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The reporting radiologist may not know enough to identify or recognise the relevant finding or to correctly dismiss insignificant abnormalities. He may be complacent or apply faulty reasoning.

She may consistently over- or under-read abnormalities. He may not communicate his findings or their significance appropriately [ 27 ]. Unavailability of previous studies for comparison was a more common contributor in the pre-PACS [picture archiving and communication system] era, but should not be a significant factor in the current digital age. Inadequate clinical information or inappropriate expectations of the capabilities of a radiological technique can lead to misunderstanding or miscommunication between the referring doctor and the radiologist [ 33 ].

The impact of lack of clinical information may be over-estimated, however. In , Tudor evaluated the impact of the availability of clinical information on error rates when reporting plain radiographs. Frequent clinico-radiological contacts have been shown to have a significant positive influence on clinical diagnosis and further patient management; these are best undertaken through formal clinico-radiological conferences [ 34 ], but are often informal, and can have a distracting effect when they interfere with other, ongoing work.

Modern healthcare systems frequently demand what has been called hyper-efficient radiology, where almost instantaneous interpretation of large datasets by radiologists is expected, often in patients with multiple co-morbidities, and sometimes for clinicians whose in-depth knowledge of the patients is limited or suboptimal [ 35 ]. The pace and pattern of in-hospital care often results in imaging tests being requested before patients have been carefully examined or before detailed histories have been taken. It is hardly surprising that relevant information is not always communicated fully or in a timely manner.

There is constant pressure on radiology departments to increase speed and output, often without adequate prior planning of workforce requirements. Error rates in reporting body CT have been shown to increase substantially when the number of cases exceeds a daily threshold of 20 [ 30 ].

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Many of us feel we are reporting too many studies, too quickly, without adequate time to fully consider our reports. This results in the obvious risk of reduced accuracy in what we report, but also in more unexpected dangers. Data from [ 37 ] show variation in the number of clinical radiologists per , population in selected European countries, ranging from 3. Against this background, the total number of imaging tests performed in virtually all developed countries continues to rise, with the greatest increase in data- and labour-intensive cross-sectional imaging studies ultrasound, CT and MR.

In , a national survey of radiologist workload showed that in , Ireland had approximately two-thirds of the consultant radiologists needed to cope with the workload at the time, applying international norms [ 38 — 40 ]. With increasing workload since that time, and only a modest increase in radiologist numbers, that radiologist shortfall has only worsened. The decrease in detection rate was greater among residents than attending radiologists. The authors quote conflicting research from the s and s, some of which found a lower rate of detection of lung nodules on chest x-rays at the end of the day, and some which found no change in performance between early and late reporting [ 41 ].

The length of continuous duty shifts and work hours for many healthcare professionals is much greater than that allowed in other safety-conscious industries, such as transportation or nuclear power [ 42 ]. Sleep deprivation has been shown experimentally to produce effects on certain mental tasks equivalent to alcohol intoxication [ 42 ]. Not surprisingly, this form of fatigue increases later in the day, and leads to unconscious taking of shortcuts in cognitive processes, resulting in poor judgement and diagnostic errors. Radiology trainees providing preliminary interpretations during off-hours are especially prone to this effect [ 43 ].

Inattentional blindness describes the phenomenon wherein observers miss an unexpected but salient event when engaged in a different task. Researchers from the Harvard Visual Attention Lab provided 24 experienced radiologists with a lung nodule detection task.

Each radiologist was given five CTs to interpret, each comprising — images, and each containing an average of ten lung nodules. In the last case, the image of a gorilla dark, in contrast to bright lung nodules on lung window settings 48 times larger than the average nodule, was faded in and out close to a nodule over five frames.

Twenty of the 24 radiologists did not report seeing the gorilla, despite spending an average of 5. The current dominant theoretical model of cognitive processing in real-life decision-making is the dual-process theory of reasoning [ 43 , 45 ], which postulates type 1 automatic and type 2 more linear and deliberate processes. In radiology, pattern recognition leading to immediate diagnosis constitutes type 1 processing, while the deliberate reasoning that occurs when the abnormality pattern is not instantly recognised constitutes type 2 reasoning [ 43 ].

Dynamic oscillation occurs between these two forms of processing during decision-making. Both of these types of mental processing are subject to biases and errors, but type 1 processing is especially so, due to the mental shortcuts inherent in the process [ 43 ]. A cognitive bias is a replicable pattern in perceptual distortion, inaccurate judgement and illogical interpretation, persistently leading to the same pattern of poor judgement.


Type 1 processing is a useful and frequent technique used in radiological interpretation by experienced radiologists, and rather than eliminating it and its inherent biases, the best strategy for minimising these biases may be learning deliberate type 2 forcing strategies to override type 1 thinking where appropriate [ 43 ].

One might imagine that being aware of potential biases would empower a radiologist to avoid these pitfalls; however, experimental efforts to reduce diagnostic error in specialties other than radiology by applying de-biasing algorithms have been unsuccessful [ 1 ]. Examples of cognitive biases likely to feature in faulty radiological thinking [ 1 , 42 ].

Many radiologists have traditionally believed that their role in patient care consists in reporting imaging studies. This limited view is no longer tenable, as radiologists have expanded into areas of economic gatekeeping, multidisciplinary team participation, advocacy, and acting as controllers of patient and staff safety. Another role of increasing importance is that of identifying and learning from error and discrepancies, and leading efforts to change systems when systemic issues underpin such errors [ 46 ]. Although it requires a nuanced understanding of the complexity of medical care often not appreciated by patients, politicians or the mass media, acceptance of the concept of necessary fallibility needs to be encouraged; public education can help.

Fortunately, many errors identified by retrospective reviews are of little or no significance to patients; conversely, some significant errors are never discovered [ 3 ].

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The public has a right to expect that all healthcare professionals strive to exceed the appropriate threshold which defines the border between clinically acceptable, competent practice, and negligence or incompetence. Difficulties arise, however, in attempting to identify exactly where that threshold lies.

Quality management or quality improvement - QI in radiology involves the use of systematically collected and analysed data to ensure optimal quality of the service delivered to patients [ 48 ]. Increasingly, physician reimbursement for services and maintenance of licensing for practice are being tied to participation in such quality management or improvement activities [ 48 ].

Various strategies have been proposed as tools to help reduce the propensity for radiological error; some of these are focused and practical, while others are rather more nebulous and aspirational:.

Errors in diagnostic radiology | Radiology Reference Article |

During the education of radiology trainees potential error-committers of the future , the inclusion of meta-awareness in the curriculum can at least make future independent practitioners aware of limitations and biases to which they are subject but of which they may not have been conscious [ 43 ]. The use of radiological—pathological correlation in decision-making, where possible, can avoid some erroneous assumptions, and can ingrain the practice of seeking histological proof of diagnoses before accepting them as incontrovertible.

Defining quality metrics , and encouraging radiologists to contribute to the collation of these metrics and to meet the benchmarks derived therefrom, can promote a culture of questioning and validation. Radiology departments and larger healthcare agencies elsewhere are engaged in similar efforts [ 50 ]. The use of structured reporting has been advocated as an error reduction strategy.

Certainly, this has value in some types of studies, and has been shown to improve report content, comprehensiveness and clarity in body CT. A potential downside to the use of such standardised reports is the risk that unexpected significant findings outside the specific area of clinical concern may be missed by a clinician reading a standardised report under time pressure, and focusing only on the segment of the report that matches the pre-test clinical concern. Careful composition of a report conclusion by the reporting radiologist should minimise this risk.

Radiologists should pay appropriate attention to the structure, content and language of even those reports where standardised report templates are not being used. This can be considered as both a contribution to workload and an opportunity: acting as our own proofreaders gives us the facility to tweak our initial dictation to optimise its comprehensibility, and to make reading and understanding it easy.

We should embrace this opportunity rather than complaining about the time lost to this activity, and we should ensure that we train our future colleagues in this fundamental task of clear, effective communication. The use of computer-aided detection certainly has a role in minimising the likelihood of missing some radiologic abnormalities, especially in mammography and lung nodule detection on CT, but carries the negative consequence of the increased sensitivity being accompanied by decreased specificity [ 43 ]; radiologist input remains essential to sorting the wheat from the chaff.

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Accommodative relaxation shifting the focal point from near to far, or vice versa is an effective strategy for reducing visual fatigue, and should be performed at least twice per hour during prolonged radiology reporting [ 43 ]. This does not mean that we should be hidebound by these scoring systems.

US experience with RadPeer scoring has been similar, leading to an overemphasis on scoring and underemphasis on commenting, and low compliance with little feedback [ 55 ]. Marked variability in inter-rater agreement has been found in the assignment of RadPeer scores to radiological discrepancies [ 56 ]. Over time, in response to greater experience with its use, the language and scoring system in RadPeer has been modified [ 57 ]. Therefore, the emphasis on considering cases of error or discrepancy is moving away from the assignment of specific scores, and towards fostering a shared learning experience [ 58 ].

QI discrepancy meetings : Studies have recently shown that the introduction of a virtual platform for QI meetings, allowing radiologists to review cases and submit feedback on a common information technology IT platform at a time of their choosing as opposed to gathering all participants in a room at one time for the meeting , can significantly improve attendance and participation in these exercises, and thus increase available learning [ 59 , 60 ].

Presenting a small number of key images chosen by the meeting convener , as opposed to using the full PACS study file, is a way to reduce the potential for loss of anonymity of the patient and the reporting radiologist during QI meetings, while maintaining the meeting focus of the key learning points [ 61 ]. Locally adapted models of these meetings may be required in order to ensure maximum radiologist participation and to accommodate those who work exclusively in subspecialty areas or via teleradiology [ 62 ].

The Swedish eCare Feedback programme has been running for a number of years, based on extensive double-reporting, identification of cases where disagreement occurs, and collective study of those cases for learning points [ 30 ]. Inevitably, this approach tends to drive error recognition and reporting underground, with the consequent loss of opportunities for learning and process improvement. Hybrids are possible. In , Hussain et al.

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