Quick Summary
Experts emphasize the importance of evaluating AI technologies within a governance framework in healthcare. Tools provided by vendors must ensure safety, effectiveness, and ethical standards to achieve optimal patient outcomes.
Key Evaluation Criteria
- Correctness and Transparency: Assessing the accuracy of AI outputs and the clarity of the algorithms used.
- Fairness and Equity: Ensuring that AI systems do not introduce bias and are accessible to all patient demographics.
- Integrated Workflow: Evaluating how well AI tools fit into existing clinical workflows.
- Safety and Privacy: Protecting patient data and ensuring that AI systems do not compromise patient safety.
Informed Decision-Making
By identifying these risk areas, healthcare systems can make better-informed decisions regarding the adoption of AI tools. This allows technology deployment teams to create appropriate risk mitigation strategies tailored to specific tools and workflows.
Establishing Governance Frameworks
Glenn Wasson, the analytics administrator at UVA Health, highlights that a strong governance framework is essential for healthcare organizations to leverage commercial AI systems effectively while minimizing risks and maintaining public trust. Wasson will discuss these topics in an upcoming HIMSS25 educational session titled “Dear AI Vendors: This Is What We Need.”
Insights from Glenn Wasson
Wasson oversees data operations, analytics, data science, and visualization at UVA Health, focusing on predictive care and population risk modeling. In a recent interview, he shared insights on the evolving role of AI in healthcare.
Understanding AI’s Impact
Wasson noted that AI is becoming integral to various healthcare functions, from diagnosis and treatment planning to billing and resource management. However, it also introduces unique risks that organizations must understand to govern AI effectively.
Focus of HIMSS25 Session
The HIMSS25 session will explore various applications of AI in healthcare, including:
- Diagnosis prediction and treatment selection
- Personalized medicine
- Staff scheduling and resource allocation
- Remote monitoring and billing improvements
Wasson aims to foster a dialogue between providers and vendors to enhance transparency around data, algorithms, and workflows, ultimately building confidence in AI tools.
Key Takeaways for Attendees
Participants will gain insights into the novel aspects of AI evaluation that differ from traditional technology assessments. The session will provide a framework for evaluating AI systems through a structured dialogue between providers and vendors, focusing on identifying risks and mitigation strategies.
Event Details
Wasson’s session is scheduled for Tuesday, March 4, from 10:15-11:15 a.m. at HIMSS25 in Las Vegas.
