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

The electronic patient-reported outcome (ePRO) Dataset Structure and Standardization Project is a multistakeholder initiative formed by Critical Path Institute's PRO Consortium and Electronic Clinical Outcome Assessment (eCOA) Consortium to address issues related to ePRO dataset structure and standardization and to provide best practice recommendations for clinical trial sponsors and 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 and ePRO forms, which would be mitigated through the application of CDISC standards for ePRO data capture and transfer. The project was formed to collate and examine the issues arising from the lack of adoption of standardized approaches and this paper details recommendations to address those issues. 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.

Implementing Single Source: the STARBRITE proof-of-concept study.

OBJECTIVE: Inefficiencies in clinical trial data collection cause delays, increase costs, and may reduce clinician participation in medical research. In this proof-of-concept study, we examine the feasibility of using point-of-care data capture for both the medical record and clinical research in the setting of a working clinical trial. We hypothesized that by doing so, we could increase reuse of patient data, eliminate redundant data entry, and minimize disruption to clinic workflow. DESIGN: We developed and used a point-of-care electronic data capture system to record data during patient visits. The standards-based system was used for clinical research and to generate the clinic note for the medical record. The system worked in parallel with data collection procedures already in place for an ongoing multicenter clinical trial. Our system was iteratively designed after analyzing case report forms and clinic notes, and observing clinic workflow patterns and business procedures. Existing data standards from CDISC and HL7 were used for database insertion and clinical document exchange. RESULTS: Our system was successfully integrated into the clinic environment and used in two live test cases without disrupting existing workflow. Analyses performed during system design yielded detailed information on practical issues affecting implementation of systems that automatically extract, store, and reuse healthcare data. CONCLUSION: Although subject to the limitations of a small feasibility study, our study demonstrates that electronic patient data can be reused for prospective multicenter clinical research and patient care, and demonstrates a need for further development of therapeutic area standards that can facilitate researcher use of healthcare data.