Current State and Near-Term Priorities for AI-Enabled Diagnostic Support Software in Health Care

News Update

Current State and Near-Term Priorities for AI-Enabled Diagnostic Support Software in Health Care

Date

January 23, 2019
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 diagnostic support software (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. Download White Paper: Current State and Near-Term Priorities for AI-Enabled Diagnostic Support Software in Health Care

This white paper is funded by the Gordon and Betty Moore Foundation through Grant GBMF7277 to the Duke-Margolis Center of Health Policy. 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.

Download White Paper:

Current State and Near-Term Priorities for AI-Enabled Diagnostic Support Software in Health Care

 

Project Team

Christina E. Silcox

Managing Associate, Duke-Margolis Center for Health Policy

 

Isha Sharma

Senior Research Assistant, Duke-Margolis Center for Health Policy

 

M. Bennett Wright

Margolis Scholar, Duke Law School

 

 

Working Group*

Kathleen Blake

Vice President, Healthcare Quality,

American Medical Association

 

Richard Frank

Chief Medical Officer,

Siemens Healthineers

 

James Hickman

Software Developer, Machine Learning,

Epic

 

Erich Huang

Co-Director,

Duke Forge

 

Kamal Jethwani

Senior Director,

Partners Connected Health Innovation

 

Shantanu Nundy

Professorial Lecturer,

George Washington University 

 

W. Nicholson Price

Assistant Professor of Law,

University of Michigan Law School

 

Arti Rai

Elvin R. Latty Professor and Co-Director,

The Center for Innovation Policy,

Duke Law

 

Cynthia Rudin

Associate Professor, Computer Science, Electrical and Computer Engineering,

Duke University

 

Sylvia Trujillo

Senior Washington Counsel,

American Medical Association

 

Daniel Yang

Program Fellow,

Gordon and Betty Moore Foundation

 

* Affiliations on 1/23/2019