Bending the patient safety curve: how much can AI help?

Abstract

This 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. It also outlines some of the limitations of these AI systems and the challenges with evaluation of these systems. Finally, it outlines the importance of developing a proactive agenda for AI in healthcare that includes marked increased funding of research and evaluation in this area.

The World Federation of Chiropractic Global Patient Safety Task Force: a call to action

“…Chiropractic needs to collect, analyze, and publish highquality, transparent safety data to function as a learning profession. Electronic systems and modern computational methods can support real-time risk management for anticipative and proactive learning and rapid adaptation, rather than reactive management, of patient safety events [29][30][31]. Ensuring that resource-challenged communities are meaningfully engaged in development is critical to maximize the adoption of a global network of health information systems.…”

How can artificial intelligence decrease cognitive and work burden for front line practitioners?

“…Recently, the ONC has published new detailed guidance on AI and decision support interventions to improve transparency, promote trustworthiness, and incentivize the development and wider use of fair, appropriate, valid, effective, and safe decision support for patients. 1 However, minimal AI development or deployment has been focused on its impact on workload or cognitive burden for frontline workers, 2 , 3 an issue that has become a primary concern due to severe staffing shortages among all types of healthcare workers. This article reviews critical issues for the use of AI to reduce cognitive and work burden for frontline healthcare workers.…”

Patient Safety and Artificial Intelligence in Clinical Care

“…picked up 7% of 2552 patients with sepsis, resulting in delayed antibiotic administration and failure to identify 1709 patients with sepsis that the hospital identified through other means. 3 To realize the potential benefits of AI and reduce risk, patient safety safeguards must be developed and put in place. 4 Historically, health care has been slow to respond to patient safety challenges presented by new technologies.…”

“…It has taken almost a decade to begin to address these issues, and serious safety challenges persist. 6 President Biden's October 30, 2023, executive order calls for the Secretary of Health and Human Services to establish an AI safety program within 365 days that (1) establishes a framework for approaches to identify clinical errors resulting from AI and creates specifications for a central tracking repository, (2) analyzes data and generates guidelines for improvement, and (3) disseminates these guidelines to health care organizations (eg, hospitals, clinics, and other organizations providing patient care) and other stakeholders. 7 The executive order lays the foundation for the development of broader patient safety safeguards to protect against patient safety risks that may emerge from the use of AI in clinical settings.…”

“…Yet if not designed, developed, implemented, and used appropriately, AI in clinical settings may contribute to patient harm. For example, a widely used AI system intended to detect patients with sepsis only picked up 7% of 2552 patients with sepsis, resulting in delayed antibiotic administration and failure to identify 1709 patients with sepsis that the hospital identified through other means …”