar,
Nikuj Sethi,
Jon Edwards,
Amrit Ray
Publication year - 2020
Publication title -
journal of multidisciplinary healthcare
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.65
H-Index - 30
ISSN - 1178-2390
DOI - 10.2147/jmdh.s262776
Subject(s) - computer science , data science , business , computational biology , biology
A vast quantity of real-world data (RWD) are available to healthcare researchers. Such data come from diverse sources such as electronic health records, insurance claims and billing activity, product and disease registries, medical devices used in the home, and applications on mobile devices. The analysis of RWD produces real-world evidence (RWE), which is clinical evidence that provides information about usage and potential benefits or risks of a drug. This review defines and explains RWD, and it also details how regulatory authorities are using RWD and RWE. The main challenges in harnessing RWD include collating and analyzing numerous disparate types or categories of available information including both structured (eg, field entries) and unstructured (eg, doctor notes, discharge summaries, social media posts) data. Although the use of artificial intelligence to capture, amalgamate, standardize, and analyze RWD is still evolving, it has the potential to support the increased use of RWE to improve global health and healthcare.