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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 403 Results
Bell SK, Bourgeois FC, Dong J, et al. Milbank Q. 2022;Epub Dec 20.
Patients who access their electronic health record (EHR) through a patient portal have identified clinically relevant errors such as allergies, medications, or diagnostic errors. This study focused on patient-identified diagnostic safety blind spots in ambulatory care clinical notes. The largest category of blind spots was diagnostic misalignment. Many patients indicated they reported the errors to the clinicians, suggesting shared notes may increase patient and family engagement in safety.

Newman-Toker DE, Peterson SM, Badihian S, et al. Rockville, MD: Agency for Healthcare Research and Quality; December 2022. AHRQ Publication No. 22(23)-EHC043.

Although diagnostic accuracy in the emergency department (ED) is high, diagnostic errors still occur. This evidence review estimated that 1 in 18 ED patients receive an incorrect diagnosis, which translates to 7.4 million patients misdiagnosed every year (or 5.7% of all ED visits annually). Five conditions were found to be most vulnerable to misdiagnosis: stroke, heart attack, aortic aneurysm/ dissection, spinal cord injury and blood clots. The evidence review identified variation in diagnostic error rates across demographic groups; female sex and non-White race were often associated with increased risk for diagnostic errors. Serious misdiagnosis-related harms were often associated with clinician bedside judgement and other cognitive failures. 
Hailu EM, Maddali SR, Snowden JM, et al. Health Place. 2022;78:102923.
Racial and ethnic health disparities are receiving increased attention, and yet structural racism continues to negatively impact communities of color. This review identified only six papers studying the impact of structural racism on severe maternal morbidity (SMM). Despite heterogeneity in measures and outcomes, the studies all demonstrated a link between structural racism and SMM; additional research is required.
Ahmajärvi K, Isoherranen K, Venermo M. BMJ Open. 2022;12:e062673.
Diagnostic errors continue to be a source of patient harm. This retrospective study identified patient- and organizational-level factors contributing to misdiagnosis of chronic wounds in primary care. Less than half of patients referred from primary care to specialist wound care teams had the correct diagnosis. Notably, 36% of patients who presented to primary care had signs of infection, however 61% received antibiotics, raising concerns of antibiotic overuse.
WebM&M Case December 14, 2022

This case describes a man in his 70s with a history of multiple myeloma and multiple healthcare encounters for diarrhea in the previous five years, which had always been attributed to viral or unknown causes, without any microbiologic or serologic testing. The patient was admitted to the hospital with gastrointestinal symptoms and diagnosed with cholecystitis and gangrenous gallbladder. Two months after his admission for cholecystitis, he was readmitted for severe vomiting and hypotension.

Boxley C, Krevat SA, Sengupta S, et al. J Patient Saf. 2022;18:e1196-e1202.
COVID-19 changed the way care is delivered to hospitalized patients and resulted in new categories and themes in patient safety reporting. This study used machine learning to group of more than 2,000 patient safety event (PSE) reports into eight clinically relevant themes, including testing delays, diagnostic errors, pressure ulcers, and falls.
Malik MA, Motta-Calderon D, Piniella N, et al. Diagnosis (Berl). 2022;9:446-457.
Structured tools are increasingly used to identify diagnostic errors and related harms using electronic health record data. In this study, researchers compared the performance of two validated tools (Safer Dx and the DEER taxonomy) to identify diagnostic errors among patients with preventable or non-preventable deaths. Findings indicate that diagnostic errors and diagnostic process failures contributing to death were higher in preventable deaths (56%) but were also present in non-preventable deaths (17%).
O’Hare AM, Vig EK, Iwashyna TJ, et al. JAMA Netw Open. 2022;5:e2240332.
Long COVID-19 can be challenging to diagnose. Using electronic health record (EHR) data from patients receiving care in the Department of Veterans Affairs, this qualitative study explored the clinical diagnosis and management of long COVID symptoms. Two themes emerged – (1) diagnostic uncertainty about whether symptoms were due to long COVID, particularly given the absence of specific clinical markers and (2) care fragmentation and poor care coordination of post-COVID-19 care processes.
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.
WebM&M Case November 16, 2022

A 61-year-old women with a mechanical aortic valve on chronic warfarin therapy was referred to the emergency department (ED) for urgent computed tomography (CT) imaging of the right leg to rule out an arterial clot. CT imaging revealed two arterial thromboses the right lower extremity and an echocardiogram revealed a thrombus near the prosthetic heart valve. The attending physician ordered discontinuation of warfarin and initiation of a heparin drip.

Kunitomo K, Harada T, Watari T. BMC Emerg Med. 2022;22:148.
Cognitive biases can impede diagnostic decision-making and contribute to diagnostic delays and patient harm. This study explored the types of cognitive biases contributing to diagnostic errors in emergency rooms in Japan. The most common biases reported were overconfidence, confirmation bias, availability bias, and anchoring bias. Findings indicate that most diagnostic errors involved overlooking another disease in the same organ group or related organ (e.g., diagnosing headache rather than stroke).
Wiegand AA, Dukhanin V, Sheikh T, et al. Diagnosis (Berl). 2022;9:458-467.
Previous research has identified gender and racial disparities in the burden of diagnostic errors. In this study, researchers conducted a series of human-centered design workshops with a diverse set of stakeholders who generated a set of design challenges, principles, and solutions for addressing diagnostic disparities, improving healthcare quality, and promoting equity and inclusion of marginalized patients. Participants also identified two prototypes for the solutions – a visit preparation guide to teach patients how to advocate for themselves and a tool for identifying patients who may be at increased risk for experiencing a diagnostic error.

Schiff G. Chapter In: Loscalzo J, Fauci A, Kasper D, et al, eds. Harrison's Principles of Internal Medicine, 21e. New York, NY: McGraw Hill; 2022

The task of performing a safe diagnosis has gone beyond the use of technical skill and knowledge. This book chapter introduces the application of intersecting concepts such as human factors engineering, cognition, information technology, and learning systems to achieve diagnostic improvement.
Kanter MH, Ghobadi A, Lurvey LD, et al. Diagnosis (Berl). 2022;9:430-436.
Diagnostic errors are an emerging area of patient safety research; as such, innovative methods to identify and prevent diagnostic errors are being developed. This commentary describes the development, implementation, and sustainment of a novel method of investigation. The e-Autopsy/e-Biopsy method includes dedicated patient safety staff and volunteer clinical specialists to review events and identify trends. The process is illustrated with three diagnoses: ectopic pregnancy, abdominal aortic aneurysms, and advanced colon cancer.
Michelson KA, McGarghan FLE, Patterson EE, et al. BMJ Qual Saf. 2022;Epub Sep 30.
Adverse events in pediatric emergency departments (ED) are rare, but largely preventable. This study examined characteristics and risk factors of patients with delayed diagnosis (i.e., presented to the ED within one week of a previous visit) and patients without delayed diagnosis of one of 7 serious medical conditions. Patients who were Hispanic or non-Hispanic Black, had public or other insurance, or non-English speaking were associated with delayed diagnosis.

Washington DC: United States Government Accountability Office and National Academy of Medicine;  September 2022. Report no. GAO-22-104629.

Machine learning is a subset of artificial intelligence that has potential to improve diagnosis. This report examines the value of existing machine learning diagnostic technologies and discusses concerns and policy impacts of their use over time. The authors suggest evaluation, data access and collaboration as strategies to enhance policy supporting technology development and safety.
Liu G, Chimowitz H, Isbell LM. Diagnosis (Berl). 2022;9:295-305.
Clinician’s emotions can influence their decision making, particularly with “difficult” patients. This article describes the role affect takes in clinical reasoning, including diagnosis. Strategies to counter the impact of emotional affect, such as emotional intelligence education, are presented.

Rockville, MD: Agency for Healthcare Research and Quality; October 2022. AHRQ Publication no. 22(23)-0047-2-EF.

Delayed, wrong, and missed diagnoses are common challenges for patients, families, and clinicians, yet physicians rarely receive feedback on their actions to enhance diagnostic decision making. This publication provides clinicians with tools to assess and calibrate diagnostic performance in support of individual learning and improvement.
Fleming EA. JAMA. 2022;328:1297-1298.
Honest apology is known to support healing from medical error for clinicians, patients, and families. This essay shares the experience of one physician who missed signs of a heart attack, mislabeling the condition as fatigue, who then apologized for the mistake. The author highlights how openness about the error was crucial in the continuation of the care relationship.