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Board Member and Chief Commercial Officer

Managing Director, Healthcare Capital LLC

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Board Member and Strategic Advisor

American attorney

Democratic Party official

Technology Advisors

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                    Principal Research Scientist                       

Massachusetts Institute of Technology Clinical Research Director, Laboratory of Computational Physiology

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    Co-Director, Master's Program in Health Data Science                                             Biostatistics                                           Harvard T.H. Chan School of Public Health

Enterprise Ready
AI Co-Pilot

Leading the charge in prior authorization innovation

Revolutionizing healthcare with our advanced prior authorization platform.

Industry Standard efficient and precise AI model

Cost Savings

Our proprietary authorization engine reduces costs associated with PA and suggests pre-approved and personalized care pathways that plans may choose to offer members, ensuring both medical appropriateness and cost-effectiveness. This approach not only optimizes healthcare spending but also ensures that members receive timely care.

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Admin Burden

Basys encodes plan policies and EHRs, distilling hundreds of pages of documentation into simple checklists of criteria for coverage eligibility. The algorithm eliminates unnecessary PA requests, collects missing information from providers, and highlights important criteria so that health plan admin save time reviewing requests.

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Accuracy

Trained with data from over 10 million patient medical and claims records from Mayo Clinic and other partners, and drug insights from Eli Lilly & Co., our engine resolves prior auth with 98% accuracy. Basys developed a self-learning mechanism that continually reviews decision accuracy, improving quality of care and decision efficiency.

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Decision Speed

Our engine resolves prior auth queries in seconds, reducing average decision time by 8 days. Basys also assists health plans in providing members and providers with clear and evidence-based explanations for PA decisions by automatically outlining health plan criteria, EHRs, and relevant literature to objectively support determinations.

AI Co-pilot for Healthcare:
Assisting with Prior Authorization and Utilization Management

For Payers

  • Reduced administrative burden

  • Frictionless provider relationships

  • Better cost with clinically appropriate​ guidelines

For Providers

  • Reduced operational burden

  • Automated prior auth

  • Bringing more transparency to the health plan policies

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