Current State and Near-Term Priorities for AI-Enabled Diagnostic Support Software in Health Care
Artificial intelligence (AI) systems and applications is now poised to disrupt healthcare, with the potential to improve patient outcomes, reduce costs, and enhance work-life balance for healthcare providers through integration with clinical decision support (CDS) software.
AI-enabled diagnostic support software (DxSS)—a subset of CDS software—shows promise to augment clinicians’ intelligence, support their decision-making processes, help them arrive at the correct diagnosis faster, reduce unnecessary testing and treatments otherwise resulting from misdiagnosis, and reduce pain and suffering by starting treatments earlier.
To foster innovation and incentivize adoption of safe and effective AI-enabled CDS software, with a particular focus on DxSS, the Duke-Margolis Center for Health Policy convened experts from the healthcare and artificial intelligence ecosystem to develop an overview of AI-enabled CDS software and the current regulatory and policy environment surrounding it, as well as identify barriers that may be slowing development, adoption, and use of this type of software.
This report is offered as a resource for developers, regulators, clinicians, policy makers, and other stakeholders as they strive to effectively, ethically, and safely incorporate AI as a fundamental component in diagnostic error prevention and other types of CDS.
This white paper is funded by the Gordon and Betty Moore Foundation. Any opinions expressed in this paper are solely those of the authors, and do not represent the views or policies of any other organizations external to Duke-Margolis.
Christina Silcox, PhD
Research Director, Digital Health
Adjunct Assistant Professor
Senior Team Member
Margolis Core Faculty