Health systems deploying AI clinical trial matchmaking typically see 35-50% increases in trial enrollment within the first 12 months, translating to $600K - $1.5M in additional annual trial revenue depending on your sponsor relationships and trial volume. Coordinators reclaim 6-10 hours per week previously spent on manual chart review, enabling reallocation to higher-value enrollment conversations and protocol compliance tasks. Match accuracy improves 20-30% because the system doesn't fatigue; false-positive rates - patients flagged as eligible but ineligible upon review - drop by 15-25%, reducing coordinator wasted effort and improving sponsor confidence in your enrollment data.
Over 12 months post-deployment, ROI compounds as the model learns from your enrollment patterns. Early months show enrollment velocity gains (faster time-to-first-patient, higher conversion rates). By month 6-9, improved match precision reduces coordinator review burden further, enabling one coordinator to manage 40-60% more active trials. By month 12, your institution becomes a preferred enrollment site for sponsors - higher trial volume, faster enrollment, cleaner data - creating a virtuous cycle. Cumulative first-year ROI typically exceeds 250-350% when factoring in enrollment revenue, coordinator productivity gains, and reduced sponsor audit findings.