Characteristics of Radiologists Serving as Medical Malpractice Expert Witnesses for Defense Versus Plaintiff

PurposePrevious studies have reported higher qualification characteristics for anesthesiologists, neurosurgeons, orthopedic surgeons, and otolaryngologists serving as defense (versus plaintiff) medical malpractice expert witnesses. We assessed such characteristics for radiologist expert witnesses.MethodsUsing the Westlaw legal research database, we identified radiologists serving as experts in all indexed medical malpractice cases between 2010 and 2019. Online databases were used to identify years of practice experience and scholarly bibliometrics. Using Medicare claims, individual radiologist practice types and mixes were ascertained. Radiologists testifying at least once each for defense and plaintiff were excluded from our defense-only versus plaintiff-only comparative analysis.ResultsInitial Boolean searches yielded 1,042 potential cases; subsequent manual review identified 179 radiologists testifying in 231 lawsuits: 143 testified in one case (58 defense, 85 plaintiff) and 36 testified in multiple cases (10 defense-only, 14 plaintiff-only, 12 both). The 68 defense-only experts had fewer years of practice experience than the 99 plaintiff-only experts (28.3 versus 31.8 years, P = .02), but the two groups were otherwise similar in both practice type (44.6% versus 54.9% academic, P = .62) and mix (63.8% versus 65.8% practiced as subspecialists, P = .37) and as well as numbers of publications (60.5 versus 62.8, P = .86), citations (1,994.1 versus 2,309.2, P = .56), and h-indices (17.2 versus 16.8, P = .89).ConclusionsIn contrast to other specialists, radiologists serving as medical malpractice expert witnesses for defense and plaintiff display similar qualifications across various characteristics. Published practice parameter guidelines and experts’ ability to blindly review archived original images might together explain this interspecialty discordance.     

Pediatric Emergency Imaging Studies in Academic Radiology Departments: A Nationwide Survey of Staffing Practices

ObjectiveParticularly for pediatric patients presenting with acute conditions or challenging diagnoses, identifying variation in emergency radiology staffing models is essential in establishing a standard of care. We conducted a cross-sectional survey among radiology departments at academic pediatric hospitals to evaluate staffing models for providing imaging interpretation for emergency department imaging requests.MethodsWe conducted an anonymous telephone survey of academic pediatric hospitals affiliated with an accredited radiology residency program across the United States. We queried the timing, location, and experience of reporting radiologists for initial and final interpretations of emergency department imaging studies, during weekday, overnight, and weekend hours. We compared weekday with overnight, and weekday with weekend, using Fisher’s exact test and an α of 0.05.ResultsSurveying 42 of 47 freestanding academic pediatric hospitals (89%), we found statistically significant differences for initial reporting radiologist, final reporting radiologist, and final report timing between weekday and overnight. We found statistically significant differences for initial reporting radiologist and final report timing between weekday and weekend. Attending radiologist involvement in initial reports was 100% during daytime, but only 33.3% and 69.0% during overnight and weekends. For initial interpretation during overnight and weekend, 38.1% and 28.6% use resident radiologists without attending radiologists, and 28.6% and 2.4% use teleradiology. All finalized reports as soon as possible during weekdays, but only 52.4% and 78.6% during overnight and weekend.DiscussionA minority of hospitals use 24-hour in-house radiology attending radiologist coverage. During overnight periods, the majority of academic pediatric emergency departments rely on resident radiologists without attending radiologist supervision or outside teleradiology services to provide initial reports. During weekend periods, over a quarter rely on resident radiologists without attending radiologist supervision for initial reporting. This demonstrates significant variation in staffing practices at academic pediatric hospitals. Future studies should look to determine whether this variation has any impact on standard of care.     

Radiology Practice Consolidation: Fewer but Bigger Groups Over Time

PurposeThe aim of this study was to assess recent trends in US radiology practice consolidation.MethodsRadiologist practice characteristics were obtained from the Medicare Physician Compare database for 2014 and 2018. Radiologists were classified on the basis of their largest identifiable practice affiliations. Single-specialty radiology practices were identified using practice names. Temporal trends in practice sizes were assessed.ResultsAt the individual radiologist level from 2014 to 2018, the fraction of all radiologists in groups with 1 or 2 members declined from 3.2% to 2.1%, 3 to 9 members from 10.2% to 6.7%, 10 to 24 members from 18.2% to 14.1%, 25 to 49 members from 16.6% to 15.1%, and 50 to 99 members from 13.3% to 11.5%. In contrast, the fraction in groups with 100 to 499 members increased from 15.7% to 21.8% and with ≥500 members from 22.9% to 28.7%. At the practice level, the fraction of all radiologists’ practices with 1 or 2 members decreased from 26.9% to 22.8%, whereas the fraction with 100 to 499 members increased from 7.6% to 10.2% and with ≥500 members from 2.5% to 4.1%. Similar shifts were present for single-specialty radiology practices and all geographic regions nationally. The 30,492 radiologists identified in 2014 were affiliated with 4,908 group practices, including 2,812 single-specialty practices. In comparison, the 32,096 radiologists identified in 2018 were affiliated with 4,193 group practices (a 14.6% decline), including 2,216 single-specialty practices (a 21.2% decline).ConclusionsIn very recent years, the US radiologist workforce has consolidated, leading to increased practice sizes and a substantial decline in the number of distinct practices, disproportionately affecting single-specialty radiology practices. The impact of this consolidation on cost, quality, and patient access merits further attention.     

Optimizing Imaging Clinical Decision Support: Perspectives of Pediatric Emergency Department Physicians

PurposeThe aim of this study was to solicit perspectives of pediatric emergency department physicians (PEDPs) to determine how software-based clinical decision support mechanisms (CDSMs) may integrate with existing imaging clinical decision support (ICDS) to optimize imaging utilization at the authors’ institution.MethodsThrough qualitative interviews, the authors explored how PEDPs define ICDS, how they seek and obtain radiologist consultation, and how the rollout of CDSMs at the institution may potentially affect clinical practice. Codes were developed and explicitly defined through literature review and analysis of a subset of interviews. Coding results informed thematic categories used to develop an explanatory model.ResultsAnalysis revealed three major thematic categories: (1) common influences on the decision process, (2) radiology consultation experience, and (3) PEDPs’ perspectives on CDSMs. PEDPs described radiologist consultation as a valuable component of ICDS but reported difficulty in coordinating imaging strategies with radiologists and other subspecialists. PEDPs described the exchange of ideas as especially worthwhile for scenarios that do not fit neatly into clinical pathways. Barriers to radiologist consultation include time, access to radiologists, and not wanting to disrupt radiologists’ workflow. PEDPs expressed optimism that CDSMs may improve their workflow and facilitate effective interaction with radiologists.ConclusionsPEDPs suggested that radiologist consultation will continue to be a valuable component of ICDS after the implementation of CDSMs by providing discussion-driven guidance to complement CDSM recommendations. The results also indicate that radiologists may consider strategies to facilitate effective interaction with PEDPs and reconcile conflicts of CDSMs with clinical practice.     

Second-Opinion Reads in Interstitial Lung Disease Imaging: Added Value of Subspecialty Interpretation

PurposeThe purpose of this study was to determine how often a second-opinion interpretation of interstitial lung disease (ILD) by an academic cardiothoracic radiologist is discordant with the initial interpretation by a nonacademic radiologists and how often the clinical diagnosis determined by multidisciplinary consensus agrees with the initial and second-opinion interpretations.MethodsThis retrospective study included 364 consecutive second-opinion CT examination reports of imaging from nonacademic radiology practices from July 2014 to May 2016. The second-opinion interpretations, provided by seven fellowship-trained cardiothoracic radiologists, were compared with the initial interpretations and the clinical diagnoses determined by multidisciplinary consensus.ResultsTwo hundred ninety-six consecutive reports met the inclusion criteria, and two hundred had findings of ILD. The initial interpretations lacked specific diagnoses in 41% of reports, but the second-opinion reports lacked specific diagnoses in only 7%. When a diagnosis was provided, the second-opinion diagnosis disagreed with the initial interpretation in 25% of cases. The clinical-consensus diagnosis was concordant with that of the academic radiologists 85% of the time but concordant with the initial interpretation only 44% of the time. The academic radiologists’ diagnostic sensitivity was higher than that of the initial radiologists for the four most common diagnoses: usual interstitial pneumonitis (0.91 versus 0.4), sarcoidosis (0.94 versus 0.60), hypersensitivity pneumonitis (0.79 versus 0.17), and nonspecific interstitial pneumonitis (0.72 versus 0.14).ConclusionsAcademic cardiothoracic radiologists were more likely to provide specific diagnoses for ILD, and these diagnoses were more likely to be concordant with the multidisciplinary consensus.     

Use of a PACS Embedded System for Communicating Radiologist to Technologist Learning Opportunities and Patient Callbacks

ObjectiveThis study aimed to determine effect of modality, care setting, and radiology subspecialty on frequency of diagnostic image quality issues identified by radiologists during image interpretation.MethodsThis Institutional Review Board-exempt retrospective study was performed 10/1/18-6/30/20 at an academic radiology practice performing 700,000+ examinations annually. A closed-loop communication tool integrated in PACS workflow enabled radiologists to alert technologists to image quality issues. Radiologists categorized communications as requiring patient callback, or as technologist learning opportunities if image quality was adequate to generate a diagnostic report. Fisher's exact test assessed impact of imaging modality, radiology subspecialty, and care setting on radiologist-identified image quality issues.Results976,915 imaging examinations were performed during the study period. Radiologists generated 1,935 technologist learning opportunities (0.20%) and 208 callbacks (0.02%). Learning opportunity rates were highest for MRI (0.60%) when compared to CT (0.26%) and radiography (0.08%) (p<0.0001). The same was true for patient callbacks (MRI 0.13%, CT 0.02%, radiography 0.0006%; p<0.0001). Outpatient examinations generated more learning opportunities (1479/637,092; 0.23%) vs. inpatient (305/200,206; 0.15%) and Emergency Department (151/139,617; 0.11%) (p<0.0001). Abdominal subspecialists were most likely to generate learning opportunities when compared to other subspecialists and cardiovascular imagers were most likely to call a patient back.ConclusionsImage quality issues identified by radiologists during the interpretation process were rare and 10 times more commonly categorized as learning opportunities not interfering with a clinically adequate report than as requiring patient callback. Further work is necessary to determine if creating learning opportunities leads to fewer patients requiring repeat examinations.     

Workflow Interruptions and Effect on Study Interpretation Efficiency

BackgroundInterruptions have been shown to adversely impact efficiency, accuracy, and patient safety.ObjectiveTo analyze the frequency and types of interruptions and effect on report interpretation efficiency.Materials and methodsA business process improvement team was consulted to make detailed recordings of the activities of the radiologists. Activities were categorized as interpreting studies, active interruptions initiated by the radiologist, and passive interruptions initiated by an external source.ResultsThirteen board-certified, pediatric radiologists were observed for 61 hours. Radiologists spent 52% of their time interpreting studies, 29% on active interruptions, and 18% on passive interruptions. Approximately 50% of non-interpretive time involved in-person conversations or consults and 16% involved phone calls of which 67% were incoming. The longest time period without an interruption was 20 minutes. 85% of the time, an interruption came within 3 minutes of beginning an interpretation and lasted 1 minute or less 70% of the time. Interruptions increased the time a radiologist needed to read a study by 1 minute for radiographs, 2 minutes for ultrasounds, 6 minutes for CTs, and 10 minutes for magnetic resonance imaging.ConclusionTotal interruption time nearly equaled the total time interpreting studies for radiologists, and interruptions decreased efficiency and increased report interpretation times for all modalities studied. This study highlights the type and extent of interruptions in radiology and examines the effect on report interpretation times. With the frequency of interruptions and impact on efficiency, there is a need to dedicate resources to manage the radiologist workflow. Strategic interventions may ultimately improve outcomes, efficiency, and the overall work environment.     

The Patient Experience in Radiology: Observations From Over 3,500 Patient Feedback Reports in a Single Institution

PurposeTo identify factors associated with the patient experience in radiology based on patient feedback reports from a single institution.MethodsIn a departmental patient experience committee initiative, all imaging outpatients are provided names and roles of all departmental employees with whom they interact, along with contact information for providing feedback after their appointment. All resulting feedback was recorded in a web-based database. A total of 3,675 patient comments over a 3-year period were assessed in terms of major themes. Roles of employees recognized within the patient comments were also assessed.ResultsPatient feedback comments most commonly related to professional staff behavior (74.5%) and wait times (11.9%), and less commonly related to a spectrum of other issues (comfort during the exam, quality of the facilities, access to information regarding the exam, patient privacy, medical records, the radiology report, billing). The most common attributes relating to staff behavior involved patients’ perceptions of staff caring, professionalism, pleasantness, helpfulness, and efficiency. Employees most commonly recognized by the comments were the technologist (50.2%) and receptionist (31.6%) and much less often the radiologist (2.2%). No radiologist was in the top 10% of employees in terms of the number of comments received.ConclusionPatients' comments regarding their experiences in undergoing radiologic imaging were largely influenced by staff behavior and communication (particularly relating to technologists and receptionists), as well as wait times, with radiologists having a far lesser immediate impact. Radiologists are encouraged to engage in activities that promote direct visibility to their patients and thereby combat risks of the perceived “invisible” radiologist.     

Radiologists’ Self-Assessment Versus Peer Assessment of Perceived Probability of Recommending Additional Imaging

ObjectiveDetermine radiologist ability to accurately select the probability of recommendation of additional imaging (RAI) for themselves and colleagues when arrayed in a feedback report.MethodsIn this institutional review board–approved study, we analyzed 318,366 diagnostic imaging reports from examinations performed in the radiology department of a large quaternary teaching hospital during calendar year 2016. A validated machine learning algorithm identified reports containing RAI. A multivariable logistic regression model was then used to determine the probability of RAI. In 2018, an e-mailed survey asked radiologists to identify their own RAI probability and that of their colleagues from a report arrayed lowest to highest. Radiologists were grouped into quartiles based on their RAI probability. χ² Analysis compared self-assessment and assessment of colleagues between quartiles.ResultsForty-eight of 57 radiologists completed the survey (84.2%). Fourteen (29.2%) accurately self-identified their RAI probability (chose the correct quartile); 34 (70.8%) did not. There was no statistically significant difference between quartiles of radiologists and their ability to self-identify their RAI probability (ie, radiologists in the bottom or top quartile of RAI probabilities did not correctly predict their RAI probability). However, radiologists were better able to identify the RAI probability of their colleagues who were in the top and bottom quartiles.DiscussionRadiologists were unable to estimate their own RAI probability but were better at predicting the RAI probability of colleagues. Given that radiologists, and physicians in general, may be poor evaluators of their own performance, objective assessment tools are likely needed to help reduce unwarranted variation.     

Early Adoption of a Certainty Scale to Improve Diagnostic Certainty Communication

ObjectiveAssess the early voluntary adoption of a certainty scale to improve communicating diagnostic certainty in radiology reports.MethodsThis institutional review board–approved study was part of a multifaceted initiative to improve radiology report quality at a tertiary academic hospital. A committee comprised of radiology subspecialty division representatives worked to develop recommendations for communicating varying degrees of diagnostic certainty in radiology reports in the form of a certainty scale, made publicly available online, which specified the terms recommended and the terms to be avoided in radiology reports. Twelve radiologists voluntarily piloted the scale; use was not mandatory. We assessed proportion of recommended terms among all diagnostic certainty terms in the Impression section (primary outcome) of all reports generated by the radiologists. Certainty terms were extracted via natural language processing over a 22-week postintervention period (31,399 reports) and compared with the same 22 calendar weeks 1 year pre-intervention (24,244 reports) using Fisher’s exact test and statistical process control charts.ResultsOverall, the proportion of recommended terms significantly increased from 8,498 of 10,650 (80.0%) pre-intervention to 9,646 of 11,239 (85.8%) postintervention (P < .0001 and by statistical process control). The proportion of recommended terms significantly increased for 8 of 12 radiologists (P < .0005 each), increased insignificantly for 3 radiologists (P > .05), and decreased without significance for 1 radiologist.ConclusionDesigning and implementing a certainty scale was associated with increased voluntary use of recommended certainty terms in a small radiologist cohort. Larger-scale interventions will be needed for adoption of the scale across a broad range of radiologists.     

Wellness Program Implementation in an Academic Radiology Department: Determination of Need,Organizational Buy-in,and Outcomes

ObjectiveTo implement a multifaceted wellness program in an academic radiology department to prevent burnout and to assess initial outcomes with special focus on the challenges related to the coronavirus disease 2019 (COVID-19) pandemic.MethodsA wellness program was established to address institutional and personal factors of burnout. The program focused on interventions to improve efficiency of practice, provide personal and career support, and create a culture of wellness. The components of the program were designed with input from radiology faculty, and the program was financially supported by the hospital’s physician organization. A survey was performed 6 months after the initiation of the program to determine radiologist engagement and satisfaction. With the onset of the COVID-19 pandemic, a new survey was administered to identify needs of faculty and adjust initiatives. This study was exempt from institutional review board approval.ResultsThe majority of radiologists (79%) agreed or strongly agreed that the wellness program provided opportunities to connect with coworkers. All radiologists agreed that the program was helpful and should be continued. During the COVID-19 pandemic, 49% of physicians requested initiatives focused on well-being, emotional health, and mindfulness to support them during the crisis.ConclusionsThe implementation of a faculty wellness program in an academic radiology department addressed institutional and personal factors of burnout, allowed faculty to connect with coworkers, and was found to be helpful by all radiologists. The COVID-19 pandemic shifted needs to well-being and emotional health initiatives. Follow-up data are necessary to assess its effect on burnout reduction.     

Development and Implementation of a Multisite Registry Using Structured Templates for Actionable Findings in the Kidney

PurposeThe aim of this study was to scale structured report templates categorizing actionable renal findings across health systems and create a centralized registry of patient and report data.MethodsIn January 2017, three academic radiology departments agreed to prospectively include identical structured templates categorizing the malignant likelihood of renal findings in ≥90% of all adult ultrasound, MRI, and CT reports, a new approach for two sites. Between November 20, 2017, and September 30, 2019, deidentified HL7 report data were transmitted to a centralized ACR registry. An automated algorithm extracted categories. Radiologists were requested to addend reports with missing or incomplete templates after the first month. Separately, each site submitted patient sociodemographic and clinical data 12 months before and at least 3 months after enrollment.ResultsA total of 164,982 eligible radiology reports were transmitted to the registry; 4,159 (2.5%) were excluded because of missing categories or radiologist names. The final cohort included 160,823 examinations on 102,619 unique patients. Mean template use before and after addendum requests was 99.3% and 99.9% at SITE1, 86.5% and 94.6% at SITE2, and 91.4% and 96.0% at SITE3. Matching patient sociodemographic and clinical data were obtained on 96.9% of reports from SITE1, 94.2% from SITE2, and 96.0% from SITE3. Regulatory, cultural, and technology barriers to the creation of a multisite registry were identified.ConclusionsBarriers to the adoption of unified structured report templates for actionable kidney findings can be addressed. Deidentified report and patient data can be securely transmitted to an external registry. These data can facilitate the collection of diverse evidence-based population imaging outcomes.     

Influences of Radiology Trainees on Screening Mammography Interpretation

PurposeParticipation of radiology trainees in screening mammographic interpretation is a critical component of radiology residency and fellowship training. The aim of this study was to investigate and quantify the effects of trainee involvement on screening mammographic interpretation and diagnostic outcomes.MethodsScreening mammograms interpreted at an academic medical center by six dedicated breast imagers over a three-year period were identified, with cases interpreted by an attending radiologist alone or in conjunction with a trainee. Trainees included radiology residents, breast imaging fellows, and fellows from other radiology subspecialties during breast imaging rotations. Trainee participation, patient variables, results of diagnostic evaluations, and pathology were recorded.ResultsA total of 47,914 mammograms from 34,867 patients were included, with an overall recall rate for attending radiologists reading alone of 14.7% compared with 18.0% when involving a trainee (P < .0001). Overall cancer detection rate for attending radiologists reading alone was 5.7 per 1,000 compared with 5.2 per 1,000 when reading with a trainee (P = .517). When reading with a trainee, dense breasts represented a greater portion of recalls (P = .0001), and more frequently, greater than one abnormality was described in the breast (P = .013). Detection of ductal carcinoma in situ versus invasive carcinoma or invasive cancer type was not significantly different. The mean size of cancers in patients recalled by attending radiologists alone was smaller, and nodal involvement was less frequent, though not statistically significantly.ConclusionsThese results demonstrate a significant overall increase in recall rate when interpreting screening mammograms with radiology trainees, with no change in cancer detection rate. Radiology faculty members should be aware of this potentiality and mitigate tendencies toward greater false positives.     

Best Reporting Practices for Multipart CT Scans: A Pilot Evaluation and Construction of the Optimal Analysis Methodology

PurposeCommunication failure between radiologists and referring physicians contributes to a substantial portion of medical errors. With a rising number of complex imaging orders and subspecialization among radiologists, the best method of reporting those results has yet to be evaluated. The aim of this study was to create, validate, and pilot a survey to reveal best practices for communication of radiologic findings, specifically addressing multipart CT scans of the chest, abdomen, and pelvis.MethodsA survey consisting of Likert-type and narrative response items was created, tested, and validated. It was then administered to physicians of five specialties (including radiology) at an urban quaternary care academic center and an affiliated community hospital.ResultsThe pilot survey results revealed that there was a small preference among both radiologists and referring physicians to have a single radiologist read in a single report for a multipart CT scan, rather than multiple subspecialist radiologists and reports. The findings were supported by narrative response explanations as well and demonstrate the importance of a rapid, clear, and cohesive image interpretation, despite the growing trend of radiology subspecialization. The results of the survey also confirmed its validity through an assessment with Messick’s five sources of validity evidence.ConclusionsThe survey’s validity indicates its generalizability to a future national survey to physicians of multiple specialties to further identify the preference of physicians on reporting of complex radiologic studies, in the setting of increased radiologic subspecialization.     

Agreement in the reporting of General Practitioner requested musculoskeletal radiographs: Reporting radiographers and consultant radiologists compared with an index radiologist

IntroductionThis study assessed the inter-observer agreement of reporting radiographers and consultant radiologists compared with an index radiologist when reporting General Practitioner (GP) requested musculoskeletal radiographs. The potential effect of discordant reports on patient management and outcome was also examined.MethodsThree reporting radiographers, three consultant radiologists and an index radiologist reported on a retrospective randomised sample of 219 GP requested musculoskeletal radiographs, in conditions simulating clinical practice. A speciality doctor in radiology compared the observers’ reports with the index radiologist report for agreement and assessed whether any discordance between reports was clinically important.ResultsOverall agreement with the index radiologist was 47.0% (95% CI, 40.5–53.6) and 51.6% (95% CI, 45.0–58.1) for the consultant radiologists and reporting radiographers, respectively. The results for the appendicular and axial skeleton were 48.6% (95% CI, 41.3–55.9) and 40.9% (95% CI, 27.7–55.6) for the radiologists, and 52.6% (95% CI, 45.2–59.8) and 47.7% (95% CI, 33.8–62.1) for the radiographers, respectively. The difference in overall observer agreement between the two professional groups with the index radiologist was not statistically significant (p = 0.34). Discordance with the index radiologist's reports was judged to be clinically important in less than 10% of the observer's reports.ConclusionReporting radiographers and consultant radiologists demonstrate similar levels of concordance with an index radiologist when reporting GP requested musculoskeletal radiographs.Implications for practiceThese findings contribute to the wider evidence base that selected radiographers with appropriate postgraduate education and training are proficient to report on musculoskeletal radiographs, irrespective of referral source.     

Ultrasound and Dual-Energy X-Ray Absorptiometry Report Transcription Error Rates and Strategies for Reduction

PurposeRadiologists play an essential role in patient care by providing accurate and timely results. An error-free radiology report is an expectation of both patients and referring physicians. Software is currently available that can eliminate measurement and side types of errors while saving radiologists and sonographers time. The objectives of this study were to evaluate the potential reduction in report errors, estimate the potential time savings associated with implementation, and conduct a cost-benefit analysis of implementing two software programs.MethodsData on the number of measurement errors and side errors in ultrasound and dual-energy x-ray absorptiometry reports were collected, and the time required for data entry that the software would reduce was measured by report type. Generalized estimating equations regression was used to estimate error rates and data entry times and corresponding 95% confidence intervals by report type for radiologists and sonographers. Current wages and report volumes were then applied to the time savings to estimate the annual wage savings. Projected volume increases were applied to the annual estimates to generate a 5-year savings estimate.ResultsOverall, measurement errors occurred in 6% to 28% of ultrasound reports, depending on the report type. Side errors were rare. It was estimated that over 5 years, the software could save $693,777 in radiologist wages and $130,771 in sonographer wages, a total of $824,548 (range, $621,866-$1,039,714).ConclusionsThe use of data integration software would both significantly reduce errors in ultrasound and dual-energy x-ray absorptiometry reports and save a considerable amount of time and money.     

The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program

PurposeAdvances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey was conducted among trainees and attending radiologists at a single residency program.MethodsAn anonymous questionnaire was distributed. Comparisons of categorical data between groups (trainees and attending radiologists) were made using Pearson χ² analysis or an exact analysis when required. Comparisons were made using the Wilcoxon rank sum test when the data were not normally distributed. An α level of 0.05 was used.ResultsThe overall response rate was 66% (69 of 104). Thirty-six percent of participants (n = 25) reported not having read a scientific medical article on the topic of artificial intelligence during the past 12 months. Twenty-nine percent of respondents (n = 12) reported using artificial intelligence tools during their daily work. Trainees were more likely to express doubts on whether they would have pursued diagnostic radiology as a career had they known of the potential impact artificial intelligence is predicted to have on the specialty (P = .0254) and were also more likely to plan to learn about the topic (P = .0401).ConclusionsRadiologists lack exposure to current scientific medical articles on artificial intelligence. Trainees are concerned by the implications artificial intelligence may have on their jobs and desire to learn about the topic. There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology.