AI-Powered Medical Chart Abstraction & Data Extraction

The contract seeks the development and training of advanced AI and machine learning models designed to extract diagnostic data and clinical information from unstructured medical records, with a specific focus on enabling temporal reasoning and relevance filtering to ensure accurate and context-aware information retrieval. The project aims to enhance the ability of automated systems to interpret complex, longitudinal patient data by identifying relationships between clinical events over time and prioritizing the most pertinent details for healthcare applications. This effort is critical for improving clinical decision support, research data preparation, and administrative efficiency in healthcare settings. The solicitation is classified as a subcontract under NAICS code 511210, related to software publishing, and is managed by the Office of Acquisition and Grants Management within the Department of Health and Human Services. The opportunity was posted on July 22, 2026, with a response deadline of August 20, 2026, and is open to qualified entities capable of delivering scalable, secure, and compliant AI solutions for medical data abstraction. While no specific geographic performance location or set-aside designation is indicated, proposers must demonstrate technical expertise in natural language processing, electronic health record interoperability, and healthcare data standards to meet the functional requirements of the project.