Real-Time EHR-to-EDC Technology Slashes Clinical Trial Data-Entry Time at Mount Sinai

Clinical trials have long been haunted by a deceptively simple problem: the data that researchers need already exists inside the hospital’s electronic health record, yet study teams are still required to retype it, field by field, into a separate electronic data capture system. That double entry consumes hours of skilled staff time, invites transcription errors, and slows the pace at which promising therapies can be evaluated. Now, one of the largest cancer research enterprises in the United States reports that it has largely engineered this bottleneck out of its daily operations. The Mount Sinai Tisch Cancer Center in New York has moved its real-time electronic health record-to-electronic data capture technology from an initial pilot into routine use across its entire cancer research program, and the early performance numbers are striking.

The platform, powered by IgniteData’s Archer technology and integrated directly with Mount Sinai’s Epic electronic health record system, automatically transfers structured clinical information from patient charts into the electronic data capture systems used to manage clinical trials. Since its debut at Mount Sinai in 2025, the integration has been activated across all 16 disease groups at the Tisch Cancer Center, spanning everything from breast and lung cancer to myeloid leukemia and multiple myeloma. Perhaps most tellingly, the technology is no longer an optional add-on: it has been incorporated into the standard startup process for new clinical trials, meaning that every study launched at the center now begins with automated data flow built in from day one.

The early results quantify what has long been an aspirational goal for the clinical research informatics community. Approximately 70 percent of the data required on electronic case report forms—the standardized questionnaires used to collect information for clinical studies—is now populated automatically at each patient visit. Average data-entry time per visit has fallen from 5.5 minutes to 2.5 minutes, a reduction of more than 50 percent. In the data evaluated to date, the system has demonstrated 100 percent data accuracy, with a 0 percent re-query rate, meaning that automated entries have not generated the follow-up clarification requests that typically burden study coordinators and data managers.

Those figures matter because of what they replace. In the traditional clinical trial workflow, research teams must manually transfer information from the electronic health record into separate electronic data capture systems, a process that is time-consuming, creates repeated opportunities for transcription errors, and pulls highly trained research staff into repetitive administrative work. Each manual keystroke is a potential discrepancy that must later be identified, queried, and resolved, often weeks after the patient visit. By allowing relevant clinical information to flow securely from Epic into the trial systems, the Archer platform reduces duplicate data entry and makes information available to research teams far more efficiently, compressing a cycle that once stretched over days or weeks into something approaching real time.

Karyn Goodman, MD, MS, Professor and Vice Chair of Clinical Research in the Department of Radiation Oncology and Associate Director of Clinical Research at the Mount Sinai Tisch Cancer Center, framed the shift as a structural change in how the institution conducts research. “This is an important step forward in how we conduct clinical research at Mount Sinai,” she said. “When we can move accurate information directly from the electronic health record into a clinical trial system, our research teams spend less time entering the same information twice and more time focused on caring for patients and advancing research.”

The efficiency argument is only part of the story. Clinical trial data quality has been a persistent pain point across the industry, with sponsors and sites alike devoting enormous resources to reconciling discrepancies between what a hospital chart says and what a trial database contains. IgniteData CEO Zach Taft emphasized that the technology is designed around selectivity as much as speed. “IgniteData is focused not just on moving data but moving the data that matters,” he said. “Our commitment to sites and sponsors is to seamlessly transfer the data required for clinical trials in the required formats. This ensures data is consistent, accurate, and tracible – ultimately fueling more efficient clinical trials.” The distinction is significant: indiscriminate data dumps from an electronic health record can overwhelm a trial database, whereas targeted, format-conformant transfer is what allows downstream monitoring and regulatory review to proceed smoothly.

For the people operating trials on the ground, the change registers in the texture of the working day. Alex Lieberman-Cribbin, Clinical Trials Manager at the Icahn School of Medicine at Mount Sinai, described the practical effect on study teams. “This technology is making a real difference in the day-to-day work of clinical research teams,” he said. “By reducing the amount of time spent on manual data entry, we can focus more of our time on study coordination, patient care, and making sure our clinical trials run as efficiently as possible.” In an era when clinical research faces chronic staffing pressures and intense competition for patient enrollment, redirecting coordinator hours from transcription to patient-facing and scientific work represents a meaningful reallocation of scarce resources.

The Mount Sinai program is also pushing the technology beyond its initial comfort zone. The center is extending the EHR-to-EDC workflow to handle more complex categories of trial data, including real-world medical history, concomitant medications, and efficacy laboratory data—data types that are structurally messier than the discrete fields captured in early deployments. The program has already expanded to support cellular therapies, including CAR-T cell therapy, a class of individually manufactured immunotherapies whose trials generate unusually intricate and time-sensitive data requirements. By embedding the integration into trial startup and broadening its use across disease groups and data types, the Tisch Cancer Center is positioning automated data collection as a default feature of its research operations rather than a special project.

The initiative builds on the Tisch Cancer Center’s designation from the National Cancer Institute as a comprehensive cancer center, a status that reflects broad institutional commitments to research infrastructure, data quality, and patient access to innovative clinical trials. Comprehensive cancer centers are expected to serve as engines of translational research, and the administrative machinery behind their trials increasingly determines how quickly scientific questions can be answered. If a center can cut per-visit data entry by more than half while eliminating re-queries, the cumulative effect across hundreds of concurrent trials and thousands of patient visits is a substantial gain in research throughput—time that can be reinvested in enrolling patients, monitoring safety, and analyzing results.

The broader significance of the Mount Sinai results lies in the demonstration that EHR-to-EDC integration can perform reliably at institutional scale. Pilot projects in this domain have existed for years, but the recurring challenge has been moving from a favorable demonstration to routine, accurate operation across an entire research portfolio with heterogeneous studies, sponsors, and data standards. With the technology now live across 16 disease groups, wired into new trial startup, and extending into complex therapeutic areas such as cellular therapy, Mount Sinai has provided a concrete, quantified template for what routine automated trial data collection looks like in practice. As more academic centers and sponsors confront the mounting administrative burden of clinical research, the message from New York is that the era of retyping the hospital chart into the trial database is, at least at one comprehensive cancer center, coming to an end.

Subject of Research: Real-time electronic health record to electronic data capture integration for clinical trial data management

Article Title: Mount Sinai Tisch Cancer Center cuts clinical trial data-entry time by more than half with real-time EHR-to-EDC technology

Article References: Mount Sinai Tisch Cancer Center cuts clinical trial data-entry time by more than half with real-time EHR-to-EDC technology. (n.d.). Original publication

Image Credits: AI Generated

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Keywords: clinical trials, electronic health records, electronic data capture, Mount Sinai, IgniteData, Archer platform, Epic, cancer research, data automation, CAR-T cell therapy, NCI comprehensive cancer center, health informatics