Overview
A healthcare organization aimed to accelerate clinical trial recruitment by improving the accuracy and speed of patient eligibility identification and matching.
The objective was to increase patient recruitment rates, reduce time-to-enrollment, and improve trial success outcomes while enhancing patient experience and selection quality.
Challenge
Clinical trial recruitment was slow, manual, and inefficient:
- Difficulty identifying eligible patients from large, fragmented clinical datasets
- High dependency on manual screening of medical records
- Low recruitment rates due to poor matching accuracy
- Long delays in patient onboarding and enrollment
- Limited visibility into trial-ready patient populations
This resulted in extended trial timelines, increased costs, and suboptimal participant selection.
Solution
An AI-powered clinical trial recruitment and patient matching system was implemented to automate eligibility identification and optimize enrollment:
- Patient Eligibility Matching Engine
Analyzes structured and unstructured clinical data to identify eligible candidates - Clinical Criteria Interpretation Layer
Translates trial protocols into machine-readable eligibility rules - Patient Stratification System
Categorizes patients based on medical history, demographics, and risk profiles - Automated Recruitment Workflow Support
Prioritizes and surfaces high-fit candidates for clinical teams - Real-Time Trial Cohort Optimization
Continuously refines patient pools as new data becomes available - Integration with EHR/EMR Systems
Enables seamless access to patient records for matching and validation
KPIs Impacted
- Patient Recruitment Rate
Increased through faster and more accurate identification of eligible patients - Clinical Trial Success Rate
Improved through better cohort selection and reduced dropout risk - Patient Satisfaction Score
Enhanced through faster enrollment and better trial matching - Time-to-Enrollment
Reduced significantly via automated eligibility screening
Results
- 30–60% increase in patient recruitment rate
- 15–30% improvement in clinical trial success rate
- 10–20% improvement in patient satisfaction scores
- 25–50% reduction in time-to-enrollment
Business Impact
- Faster clinical trial execution and reduced time-to-market for therapies
- Improved quality and relevance of trial participant cohorts
- Reduced manual burden on clinical research teams
- Enhanced efficiency in clinical research operations
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