Liability of interpreting too many radiographs

Mandating Limits on Workload, Duty, and Speed in Radiology

Research has not yet quantified the effects of workload or duty hours on the accuracy of radiologists. With the exception of a brief reduction in imaging studies during the 2020 peak of the COVID-19 pandemic, the workload of radiologists in the United States has seen relentless growth in recent years. One concern is that this increased demand could lead to reduced accuracy. Behavioral studies in species ranging from insects to humans have shown that decision speed is inversely correlated to decision accuracy. A potential solution is to institute workload and duty limits to optimize radiologist performance and patient safety. The concern, however, is that any prescribed mandated limits would be arbitrary and thus no more advantageous than allowing radiologists to self-regulate. Specific studies have been proposed to determine whether limits reduce error, and if so, to provide a principled basis for such limits. This could determine the precise susceptibility of individual radiologists to medical error as a function of speed during image viewing, the maximum number of studies that could be read during a work shift, and the appropriate shift duration as a function of time of day. Before principled recommendations for restrictions are made, however, it is important to understand how radiologists function both optimally and at the margins of adequate performance. This study examines the relationship between interpretation speed and error rates in radiology, the potential influence of artificial intelligence on reading speed and error rates, and the possible outcomes of imposed limits on both caseload and duty hours. This review concludes that the scientific evidence needed to make meaningful rules is lacking and notes that regulating workloads without scientific principles can be more harmful than not regulating at all.

Double Reading of Outsourced CT/MR Radiology Reports: Retrospective Analysis

OBJECTIVES

Our objective was to determine disagreement rates in radiological reports provided by using a double-reading protocol in a national teleradiology company.

METHODS

From January 2015 to July 2016, 134169 radiological exams from 36 French centers, benefited outsourced interpretations by certified radiologists, in both regular and after-hours activities. Of these, 2040 CT and MR-scans (1.5%) were subjected to a second opinion by other radiologists in the field of their anatomical specialty (cerebral, thoracic, abdominal-pelvic, and osteoarticular). A five-point agreement scale graded from 0 to 4 was assigned for each exam. Disagreements were considered as minor if no clinical consequence for patient (scores 1 and 2) and major if potential clinical consequence (score 3 and 4). Independent radiologists performed a retrospective analysis and a stratified statistical analysis.

RESULTS

Double reading was performed on CT-scans (n = 934/2040, 45.8%) and MR-scans (n = 1106/2040, 54.2%) performed in regular (80.1%) and after-hours activities (19.9%). Disagreement scores occurred in 437 exams (21.4%), including major disagreements in 59 (2.9%). Among these, 48/754 were assigned by the thoracic second reader (6.4%), 6/70 by the abdominal-pelvic second reader (8.6%), 3/901 by the osteoarticular second reader (0.3%), and 2/315 by the cerebral second reader (0.6%), with statistical significant difference. No additional disagreement rate was observed in regular and after-hours activities (P = 0.63).

CONCLUSIONS

Double-reading of outsourced CT and MRI interpretations yielded 21.4% disagreement rate, with potential clinical consequence for patient in 2,9% of the cases. These results are in accordance with those previously reported and suggests that quality assurance of outsourced interpretations is needed.

Deep Learning Improves Osteonecrosis Prediction of Femoral Head After Internal Fixation Using Hybrid Patient and Radiograph Variables

Femoral neck fractures (FNFs) are a great public health problem that leads to a high incidence of death and dysfunction. Osteonecrosis of the femoral head (ONFH) after internal fixation of FNF is a frequently reported complication and a major cause for reoperation. Early intervention can prevent osteonecrosis aggravation at the preliminary stage. However, at present, failure to diagnose asymptomatic ONFH after FNF fixation hinders effective intervention at early stages. The primary objective of this study was to develop a predictive model for postoperative ONFH using deep learning (DL) methods developed using plain X-ray radiographs and hybrid patient variables. A two-center retrospective study of patients who underwent closed reduction and cannulated screw fixation was performed. We trained a convolutional neural network (CNN) model using postoperative pelvic radiographs and the output regressive radiograph variables. A less experienced orthopedic doctor, and an experienced orthopedic doctor also evaluated and diagnosed the patients using postoperative pelvic radiographs. Hybrid nomograms were developed based on patient and radiograph variables to determine predictive performance. A total of 238 patients, including 95 ONFH patients and 143 non-ONFH patients, were included. A CNN model was trained using postoperative radiographs and output radiograph variables. The accuracy of the validation set was 0.873 for the CNN model, and the algorithm achieved an area under the curve (AUC) value of 0.912 for the prediction. The diagnostic and predictive ability of the algorithm was superior to that of the two doctors, based on the postoperative X-rays. The addition of DL-based radiograph variables to the clinical nomogram improved predictive performance, resulting in an AUC of 0.948 (95% CI, 0.920-0.976) and better calibration. The decision curve analysis showed that adding the DL increased the clinical usefulness of the nomogram compared with a clinical approach alone. In conclusion, we constructed a DL facilitated nomogram that incorporated a hybrid of radiograph and patient variables, which can be used to improve the prediction of preoperative osteonecrosis of the femoral head after internal fixation.

An investigation to ascertain whether or not time pressure influences the accuracy of final year student radiographers in abnormality detection when interpreting conventional appendicular trauma radiographs: A pilot study

INTRODUCTION

There is an increasing demand on diagnostic imaging departments, a shortage of radiologists, and a backlog of images requiring a report across several trusts in the UK. A negative impact on performance can result in significant outcomes for the patient. The aim of this study is to ascertain whether decisions made under time pressure will affect the accuracy of the interpretation of conventional radiographs.

METHODS

Final year undergraduate diagnostic radiography students were recruited [n = 21] and separated into three groups of seven at random, assigning time limits per image for a set of normal and abnormal conventional appendicular radiographs; 15 s (high pressure), 30 s (moderate pressure) and unlimited time (low pressure). Each image was assessed, and answers were recorded as normal or abnormal with an approximate location of the pathology.

RESULTS

The ANOVA test revealed no statistical significance amongst results. The mean accuracy was highest in the 15 s group (82.86%) and lowest in the unlimited time group (74.52%). The results also demonstrated a decrease in accuracy with increased image review times within the unlimited time group; with the quickest participant achieving 88.33% and the slowest, 56.67%.

CONCLUSION

The results demonstrated no statistical significance. However, it is recommended to conduct a similar study using sufficient reporting practitioners to enable direct parallels to be drawn with statistical significance.

IMPLICATIONS FOR PRACTICE

The results signify an importance for imaging departments to manage the number of staff and their workload. Subsequently, this aims to ensure reporting practitioners work at their optimum stress level for efficient work performance.

Performance of a Deep Learning Algorithm in Detecting Osteonecrosis of the Femoral Head on Digital Radiography: A Comparison With Assessments by Radiologists

OBJECTIVE. The objective of our study was to compare the sensitivity of a deep learning (DL) algorithm with the assessments by radiologists in diagnosing osteonecrosis of the femoral head (ONFH) using digital radiography. MATERIALS AND METHODS. We performed a two-center, retrospective, noninferiority study of consecutive patients (≥ 16 years old) with a diagnosis of ONFH based on MR images. We investigated the following four datasets of unilaterally cropped hip anteroposterior radiographs: training (n = 1346), internal validation (n = 148), temporal external test (n = 148), and geographic external test (n = 250). Diagnostic performance was measured for a DL algorithm, a less experienced radiologist, and an experienced radiologist. Noninferiority analyses for sensitivity were performed for the DL algorithm and both radiologists. Subgroup analysis for precollapse and postcollapse ONFH was done. RESULTS. Overall, 1892 hips (1037 diseased and 855 normal) were included. Sensitivity and specificity for the temporal external test set were 84.8% and 91.3% for the DL algorithm, 77.6% and 100.0% for the less experienced radiologist, and 82.4% and 100.0% for the experienced radiologist. Sensitivity and specificity for the geographic external test set were 75.2% and 97.2% for the DL algorithm, 77.6% and 75.0% for the less experienced radiologist, and 78.0% and 86.1% for the experienced radiologist. The sensitivity of the DL algorithm was noninferior to that of the assessments by both radiologists. The DL algorithm was more sensitive for precollapse ONFH than the assessment by the less experienced radiologist in the temporal external test set (75.9% vs 57.4%; 95% CI of the difference, 4.5-32.8%). CONCLUSION. The sensitivity of the DL algorithm for diagnosing ONFH using digital radiography was noninferior to that of both less experienced and experienced radiologist assessments.

Mammography to tomosynthesis: examining the differences between two-dimensional and segmented-three-dimensional visual search

Background

Radiological techniques for breast cancer detection are undergoing a massive technological shift—moving from mammography, a process that takes a two-dimensional (2D) image of breast tissue, to tomosynthesis, a technique that creates a segmented-three-dimensional (3D) image. There are distinct benefits of tomosynthesis over mammography with radiologists having fewer false positives and more accurate detections; yet there is a significant and meaningful disadvantage with tomosynthesis in that it takes longer to evaluate each patient. This added time can dramatically impact workflow and have negative attentional and cognitive impacts on interpretation of medical images. To better understand the nature of segmented-3D visual search and the implications for radiology, the current study looked to establish a new testing platform that could reliably examine differences between 2D and segmented-3D search.

Results

In Experiment 1, both professionals (radiology residents and certified radiologists) and non-professionals (undergraduate students) were found to have fewer false positives and were more accurate in segmented-3D displays, but at the cost of taking significantly longer in search. Experiment 2 tested a second group of non-professional participants, using a background that more closely resembled a mammogram, and replicated the results of Experiment 1—search was more accurate and there were fewer false alarms in segmented 3D displays but took more time.

Conclusion

The results of Experiments 1 and 2 matched the performance patterns found in previous radiology studies and in the clinic, suggesting this novel experimental paradigm potentially provides a flexible and cost-effective tool that can be utilized with non-professional populations to inform relevant visual search performance. From an academic perspective, this paradigm holds promise for examining the nature of segmented-3D visual search.

What is the relation between number of sessions worked and productivity of radiologists-a pilot study?

Increasing workloads and the current austerity measures are putting UK radiology departments under considerable stress. We need to look at the most efficient ways to manage radiology departments in order to cope with increasing demand. Consequently, a system is needed that can compare productivity between radiologists with different jobs. We measured workload in a UK radiology department and compared the productivities of consultants working different numbers of sessions, which are called programmed activities (PAs), to identify the optimal job plan structure for reporting productivity. Reporting data was gathered from electronic records for 14 consultants working different numbers of PA during the period April 2010-March 2011. These were converted into relative value unit (RVU) scores using a modified RCSI RVU system. Crude and net workloads were calculated for each consultant by dividing their total RVU score by the number of PAs they were contracted for and how many they spent reporting. The consultants reported 118,001 imaging studies. There was statistically significant variation in productivity between consultants working different numbers of PAs on χ (2) analysis (p < 0.05). Consultants working 12 PAs were more productive than consultants working 11 PAs, with net workloads of 7636 RVU/PA/year versus net 6146 RVU/PA/year, p < 0.05. Although UK consultants working 12 PAs per week are more productive than their colleagues, the reasons why are unclear. We have identified a method that can be developed further to identify efficient working practices in UK radiology departments. However, a UK-specific RVU system would make this productivity analysis more accurate.

Error and discrepancy in radiology: inevitable or avoidable?

Errors and discrepancies in radiology practice are uncomfortably common, with an estimated day-to-day rate of 3-5% of studies reported, and much higher rates reported in many targeted studies. Nonetheless, the meaning of the terms "error" and "discrepancy" and the relationship to medical negligence are frequently misunderstood. This review outlines the incidence of such events, the ways they can be categorized to aid understanding, and potential contributing factors, both human- and system-based. Possible strategies to minimise error are considered, along with the means of dealing with perceived underperformance when it is identified. The inevitability of imperfection is explained, while the importance of striving to minimise such imperfection is emphasised.

TEACHING POINTS

• Discrepancies between radiology reports and subsequent patient outcomes are not inevitably errors. • Radiologist reporting performance cannot be perfect, and some errors are inevitable. • Error or discrepancy in radiology reporting does not equate negligence. • Radiologist errors occur for many reasons, both human- and system-derived. • Strategies exist to minimise error causes and to learn from errors made.

Improving Patient Care Through Medical Image Perception Research

The interpretation of medical images across medical specialties is critical to patient care. As technology changes, so does health care, and clinicians today are increasingly viewing medical images in a variety of environments. Although access to such data is useful, even clinicians with expertise in image interpretation make errors. These errors may become more frequent as clinician workdays become longer and the number of images to be interpreted becomes larger. To prevent errors in medical image interpretation, we need to understand the underlying perceptual and cognitive mechanisms that guide image interpretation. We can then use what is learned to develop better training methods, automated image analysis, and processing tools. We can devise methods to reduce clinician fatigue and stress, and develop practice guidelines thereby improving patient care and outcomes.

Delayed diagnosis of lung cancer after missed vertebral metastasis on CT

A 71-year-old man presented with a 4-month history of severe atraumatic monolateral hip pain. Radiographs were normal, and MRI had to be aborted owing to heating up of a remnant of an old spinal cord stimulator. CT revealed squamous cell lung carcinoma with widespread metastases of the spine and pelvis, causing L1 nerve root compression. In retrospect, a lytic lesion consistent with spinal metastasis was found on CT taken 5 months previously, soon after the onset of hip pain, but this was missed by the reporting radiologist at that time. This case highlights that errors in radiology reporting are inevitable, but can be minimized by using a systematic approach to carefully review all available images to avoid missing unexpected pathology.

Medical imaging displays and their use in image interpretation

The adequate and repeatable performance of the image display system is a key element of information technology platforms in a modern radiology department. However, despite the wide availability of high-end computing platforms and advanced color and gray-scale monitors, the quality and properties of the final displayed medical image may often be inadequate for diagnostic purposes if the displays are not configured and maintained properly. In this article-an expanded version of the Radiological Society of North America educational module "Image Display"-the authors discuss fundamentals of image display hardware, quality control and quality assurance processes for optimal image interpretation settings, and parameters of the viewing environment that influence reader performance. Radiologists, medical physicists, and other allied professionals should strive to understand the role of display technology and proper usage for a quality radiology practice. The display settings and display quality control and quality assurance processes described in this article can help ensure high standards of perceived image quality and image interpretation accuracy.

Workload of consultant radiologists in a large DGH and how it compares to international benchmarks

AIM

To measure radiologist workloads in a UK radiology department using relative value units (RVUs), and compared these data to current international standards from Australia and Ireland.

MATERIALS AND METHODS

Data on reporting throughput was gathered for 13.5 whole-time equivalent (WTE) consultants at the DGHs of East Lancashire Hospitals Trust (ELHT) between April 2010 to March 2011. RVUs were assigned to the reported imaging studies to create a crude RVU/WTE score. This was compared to benchmarks from Australia and results from a similar study in Ireland. Time spent on teaching, multidisciplinary teams, and administration was factored in to create a net RVU/WTE score, more accurately assessing workload.

RESULTS

Radiologists in ELHT reported 110,315 imaging studies, producing a total of 649,617 RVUs. Crude reporting workloads were 48,119.78 RVUs/WTE, and net workloads were 83,674.00 RVUs/WTE (with consultants spending 42.49% of their time on non-reporting commitments). These crude and net workloads are far above the Australian maximum reporting benchmark of 45,000 RVUs.

CONCLUSION

The workload is much higher than international benchmarks, indicating high-quality service and excellent value for money, but also highlights understaffing. Foreign RVU systems do not accurately reflect current UK practices and a UK-specific RVU system should be developed to assess staffing and analyse performance.

Do long radiology workdays affect nodule detection in dynamic CT interpretation?

PURPOSE

A previous study demonstrated decreased diagnostic accuracy for finding fractures and decreased ability to focus on skeletal radiographs after a long working day. Skeletal radiographic examinations commonly have images that are displayed statically. The aim of this study was to investigate whether diagnostic accuracy for detecting pulmonary nodules on CT of the chest displayed dynamically would be similarly affected by fatigue.

METHODS

Twenty-two radiologists and 22 residents were given 2 tests searching CT chest sequences for a solitary pulmonary nodule before and after a day of clinical reading. To measure search time, 10 lung CT sequences, each containing 20 consecutive sections and a single nodule, were inspected using free search and navigation. To measure diagnostic accuracy, 100 CT sequences, each with 20 sections and half with nodules, were displayed at preset scrolling speed and duration. Accuracy was measured using receiver operating characteristic curve analysis. Visual strain was measured via dark vergence, an indicator of the ability to keep the eyes focused on the display.

RESULTS

Diagnostic accuracy was reduced after a day of clinical reading (P = .0246), but search time was not affected (P > .05). After a day of reading, dark vergence was significantly larger and more variable (P = .0098), reflecting higher levels of visual strain, and subjective ratings of fatigue were also higher.

CONCLUSIONS

After their usual workday, radiologists experience increased fatigue and decreased diagnostic accuracy for detecting pulmonary nodules on CT. Effects of fatigue may be mitigated by active interaction with the display.

Ductal carcinoma in situ in the Department of Defense

OBJECTIVE

Our objective is to investigate some of the trends and variables within the ductal carcinoma in situ (DCIS) diagnosed population and to compare them with the greater civilian populations to identify any possible areas of deficiency or superiority in comparison with civilian institutions.

DESIGN

A retrospective analysis of 5023 patients.

SETTING

81st Medical Group Clinical Research Laboratory at Keesler AFB, Mississippi.

PARTICIPANTS

All patients treated for ductal carcinoma in situ entered into the Automated Central Tumor Registry (ACTUR) between January 1988 and December 2009.

RESULTS

Overall, the rate of finding invasive components after surgery for suspected DCIS was 8.6% (95% confidence interval [CI] = 7.79-9.33). Compared with other published rates, the military has a statistically significant lower rate (p < 0.001). From age 25 until age 65, there is a significant negative correlation of finding invasive cancer after treatment for DCIS (Spearman Rank Correlation = -0.051, p = 0.001). No statistically significant correlations were found between tumor size or grade and finding an invasive component.

CONCLUSIONS

The military medical system has provided a reduced probability of finding invasive cancer after treatment for DCIS compared to civilian institutions. Reduced physician workload, patient proactiveness, and public health involvement are among the likely factors.

Measuring radiologist workload: how to do it, and why it matters

This article discusses the results and implications of a nationwide survey of radiologist workload. Although the results are specific to one country, the method used, the underlying issues and the discussion engendered should be of interest to all radiologists worldwide. The balance between quality and quantity is highlighted, and the growing impact of activities outside of traditional reporting is considered. Variations in health care funding and staffing amongst countries clearly influence patterns of workload. It is hoped that this discussion will lead other radiologists to consider the method used, and to analyse workload in other countries, with a view to creating more robust workload data and stimulating debate.

Clinical Risk Management in radiology. Part II: applied examples and concluding remarks

With the aim of providing a clearer understanding of the tools used for evaluating risk in the radiological setting and how they are applied, this second part presents two practical examples. The first is a proactive analysis applied to CT, whereas the second is a reactive analysis performed following a sentinel event triggered by a CT study allocated to the wrong patient in the RIS-PACS system.

Teleradiology in Singapore – Taking Stock and Looking Ahead

Teleradiology will have a significant impact on the delivery of healthcare and the practice of medicine. In order to ensure a positive outcome, the expected benefits, limitations and potential pitfalls of teleradiology must be carefully considered. For Singapore, teleradiology can be used to facilitate a quantum leap in the standards of radiological services. This can be achieved through the development of an integrated, nationwide, high-speed radiology network which will allow patients to have access to high-quality and responsive subspecialty radiology expertise located throughout the country. If judiciously implemented, teleradiology has the potential to propel Singapore radiology to an unprecedented level of professional quality and service delivery, and will provide the framework for sustainable radiological insourcing from other countries.

Radiological error: analysis, standard setting, targeted instruction and teamworking

Diagnostic radiology does not have objective benchmarks for acceptable levels of missed diagnoses. Until now, data collection of radiological discrepancies has been very time consuming. The culture within the specialty did not encourage it. However, public concern about patient safety is increasing. There have been recent innovations in compiling radiological interpretive discrepancy rates which may facilitate radiological standard setting. However standard setting alone will not optimise radiologists' performance or patient safety. We must use these new techniques in radiological discrepancy detection to stimulate greater knowledge sharing, targeted instruction and teamworking among radiologists. Not all radiological discrepancies are errors. Radiological discrepancy programmes must not be abused as an instrument for discrediting individual radiologists. Discrepancy rates must not be distorted as a weapon in turf battles. Radiological errors may be due to many causes and are often multifactorial. A systems approach to radiological error is required. Meaningful analysis of radiological discrepancies and errors is challenging. Valid standard setting will take time. Meanwhile, we need to develop top-up training, mentoring and rehabilitation programmes.

Radiological error: analysis, standard setting, targeted instruction and teamworking

Diagnostic radiology does not have objective benchmarks for acceptable levels of missed diagnoses. Until now, data collection of radiological discrepancies has been very time consuming. The culture within the specialty did not encourage it. However, public concern about patient safety is increasing. There have been recent innovations in compiling radiological interpretive discrepancy rates which may facilitate radiological standard setting. However standard setting alone will not optimise radiologists' performance or patient safety. We must use these new techniques in radiological discrepancy detection to stimulate greater knowledge sharing, targeted instruction and teamworking among radiologists. Not all radiological discrepancies are errors. Radiological discrepancy programmes must not be abused as an instrument for discrediting individual radiologists. Discrepancy rates must not be distorted as a weapon in turf battles. Radiological errors may be due to many causes and are often multifactorial. A systems approach to radiological error is required. Meaningful analysis of radiological discrepancies and errors is challenging. Valid standard setting will take time. Meanwhile, we need to develop top-up training, mentoring and rehabilitation programmes.

The private-practice perspective of the manpower crisis in radiology: Greener pastures?

Rising consumer expectations and a rapidly aging population point to a long-term shortage of all physicians, including radiologists. While attention has been drawn to the escalating manpower crisis in academic radiology departments, the private-practice perspective has been generally overlooked. Although clinical workloads and income are higher in private practice, studies have shown higher satisfaction levels (likely because of a greater variety of work) among academic radiologists. As the distinction between community and teaching hospitals has become increasingly blurred, there is now considerable overlap in the skill sets, sources of job satisfaction, and stresses that are encountered in both practice settings. Perhaps more than at any time in the recent past, diagnostic radiologists in academic and private practice share more in common than any perceived differences. Both groups must work together in concert with the ACR to address the growing manpower shortage, as well as the other challenges that confront diagnostic radiology at the beginning of the 21st century.

Trends in on-call workload in an academic medical center radiology department 1998-20021

RATIONALE AND OBJECTIVES

The workload in radiology departments is increasing rapidly. This study was designed to determine whether and to what extent the workload is being generated outside of traditional working hours (defined as 0800-1700 Monday thru Friday, excluding holidays).

MATERIALS AND METHODS

Exam statistics were derived from the radiology department's automated examination scheduling and reporting system for four successive fiscal years. The distribution of the number of studies completed throughout the 24-hour day and the 7-day week was charted.

RESULTS

A large proportion of studies are being completed outside of traditional working hours. Moreover, as the overall workload of the department increased, the proportion of studies being completed during nontraditional working hours was increasing at an even faster pace, particularly in the cross-sectional imaging modalities. Computed tomography, magnetic resonance imaging, and ultrasound have increased by 59%, 51%, and 30%, respectively, over 4 years. The on-call proportions have increased from 34% to 40% and 13% to 18% for computed tomography and ultrasound, respectively, over 4 years and from 44% to 50% for magnetic resonance imaging over 3 years.

CONCLUSION

These trends have implications for radiologist and radiology technologist staffing. The department has already modified the scheduling of technologist staffing to provide in-house extended-hours coverage in most modalities. As the number of studies conducted outside of traditional working hours continues to expand and the demand for contemporaneous readings increases, radiologist staffing may need to be adjusted as well. Traditional on-call coverage may be insufficient to competently handle the growing workload. This may have particular implications for radiology residency programs.

2002 Australian radiology workforce report

This paper describes the current status of radiologist provision in Australia, and explores issues relating to its current adequacy, as well as analysing projections of supply and requirements, and their balancing. Data are drawn from several sources including the results of the Royal Australian and New Zealand College of Radiologists Workforce Survey 2000, and the report of the Australian Medical Workforce Advisory Committee Radiology Working Party 2001. The main conclusions to be drawn are that: (i) there is a current shortfall of radiologist supply in Australia; (ii) future requirements (taking all factors into consideration) are expected to grow at a greater rate than projected supply (based on the status quo); and (iii) supply of radiologists should therefore be increased. These conclusions are roughly in line with those from other countries, such as the UK, Canada and USA. Radiologists practising in Australia also appear to have relatively high productivity, including by some international comparisons. These findings are presented in the context of current issues in Australian medical imaging, including provider consolidation and corporatization, globalization and funding.

Error in radiology

Literature review indicates high levels of error within radiology. The aetiology of radiological error is multi-factorial. While individuals have a duty to progressively improve their performance, the experience of safety cultures in other high-risk human activities has shown that a system approach of root cause analysis is the method required to reduce error significantly.