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Evidence from a Phase III cancer trial points to notable advances in data-transfer tech.
In 2021, University College London Hospitals NHS Foundation Trust (UCLH), IgniteData, and AstraZeneca embarked on a ground-breaking collaboration to evaluate how electronic health record (EHR)-to-electronic data capture (EDC) data-transfer technology would perform in a real clinical trial setting versus traditional data transcription methods. To ensure a true comparison, the EHR-to-EDC pilot would be designed as a live mirror study and use real patient data; it would run in parallel with a live AstraZeneca-sponsored Phase III oncology trial. Furthermore, clear evaluation criteria would be defined in advance, and the results would be benchmarked against the data transcription methods used in the real study.
First off, a rigorous proof-of-concept pilot would stress-test the maturity of IgniteData’s EHR-to-EDC data mapping capabilities. The solution’s connection, authentication, and data transfer abilities would also be assessed: And only on successful completion, would the greenlight be given to the launch of a fully-fledged live mirror pilot.
So how would EHR-to-EDC perform when shadowing a live AstraZeneca-sponsored oncology trial at UCLH? Here, we examine the aims behind this three-way collaboration and consider what the latest evidence from this “pilot within a live trial” reveals.
This pivotal collaboration was born of the fact that the traditional approach to collecting clinical trial data has long been growing increasingly complex. Over 70% of data currently used in clinical trials is duplicated between research systems and hospital EHRs, and around 20% of the total costs of a study is typically allocated to duplicating and verifying data.
There are, of course, additional drivers for change. Not least, the widely reported health industry data explosion. The healthcare industry generates around 30% of the world’s data1 and is showing no sign of slowing down. Clinical trials are no exception to this trend. Recent studies2 have shown that a Phase III oncology trial typically generates an average of 3.6 million data points. That is three times the data collected by late-stage trials 10 years ago
In such circumstances, replacing the laborious manual transcription of data with technology that enables researchers to re-use the regulatory-grade data already in hospitals’ EHRs offers a compelling way forward.
Attempts to overcome the clinical trial data challenge outlined above were for a long time stalled by the interoperability of healthcare systems. Today, the prevalence of EHR systems that use HL7 Fast Health Interoperability Resources (FHIR) standards and incorporate a Substitutable Medical Applications and Reusable Technologies (SMART) on FHIR application programming interface (API), means that the possibility of electronically transferring patient data to a study database instead of using manual methods has become a reality.
Yet, despite these important technology advances, there remained a lack of hard evidence supporting the efficacy of data-transfer technology in a real setting. Which brings us back to the purpose of the UCLH, IgniteData, and AstraZeneca collaboration.
Between 2018 to 2020, the EHR2EDC Consortium, of which AstraZeneca, Sanofi, and Janssen were founding members—along with a group of European hospitals, and The European Institute of Innovation Through Health Data (i-HD)—set out to determine the optimum technology solution for transferring data between EHRs and EDC.
Having conducted a rigorous review of 20 potential technology providers, the Consortium collectively identified IgniteData as a top-performing technology provider in the EHR-to-EDC space. Following this achievement, AstraZeneca then selected IgniteData as vendor of choice for a landmark EHR-to-EDC live mirror study project at UCLH.
To recap, the aim of this project, which began in 2022, was to objectively quantify the performance of EHR-to-EDC data transfer in a real-trial setting and measure the success of this approach versus traditional data transcription methods. To achieve these goals, and with the site and sponsor selected—UCLH and AstraZeneca—it was agreed that the pilot would specifically evaluate critical factors such as data availability in EHR, data quality and accuracy, data transfer to EDC, perceived healthcare provider (HCP) experience, site burden, and time savings.
The evaluation criteria for the project were defined as per the table below.
In the first phase of the project, IgniteData’s cloud-based technology, Archer, was embedded within the non-production EHR at UCLH, thus ensuring that there was no risk to the real randomized controlled trials (RCTs) at these sites, nor to live patient data in the EHR. It was also established that the site’s staff could easily select and transfer structured data into AstraZeneca’s Medidata Rave system.
Archer is a virtual research assistant that enables the transfer if clinically-validated data from hospitals’ EHR to sponsors’ research systems. It uses HL7 FHIR through SMART on FHIR APIs to create a data conduit that integrates with many EHRs and EDCs.
Archer has a mapping engine, built in consultation with hospitals and sponsors and designed specifically for mapping healthcare data. This streamlines the mapping data task, helping to eliminate errors and duplication of efforts.
Following the successful completion of the non-production pilot, and with consent gained from participants, ethics committees, and regulatory authorities to push real patient data from UCLH’s EHR to AstraZeneca’s EDC, the collaborative evidence-building project was ready to move into the live mirroring phase by the end of 2022.
At this stage of the project, the most data intensive categories in the Phase III oncology study—vital signs, local laboratory results, and concomitant medication—were mapped by Archer. Four patients from an AstraZeneca-sponsored Phase III cancer study were enrolled into a live mirror study; and data from the first five of their visits were electronically transferred from UCLH’s EHR to a copy of the study database. In all, 6,664 data points were transferred from the EHR to the EDC using Archer during this phase.
The live pilot established that IgniteData’s data- transfer technology, Archer, could map 100% of vital signs and labs data, and was able to successfully transfer 100% of mapped data from these domains.
Transferring mapped data using Archer showed time savings compared to manual methods. Savings were achieved even including the time taken to do extra manual lookups to check data accuracy—which would not be needed in a real trial setting. In addition, Archer could significantly reduce source data verification (SDV) and query resolution time in a live study—a factor not considered here.
IgniteData’s mapping analysis found that the 15% of forms mapped by Archer accounted for 45% of all study data. Overall, 96% of the targeted fields for the selected data domains of the case report form (CRF)—vital signs, labs and concomitant medication—were mapped.
Unscheduled visits were not included in the live mirror study, as this capability was still in development at the time of running the pilot: however, they will be included in subsequent pilots, which will significantly increase the amount of data accounted for.
HCP experience was measured using a 7-Lickert scale questionnaire: for user experience and perceived reduction in site burden, the overall score was positive.
As anticipated from the outset, running a live mirror study in a real setting provided insights and highlighted opportunities. Overall, Archer was shown to achieve impressive levels of accuracy, and the data transferred by Archer always matched the data in the EHR, a fact with positive implications for SDV in the future.
Unscheduled visits—a requirement for using Archer in a live RCT—has been incorporated into the next pilot, and this capability was also reaffirmed as an important means of increasing the amount of data that could be transferred with minimal effort.
Conducting the live pilot highlighted several learnings in relation to the end-to-end process of transferring concomitant medication data between hospital and sponsor systems—and has allowed the collaborators to formulate a strategy around solving these complexities going forward.
More broadly, new opportunities were identified, such as optimizing CRF design when using EHR-to-EDC, investigating medical coding of EHR medications, and looking at the feasibility of using EHR-to-EDC in other domains.
These learnings will feed directly into the next pilot, which is already underway. There is certainly more to do, but the collaborators are confident that the steps taken to date constitute a major step forward in establishing EHR-to-EDC as the go-to option for clinical trial data requirements. While sites look forward to benefits such as reduced site burden, sponsors are equally excited about driving data transformation for clinical trials in a collaborative way that cements their status as “sponsors of choice” for sites.
Authors’ note: UCLH uses the Epic comprehensive electronic health record (EHR). This work was supported by UCLH’s in-house EHR team funded by the NIHR UCLH Biomedical Research Centre and Research Data Managers from UCLH’s Cancer Clinical Trials Unit.
Mats Sundgren, PhD, IgniteData strategy advisor and former global, integration lead for electronic health records (EHR) services, AstraZeneca, Wai Keong Wong, PhD, FRCPath, MRCP, formerly the chief research information officer and consultant haematologist, UCLH/NIHR BRC clinical and research informatics unit, Nausheen Saleem, EHR deputy delivery manager for research & innovation, University College London Hospitals NHS Foundation Trust, Sarah Taylor, research manager, cancer clinical trials unit, University College London Hospitals NHS Foundation Trust, Lars Fransson, senior clinical IT nusiness partner, AstraZeneca, Nick Collins, EDC IT product lead, AstraZeneca, David Gustafsson, associate director, project data manager, AstraZeneca, Mikael Forsby, clinical operations program director, AstraZeneca, and Richard Yeatman, chief technical officer, IgniteData