The Impact of Big Data Research on Practice, Policy, and Cancer Care
Plain-language summary
This review examines how aggregating and analyzing large data sources can inform cancer clinical practice and policy, focusing on three types: pooled clinical trial data, administrative and insurance claims data, and electronic health record data. It weighs the benefits of each source against their inherent limitations and offers next steps for researchers, clinicians, and policymakers. The authors suggest that combining these data sources, and eventually applying machine learning, could improve knowledge and patient outcomes.
Read the full paper (DOI: 10.1200/EDBK_238057).
This is a plain-language summary written for discoverability; the authoritative version is the published paper. Part of Travis Osterman's peer-reviewed publications.