Microsoft and 16 health systems debut network for responsible AI

The Trustworthy & Responsible AI Network, or TRAIN, aims to put responsible AI principles into action to enhance the quality, safety and trustworthiness of healthcare AI.
By Bill Siwicki
10:50 AM

Credit: sankai/Getty Images

This week at HIMSS24 saw the debut of the Trustworthy & Responsible AI Network, or TRAIN, a network that aims to operationalize responsible AI principles to improve the quality, safety and trustworthiness of AI in healthcare.

A new consortium of healthcare organizations is behind TRAIN. Members include AdventHealth, Advocate Health, Boston Children's Hospital, Cleveland Clinic, Duke Health, Johns Hopkins Medicine, Mass General Brigham, MedStar Health, Mercy, Mount Sinai Health System, Northwestern Medicine, Providence, Sharp HealthCare, University of Texas Southwestern Medical Center, University of Wisconsin School of Medicine and Public Health, Vanderbilt University Medical Center, and Microsoft as the technology-enabling partner.

The network is collaborating with OCHIN, which serves a national network of community health organizations with expertise, clinical insights and tailored technologies, and TruBridge, a conduit to community healthcare, to help ensure every organization, regardless of resources, has access to TRAIN's benefits.

New AI systems have the potential to transform healthcare by enabling better care outcomes, improving efficiency and productivity, and reducing costs. From helping screen patients, to developing new treatments and drugs, to automating administrative tasks and enhancing public health, AI is creating new possibilities and opportunities for healthcare organizations and practitioners.

As new uses of AI in healthcare continue to unfold and grow, the need for rigorous development and evaluation standards becomes even more important to ensure effective and responsible applications of AI, TRAIN said.

Through collaboration, TRAIN members potentially can help improve the quality and trustworthiness of AI by sharing best practices related to the use of AI in healthcare settings, enabling registration of AI used for clinical care or clinical operations through a secure online portal, providing tools to enable measurement of outcomes associated with the implementation of AI, and facilitating the development of a federated national AI outcomes registry for organizations to share among themselves. The registry will capture real-world outcomes related to efficacy, safety and optimization of AI algorithms.

"Even the best healthcare today still suffers from many challenges that AI-driven solutions can substantially improve," said Dr. Peter J. Embí, professor and chair of the department of biomedical informatics and senior vice president for research and innovation at Vanderbilt University Medical Center.

"However, just as we wouldn't think of treating patients with a new drug or device without ensuring and monitoring their efficacy and safety, we must test and monitor AI-derived models and algorithms before and after they are deployed across diverse healthcare settings and populations, to help minimize and prevent unintended harms," he continued.

"It is imperative that we work together and share tools and capabilities that enable systematic AI evaluation, surveillance and algorithm vigilance for the safe, effective and equitable use of AI in healthcare," he added. "TRAIN is a major step toward that goal."

When it comes to AI's tremendous capabilities, there is no doubt the technology has the potential to transform healthcare, said Dr. David Rhew, global chief medical officer and vice president of healthcare at Microsoft.

"However, the processes for implementing the technology responsibly are just as vital," he concluded. "By working together, TRAIN members aim to establish best practices for operationalizing responsible AI, helping improve patient outcomes and safety while fostering trust in healthcare AI."

Follow Bill's HIT coverage on LinkedIn: Bill Siwicki
Email him: bsiwicki@himss.org
Healthcare IT News is a HIMSS Media publication.

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