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September 9, 2021

Inferential Challenges for Real-world Evidence in the Era of Routinely Collected Health Data: Many Researchers, Many More Hypotheses, a Single Database

Author Affiliations
  • 1Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island
  • 2Center for Gerontology & Healthcare Research and Center for Evidence Synthesis in Health, Brown University School of Public Health, Providence, Rhode Island
  • 3Department of Statistics and Operations Research, Tel-Aviv University, Tel-Aviv, Israel
JAMA Oncol. 2021;7(11):1605-1607. doi:10.1001/jamaoncol.2021.3537

Routinely collected health data (RCHD) from administrative claims, electronic medical records, disease registries, and other sources transform the way in which knowledge about cancer is generated. Created and collected as part of routine oncological practice, these data capture cancer-related care provided to real-world patients in real-world settings. As with other types of real-world data, including data generated by patients through websites and wearable devices, measures of social determinants of health, and environmental exposures, RCHD are increasingly popular among researchers, funders, and policy makers because of the potential to generate actionable evidence. The availability of RCHD at low or no cost for large patient populations with long followed-up periods and almost real-time updates has attracted numerous researchers pursuing a nearly infinite number of research questions using any particular set of RCHD.

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