Washington, DC – June 26, 2024 – Today the Coalition for Health AI (CHAI) released a draft framework for responsible health AI with an invitation for public review and comment. The framework, consisting of an Assurance Standards Guide, provides considerations to ensure standards are met in the deployment of AI in healthcare. This draft framework was created with a consensus-based approach, drawing upon the expertise and knowledge of multiple, diverse stakeholders from across the healthcare ecosystem.
A set of draft companion documents, called The Assurance Reporting Checklists, provides criteria to evaluate standards across the AI lifecycle; from identifying a use case and developing a product to deployment and monitoring.
The principles underlying the design of these documents align with the National Academy of Medicine’s AI Code of Conduct, the White House Blueprint for an AI Bill of Rights, several frameworks from the National Institute of Standards and Technology, as well as the Cybersecurity Framework from the Department of Health and Human Services Administration for Strategic Preparedness & Responses.
“We reached an important milestone today with the open and public release of our draft assurance standards guide and reporting tools,” said Dr. Brian Anderson, CHAI’s chief executive officer. “This step will demonstrate that a consensus-based approach across the health ecosystem can both support innovation in healthcare and build trust that AI can serve all of us.”
Multiple, diverse stakeholders are involved in the selection, development, deployment, and use of AI solutions intended for patient care and related health system processes. This includes clinicians, nurses, AI technology developers, data scientists, bioethicists, and regulators, as well as those impacted by the technologies, such as patients and their caregivers.
The Guide aims to help build consensus among stakeholders from different backgrounds, providing a common language and understanding of the life cycle of health AI solutions, and highlighting best practices when designing, developing and deploying AI within healthcare workflows. This will help ensure effective, useful, safe, secure, fair, and equitable care. CHAI will use the input from the public to finalize the Guide and update it as needed in the future. Ysabel Duron, Founder and Executive Director of the Latina Cancer Institute, is one of more than a hundred participants who have helped, and will continue to, shape the guidelines. “AI could be a powerful tool in overcoming barriers and bridging the gap in healthcare access for Latino patients and medical professionals, but it also could do harm if we are not at the table. We hope that CHAI’s Guide, with collaboration and engagement of diverse and multi-sector patient voices, will provide a safeguard against bias, discrimination and unintended harmful results.”
The Checklists translate the consensus considerations into actionable evaluation criteria, to assist the independent review of health AI solutions throughout their lifecycle to ensure they are effective, valid, secure and minimize bias. The Checklists are to be used by independent reviewers and organizations evaluating AI solutions, as well as individuals involved in the AI lifecycle for reviewing their work. Public reporting of the results of applying the Checklists ensures transparency of the risks and benefits of an AI solution, which will help organizations and their leadership make decisions about the development and deployment of these technologies.
“Shared ways to quantify the usefulness of AI algorithms will help ensure we can realize the full potential of AI for patients and health systems,” said Dr. Nigam H. Shah, a CHAI co-founder and board member; and chief data scientist for Stanford Health Care. “The Guide represents the collective consensus of our 2,500 strong CHAI community including patient advocates, clinicians and technologists.”
The Guide and Checklists address an urgent need for consensus standards and practical guidance to ensure that AI in healthcare benefits all populations, including groups from underserved and under-represented communities. To enable a range of practical uses, the Guide describes six diverse examples to demonstrate variations in considerations and best practices in the real world:
- Predictive EHR Risk Use Case (Pediatric Asthma Exacerbation)
- Imaging Diagnostic Use Case (Mammography)
- Generative AI Use Case (EHR Query and Extraction)
- Claims-Based Outpatient Use Case (Care Management)
- Clinical Ops & Administration Use Case (Prior Authorization with Medical Coding)
- Genomics Use Case (Precision Oncology with Genomic Markers)
In April 2023, CHAI released the “Blueprint for Trustworthy AI Implementation Guidance and Assurance for Healthcare”, the first broad consensus-based effort among subject matter experts from leading academic medical centers, regional health systems patient advocates and a range of healthcare and technology stakeholders in collaboration with federal agencies. The Guide combines principles from the Blueprint with guidance from federal agencies and the Checklists provide actionable steps for applying assurance standards in day-to-day operational processes. The Guide and Checklists were reviewed by CHAI’s editorial board and presented during its May community convening of patient advocates, regional and local health system leaders, technology developers, regulators and industry standard groups and stakeholders at Stanford University.
CHAI will proactively engage stakeholders across the healthcare ecosystem including patient advocates, under-resourced local health systems and start-ups for additional feedback. The public comment period will run for 60 days. To provide feedback, please use this form.
About CHAI
The CHAI (Coalition for Health AI) mission is to be the trusted source of guidelines for Responsible AI in Health that serves all. It aims to ensure high-quality care, foster trust among users, and meet the growing healthcare needs. As a coalition bringing together leaders and experts representing health systems, startups, government and patient advocates, CHAI has established diverse working groups focusing on privacy & security, fairness, transparency, usefulness, and safety of AI algorithms.
Press Contact:
Andrea Heuer
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