The AHRQ PSNet Collection comprises an extensive selection of resources relevant to the patient safety community. These resources come in a variety of formats, including literature, research, tools, and Web sites. Resources are identified using the National Library of Medicine’s Medline database, various news and content aggregators, and the expertise of the AHRQ PSNet editorial and technical teams.
This review expands upon previous work evaluating implementation strategies for high-reliability organizations. Review findings indicate that health care system adoption of high-reliability principles is associated with improved outcomes, but the level of evidence is low. Future research should include concurrent control groups to minimize bias and focus on whether certain high-reliability frameworks, metrics, or intervention components lead to greater improvements.
Choudhury A, Asan O. JMIR Med Inform. 2020;8:e18599.
This systematic review explored how artificial intelligence (AI) based on machine learning algorithms and natural language processing is used to address and report patient safety outcomes. The review suggests that AI-enabled decision support systems can improve error detection, patient stratification, and drug management, but that additional evidence is needed to understand how well AI can predict safety outcomes.
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