The Institute for Safe Medication Practices sponsors the annual Cheers Awards to recognize both individuals and institutions for their commitment to medication safety. The 2023 awards recognized Susan Donnell Scott PhD for her work focusing on support mechanisms for clinicians involved in medical error.

Patient safety progress is dynamic, consistently producing evidence for application to generate improvements. This report is the fourth in a series funded by the Agency for Healthcare Research and Quality to track a prioritized set of emerging and existing safety approaches to confirm their value and effectiveness. This report will be compiled as new conclusions are formulated. Each review will be posted to the collection as they are completed. The first three Making Healthcare Safer reports, published in 2001, 2013, and 2020, have each served as a consolidated evidence source for clinicians, health system leadership, researchers, and government agencies. Chapter protocols and the results of an examination on patient and family engagement and report cards as a surgical improvement mechanism are now available. 

Failure mode and effect analysis (FMEA) is a proactive method to identify risks at each step in the process. Attendees of this training will learn how and why healthcare FMEA is performed, and apply their learning to case studies.

Patient safety in dermatology has received increasing attention over the past ten years. Part 1 of this series provides examples of patient safety concerns in dermatology (e.g., medication errors, teledermatology) and how key patient safety concepts such as safety culture and root cause analysis can be applied in dermatology settings. Part 2 of this series applies three quality improvement frameworks (LEAN, Six Sigma, and IHI-QI) can be used to improve the quality and safety of dermatology practice.

Diagnostic errors are common in the ambulatory environment. This article discusses five tools to help primary care practices implement diagnostic safety improvement strategies. The authors share overarching considerations to support tool implementation including keeping efforts modest and seeing diagnostic safety beyond the clinical realm.

Obstetric hemorrhage and severe high blood pressure during pregnancy are leading known causes of preventable maternal harms in the United States. The AHRQ Safety Program for Perinatal Care, Phase 2 developed toolkits consisting of case scenarios, slides, and facilitators guides to work in tandem to address these threats to maternal safety. The materials inform training opportunities to improve the safety culture of labor and delivery units and decrease maternal and neonatal adverse events that result from poor communication and system failures.

As artificial intelligence (AI) and machine learning (ML) become established in health care, it is critical for clinicians and patients to effectively collaborate to use AI safely. This Issue Brief adds to a series of diagnostic-focused reports and presents a framework to guide patients and clinicians on working as team members when using AI and ML to make diagnostic decisions.