Errors In Radiology Research Articles

It's not about the errors, it's about the learning: How the Royal College of Radiologists has developed a Radiology Events and Learning process in the United Kingdom.

The Royal College of Radiologists (RCR) is based in the United Kingdom but is a global organisation with members and fellows worldwide. In this invited article, the chair of the RCR Radiology Events and Learning (REAL) panel recounts his experience in looking at radiological errors. He starts with his personal work auditing his own mistakes as a junior consultant, describes what he learned in his departmental role in a large teaching hospital running a Radiology Events and Learning Meeting (REALM) and gives an overview of some of the work done over the last two decades by the RCR. This includes publishing national guidelines which set standards for running a REALM, setting up the REAL panel which produces a quarterly newsletter of cases from RCR members, and running an annual conference to share information with local radiology departments around the country. A review of the literature describing the drivers for this work and looking at the parallels with industry lies alongside the practical tips he found useful which he hopes would be helpful to anyone setting up their own departmental errors or discrepancy meeting.

Gender Differences in Diagnostic Radiology Practice: An Observational Study.

To investigate gender differences in diagnostic radiology practice, specifically, the differences in scope of practice, the frequency of consultations to other colleagues, and the error rates. A retrospective observational study was performed including radiologists working for a European teleradiologyprovider between 2013 and 2019. Main outcome measures included the adjusted odds ratio of female gender for reporting cases in more than one subspecialty, the adjusted incidence rate ratio (IRR) of female gender for the count of second opinion requests to other colleagues, and the adjusted IRR of female gender for the count of radiologic errors. Multivariable adjustment was performed for covariates associated with experience, type of cases reported, part- or full-time employment, and reporting speed. A total of 213 radiologists (36% female) were included in the analysis of gender differences in scope of practice. Femalegender was associated with a lower odds of reporting cases in more than one subspecialty with an odds ratio of 0.46 (95%confidence interval, 0.22-0.96). A total of 204 radiologists (36% female) were included in the analysis of gender differences in the count of second opinion requests to colleagues. There was a trend toward an association between female gender and higherodds of requesting a second opinion with an adjusted IRR of 1.6 compared with male gender, but it was not statistically significant (P= .08). A total of 199 radiologists were included (37% female) in the analysis of gender differences in the number ofradiologic errors. Female gender was associated with a decrease in the odds of error with an IRR of 0.8 (95% confidence interval,0.64-0.995). Female radiologists tend to have a narrower scope of practice and make fewer mistakes than their male counterparts, even after detailed adjustment for factors that might explain gender differences in scope of practice and errors.

Impact of diagnostic errors on adverse outcomes: learning from emergency department revisits with repeat CT or MRI

BackgroundTo investigate diagnostic errors and their association with adverse outcomes (AOs) during patient revisits with repeat imaging (RVRIs) in the emergency department (ED).ResultsDiagnostic errors stemming from index imaging studies and AOs within 30 days in 1054 RVRIs (≤ 7 days) from 2005 to 2015 were retrospectively analyzed according to revisit timing (early [≤ 72 h] or late [> 72 h to 7 days] RVRIs). Risk factors for AOs were assessed using multivariable logistic analysis. The AO rate in the diagnostic error group was significantly higher than that in the non-error group (33.3% [77 of 231] vs. 14.8% [122 of 823], p < .001). The AO rate was the highest in early revisits within 72 h if diagnostic errors occurred (36.2%, 54 of 149). The most common diseases associated with diagnostic errors were digestive diseases in the radiologic misdiagnosis category (47.5%, 28 of 59) and neurologic diseases in the delayed radiology reporting time (46.8%, 29 of 62) and clinician error (27.3%, 30 of 110) categories. In the matched set of the AO and non-AO groups, multivariable logistic regression analysis revealed that the following diagnostic errors contributed to AO occurrence: radiologic error (odds ratio [OR] 3.56; p < .001) in total RVRIs, radiologic error (OR 3.70; p = .001) and clinician error (OR 4.82; p = .03) in early RVRIs, and radiologic error (OR 3.36; p = .02) in late RVRIs.ConclusionDiagnostic errors in index imaging studies are strongly associated with high AO rates in RVRIs in the ED.

Error and cognitive bias in diagnostic radiology.

Errors in diagnostic radiology are not infrequent. Patient harm related to these errors is however less common and may be avoided via various preventative mechanisms within the medical system including, but not limited to, multidisciplinary meetings, second opinions, subspecialty expertise and clinician experience. Failure at a number of points in the system is often required to result in patient harm. Radiologists, and in particular departmental leaders, should proactively address the known underlying root causes of diagnostic errors and cognitive biases, ensure systems are in place to promptly discover and control unmitigated root causes as they arise and ensure an unbiased 'blameless' or 'just' culture of error investigation and proces sing including the implementation of non-punitive peer feedback and peer learning. This article provides an overview of errors in diagnostic radiology including the causes and potential ramifications and how we might reduce their frequency and impact.

Analysis of misses in imaging of head and neck pathology by attending neuroradiologists at a single tertiary academic medical centre

To analyse errors in head and neck (H&N) pathology made by attending neuroradiologists at a single tertiary-care centre. A neuroradiology quality assurance (QA) database of radiological errors was searched for attending physician errors in H&N pathology from 2014-2020. Data were limited to computed tomography (CT) and magnetic resonance imaging (MRI) reports. Data were collected on missed pathologies and study types. Misses were grouped into three categories: central neck (thyroid gland, aerodigestive tract), lateral neck (salivary glands, lymph nodes, soft tissues), and face/orbits (orbits, sinuses, masticator space). During the study period, a total of 283,248 CT and MRI neuroradiology examinations were interpreted (all indications). Seventy-four H&N misses were identified comprising 85.1% perceptual and 14.9% interpretive errors. The distribution of errors was face/orbits (37.8%), central neck (36.5%), and lateral neck (25.7%). Clinically significant errors were found most commonly in the aerodigestive tract (21%), orbits (17.7%), masticator space, and parotid glands (14.5% each). The majority (67.6%) of the misses were detected on examinations that were not performed for a primary H&N indication; MRI brain was the most common examination (27%). Clearly malignant or potentially malignant masses accounted for 48.6% of all misses. The majority of H&N misses were perceptual and were detected on examinations not performed for a H&N indication. Clearly malignant or potentially malignant masses represented half of all misses.

Diagnostic Errors in Neuroradiology: A Message to Emergency Radiologists and Trainees.

Diagnostic errors in neuroradiology are inevitable, yet potentially avoidable. Through extensive literature search, we present an up-to-date review of the psychology of human decision making and how such complex process can lead to radiologic errors. Our focus is on neuroradiology, so we augmented our review with multiple explanatory figures to show how different errors can reflect on real-life clinical practice. We propose a new thematic categorization of perceptual and cognitive biases in this article to simplify message delivery to our target audience: emergency/general radiologists and trainees. Additionally, we highlight individual and organizational remedy strategies to decrease error rate and potential harm.

Blind spots on CT imaging of the head: Insights from 5 years of report addenda at a single institution

BackgroundErrors of detection (“misses”) are the major source of error in radiology. There is sparse prior literature describing patterns of detection error on CT head imaging. PurposeThe objective of this study was to gain insight to areas on CT head imaging where radiologists are most likely to miss clinically relevant findings. MethodsWe performed a cross-sectional study of consecutive reports of CT imaging of the head at a single institution spanning 5/1/2013–5/1/2018 (5 years). Detection errors described in addenda were categorized according to anatomic location, type of pathology, and potential impact on management. Blind spots were defined by the most common sites of missed findings. ResultsA total of 165,943 reports for CT head imaging were obtained. Addenda were found in 1658 (~1%) of reports, of which 359 (21.7%) described errors of detection. Within the extracranial soft tissues (n = 73) the most common “misses” were at incidentally imaged parotid glands and the frontal scalp. Within osseous structures (n = 149), blind spots included the nasal and occipital bones. Vascular lesions (n = 47) which passed detection were most common at the distal MCA, carotid terminus and sigmoid sinus/jugular bulb. No predisposition was seen for anatomic subsites within the CSF space (n = 60) and brain parenchyma (n = 65). ConclusionsConsistent patterns of blind spots are revealed. Radiologic teaching and search patterns to account for these sites of error may accelerate trainee competence and improve accuracy in the practice of radiology.

Visual Perception: How Better Imaging Can Make Things Worse

Summary Visual search is critical to daily life and to socially important tasks — from cancer screening to airport security. New research shows how a technological advancement can interact with the human visual system to improve search for one type of target while making matters worse for another. Part of the problem is that we are surprisingly bad at knowing where we have looked.

Performance of an artificial intelligence tool with real-time clinical workflow integration - Detection of intracranial hemorrhage and pulmonary embolism.

Performance of an artificial intelligence tool with real-time clinical workflow integration - Detection of intracranial hemorrhage and pulmonary embolism.

The cognitive and perceptual processes that affect observer performance in lung cancer detection: a scoping review.

IntroductionEarly detection of malignant pulmonary nodules through screening has been shown to reduce lung cancer‐related mortality by 20%. However, perceptual and cognitive factors that affect nodule detection are poorly understood. This review examines the cognitive and visual processes of various observers, with a particular focus on radiologists, during lung nodule detection.MethodsFour databases (Medline, Embase, Scopus and PubMed) were searched to extract studies on eye‐tracking in pulmonary nodule detection. Studies were included if they used eye‐tracking to assess the search and detection of lung nodules in computed tomography or 2D radiographic imaging. Data were charted according to identified themes and synthesised using a thematic narrative approach.ResultsThe literature search yielded 25 articles and five themes were discovered: 1 – functional visual field and satisfaction of search, 2 – expert search patterns, 3 – error classification through dwell time, 4 – the impact of the viewing environment and 5 – the effect of prevalence expectation on search. Functional visual field reduced to 2.7° in 3D imaging compared to 5° in 2D radiographs. Although greater visual coverage improved nodule detection, incomplete search was not responsible for missed nodules. Most radiological errors during lung nodule detection were decision‐making errors (30%–45%). Dwell times associated with false‐positive (FP) decisions informed feedback systems to improve diagnosis. Interruptions did not influence diagnostic performance; however, it increased viewing time by 8% and produced a 23.1% search continuation accuracy. Comparative scanning was found to increase the detection of low contrast nodules. Prevalence expectation did not directly affect diagnostic accuracy; however, decision‐making time increased by 2.32 seconds with high prevalence expectations.ConclusionVisual and cognitive factors influence pulmonary nodule detection. Insights gained from eye‐tracking can inform advancements in lung screening. Further exploration of eye‐tracking in lung screening, particularly with low‐dose computed tomography (LDCT), will benefit the future of lung cancer screening.

Medical Error, Adverse Events, and Complications in Interventional Radiology: Liability or Opportunity?

This review suggests that there is a critical need to renew understanding of adverse events and complications within interventional radiology and to redefine a robust commitment to patient safety a...

Errors in radiology – does reporting speed matter? A retrospective analysis of discrepancy reporting times

Category: Other

Seeing isn't necessarily believing: Misleading contextual information influences perceptual-cognitive bias in radiologists.

A substantial number of medical errors in radiology are attributed to failures of perception or decision making, although it is believed that experience (or expertise) might buffer diagnosticians from some types of perceptual-cognitive bias. We examined how the quality of contextual information influences decision making and how underlying perceptual-cognitive processes change as a function of experience and diagnostic accuracy. Twenty-one radiologists dictated their findings on 16 deidentified musculoskeletal radiographic cases while wearing a mobile-eye tracking system. Patient histories were mismatched on a subset of cases to be miscued relative to the correct diagnosis. Experienced radiologists outperformed less-experienced participants, but no systematic differences in gaze behaviors emerged between groups. Miscued case notes increased perceptual-cognitive bias in both groups, resulting in an approximate 40% decrease in diagnostic accuracy. Most errors were judgment errors, meaning participants visually fixated on the abnormality for longer than a second yet still failed to make the correct diagnosis. Findings suggest a physician's confidence in their diagnosis might be misplaced after spending insufficient time extracting relevant information from key areas of the visual display, or when decisions are based primarily on a priori expectations derived from patient histories. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Errors in MDCT diagnosis of acute mesenteric ischemia.

The causes of diagnostic errors during daily medical practice can be several, mainly attributable to perceptual, interpretive and communication factors. The eventuality of radiological error is much more amplified in the emergency setting where a high number of complex multidetector-row computed tomography (MDCT) images must be evaluated quickly and critical time decisions need to be taken. In particular, in this context, the diagnosis of vascular intestinal diseases represents a crucial and difficult challenge in case of acute abdominal pain given the importance of being able to identify patient with high suspicious for intestinal ischemia and for a specific patient to judge if his ischemia is reversible or irreversible. Awareness of potential biases which can lead to diagnostic errors together with an extensive knowledge of the imaging features of these pathologies can lead to promptly recognize them with fewer mistakes, improving patients' outcome. This article reviews the MDCT findings of acute intestinal ischemia and acute colonic ischemia and analyzes the main types of diagnostic errors, underlining the importance of being familiarized with them to avoid misdiagnosis.

Implementation of an Artificial Intelligence-Based Double Read System in Capturing Pulmonary Nodule Discrepancy in CT Studies

Studies show that up to 80% of all radiology errors are due to errors in perception. Early detection is critical for good outcomes in patients with primary lung cancer and lung metastasis. However, pulmonary nodules can be easily missed due to their small size. We prospectively applied a machine vision algorithm to CT studies containing lung parenchyma to detect pulmonary nodules, as well as a natural language processing algorithm to the text of the report to identify documentation of pulmonary nodules. Apparent discrepancies in perception – instances where a pulmonary nodule was not reported – were flagged for a secondary review by a radiologist. Four thousand and nine hundred studies were prospectively processed, of which 450 cases with potential discrepancies were detected. Preliminary manual analysis was performed to analyze the base error rate and to optimize thresholds for the machine vision and natural language processing algorithms, and 104 cases were flagged for final review. Of these 104 cases, 50 cases contained undocumented pulmonary nodules. Among these cases, 7 cases were classified as likely to be significant, where report addendums were done and the clinicians notified. We have successfully implemented an automated double read system to detect pulmonary nodule discrepancies, with minimal disruption to the radiology workflow and while keeping personal health information on-premises. This successful implementation demonstrates the viability of using an automated and secure radiology double-read system to improve patient safety in radiology workflows, either at a health system or an independent radiology practice.

A new complication registration system for errors in radiology: Initial 5-year experience in a tertiary care radiology department

PurposeTo describe and evaluate our initial 5-year experience with a new complication registration system for errors in radiology. Materials and methodsThis study reviewed all cases that were submitted to a new complication registration system of a tertiary care radiology department between 2015–2019. ResultsSixty-seven cases were included. In the group of diagnostic complications/errors (n = 34), there were 21 perceptual errors and 13 cognitive errors. This 61.8 % (21/34) perceptual error rate was not significantly different (P = 0.297) from the 70 % perceptual error rate known from previous literature. In the group of interventional complications (n=19), most cases (47.4 % [9/19]) concerned symptomatic or major hemorrhage. In the group of organizational complications/errors (n=14), the leading incident type according to the International Classification System for Patient Safety was clinical process/procedure with wrong body part/side/site as subclassification (35.7 % [5/14]). Harm severities were none (n=35), mild (n=10), moderate (n=10), severe (n=6), death (n=5), and unknown (n=1). Harm severity of interventional complications was significantly higher (P < 0.05) than that of organizational complications, while there were no significant differences in harm severities between other groups of complications. ConclusionIt is feasible to implement the radiologic complication registration system that was described in this study. Perceptual mistakes, hemorrhage, and procedures on the wrong body part/side/site dominated in the categories of diagnostic, interventional, and organizational complications/errors, respectively, and these should be the topic of vigilance in clinical practice and further research. Future studies are also required to determine whether this complication registration system reduces radiologic errors and improves healthcare quality.

Lasting lessons learnt in the radiology department from the battle with COVID-19

Lasting lessons learnt in the radiology department from the battle with COVID-19

Effect of a communication lecture tutorial on breast imaging trainees' confidence with challenging breast imaging patient interactions

PurposeThe aim of the study was to evaluate the effect of a one-hour lecture based communication curriculum on breast imaging trainees' confidence in communicating with patients in a challenging communication setting such as delivering bad news or radiologic error disclosure. Methods12 breast imaging trainees from an academic fellowship program completed questionnaires before and after a communication tutorial. A four breast imaging specific scenario questionnaire assessed confidence by asking the trainees to rank agreement with statements related to their attitude in those specific settings. 12-month follow-up questionnaire was sent to the graduating fellows assessing their -overall confidence in patient communication, the contribution of the curriculum to their self-perceived communication skill and their likelihood in disclosing a radiologic error to a patient. ResultsAll trainees completed the pre and post lecture questionnaire. After the communication tutorial, all trainees reported increased confidence in communicating with patients in a variety of challenging settings with pre lecture survey mean confidence score of 38/98 and post lecture survey mean score of 85.3/98, P = 0.003. Three of eight trainees who completed the 12-month follow up questionnaire reported confidence in their communication skills and reported that the tutorial significantly contributed to their communication skill development. All three agreed that they would be likely to disclose a medical error should they encounter it in their future career. ConclusionsA limited resource one-hour lecture communication tutorial provides effective communication training for breast imaging fellows and is a promising part of a breast imaging curriculum.

Sources of Error in Interventional Radiology: How, Why, and When

This article aims to provide an overview of the sources for error in interventional radiology (IR). Being both a procedure and an imaging-based specialty, IR has unique considerations as to how error can occur. However, compared to the surgical and medical literature, data on error in IR are lacking. The available IR literature is reviewed but supplemented with lessons from other specialties and the World Health Organization. Individual risks such as cognitive bias as well as system-level factors are also considered in order to generate a taxonomy for error in IR that includes the operator, patient, team, and environment.

Avoiding and Managing Error in Interventional Radiology Practice: Tips and Tools.

While there are limited data on error in interventional radiology (IR), the literature so far indicates that many errors in IR are potentially preventable. Yet, understanding the sources for error and implementing effective countermeasures can be challenging. Traditional methods for reducing error such as increased vigilance and new policies may be effective but can also contribute to an "error cycle." A hierarchy of effectiveness for patient safety interventions is outlined, and the characteristics of "high-reliability" organizations in other "high-risk" industries are examined for clues that could be implemented in IR. The evidence behind team error reduction strategies such as checklists is considered along with individual approaches such as "slowing down when you should." However, error in medicine is inevitable, and this article also seeks to outline an evidence-based approach to managing the psychological impact of being involved in medical error as a physician.