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AI Breaksthrough: How Ochsner Health Transformed Clinical Trial Recruitment

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New Orleans, LA — In a major operational leap forward, Ochsner Health has successfully deployed artificial intelligence to solve one of modern medicine’s most persistent bottlenecks: finding and matching eligible patients with life-saving clinical trials.

As the largest non-profit health system in Louisiana and Mississippi—spanning 47 hospitals and over 370 clinics—Ochsner faced a complex challenge: ensuring patients in remote community clinics received equal access to cutting-edge therapies being studied across its sprawling network.

By partnering with AI-native platform Paradigm Health, Ochsner redesigned its clinical research pipeline, surfacing massive efficiency gains and opening treatment doors for thousands of patients.

By the Numbers: The Impact of AI Screening

The implementation of Paradigm Health’s EHR-integrated AI infrastructure yielded immediate, high-impact results across Ochsner’s oncology studies:

  • +41% Increase in Screening Capacity: Research teams can now evaluate thousands of additional health system patients without adding administrative staff.
  • 3.6x Expansion in Future-Eligible Tracking: Long-term candidate tracking increased nearly fourfold, keeping prospective participants visible as their care journeys evolve.
  • 75% Reduction in Manual Workload: Clinical research coordinators (CRCs) cut repetitive chart-review tasks by three-quarters, refocusing their expertise on candidate verification and direct patient care.

The Barrier: Bridging the Gap in Community Care

Historically, identifying patients for clinical research relied on manual chart reviews conducted by coordinators based at primary medical hubs. This traditional model inherently created geographic and temporal blind spots.

“A patient who appeared to be a good candidate might receive care in a community clinic or regional facility rather than at the location where a study team was based,” explains Dr. Joseph Biggio, Vice Chief Scientific Officer at Ochsner Health. “That meant a research opportunity could be missed simply because the right information did not reach the right team at the right time.”

Furthermore, patient eligibility is rarely static. A candidate who is ineligible today due to current treatment lines may become eligible months later following a specific lab result, diagnostic scan, or disease progression. Manually tracking these dynamic criteria across thousands of patients longitudinally proved virtually impossible without overburdening research staff.

How it Works: Smart AI Meets Human Oversight

Paradigm Health’s platform bridges this gap by continuously evaluating Ochsner’s entire patient population against active oncology trial protocols.

[ Entire Patient EHR Population ]
               │
               ▼
   [ AI Algorithm Screening ]  ◄── (Automated 75% chart-review burden reduction)
               │
               ▼
[ Pre-Screened Candidate List ]
               │
               ▼
 [ Clinical Research Coordinator ] ◄── (Human verification & professional judgment)
               │
               ▼
[ Physician Care Team Contact ] ──► [ Patient Trial Invitation ]
  1. Broad Population Scanning: The algorithm continuously monitors patient health records across all regional facilities, analyzing unstructured text, lab values, and diagnostic history.
  2. Prioritized Action Lists: Rather than reviewing raw charts, coordinators receive prioritized candidate summaries detailing the supporting clinical evidence.
  3. Longitudinal Re-Assessment: When a patient finishes a line of treatment or receives new lab work, the AI automatically reassesses their eligibility, ensuring candidate opportunities are identified at the exact moment they become relevant.
  4. Human-in-the-Loop Safeguards: Research coordinators and treating clinicians maintain full authority over eligibility confirmation, patient outreach, and consent.

What’s Next for Ochsner’s AI Roadmap?

Following the success in oncology screening, Ochsner is actively planning to expand the AI integration across other trial operations.

Key focus areas for future development include:

  • Feasibility Analysis: Utilizing health system data to predict which incoming trials are best suited to Ochsner’s unique demographic needs.
  • Automated Data Capture: Assisting coordinators with continuous real-world data collection throughout active trials.
  • Expanding Therapeutic Areas: Scaling the technology from oncology into other key specialties across the health system.

By putting advanced data infrastructure to work, Ochsner Health is demonstrating how AI can turn complex data networks into expanded clinical access—giving patients across the Gulf South access to tomorrow’s medicine today.

Source: https://www.healthcareitnews.com/news/ochsner-uses-ai-widen-clinical-trial-screening

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