AI/ML Model Development & Bias Mitigation

The contract seeks the development and training of advanced AI and machine learning models to automate prior authorization processes in healthcare, focusing on three core functions: retrieving clinical guidance, generating auto-approval suggestions, and intelligently routing cases to appropriate reviewers. The effort requires robust model design capable of handling complex medical data and clinical workflows to improve efficiency and reduce administrative burdens. A critical component of the project is the rigorous testing and active mitigation of algorithmic bias across key demographic and population segments to ensure equitable outcomes and compliance with fairness standards in healthcare decision-making. The work is to be performed in Portland, Oregon, with a response deadline of May 28, 2026. Classified under NAICS code 541715 for research and development in the physical, engineering, and life sciences, this subcontract is issued by the Oregon Procurement agency. While specific funding or award details are not provided, the emphasis on bias mitigation indicates a strong regulatory and ethical focus, requiring vendors to demonstrate not only technical proficiency but also a commitment to equitable AI deployment in public health systems. All deliverables must align with the stated objectives of enhancing automation while safeguarding against disparate impact on vulnerable populations.