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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 - 6 of 6 Results
Curated Libraries
October 10, 2022
Selected PSNet materials for a general safety audience focusing on improvements in the diagnostic process and the strategies that support them to prevent diagnostic errors from harming patients.
Curated Libraries
September 13, 2021
Ensuring maternal safety is a patient safety priority. This library reflects a curated selection of PSNet content focused on improving maternal safety. Included resources explore strategies with the potential to improve maternal care delivery and outcomes, such as high reliability, care standardization,teamwork, unit-based safety initiatives, and...
Allison MK, Marshall SA, Stewart G, et al. J Emerg Med. 2021;61:396-405.
Transgender and gender nonbinary (trans/NB) people can face discriminatory behaviors when accessing health care services. Trans/NB patients were interviewed about their experiences accessing care in emergency departments. Four themes were uncovered: 1) system and structural issues; 2) interactions with clinicians/staff; 3) perceptions of clinician knowledge and education; and 4) impact on future health and healthcare access. Recommendations for improvement were provided at the system and clinician level.
Park Y, Hu J, Singh M, et al. JAMA Netw Open. 2021;4:e213909.
Machine learning uses data and statistical methods to enhance risk prediction models and it has been promoted as a tool to improve healthcare safety. Using Medicaid claims data for a large cohort of White and Black pregnant females, this study evaluated approaches to reduce bias in clinical prediction algorithms for postpartum depression and mental health service utilization. The researchers found that a reweighing method in machine learning models was associated with a greater reduction in bias than excluding race from the prediction models. The authors suggest further examination of potentially biased data informing clinical prediction models and consideration of other methods to mitigate bias.
Snoots LR, Wands BA. AANA J. 2016;84:114-119.
Personal electronic devices such as smartphones are now ubiquitous, and many clinicians use them for both work and personal purposes. Although considered a necessity, these devices can serve as a distraction, which could compromise patient safety. This review found that many certified registered nurse anesthetists and anesthesiologists acknowledge using personal electronic devices in the operating room despite knowledge of the potential risks. Currently, no formal guidelines exist regarding what constitutes inappropriate use of such devices in the operating room. The authors call for further research in order to develop policies to balance the risks and benefits of personal electronic devices. A WebM&M commentary discusses a case where an interruption due to receiving a text message on a smartphone led to a serious medication error.