OptimizeRx Announces Results from use of AI/RWE Solution

Analysis demonstrates effectiveness of OptimizeRx’s real-world evidence solution to identify patients suitable for a specialty therapy within a narrow timeframe

OptimizeRx Corp. (the “Company”) (Nasdaq: OPRX), a leading provider of point-of-care technology solutions helping patients start and stay on therapy announced results from a recent program that used its patent-pending artificial intelligence technique and real-world data to improve time to diagnosis and therapy for a complex disease. The purpose of the customer engagement was to help healthcare providers identify patients suitable for a specialty therapy within a narrow window of treatment eligibility. The results demonstrated a significant increase in patient identification and engagement with providers as well as a meaningful improvement in overall outcomes.

During the program, the Company deployed its proprietary artificial intelligence/real-world evidence (AI/RWE) technology, using predictive analytics methods applied to various real-world datasets to identify qualified patients approaching the eligibility window for treatment on a specialty therapy. The Company then prompted the appropriate treating physicians of these patients to consider and initiate the therapy via the use of electronic health record (EHR)-based communications.

The key benefits of the treatment-specific model include:

  • Earlier Patient Identification (the ability to detect eligible patients right before they become brand-qualified, preventing them from missing the treatment window)
  • Data-Driven Qualification (the access to visibility across multiple patient datasets, including specific care settings and milestones, allowing the predictive model to identify brand-qualified patients in the absence of a single clear eligibility criterion)
  • Physician List Validation (the use of efficient, targeted, focused brand communications to specialists with eligible patients)
  • Point-of-Care Integration (the position directly in the EHR workflow, raising awareness of patient qualification when and where providers are making treatment decisions)

The results of the year-long case study were:

  • 28% increase in patients commencing the therapy per healthcare provider
  • 33% of new patients from the targeted healthcare providers identified by the model

“Timely and precise patient identification is a significant challenge for providers, especially for complex diseases that require specialty treatments,” stated Steve Silvestro, OptimizeRx’s Chief Commercial Officer. “Doctors struggle to get a complete picture of a patient’s health history because of the lack of interoperability between disparate EHR networks where the patient is being seen by other providers. That lack of clarity often leads to misdiagnosis or prolonged delay in identifying disease that ultimately results in life-altering implications for patients.

“I’m excited about the results of this program because it demonstrates how we successfully used our AI/RWE solution to work through the complex challenge physicians had in effectively identifying suitable patients for this therapy,” continued Silvestro. “With our proprietary technology, we were able to collect, sort, and make sense of information to directly identify providers who would likely have a patient suitable for this therapy and notify those providers of those patients in a timely and efficient way. We delivered extraordinary results for our manufacturing partner while reducing the complexity in the care delivery system for healthcare providers and their patients.”

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