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Clinical Research Patient Finder

Recruit eligible, diverse patients faster for clinical trials, reducing bottlenecks and trial failure risk.

Solution by Inovalon
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Overview

The Clinical Research Patient Finder is designed to streamline the recruitment process for clinical trials by enabling faster and more efficient patient enrollment. This software eliminates the chaos of traditional enrollment methods, helping to reduce bottlenecks and the risk of trial failure, thereby accelerating the delivery of life-saving therapies to patients.

By leveraging hospital electronic health records, this AI-powered solution automatically screens patients against study protocols, identifying eligible candidates in near real-time. This capability allows researchers to recruit the right mix of patients without bias, ensuring trials are both accurate and efficient.

Key Benefits

  • End Recruitment Delays: Identify eligible patients instantly, bypassing the slow, manual pre-screening processes.
  • Confident Patient Matching: Recruit a diverse and representative patient cohort without guesswork.
  • No More Spreadsheets: Access real-time reports and connect directly to EHR data to monitor site performance and progress.

The software simplifies enrollment by spotting barriers early and finding eligible patients in minutes, not weeks. Automated eligibility pre-screening keeps recruitment moving smoothly.

Additionally, the tool preserves trial accuracy by ensuring all eligible patients are found, preventing duplicate enrollments, and maintaining a diverse trial population. Real-time tracking and reporting capabilities reduce workload and errors by connecting directly to EHR data, allowing researchers to keep up with site activity efficiently.

Overall, the Clinical Research Patient Finder enhances trial success by improving recruitment speed and accuracy, ultimately leading to better patient health outcomes and reduced costs.

Meta

Category
Clinical Trial Management
Field(s)
Clinical & Trials
Target user(s)
Clinical / Diagnostic Professional
Tag(s)
Clinical Trials ManagementAI