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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 - 20 of 42 Results
Chekmeyan M, Baccei SJ, Garwood ER. J Am Coll Radiol. 2023;Epub Jul 7.
Artificial intelligence (AI) has become a useful tool to support radiologists in diagnostic imaging. In this study, discordant findings between the radiologist and AI (negative by radiologist report, positive by AI report, with unviewed AI decision support system output) triggered an automatic manual review of the diagnostic images. More than 111,000 CT studies were analyzed, with 46 triggering the automatic review; of those, 26 (0.02%) were true positives (i.e., missed diagnosis by radiologist but identified by AI).
Perspective on Safety April 26, 2023

Throughout 2022, AHRQ PSNet has shared research that elucidates the complex nature of misdiagnosis and diagnostic safety. This Year in Review explores recent work in diagnostic safety and ways that greater safety may be promoted using tools developed to improve diagnostic practices.

Throughout 2022, AHRQ PSNet has shared research that elucidates the complex nature of misdiagnosis and diagnostic safety. This Year in Review explores recent work in diagnostic safety and ways that greater safety may be promoted using tools developed to improve diagnostic practices.

Perspective on Safety March 29, 2023

In the past several decades, technological advances have opened new possibilities for improving patient safety. Using technology to digitize healthcare processes has the potential to increase standardization and efficiency of clinical workflows and to reduce errors and cost across all healthcare settings.1 However, if technological approaches are designed or implemented poorly, the burden on clinicians can increase. For example, overburdened clinicians can experience alert fatigue and fail to respond to notifications. This can lead to more medical errors.

In the past several decades, technological advances have opened new possibilities for improving patient safety. Using technology to digitize healthcare processes has the potential to increase standardization and efficiency of clinical workflows and to reduce errors and cost across all healthcare settings.1 However, if technological approaches are designed or implemented poorly, the burden on clinicians can increase. For example, overburdened clinicians can experience alert fatigue and fail to respond to notifications. This can lead to more medical errors.

Curated Libraries
March 8, 2023
Value as an element of patient safety is emerging as an approach to prioritize and evaluate improvement actions. This library highlights resources that explore the business case for cost effective, efficient and impactful efforts to reduce medical errors.
Curated Libraries
January 19, 2023
The Primary-Care Research in Diagnosis Errors (PRIDE) Learning Network was a Boston-based national effort to improve diagnostic safety. Hosted by the State of Massachusetts’ Betsy Lehman Center, it was led by the Harvard Brigham and Women’s Center for Patient Safety Research and Practice with funding from the Gordon and Betty Moore Foundation. ...
Sibbald M, Abdulla B, Keuhl A, et al. JMIR Hum Factors. 2022;9:e39234.
Electronic differential diagnostic support (EDS) are decision aids that suggest one or more differential diagnoses based on clinical data entered by the clinician. The generated list may prompt the clinician to consider additional diagnoses. This study simulated the use of one EDS, Isabel, in the emergency department to identify barriers and supports to its effectiveness. Four themes emerged. Notably, some physicians thought the EDS-generated differentials could reduce bias while others suggested it could introduce bias.
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.
Liberman AL, Cheng NT, Friedman BW, et al. Diagnosis (Berl). 2022;9:225-235.
Missed diagnosis of stroke in emergency medicine settings is an important patient safety problem. In this study, researchers interviewed emergency medicine physicians about their perspectives on diagnostic neurology and use of clinical decision support (CDS) tools. Themes emerged related to challenges in diagnosis, neurological complaints, and challenges in diagnostic decision-making in emergency medicine, more generally. Participating physicians were enthusiastic about the possibility of involving CDS tools to improve diagnosis for non-specific neurological complaints.
Salwei ME, Hoonakker PLT, Carayon P, et al. Hum Factors. 2022;Epub Apr 4.
Clinical decision support (CDS) systems are designed to improve diagnosis. Researchers surveyed emergency department physicians about their evaluation of human factors-based CDS systems to improve diagnosis of pulmonary embolism. Although perceived usability was high, use of the CDS tool in the real clinical environment was low; the authors identified several barriers to use, including lack of workflow integration.
WebM&M Case August 25, 2021

A 31-year-old woman presented to the ED with worsening shortness of breath and was unexpectedly found to have a moderate-sized left pneumothorax, which was treated via a thoracostomy tube. After additional work-up and computed tomography (CT) imaging, she was told that she had some blebs and mild emphysema, but was discharged without any specific follow-up instructions except to see her primary care physician.

Stark N, Kerrissey M, Grade M, et al. West J Emerg Med. 2020;21:1095-1101.
This article describes the development and implementation of a digital tool to centralize and standardize COVID-19-related resources for use in the emergency department (ED). Clinician feedback suggests confirms that the tool has affected their management of COVID-19 patients. The tool was found to be easily adaptable to accommodate rapidly evolving guidance and enable organizational capacity for improvisation and resiliency.  

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.
Carayon P, Hoonakker P, Hundt AS, et al. BMJ Qual Saf. 2020;29:329-340.
This simulation study assessed whether integrating human factors engineering into a clinical decision support system can improve the diagnosis of pulmonary embolism (PE) in the ED. Authors found that this approach can improve the PE diagnostic process by saving time, reducing perceived workload and improving physician satisfaction with the technology.
Rodriguez-Ruiz A, Lång K, Gubern-Merida A, et al. J Natl Cancer Inst. 2019;111:916-922.
Artificial intelligence (AI) may have the capacity to improve diagnosis. Researchers found that an AI system was able to detect breast cancer using mammography with accuracy similar to that of the average of the 101 radiologists whose interpretations were included in the study.
Massalha S, Clarkin O, Thornhill R, et al. Can J Cardiol. 2018;34:827-838.
Decision support tools can help reduce diagnostic uncertainty. Discussing how artificial intelligence can be utilized to inform diagnostic decision making and improve the accuracy of cardiac image interpretation, this review suggests that use of such technology can reduce production pressure and cognitive load for imaging physicians.
Meyer AND, Thompson PJ, Khanna A, et al. J Am Med Inform Assoc. 2018;25:841-847.
Clinical decision support is a widely recommended patient safety strategy. This study examined whether a mobile application created by the Centers for Disease Control and Prevention improved clinician decision-making about anticoagulation test ordering for simulated case vignettes. Each participating physician completed a series of vignettes; half used the application and half did not. When using the application, physicians demonstrated greater diagnostic accuracy and confidence, and they needed less time to complete each vignette. The authors suggest that mobile applications may be useful for providing decision support.
Auerbach AD, Neinstein A, Khanna R. Ann Intern Med. 2018;168:733-734.
Digital tools have the potential to improve diagnosis, patient self-care, and patient–clinician communication. This commentary argues that digital tools that alter diagnosis or treatment require examination to ensure safety. The authors provide recommendations such as involving experts in evaluating the tools, engaging information technologists, and continuous local review and assessment to identify and address risks associated with use of such tools in practice.
Liberman AL, Newman-Toker DE. BMJ Qual Saf. 2018;27:557-566.
Patient safety measurement remains challenging. This article describes a framework to address gaps in measuring diagnostic error. The authors propose utilizing big data to develop diagnostic performance dashboards and benchmarking tools that support proactive learning and improvement strategies.