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Best Practice Recommendations for Electronic Patient-Reported Outcome (ePRO) Dataset Structure and Standardization to Support Drug Development.

Stacie HudgensScottie KernAlexandra I BarsdorfSally CassellsAlison RoweBellinda L King-KallimanisCheryl CoonGeoff LowSonya Eremenco
Published in: Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research (2023)
The ePRO Dataset Structure and Standardization Project is a multi-stakeholder initiative formed by Critical Path Institute's Patient-Reported Outcome (PRO) Consortium and Electronic Clinical Outcome Assessment (eCOA) Consortium to address issues related to electronic patient-reported outcome (ePRO) dataset structure and standardization and to provide best practice recommendations for clinical trial sponsors and electronic clinical outcome assessment (eCOA) providers. Given the many benefits of utilizing electronic modes to capture PRO data, clinical trials are increasingly using these methods, yet there are challenges to using data generated by eCOA systems. Clinical Data Interchange Standards Consortium (CDISC) standards are used in clinical trials to ensure consistency in data collection, tabulation, and analysis and to facilitate regulatory submission. Currently, ePRO data are not required to follow a standard model and the data models used often vary by eCOA provider and sponsor. This lack of consistency creates risks for programming and analysis and difficulties for analytics functions generating the required analysis and submission datasets. There is a disconnect between data standards used for study data submission and those used for data collection via case report forms (CRFs) and ePRO forms, which would be mitigated through the application of CDISC standards for ePRO data capture and transfer. Recommendations to address issues with ePRO dataset structure and standardization include adopting CDISC standards in the ePRO data platform, timely involvement of key stakeholders, ensuring ePRO controls are implemented, addressing issues of missing data early in development, ensuring quality control and validation of ePRO datasets, and use of read-only datasets.
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