The Guardian Research Network: A Real-World Data Source for Pharmacoepidemiologic Research and Regulatory Applications.

backgroundThe quality of real-world data (RWD) directly impacts the value of real-world evidence (RWE) generated for regulatory decision-making. Data owners and investigators must be prepared to provide documentation on data quality assessments to regulators when submitting secondary data for regulatory purposes. While robust feasibility is required to justify the relevance of a data source for a specific research question, the reliability of the data, including the chain of custody and data journey prior to reaching the end user, is of equal importance for drawing valid, meaningful conclusions.

aimsRecently, Castellanos et al. constructed a definition of RWD quality by synthesizing definitions across published guidelines to characterize quality attributes of Flatiron Health RWD. In this paper, the transparent reporting of how data quality attributes (as defined by Castellanos et al.) are met in a single RWD source is replicated for the Guardian Research Network (GRN), a database of aggregated electronic health records (EHRs) collected from a geographically representative consortium of regional community health systems with experienced cancer research programs. MATERIALS &

methodsWe first describe GRN, including the data elements collected, timeliness of data availability, representativeness, and data access considerations. We then provide descriptions of how data reliability (accuracy, traceability, timeliness, completeness) and relevance (availability, sufficiency, representativeness) are ensured and assessed in GRN, including illustrative examples of relevant data quality checks.

resultsDescriptions of GRN's data quality processes demonstrate structured approaches to ensuring both reliability and relevance, aligned with published guidelines. Illustrative examples highlight the application of specific quality checks and their outcomes for GRN data. DISCUSSION: These findings illustrate the importance of documenting and communicating data quality attributes for RWD sources intended for regulatory use. Structured, transparent reporting can support more informed feasibility assessments and facilitate regulator confidence in RWE generation.

conclusionContinued development of structured approaches to identifying data fit for regulatory use underscores the need for comprehensive information about putative data sources during feasibility to inform decision making, study design, and elicit transparent conversations with regulators.