This article is Part 2 of a four-part series examining healthcare AI implementation. The piece addresses how health systems can identify and implement AI solutions that deliver genuine clinical value.
The Problem with Current Procurement
The current AI procurement model forces health systems to commit to vendors before validating performance. This creates unnecessary risk and leads to failed implementations.
Vega Health proposes an alternative: accessing curated, validated models from leading institutions like Duke Health.
Three Core Criteria for Marketplace Models
The company requires models to demonstrate:
Real-world clinical implementation with results: No theoretical models—only solutions that have been deployed and measured in actual healthcare settings
Peer-reviewed publication validating performance: Academic rigor ensures claims are backed by evidence
Completion of standardized Model Label Fact Sheets: Transparency about how models work, their limitations, and their intended use cases
Beyond Model Distribution
Rather than simply distributing models, Vega Health configures complete solutions including clinical workflows, user interfaces, communication protocols, and monitoring capabilities tailored to individual health system environments.
Strategic Value Proposition
The company emphasizes moving from reactive vendor responses to proactive, evidence-based AI strategy. Health systems can locally validate solutions using their own data before implementation commitments.
Solution selection means little without demonstrated sustained value delivery. Part 3 will focus on implementation and monitoring.
