P112: EMR to EDC Solution Improves Efficiencies of Clinical Research Studies

Poster Presenter

Eva Oakkar

Associate Principal, Emerging Methods and Solutions
IQVIA
United States

Objectives

To assess improvements in data quality and reduction in site burden by leveraging a novel methodology to automatically extract and harmonize clinical data from patients’ electronic medical records (EMR) and transfer these data into a study electronic data capture (EDC) system.

Method

For a study in multiple myeloma, this novel solution is tested at 2 sites (out of 29 US study sites), which extracts (with patient consent) relevant data directly from patients’ EMR (demographics, treatments, medications, ECOG and co-morbidities) and harmonizes the data as per study requirements.

Results

To date, 10 patients have been enrolled at these 2 sites. Approximately 10% of data elements in the study EDC were automatically pre-filled leveraging the EMR to EDC solution. A ~20% decrease in data quality queries was observed at the sites that leveraged this novel solution compared to the other sites that manually entered data in the study EDC. Certain records, such as concomitant medications and ECOG assessments were more complete through the automated data transfer. In a qualitative assessment of user experience, sites have acknowledged the value of this novel data collection methodology as it has the potential to reduce the site’s burden to participate in research studies, but sites also provided valuable feedback on how to further improve the EMR to EDC workflow (e.g. harmonize medication data from transactional records to 1 record per medication; allow for clinical validation of certain data, such as medication or treatment dates, prior to transferring data into EDC).

Conclusion

Increasing acceptance by regulators and payers as well as growing adoption of data standards, allow for reliable real-world data to be leveraged in oncology studies. Leveraging EMR data and sophisticated technologies for harmonizing otherwise complex oncology data has the potential to transform the oncology research space by reducing data entry burden, and improving the quality and richness of the data available. The EMR to EDC solution described here will be continuously improved in an iterative manner to incorporate lessons learned from this pilot as well as to expand the site network with the EMR to EDC capability.