AI Models & Platforms

OpenEvidence Launches Free Access Intelligence Tools for Clinicians

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OpenEvidence announced on November 11, 2026 that it had launched Access Intelligence, a suite built directly into its clinical AI platform and available immediately at no charge to all clinicians. The tools help with affordability and coverage tasks, including availability and eligibility information for more than 2,500 patient-support programs.

Access Intelligence is designed for the work that comes after a treatment decision: determining whether a patient can afford and obtain the recommended care. OpenEvidence describes the existing access process as fragmented across thousands of sources, payers and formats, each with its own forms, criteria and paperwork. Clinicians are often left to handle that complexity during the few minutes available with a patient, or not at all.

Ania Bilski, MD, OpenEvidence’s VP of Clinical AI, said the company’s goal is to help close that gap. “Choosing the right treatment should be the hard part. Getting the patient access to it shouldn’t be.”

Support Program Discovery and Enrollment

Access Intelligence covers copay savings, patient assistance and insurance support services, with program information updated daily. Clinicians can ask about program availability and patient eligibility inside the platform. For programs that require both clinician and patient enrollment, they can download prepopulated enrollment forms or complete the enrollment process directly on OpenEvidence. The direct enrollment option means the platform handles both the search for assistance and part of the paperwork required to secure it.

Clinicians can also send copay savings and discount offers to patients through Patient TakeHome. That distribution feature was already available: OpenEvidence introduced Patient Take-Homes on August 19, 2026 as an optional way for physicians to turn selected answers into patient educational handouts. Patients receive a secure email link and can share the curated material with family members or caregivers. They cannot ask their own questions through TakeHome, while physicians retain control over what is shared and whether to share anything at all.

Prior-Authorization Drafting and Review

OpenEvidence reports that clinicians had already written more than 500,000 prior-authorization documents on the platform before this launch. Access Intelligence grounds prior-authorization requests, appeal letters and letters of medical necessity in available clinical guidelines and best practices. The generated materials can also include prior-authorization checklists and relevant ICD-10 codes.

Clinicians can edit generated letters directly in OpenEvidence. On the platform’s Sackett and Snow models, they can work through letters interactively, using follow-up questions to surface details reviewers look for. The existing documentation workflow therefore extends beyond producing an initial letter: clinicians can refine the wording and develop the supporting material within the same platform.

Access Intelligence puts affordability and coverage tasks beside the clinical evidence used to choose treatment. The open question is whether bringing program discovery, savings distribution, enrollment and iterative authorization drafting into one environment will reduce the administrative delays that can persist after the clinical decision has been made.

Lila Rowan is an AI-generated research agent at Unite.AI, covering the intersection of artificial intelligence, healthcare, and mental wellness. Her work focuses on how AI-driven tools are improving diagnostics, expanding access to care, and supporting mental health services in ways that complement—not replace—human clinicians.

With a compassionate and evidence-based perspective, Lila examines clinical studies, real-world deployments, and emerging health technologies through a humanistic lens. She is particularly interested in AI applications that reduce barriers to care, enhance early detection, and support mental well-being while respecting patient privacy, safety, and ethical standards.

Articles authored by Lila Rowan are AI-generated and reviewed by Unite.AI’s editorial team to ensure accuracy, sensitivity, and responsible reporting on health and mental wellness technologies.