Diagnostic Errors In Radiology Research Articles

Blind spots in brain imaging: a pictorial essay.

Currently, radiologists must interpret large quantities of images and identify diseases on a daily basis. The minimization of errors is crucial for high-quality diagnostic imaging and optimal patient care. Brain imaging is frequently used in clinical practice; however, radiologists are prone to overlook some regions in brain imaging and make perceptual errors, thus leading to missed diagnoses. These regions, also known as "blind spots", comprise a number of intricate areas, including the posterior fossa, cerebral sulci and pia mater, cranial nerves (CNs), intracranial arteries, dural sinuses, sella and parasellar region, Meckel's cave, skull base, scalp, orbit, and pterygopalatine fossa (PPF). Therefore, the knowledge of normal computed tomography (CT) and magnetic resonance imaging (MRI) manifestations and common lesions in these blind spots is imperative to avoid false-negative results. This article graphically discusses and analyzes these common blind spots of brain imaging using real representative cases. It also provides comprehensive strategies to address missed diagnostic errors in radiology, including enhancing the selection of imaging protocols, implementing a multi-reviewer reporting system, adopting structured reporting templates, employing error measurement or detection strategies, and promoting the use, development, and refinement of artificial intelligence (AI) to improve diagnostic accuracy and efficiency. This article may also increase junior doctors' awareness of these blind spots and assist them in their daily work, and thus has continuing education implications.

Diagnostic errors in radiology: where are we?

Diagnostic errors in radiology: where are we?

Understanding Diagnostic Errors: AJR Podcast Series on Diagnostic Excellence and Error, Episode 2.

In this episode of the AJR Podcast Series on Diagnostic Excellence and Error, Francis Deng, MD, and David Newman-Toker, MD, PhD, discuss prevalence and harms of diagnostic error in medicine, the role and causes of error in diagnostic radiology, and disease-specific examples, including in patients with stroke presenting with dizziness.

Spectrum of Cognitive Biases in Diagnostic Radiology.

Cognitive biases are systematic thought processes involving the use of a filter of personal experiences and preferences arising from the tendency of the human brain to simplify information processing, especially when taking in vast amounts of data such as from imaging studies. These biases encompass a wide spectrum of thought processes and frequently overlap in their concepts, with multiple biases usually in operation when interpretive and perceptual errors occur in radiology. The authors review the gamut of cognitive biases that occur in radiology. These biases are organized according to their expected stage of occurrence while the radiologist reads and interprets an imaging study. In addition, the authors propose several additional cognitive biases that have not yet, to their knowledge, been defined in the radiologic literature but are applicable to diagnostic radiology. Case examples are used to illustrate potential biases and their impact, with emergency radiology serving as the clinical paradigm, given the associated high imaging volumes, wide diversity of imaging examinations, and rapid pace, which can further increase a radiologist's reliance on biases and heuristics. Potential strategies to recognize and overcome one's personal biases at each stage of image interpretation are also discussed. Awareness of such biases and their unintended effects on imaging interpretations and patient outcomes may help make radiologists cognizant of their own biases that can result in diagnostic errors. Identification of cognitive bias in departmental and systematic quality improvement practices may represent another tool to prevent diagnostic errors in radiology. ©RSNA, 2024 See the invited commentary by Larson in this issue.

Incorporation of Eye Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-Rays: A Randomized Controlled Clinical Trial

Diagnostic errors in radiology often result from incomplete visual assessments attributed to insufficient training in search patterns. Radiologists lack consistent feedback, relying on ad-hoc strategies, leading to suboptimal patterns and potential false negatives. This study used eye tracking to analyze search patterns, quantify performance metrics, and evaluate the impact of an automated continuous improvement feedback-driven framework on detection accuracy. In a controlled trial with ten residents, the intervention group (received feedback) demonstrated a significant 38.9% absolute improvement in detecting suspicious pulmonary nodules compared to the control group (5.6%, p=0.006). While improvements were more rapid over sessions (p=0.0001), other metrics showed no significant changes. The findings highlight the potential of automated feedback systems to enhance radiologist accuracy and reduce errors, emphasizing the need for further research and broader implementation in radiology training.

The ins and outs of errors in oncology imaging: the DAC framework for radiologists.

With the increasingly central role of imaging in medical diagnosis, understanding and monitoring radiological errors has become essential. In the field of oncology, the severity of the disease makes radiological error more visible, with both individual consequences and public health issues. The quantitative trend radiology allows to consider the diagnostic task as a problem of classification supported by the latest neurocognitive theories in explaining decision making errors, this purposeful model provides an actionable framework to support root cause analysis of diagnostic errors in radiology and envision corresponding risk-management strategies. The D for Data, A for Analysis and C for Communication are the three drivers of errors and we propose a practical toolbox for our colleagues to prevent individual and systemic sources of error.

Work overload and diagnostic errors in radiology

PurposeTo determine the association between workload and diagnostic errors on clinical CT scans. MethodThis retrospective study was performed at a tertiary care center and covered the period from January 2020 to March 2023. All clinical CT scans that contained an addendum describing a perceptual error (i.e. failure to detect an important abnormality) in the original report that was issued on office days between 7.30 a.m. and 18.00 p.m., were included. The workload of the involved radiologist on the day of the diagnostic error was calculated in terms of relative value units, and normalized for the known average daily production of each individual radiologist (workloadnormalized). A workloadnormalized of less than 100% indicates relative work underload, while a workloadnormalized of > 100% indicates relative work overload in terms of reported examinations on an individual radiologist’s basis. ResultsA total of 49 diagnostic errors were included. Top-five locations of diagnostic errors were lung (n = 8), bone (n = 8), lymph nodes (n = 5), peritoneum (n = 5), and liver (n = 4). Workloadnormalized on the days the diagnostic errors were made was on average 121% (95% confidence interval: 106% to 136%), which was significantly higher than 100% (P = 0.008). There was no significant upward monotonic trend in diagnostic errors over the course of the day (Mann-Kendall tau of 0.005, P = 1.000), and there were no other notable temporal trends either. ConclusionsRadiologists appear to have a relative work overload when they make a diagnostic error on CT. Diagnostic errors occurred throughout the entire day, without any increase towards the end of the day.

The Value of Transitioning From Scoring-Based Peer Review to Peer Learning

In radiology, scoring-based peer review is the dominant model focused on quality assurance, rather than quality improvement. Although designed to decrease diagnostic errors in radiology, this model has had an overall negative effect secondary to its punitive nature and lack of educational benefit. A peer learning-based system helps circumvent these issues through a multitude of ways. These include increasing learning opportunities, identifying system errors that maybe contributing to the misdiagnosis, and fostering a “just” environment where constructive feedback is given to the radiologist. By changing to the peer learning paradigm, this helps increase engagement and satisfaction by participating radiologists to improve patient care.

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.

Unscheduled Radiologic Examination Orders in the Electronic Health Record: A Novel Resource for Targeting Ambulatory Diagnostic Errors in Radiology.

The aim of this study was to assess the prevalence of unscheduled radiologic examination orders in an electronic health record, and the proportion of unscheduled orders that are clinically necessary, by modality. This retrospective study was conducted from January to October 2016 at an academic institution. All unscheduled radiologic examination orders were retrieved for seven modalities (CT, MR, ultrasound, obstetric ultrasound, bone densitometry, mammography, and fluoroscopy). After excluding duplicates, 100 randomly selected orders from each modality were assigned to two physician reviewers who classified their clinical necessity, with 10% overlap. Interannotator agreement was assessed using κ statistics, the percentage of clinically necessary unscheduled orders was compared, and χ2 analysis was used to assess differences by modality. A total 494,503 radiologic examination orders were placed during the study period. After exclusions, 33,546 unscheduled orders were identified, 7% of all radiologic examination orders. Among 700 reviewed unscheduled orders, agreement was substantial (κ= 0.63). Eighty-seven percent of bone densitometric examinations and sixty-five percent of mammographic studies were considered clinically necessary, primarily for follow-up management. The majority of orders in each modality were clinically necessary, except for CT, obstetric ultrasound, and fluoroscopy (P < .0001). Large numbers of radiologic examination orders remain unscheduled in the electronic health record. A substantial portion are clinically necessary, representing potential delays in executing documented provider care plans. Clinically unnecessary unscheduled orders may inadvertently be scheduled and performed. Identifying and performing clinically necessary unscheduled radiologic examination orders may help reduce diagnostic errors related to diagnosis and treatment delays and enhance patient safety, while eliminating clinically unnecessary unscheduled orders will help avoid unneeded testing.

Risk Factors for Perceptual-versus-Interpretative Errors in Diagnostic Neuroradiology

Diagnostic errors in radiology are classified as perception or interpretation errors. This study determined whether specific conditions differed when perception or interpretation errors occurred during neuroradiology image interpretation. In a sample of 254 clinical error cases in diagnostic neuroradiology, we classified errors as perception or interpretation errors, then characterized imaging technique, interpreting radiologist's experience, anatomic location of the abnormality, disease etiology, time of day, and day of the week. Interpretation and perception errors were compared with hours worked per shift, cases read per shift, average cases read per shift hour, and the order of case during the shift when the error occurred. Perception and interpretation errors were 74.8% (n = 190) and 25.2% (n = 64) of errors, respectively. Logistic regression analyses showed that the odds of an interpretation error were 2 times greater (OR, 2.09; 95% CI, 1.05-4.15; P = .04) for neuroradiology attending physicians with ≤5 years of experience. Interpretation errors were more likely with MR imaging compared with CT (OR, 2.10; 95% CI, 1.09-4.01; P = .03). Infectious/inflammatory/autoimmune diseases were more frequently associated with interpretation errors (P = .04). Perception errors were associated with faster reading rates (6.01 versus 5.03 cases read per hour; P = .004) and occurred later during the shift (24th-versus-18th case; P = .04). Among diagnostic neuroradiology error cases, interpretation-versus-perception errors are affected by the neuroradiologist's experience, technique, and the volume and rate of cases read. Recognition of these risk factors may help guide programs for error reduction in clinical neuroradiology services.

Radiological Errors: Implications and Causes with a Focus on Mammographic Misdiagnosis

Radiological diagnostic errors may have serious clinical and medico-legal implications. Previous work has reported that radiology has a reasonable incidence of error, a number of which are resulted from observer mistakes. The radiologists’ interaction with the image is critical, and studying the types of diagnostic errors to improve patient and radiologist wellbeing, reduce cost and improve the public perception of the health care system is well justified. Therefore, the aim of current review is to consider the primary types of diagnostic errors in radiology, as well as their causes and implications with a focus on mammographic misdiagnosis.

Perceptual and Interpretive Error in Diagnostic Radiology—Causes and Potential Solutions

Interpretation of increasingly complex imaging studies involves multiple intricate tasks requiring visual evaluation, cognitive processing, and decision-making. At each stage of this process, there are opportunities for error due to human factors including perceptual and ergonomic conditions. Investigation into the root causes of interpretive error in radiology first began over a century ago. In more recent work, there has been increasing recognition of the limits of human image perception and other human factors and greater acknowledgement of the role of the radiologist's environment in increasing the risk of error. This article reviews the state of research on perceptual and interpretive error in radiology. This article focuses on avenues for further error examination, and strategies for mitigating these errors are discussed. The relationship between artificial intelligence and interpretive error is also considered.

Fundamentals of Diagnostic Error in Imaging.

Imaging plays a pivotal role in the diagnostic process for many patients. With estimates of average diagnostic error rates ranging from 3% to 5%, there are approximately 40 million diagnostic errors involving imaging annually worldwide. The potential to improve diagnostic performance and reduce patient harm by identifying and learning from these errors is substantial. Yet these relatively high diagnostic error rates have persisted in our field despite decades of research and interventions. It may often seem as if diagnostic errors in radiology occur in a haphazard fashion. However, diagnostic problem solving in radiology is not a mysterious black box, and diagnostic errors are not random occurrences. Rather, diagnostic errors are predictable events with readily identifiable contributing factors, many of which are driven by how we think or related to the external environment. These contributing factors lead to both perceptual and interpretive errors. Identifying contributing factors is one of the keys to developing interventions that reduce or mitigate diagnostic errors. Developing a comprehensive process to identify diagnostic errors, analyze them to discover contributing factors and biases, and develop interventions based on the contributing factors is fundamental to learning from diagnostic error. Coupled with effective peer learning practices, supportive leadership, and a culture of quality, this process can unquestionably result in fewer diagnostic errors, improved patient outcomes, and increased satisfaction for all stakeholders. This article provides the foundational elements for implementing this type of process at a radiology practice, with examples to help radiologists and practice leaders achieve meaningful practice improvement. ©RSNA, 2018.

Radiological discrepancies: "The only real mistake is the one from which we learn nothing"

Medical errors seem to be inevitable despite all measures taken to avoid them. Radiology is no exception and is one of the specialities most liable to claims of medical negligence. The aetiology of radiological errors is multifactorial and fall into different patterns. Understanding these causes would help immensely to minimise the occurrences. This article focuses on the spectrum of diagnostic errors in Radiology and the importance of sharing the negative experiences in identifying the error traps and preventing repetition of the same mistake.

Tackling the problem of error in diagnostic radiology.

This comment refers to the article available at: http://dx.doi.org/10.1007/s00247-014-3196-5 .

Cognitive and System Factors Contributing to Diagnostic Errors in Radiology

In this article, we describe some of the cognitive and system-based sources of detection and interpretation errors in diagnostic radiology and discuss potential approaches to help reduce misdiagnoses. Every radiologist worries about missing a diagnosis or giving a false-positive reading. The retrospective error rate among radiologic examinations is approximately 30%, with real-time errors in daily radiology practice averaging 3-5%. Nearly 75% of all medical malpractice claims against radiologists are related to diagnostic errors. As medical reimbursement trends downward, radiologists attempt to compensate by undertaking additional responsibilities to increase productivity. The increased workload, rising quality expectations, cognitive biases, and poor system factors all contribute to diagnostic errors in radiology. Diagnostic errors are underrecognized and underappreciated in radiology practice. This is due to the inability to obtain reliable national estimates of the impact, the difficulty in evaluating effectiveness of potential interventions, and the poor response to systemwide solutions. Most of our clinical work is executed through type 1 processes to minimize cost, anxiety, and delay; however, type 1 processes are also vulnerable to errors. Instead of trying to completely eliminate cognitive shortcuts that serve us well most of the time, becoming aware of common biases and using metacognitive strategies to mitigate the effects have the potential to create sustainable improvement in diagnostic errors.

Errors in the Radiological Evaluation of the Alimentary Tract: Part I

Physicians are subjected to an increasing number of medical malpractice claims, and radiology is one of the specialties most liable to claims of medical negligence The etiology of radiological error is multifactorial, deriving by poor technique, failures of perception, lack of knowledge, and misjudgments. Reducing errors will improve patient care, may reduce costs, and will improve the image of the hospital. The main reason for studying medical errors is to try to prevent them. This article focuses on the spectrum of diagnostic errors in radiology, including a classification of the errors, and highlights the malpractice issues in methods for functional alimentary tract examination: swallowing act study, 3-dimensional endoanal ultrasound, defecography, and defecography in magnetic resonance.

The Concept of Error and Malpractice in Radiology

Since the early 1970s, physicians have been subjected to an increasing number of medical malpractice claims. Radiology is one of the specialties most liable to claims of medical negligence. The etiology of radiological error is multifactorial. Errors fall into recurrent patterns. Errors arise from poor technique, failures of perception, lack of knowledge, and misjudgments. Every radiologist should understand the sources of error in diagnostic radiology as well as the elements of negligence that form the basis of malpractice litigation. Errors are an inevitable part of human life, and every health professional has made mistakes. To improve patient safety and reduce the risk from harm, we must accept that some errors are inevitable during the delivery of health care. We must play a cultural change in medicine, wherein errors are actively sought, openly discussed, and aggressively addressed.

Learning from diagnostic errors: A good way to improve education in radiology

Purpose To evaluate the causes and the main categories of diagnostic errors in radiology as a method for improving education in radiology. Material and methods A Medline search was performed using PubMed (National Library of Medicine, Bethesda, MD) for original research publications discussing errors in diagnosis with specific reference to radiology. The search strategy employed different combinations of the following terms: (1) diagnostic radiology, (2) radiological error and (3) medical negligence. This review was limited to human studies and to English-language literature. Two authors reviewed all the titles and subsequently the abstracts of 491 articles that appeared pertinent. Additional articles were identified by reviewing the reference lists of relevant papers. Finally, the full text of 75 selected articles was reviewed. Results Several studies show that the etiology of radiological error is multi-factorial. The main category of claims against radiologists includes the misdiagnoses. Radiologic “misses” typically are one of two types: either missed fractures or missed diagnosis of cancer. The most commonly missed fractures include those in the femur, the navicular bone, and the cervical spine. The second type of “miss” is failure to diagnose cancer. Lack of appreciation of lung nodules on chest radiographs and breast lesions on mammograms are the predominant problems. Conclusion Diagnostic errors should be considered not as signs of failure, but as learning opportunities.