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The PSNet Collection: All Content

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.

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Displaying 1 - 3 of 3 Results
Bates DW, Levine DM, Syrowatka A, et al. NPJ Digit Med. 2021;4:54.
Artificial Intelligence (AI) is used across healthcare settings to address a variety of patient safety targets. This scoping review evaluated the potential of AI to improve patient safety across eight domains including adverse drug events, decompensation, and diagnostic errors. Both traditional (e.g. EHR) and novel (e.g. wearables) data sources can be used to develop models and interventions to improve patient safety.

Holmes A, Long A, Wyant B, et al. Rockville, MD: Agency for Healthcare Research and Quality; March 2020. AHRQ Publication No. 20-0029-EF.

This newly issued follow up to the seminal AHRQ Making Health Care Safer report (first published in 2001 and updated in 2013 critically examines the evidence supporting 47 separate patient safety practices chosen for the high-impact harms they address. It includes diagnostic errors, failure to rescue, sepsis, infections due to multi-drug resistant organisms, adverse drug events and nursing-sensitive conditions. The report discusses the evidence on cross-cutting safety practices, including safety culture, teamwork and team training, clinical decision support, patient and family engagement, cultural competency, staff education and training, and monitoring, audit and feedback. The report provides recommendations for clinicians and decision-makers on effective patient safety practices.
Jones A, Johnstone M-J. Aust Crit Care. 2017;30:219-223.
This qualitative study combined the narratives of various critical care nurses into four representative scenarios demonstrating failure to recognize clinically deteriorating patients. The authors describe inattentional blindness, a concept in which individuals in high-complexity environments can miss an important event because of competing attentional tasks, as a key factor in these failure-to-rescue events.