Raj M. Ratwani

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.

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.

Jan 2, 2024 | medstarhealth.org | Raj M. Ratwani

Research from the MedStar Health National Center for Human Factors in Healthcare demonstrates machine learning algorithms can identify patterns in patient safety reports,  allowing faster intervention and preventing harmful events. Online banking has turned financial tracking on its head—when was the last time you balanced a checkbook or wrote a check? Our researchers are working toward the same paradigm shift in understanding patient safety reports.