Clinical Trial Recruitment is the use of provider and diagnosis data to find investigators, sites, and patient populations for clinical trials — filtering by condition, procedure, and geography. It applies commercial-intelligence techniques to the research enrollment challenge.
Built on claims and diagnosis data, recruitment targeting finds the physicians and sites most likely to enroll patients quickly — critical for trial timelines.
Slow enrollment is one of the leading causes of clinical-trial delays and cost overruns. Data-driven recruitment addresses this by identifying, before a trial starts, which sites and investigators see the relevant patient population — based on real diagnosis and procedure activity rather than reputation alone.
This is especially powerful in rare disease and precision medicine, where eligible patients are scarce and finding the few physicians who treat them can make or break a trial.
Clinical trial recruitment is the process of finding investigators, sites, and patients for a clinical study. Data-driven recruitment uses provider and diagnosis data to identify the physicians and locations most likely to enroll eligible patients quickly.
Filter claims and diagnosis (ICD-10) data to the condition under study, then identify the physicians and sites treating the most relevant patients in target geographies. These high-volume sites are the strongest candidates for trial placement.
For rare diseases, eligible patients are scarce, so finding the few physicians who treat them is critical. Diagnosis and claims data pinpoint those clinicians and sites, dramatically narrowing the search compared to reputation-based site selection.
Both use provider and claims data to find the right clinicians, but trial recruitment seeks investigators and sites with eligible patient populations for research, while physician targeting finds clinicians likely to adopt a commercial product. The data foundation is shared; the goal differs.