Evaluating Real-World Data: Best Practices

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Real-world data (RWD) and the real-world evidence (RWE) generated from it are increasingly being used by biopharma companies for a range of applications. However, the quality of RWD is inconsistent, potentially limiting its utility. In a new Clinical Leader article, RWD experts from Merck lay out best practices when evaluating RWD sources for relevance and quality.

According to , “Academia and processional communities have made many efforts to improve the quality of RWD. Data quality checks and tools were built for finding potential issues at the database level, while quantitative methods have been explored for automation at large scale. Data exchange protocols (HL7, FHIR) and common data models (OHDSI, PCORnet, Sentinel, i2b2) were adopted to improve interoperability. Foundations and guidelines have been published by pioneer research groups, followed by regulators. However, we are still far from having RWD with perfect quality to support all RWE needs. In day-to-day operation, we need to determine if the quality of a RWD product meets requirements for specific diseases, treatments, and outcomes (i.e., “use case”).”

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(Source: Clinical Leader, December 20^th, 2022)