Real-World Evidence

There is no published overview of the range of generative AI applications, methods, performance evaluations, risks, or opportunities in the real-world evidence domain. Real-world evidence is clinical evidence about the usage, risks, and benefits of medical products generated through analysis of real-world data. Real-world data sources include electronic health records, administrative claims, patient registries, direct-to-participant studies, and other routinely collected healthcare datasets. Real-world evidence can inform drug development, regulatory decisions, health technology assessment, clinical decisions, and patient decisions. Generative AI potential uses in real-world evidence include participant recruitment, data extraction from studies, drug safety surveillance analysis, epidemic modelling, and streamlining literature reviews.