Right Patient. Right Trial. Real Time.
ConcertAI's Patient Matching uses AI-driven pre-screening algorithms to continuously evaluate eligibility across all patients and accelerate patient screening workflows to minimizing screen failures and accelerate enrollment. With transparent evidence logs and real-time updates, it empowers research teams to take action with confidence. Designed for both sponsors and sites, it streamlines recruitment and expands access to clinical trials.
Key Benefits of ConcertAI's Patient Matching
Speed
Reduce screen failures and accelerate enrollment through AI-powered automated screening.
Efficiency
Minimize manual data review with transparent AI that consolidates eligibility evidence.
Inclusion
Ensure equitable access by identifying diverse populations and underserved patient groups.
Compliance
Maintain data integrity and transparency with full audit trails and evidence logs.
Core Patient Matching Capabilities
Automated Screening & Matching
Every Patient, Every Data Refresh
- Continuously scans patient records against trial criteria
- Applies AI models to prioritize candidates based on eligibility
- Flags potential candidates based on disease progression and clinical changes
- Ensures no patient is overlooked during recruitment
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Transparency & Evidence Consolidation
Clear Data, Confident Decisions
- Transparent AI consolidates patient data for each eligibility criterion
- Provides easy access to supporting evidence for each patient match
- Reduces screen failure rates by ensuring complete data capture
- Operational dashboards tracks screening progress, diversity and site preformance
Real-Time Operational Dashboards
Monitor Recruitment in Real Time
- Real-time updates on patient screening volumes, enrollment status, and query resolution
- Tracks patient diversity metrics to support equity goals
- Provides sponsors with comprehensive trial conduct insights at every stage
- Highlights critical recruitment gaps to maintain study timelines
Use Case Highlights
Automated patient screening
leverages AI to continuously evaluate patient records for study eligibility, minimizing screen failures.
Diversity tracking
ensures that every patient cohort includes representative populations, with SDoH data to support inclusion efforts.
Operational dashboards
provide real-time metrics on patient screening, enrollment status, and diversity to keep studies on track.
Progression monitoring
uses AI models to flag patients whose clinical status changes, allowing timely re-screening for emerging criteria.
