Classification of Error in Abdominal Imaging: Pearls and Pitfalls for Radiologists

2018 ◽  
Vol 69 (4) ◽  
pp. 409-416 ◽  
Author(s):  
Csilla Egri ◽  
Kathryn E. Darras ◽  
Elena P. Scali ◽  
Alison C. Harris

Peer review for radiologists plays an important role in identifying contributing factors that can lead to diagnostic errors and patient harm. It is essential that all radiologists be aware of the multifactorial causes of diagnostic error in radiology and the methods available to reduce it. This pictorial review provides readers with an overview of common errors that occur in abdominal radiology and strategies to reduce them. This review aims to make readers more aware of pitfalls in abdominal imaging so that these errors can be avoided in the future. This essay also provides a systematic approach to classifying abdominal imaging errors that will be of value to all radiologists participating in peer review.

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Omer Onder ◽  
Yasin Yarasir ◽  
Aynur Azizova ◽  
Gamze Durhan ◽  
Mehmet Ruhi Onur ◽  
...  

AbstractInterpretation differences between radiologists and diagnostic errors are significant issues in daily radiology practice. An awareness of errors and their underlying causes can potentially increase the diagnostic performance and reduce individual harm. The aim of this paper is to review both the classification of errors and the underlying biases. Case-based examples are presented and discussed for each type of error and bias to provide greater clarity and understanding.


Author(s):  
Michael A. Bruno

This chapter provides an overview of the prevalence and classification of error types in radiology, including the frequency and types of errors made by radiologists. We will review the relative contribution of perceptual error—in which findings are simply not seen—as compared to other common types of error. This error epidemiology will be considered in the light of the underlying variability and uncertainties present in the radiological process. The role of key cognitive biases will also be reviewed, including anchoring bias, confirmation bias, and availability bias. The role of attentional focus, working memory, and problems caused by fatigue and interruption will also be explored. Finally, the problem of radiologist error will be considered in the context of the overall problem of diagnostic error in medicine.


CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S106-S106
Author(s):  
J. Sherbino ◽  
S. Monteiro ◽  
J. Ilgen ◽  
E. Hayden ◽  
E. Howey ◽  
...  

Introduction: Cognitive bias is often cited as an explanation for diagnostic errors. Of the numerous cognitive biases currently discussed in the literature, availability bias, defined as the current case reminds you of a recent similar example is most well-known. Despite the ubiquity of cognitive biases in medical and popular literature, there is surprisingly little evidence to substantiate these claims. The present study sought to measure the influence of availability bias and identify contributing factors that may increase susceptibility to the influence of a recent similar case. Methods: To investigate the role of prior examples and category priming on diagnostic error at different levels of expertise, we devised a 2 phase experiment. The experimental intervention was in a validation phase preceding the test, where participants were asked to verify a diagnosis which was either i) representative of Diagnosis A, and similar to a test case, ii) representative of Diagnosis A and dissimilar to a test case, iii) representative of Diagnosis B and similar to a test case. The test phase consisted of 8 written cases, each with two approximately equally likely diagnoses(A or B). Each participant verified 2 cases from each condition, for a total of 6. They then diagnosed all 8 test cases; the remaining 2 test cases had no prior example. All cases were counterbalanced across conditions. Comparison between Condition i) and ii) and no prior showed effect of prior exemplar; comparison between iii) and no prior showed effect of category priming. Because cases were designed so that both Diagnosis A and B were likely, overall accuracy was measured as the sum of proportion of cases in which either was selected. Subjects were emergency medicine staff (n=40), residents (n=39) and medical students (n=32) from McMaster University, University of Washington, and Harvard Medical School. Results: Overall, staff had an accuracy (A + B) of 98%, residents 98% and students 85% (F=35.6,p<.0001). For residents and staff there was no effect of condition (all mean accuracies 97% to 100%); for students there was a clear effect of category priming, with accuracy of 84% for i), 87% for ii) and 94% for iii) but only 73% for the no prime condition (Interaction F= 3.54, p<.002) Conclusion: Although prior research has shown substantial biasing effects of availability, primarily in cases requiring visual diagnosis, the present study has shown such effects only for novices (medical students). Possible explanations need to be explored. Nevertheless, our study shows that with increasing expertise, availability may not be a source of error.


2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S379-S379
Author(s):  
Justin B Searns ◽  
Manon Williams ◽  
Christine MacBrayne ◽  
Ann Wirtz ◽  
Sarah Parker ◽  
...  

Abstract Background Patient safety incidents (PSIs), such as diagnostic errors, are common events that may lead to significant patient harm. Few studies describe the impact that antimicrobial stewardship programs (ASPs) have preventing PSIs and recognizing diagnostic errors. Handshake Stewardship has emerged as a specific ASP model that involves prospective review of hospital-wide antimicrobial ordering with a compressed “second look” of relevant clinical and historical patient data. In person recommendations are then provided directly to the medical team. The objective of this project was to evaluate the potential impact that Handshake Stewardship has on preventing PSIs and recognizing diagnostic errors. Methods Following Children’s Hospital Colorado (CHCO) ASP’s implementation of the Handshake Stewardship model in October 2013, the CHCO ASP team began prospectively self-labeling interventions as “Great Catches” (GCs). These GCs were defined as any ASP intervention that “notably changed the trajectory of patient care.” Patient charts for all GCs from October 2014 through May 2018 were retrospectively reviewed and each intervention was assigned one or more descriptive category labels including: administration error, de-escalation/escalation of therapy, bug-drug mismatch, inappropriate dose/duration, potential adverse effect, alternative diagnosis, additional testing, prevent hospital admission, and epidemiology alerts. In addition, each intervention was scored using the previously validated “Safer Dx Instrument” to determine which GCs intervened on a potential diagnostic error. Results From October 2014 through May 2018 there were 87,322 admissions to CHCO. Our ASP team intervened on 6,735/87,322 (7.7%) of these admissions. Of these, 174/6,735 (2.6%) were prospectively labeled by ASP providers as GCs, of which 44/174 (25%) resulted in new infectious disease consultations. Conclusion Given the frequency and significance of PSIs including diagnostic error, systems are needed to help recognize and prevent patient harm. The Handshake Stewardship model may help prevent PSIs and recognize diagnostic errors among hospitalized children. Disclosures All authors: No reported disclosures.


Diagnosis ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 229-233
Author(s):  
Robert L. Trowbridge ◽  
James B. Reilly ◽  
Jerome C. Clauser ◽  
Steven J. Durning

Abstract Background Diagnostic errors are a significant cause of patient harm. Cognitive processes often contribute to diagnostic errors but studying and mitigating the effects of these errors is challenging. Computerized virtual patients may provide insight into the diagnostic process without the potential for patient harm, but the feasibility and utility of using such cases in practicing physicians has not been well described. Methods We developed a series of computerized virtual cases depicting common presentations of disease that included contextual factors that could result in diagnostic error. Cases were piloted by practicing physicians in two phases and participant impressions of the case platform and cases were recorded, as was outcome data on physician performance. Results Participants noted significant challenges in using the case platform. Participants specifically struggled with becoming familiar with the platform and adjusting to the non-adaptive and constraining processes of the model. Although participants found the cases to be typical presentations of problems commonly encountered in practice, the correct diagnosis was identified in less than 33% of cases. Conclusions The development of virtual patient cases for use by practicing physicians requires substantial resources and platforms that account for the non-linear and adaptive nature of reasoning in experienced clinicians. Platforms that are without such characteristics may negatively affect diagnostic performance. The novelty of such platforms may also have the potential to increase cognitive load. Nonetheless, virtual cases may have the potential to be a safe and robust means of studying clinical reasoning performance.


Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Justin B. Searns ◽  
Manon C. Williams ◽  
Christine E. MacBrayne ◽  
Ann L. Wirtz ◽  
Jan E. Leonard ◽  
...  

AbstractObjectivesFew studies describe the impact of antimicrobial stewardship programs (ASPs) on recognizing and preventing diagnostic errors. Handshake stewardship (HS-ASP) is a novel ASP model that prospectively reviews hospital-wide antimicrobial usage with recommendations made in person to treatment teams. The purpose of this study was to determine if HS-ASP could identify and intervene on potential diagnostic errors for children hospitalized at a quaternary care children’s hospital.MethodsPreviously self-identified “Great Catch” (GC) interventions by the Children’s Hospital Colorado HS-ASP team from 10/2014 through 5/2018 were retrospectively reviewed. Each GC was categorized based on the types of recommendations from HS-ASP, including if any diagnostic recommendations were made to the treatment team. Each GC was independently scored using the “Safer Dx Instrument” to determine presence of diagnostic error based on a previously determined cut-off score of ≤1.50. Interrater reliability for the instrument was measured using a randomized subset of one third of GCs.ResultsDuring the study period, there were 162 GC interventions. Of these, 65 (40%) included diagnostic recommendations by HS-ASP and 19 (12%) had a Safer Dx Score of ≤1.50, (Κ=0.44; moderate agreement). Of those GCs associated with diagnostic errors, the HS-ASP team made a diagnostic recommendation to the primary treatment team 95% of the time.ConclusionsHandshake stewardship has the potential to identify and intervene on diagnostic errors for hospitalized children.


2021 ◽  
pp. bmjqs-2020-011593
Author(s):  
Traber D Giardina ◽  
Saritha Korukonda ◽  
Umber Shahid ◽  
Viralkumar Vaghani ◽  
Divvy K Upadhyay ◽  
...  

BackgroundPatient complaints are associated with adverse events and malpractice claims but underused in patient safety improvement.ObjectiveTo systematically evaluate the use of patient complaint data to identify safety concerns related to diagnosis as an initial step to using this information to facilitate learning and improvement.MethodsWe reviewed patient complaints submitted to Geisinger, a large healthcare organisation in the USA, from August to December 2017 (cohort 1) and January to June 2018 (cohort 2). We selected complaints more likely to be associated with diagnostic concerns in Geisinger’s existing complaint taxonomy. Investigators reviewed all complaint summaries and identified cases as ‘concerning’ for diagnostic error using the National Academy of Medicine’s definition of diagnostic error. For all ‘concerning’ cases, a clinician-reviewer evaluated the associated investigation report and the patient’s medical record to identify any missed opportunities in making a correct or timely diagnosis. In cohort 2, we selected a 10% sample of ‘concerning’ cases to test this smaller pragmatic sample as a proof of concept for future organisational monitoring.ResultsIn cohort 1, we reviewed 1865 complaint summaries and identified 177 (9.5%) concerning reports. Review and analysis identified 39 diagnostic errors. Most were categorised as ‘Clinical Care issues’ (27, 69.2%), defined as concerns/questions related to the care that is provided by clinicians in any setting. In cohort 2, we reviewed 2423 patient complaint summaries and identified 310 (12.8%) concerning reports. The 10% sample (n=31 cases) contained five diagnostic errors. Qualitative analysis of cohort 1 cases identified concerns about return visits for persistent and/or worsening symptoms, interpersonal issues and diagnostic testing.ConclusionsAnalysis of patient complaint data and corresponding medical record review identifies patterns of failures in the diagnostic process reported by patients and families. Health systems could systematically analyse available data on patient complaints to monitor diagnostic safety concerns and identify opportunities for learning and improvement.


Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Martin A. Schaller-Paule ◽  
Helmuth Steinmetz ◽  
Friederike S. Vollmer ◽  
Melissa Plesac ◽  
Felix Wicke ◽  
...  

Abstract Objectives Errors in clinical reasoning are a major factor for delayed or flawed diagnoses and put patient safety at risk. The diagnostic process is highly dependent on dynamic team factors, local hospital organization structure and culture, and cognitive factors. In everyday decision-making, physicians engage that challenge partly by relying on heuristics – subconscious mental short-cuts that are based on intuition and experience. Without structural corrective mechanisms, clinical judgement under time pressure creates space for harms resulting from systems and cognitive errors. Based on a case-example, we outline different pitfalls and provide strategies aimed at reducing diagnostic errors in health care. Case presentation A 67-year-old male patient was referred to the neurology department by his primary-care physician with the diagnosis of exacerbation of known myasthenia gravis. He reported shortness of breath and generalized weakness, but no other symptoms. Diagnosis of respiratory distress due to a myasthenic crisis was made and immunosuppressive therapy and pyridostigmine were given and plasmapheresis was performed without clinical improvement. Two weeks into the hospital stay, the patient’s dyspnea worsened. A CT scan revealed extensive segmental and subsegmental pulmonary emboli. Conclusions Faulty data gathering and flawed data synthesis are major drivers of diagnostic errors. While there is limited evidence for individual debiasing strategies, improving team factors and structural conditions can have substantial impact on the extent of diagnostic errors. Healthcare organizations should provide the structural supports to address errors and promote a constructive culture of patient safety.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eliada Pampoulou ◽  
Donald R. Fuller

PurposeWhen the augmentative and alternative communication (ACC) model (Lloyd et al., 1990) was proposed, these components of symbols were not considered, nor were they contemplated when superordinate (Lloyd and Fuller, 1986) and subordinate levels (Fuller et al., 1992) of AAC symbol taxonomy were developed. The purpose of this paper is to revisit the ACC model and propose a new symbol classification system called multidimensional quaternary symbol continuum (MQSC)Design/methodology/approachThe field of AAC is evolving at a rapid rate in terms of its clinical, social, research and theoretical underpinnings. Advances in assessment and intervention methods, technology and social issues are all responsible to some degree for the significant changes that have occurred in the field of AAC over the last 30 years. For example, the number of aided symbol collections has increased almost exponentially over the past couple of decades. The proliferation of such a large variety of symbol collections represents a wide range of design attributes, physical attributes and linguistic characteristics for aided symbols and design attributes and linguistic characteristics for unaided symbols.FindingsTherefore, it may be time to revisit the AAC model and more specifically, one of its transmission processes referred to as the means to represent.Originality/valueThe focus of this theoretical paper then, is on the current classification of symbols, issues with respect to the current classification of symbols in terms of ambiguity of terminology and the evolution of symbols, and a proposal for a new means of classifying the means to represent.Peer reviewThe peer review history for this article is available at: https://publons.com/publon10.1108/JET-04-2021-0024


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