Our Take
The win is real and reproducible: automated screening of 353,602 patient records, 91% EHR-native data capture, and actual diversity gains prove that the bottleneck in community oncology trials is operational friction, not patient access.
Why it matters
Post-marketing oncology studies run slower and costlier at community centers than academic hospitals, leaving patients undertreated and underrepresented in evidence. This pilot shows the gap is closable with off-the-shelf integration and centralized ops, not new science.
Do this week
Clinical operations teams: audit your post-marketing enrollment timelines against the 11-month baseline in this study before Q3 2026 so you can cost out EHR-to-EDC automation for your next protocol.
Automated patient screening compressed oncology trial enrollment to 11 months
Paradigm Health (which acquired Flatiron Health's Clinical Research division in December 2025) ran a pilot post-marketing study for daratumumab across four independent US community oncology centers from April 2024 to March 2025. The study used an EHR-integrated electronic data capture platform to automate patient identification, data mapping, and workflow coordination.
The platform screened 353,602 individuals through a combination of human review and machine-assisted matching. It identified 287 as eligible, with a target enrollment of 70 participants. The pilot enrolled beyond target and did so 6.5 times faster than traditional post-marketing oncology studies (company-reported). Enrollment costs ran 20-30% lower than baseline (company-reported).
Ninety-one percent of study data was captured directly from EHR systems, eliminating manual transcription for the majority of records. Black or Hispanic participants comprised 30.5% of enrollment, more than double the 15% diversity target and substantially above representation in typical myeloma trials (per ASCO data cited in the source).
The platform bundled three operational changes: (1) centralized EHR-to-EDC data transfer via Flatiron's Clinical Pipe connector; (2) protocol design focused on critical-to-quality data fields only, reducing query and cleaning burden; and (3) centralized operations including contracting, feasibility assessment, and automated vendor payments.
Community oncology centers lag in trial access because of friction, not scarcity
Post-marketing approval studies remain deprioritized at community oncology centers relative to academic medical centers. Community sites face resource and budget constraints that make traditional trial operations untenable. Patients treated at community facilities are underrepresented in oncology evidence, narrowing therapeutic options and delaying understanding of post-approval safety and efficacy.
This pilot isolates the real constraint: operational overhead, not lack of eligible patients. Screening 353,602 records to find 287 eligible candidates shows supply exists. The 6.5x speed gain and cost reduction came not from drug discovery or statistical innovation, but from automating the clerical and coordination work that consumes community site resources.
The diversity outcome is material. Myeloma disproportionately affects Black and Hispanic populations, yet these groups remain underrepresented in trial populations. Automated screening reduced unconscious bias in patient identification and centralized operations removed the burden that typically excludes smaller sites from diverse communities.
Paradigm Health is now scaling the model: a 1,350-patient biospecimen collection study is underway across 40+ sites. The FDA is also exploring new methods for high-quality data capture in regulatory submissions, signaling openness to pragmatic trial designs supported by automated data systems.
Verify your EHR-to-EDC integration roadmap against this baseline
If your team owns post-marketing trial operations, pull the 11-month enrollment timeline and 20-30% cost reduction from this pilot as a benchmark for your next protocol negotiation. The study used existing COTS infrastructure (Flatiron's connector) and pragmatic protocol design; neither is proprietary.
Audit which patient screening and data mapping steps in your current workflow are still manual. EHR integration collapses the recruiting timeline only if protocol design prioritizes critical-to-quality fields and centralizes site operations. Protocol bloat and decentralized coordination kill the efficiency gain.
If diversity targets matter for your trial, integrate automated screening before site activation. The 30.5% achievement in this pilot came from algorithm-assisted patient identification, not recruitment messaging alone.