Build trust, strengthen governance and demonstrate accountability across the AI lifecycle.
Why It Matters
Artificial intelligence is already transforming health care. URAC’s Health Care AI Accreditation gives organizations a trusted framework to show their AI systems are safe, ethical and patient-centered.
You can demonstrate leadership, earn trust and set the standard for responsible usage of AI in health care.
Choose the path that fits your role:
Report from URAC: Quality, Trust, Safety and Responsibility in AI
In this previously recorded webinar, URAC and members of our Health Care AI Accreditation Committee share how AI is being used in health care including the benefits, risks, safety and quality considerations of using AI in settings such as pharmacies, health plans, telehealth and utilization management.
The end of the webinar includes a short introduction to URAC’s new Health Care AI Accreditation, available to any health care organization.
URAC’s Health Care AI Accreditation helps technology innovators demonstrate that their solutions meet the highest standards for safety, transparency and ethical deployment in health care.
Why It Matters For Developers
- Market Differentiation: Demonstrate to health systems, payers and investors that your AI solution meets independent quality standards.
- Faster Procurement: Reduce buyer hesitation with third-party validation of safety and trustworthiness.
- Regulatory Readiness: Develop frameworks to align with evolving U.S. and international AI governance frameworks.
- Credibility for Partnerships: Gain trust with potential clinical trial partners, strategic collaborators and enterprise customers.
Get Accredited. Build Trust in AI.
Show your commitment to safe, effective AI in health care.
Earn URAC Accreditation.
Position your AI product as the gold standard for safety, equity and compliance in health care.
Building Trust in AI: A Practical Guide for Health Care Leaders
In this previously recorded webinar, URAC and Ellipsis Health demystified the world of AI in health care and shared the tools you need to understand this rapidly evolving field. We walked through essential AI terminology so you can speak confidently about key concepts and technologies.
We then shared real examples of how various organizations are currently using AI to support care delivery, diagnostics and operational efficiency. And, we gave a balanced look at potential risks including bias, data privacy and clinical oversight gaps that organizations must consider when adopting AI.
The webinar ended with a short overview of URAC’s Health Care AI Accreditation, the first-of-its-kind framework that lets health care organizations and developers demonstrate their commitment to safe, ethical and transparent AI usage with a trusted set of standards that promote responsibility and accountability.
Whether you’re exploring AI adoption or strengthening your quality framework, this session will leave you inspired and ready to take the next step.
Health Care AI Accreditation
Artificial intelligence (AI), including machine learning and large language models, is rapidly reshaping health care. These technologies can help clinicians assess risk, inform clinical decision-making and help organizations allocate resources and structure workloads. Increasingly, they influence decisions that affect patient care.
But when AI is used in health care, accountability matters.
Why URAC ?
With 35 years of experience accrediting health care organizations, URAC is uniquely positioned to guide safe AI adoption. Our advisory committee includes experts from leading health systems, tech innovators and regulatory bodies.
What Accreditation Delivers
The Accreditation Process
