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.
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.
Stafos A, Stark S, Barbay K, et al. Am J Nurs. 2017;117:26-31.
This study compared nurses' identification of patients at risk for harm to an electronic predictive model and found that nurses more commonly identified psychological or social risks as relevant to harm. The nurses did not identify some patients whom the predictive model deemed high risk in cases where the risk had been incorporated into the plan of care. The authors suggest that nurse perceptions could inform more accurate predictive models, though neither approach was tested against an actual safety outcome.
Jutel A, Lupton D. Diagnosis (Berl). 2015;2:89-96.
This study examined currently available smartphone and software applications (or apps) designed to aid with accurate diagnosis. Although the authors described some of the potential benefits of these apps, they note that their research suggests apps should be used with caution by both clinicians and consumers, due to problems with transparency regarding sources, evidence, and credentials.
Fitzgerald M, Cameron P, Mackenzie C, et al. Arch Surg. 2011;146:218-25.
Accurate initial assessment and resuscitation of trauma patients is critical to ensuring correct treatment and survival, and although standardized algorithms have been developed for initial trauma evaluation, errors are not uncommon. This innovative randomized controlled trial implemented a computerized clinician decision support system (CDSS) to ensure adherence to standardized protocols for trauma resuscitation, and used video capture of trauma resuscitations to assess the effects of the CDSS on patient outcomes. Use of the CDSS resulted in significantly reduced errors, and also reduced morbidity compared to standard treatment. This study demonstrates the utility of a CDSS in a fast-paced, high-acuity environment.
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