David C. Classen

Oct 28, 2024 | jamanetwork.com | Dean F Sittig |David C. Classen |Andrew A. Gonzalez

Maximizing the Ability of Health IT and AI to Improve Patient Safety Twenty-five years after the landmark patient safety report "To Err is Human" was published, only marginal improvements have been realized.1 However, recent policy efforts have emerged to transform patient safety, including recommendations from the President’s Council of Advisors on Science and Technology, a new structural measure of patient safety from the Centers for Medicare & Medicaid Services (CMS), and bipartisan...

Sep 4, 2024 | jamanetwork.com | Jessica E. Galarraga |Raj M. Ratwani |David C. Classen |Christopher A. Longhurst

Addressing AI Algorithmic Bias in Health Care As artificial intelligence (AI) algorithms become an increasingly integral part of health care, ranging from diagnostic decisions and treatment plans to population health management, it is vital that rigorous processes to mitigate algorithmic bias are established.1,2 Addressing bias is not only about ensuring fair and just opportunities for optimal health outcomes but also about promoting universal safeguards for patient safety.

Aug 12, 2024 | jamanetwork.com | Raj M. Ratwani |David C. Classen |Christopher A. Longhurst

As artificial intelligence (AI) tools become more consistently used in health care, federal agencies, health care facilities, medical societies, and other stakeholders are grappling with how to ensure they do not introduce unintended patient harm.

Apr 3, 2024 | digitalcommons.library.tmc.edu | David C. Classen |Christopher A. Longhurst |Eric Thomas

AbstractThis paper reviews the current state of patient safety and the application of artificial intelligence (AI) techniques to patient safety. This paper defines patient safety broadly, not just inpatient care but across the continuum of care, including diagnostic errors, misdiagnosis, adverse events, injuries, and measurement issues. It outlines the major current uses of AI in patient safety and the relative adoption of these techniques in hospitals and health systems.

Feb 23, 2024 | jamanetwork.com | Raj M. Ratwani |David Bates |David C. Classen

Artificial intelligence (AI), the next health technology disruptor, is upon us and could greatly improve patient safety. Examples include detection and prediction of sepsis, pressure ulcers, postpartum hemorrhage, adverse drug events, and patient decompensation, to name a few.1,2 Yet if not designed, developed, implemented, and used appropriately, AI in clinical settings may contribute to patient harm.