Advances in eSource Interoperability Between EHR and EDC

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How evidence generated by the latest IgniteData ‘real-setting’ pilot study supports the case for clinical trial transformation.

The ability to re-use eSource—the high-quality, structured data that clinicians have started to capture every day in hospitals’ EHRs—is, in my view, a sure-fire way to make clinical trials much more efficient to run; and moreover, will in the longer term have a transformative effect on the way we do clinical trials.

Indeed, over many years, as a Health Data Science Director at AstraZeneca, I and like-minded others have explored various approaches to trustworthy re-use of patient hospital records for this purpose, convinced that EHR-to-EDC data transfer was a highly achievable aim.

Given the ever-increasing burden of manual data entry on local trial researchers’ time as the number of study data points continue to spiral, data re-use rather than re-entry seems not just a sensible step, but ultimately an essential one too. And today, it is also eminently possible.

EHR2EDC

Between 2018 to 2020, the EHR2EDC Consortium, of which AstraZeneca, Sanofi and Janssen were founder members—along with a group of European hospitals, and The European Institute of Innovation Through Health Data (i-HD) —set out to discover the optimum technology solution for EHR-to-EDC data transfer.

If further impetus were needed, an analysis independently conducted by the Consortium around this time, began to quantify eSource savings; the analysis showed that replacing manual re-keying and verification in a large oncology Phase III trial could result in cost savings of $15,000 per patient and save more than 87,000 researcher hours in a 3.5 million data point study.

Evidence building begins at UCLH

Having conducted a rigorous review of 20 potential solution providers, the Consortium collectively identified IgniteData as a vendor of choice for a landmark pilot EHR-to-EDC data transfer project at University College London Hospitals (UCLH). The pilot would build evidence support to the ability to achieve our aims:

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  • Time and cost savings
  • Improve data quality
  • Transform availability of data
  • Improve HCP experience

Important evidence was generated in late 2021 by from this pilot study, which used UCLH’s non-production EHR and synthetic patient data to mirror live patient visits in one sponsor’s oncology study at UCLH.

IgniteData’s HL7 FHIR solution Archer was embedded within the non-production EHR, enabling the site investigator to easily select and transfer labs and other structured data into this sponsor’s Medidata RAVE system. Findings from the pilot were impressive, even to those like myself who were anticipating great things.

For example, the 15% of forms mapped by Archer for the pilot accounted for 45% of all data required for the oncology study. Furthermore, using Archer over 20 visits freed up an estimated 66.8 hours per patient – a time-savings of 96.5% compared to traditional manual transcription methods.

Following this progress and with consent gained to push real patient data from UCLH’s EHR to the sponsor’s EDC, the IgniteData evidence-building project has seamlessly moved into its final mirroring phase. The pilot will predominantly focus on the most data intensive categories in the study such as local lab, medication, and vital signs.

Clearly, this pilot, which started in November 2022, cannot necessarily replicate a full-blown real-world study challenge; it is therefore prudent to anticipate further refinements to technology and process based on important learnings.

Nonetheless, and from a new perspective now, as I have recently moved from AstraZeneca as a Global EHR service integration lead and am now embarking on a journey as an Executive Health Data Advisor for industry and academia, I look ahead with confidence to the publication of the full results from this pivotal EHR-to-EDC project once the live mirror study phase completes at the end of January 2023.

Read this foundational article on the topic.

Mats Sundgren, PhD, MSc, is an advisor in Health Data Strategy for Industry and Academia.