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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 - 8 of 8 Results
Johnson EA, Dudding KM, Carrington JM. Nurs Inq. 2023;Epub Jul 17.
Research on artificial intelligence (AI) in medicine is rapidly increasing including AI in nursing care. In this commentary, the authors describe the challenges of using AI in healthcare and the unique implications for nursing practice and policy. In particular, nurses should be involved in the development and testing of any AI used in the nursing process.
Galatzan BJ, Carrington JM. Res Nurs Health. 2021;44:833-843.
During handoffs, nurses are exposed to a variety of interruptions and distractions which may lead to cognitive overload. Using natural language processing, researchers analyzed ten audio-recorded change of shift handoffs to estimate the cognitive load experienced by nurses. Nurses’ use of concise language has the potential to decrease cognitive overload and improve patient outcomes.
Payne TH, Hines LE, Chan RC, et al. J Am Med Inform Assoc. 2015;22:1243-50.
Clinical decision support alerts can help identify potential drug–drug interactions, but they can also contribute to alert fatigue. This commentary provides recommendations to inform the design of decision support to address drug–drug interactions. The authors suggest that improvement strategies focus on standardizing terminology and visual cues.
Gephart SM, McGrath JM, Effken JA. J Perinat Neonatal Nurs. 2011;25:275-282.
… failure to rescue in the neonatal intensive care unit. … Gephart SM, McGrath JM, Effken JA. Failure to rescue in …
Effken JA, Brewer BB, Patil A, et al. Int J Med Inform. 2005;74:605-13.
The authors describe their experience using a computerized model to understand the impact of organizational, patient unit, and patient characteristics on safety and quality. This study was supported with a grant from the Agency for Healthcare Research and Quality (AHRQ).