Radiologist Burnout According to Surveyed Radiology Practice Leaders

Advancing radiology with GPT-4: Innovations in clinical applications, patient engagement, research, and learning

The rapid evolution of artificial intelligence (AI) in healthcare, particularly in radiology, underscores a transformative era marked by a potential for enhanced diagnostic precision, increased patient engagement, and streamlined clinical workflows. Amongst the key developments at the heart of this transformation are Large Language Models like the Generative Pre-trained Transformer 4 (GPT-4), whose integration into radiological practices could potentially herald a significant leap by assisting in the generation and summarization of radiology reports, aiding in differential diagnoses, and recommending evidence-based treatments. This review delves into the multifaceted potential applications of Large Language Models within radiology, using GPT-4 as an example, from improving diagnostic accuracy and reporting efficiency to translating complex medical findings into patient-friendly summaries. The review acknowledges the ethical, privacy, and technical challenges inherent in deploying AI technologies, emphasizing the importance of careful oversight, validation, and adherence to regulatory standards. Through a balanced discourse on the potential and pitfalls of GPT-4 in radiology, the article aims to provide a comprehensive overview of how these models have the potential to reshape the future of radiological services, fostering improvements in patient care, educational methodologies, and clinical research.

Formal wellness training of academic radiology leaders improves work-life conflict

OBJECTIVE

To investigate the effect of formal leadership training of academic radiology leaders within an academic center on their own burnout and professional fulfillment.

METHODS

The study cohort was academic radiology leaders within one of the largest academic organizations of academic radiologists within the United States. All academic radiology leaders within the organization were electronically mailed a weblink to a confidential IRB-approved survey in April 2021. The survey included validated questions from the Stanford Professional Fulfillment Index (PFI), values alignment, teamwork, overload, and work-family conflict. Academic leaders were invited in May 2021 to participate in instructor-led formal training on leading wellness focusing on 5 core leadership skills - emotional intelligence, self-care, resilience support, demonstrating care, and managing burnout. An identical follow-up survey was electronically mailed 6 months after initial training in November 2021.

RESULTS

The overall response rate of academic radiology leaders was 59% (19/32). For both measures, there was acceptable internal consistency (Cronbach's α = 0.63 for work exhaustion and α = 0.90 for fulfillment). There was a statistically significant improvement in work-family conflict (3.32 vs 2.86; p = 0.04). No statistically significant differences were identified for fulfillment, work exhaustion, alignment, work overload, and teamwork scores after training.

CONCLUSION

Formal instruction in leading wellness improved work-life conflict for academic radiology leaders. There was no significant change in burnout, fulfillment nor organizational alignment of the leaders.

CLINICAL RELEVANCE STATEMENT

Formal instruction in leading wellness raised awareness and improved work-life conflict in academic radiology leaders.

The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI

The advent of Deep Learning (DL) has significantly propelled the field of diagnostic radiology forward by enhancing image analysis and interpretation. The introduction of the Transformer architecture, followed by the development of Large Language Models (LLMs), has further revolutionized this domain. LLMs now possess the potential to automate and refine the radiology workflow, extending from report generation to assistance in diagnostics and patient care. The integration of multimodal technology with LLMs could potentially leapfrog these applications to unprecedented levels.However, LLMs come with unresolved challenges such as information hallucinations and biases, which can affect clinical reliability. Despite these issues, the legislative and guideline frameworks have yet to catch up with technological advancements. Radiologists must acquire a thorough understanding of these technologies to leverage LLMs' potential to the fullest while maintaining medical safety and ethics. This review aims to aid in that endeavor.

Impact of Interruptions During Screening Mammography on Physician Well-Being and Patient Care

OBJECTIVE

To assess the impact of interruptions on radiologists' efficiency, accuracy, and job satisfaction in interpreting screening mammograms.

METHODS

This institutional review board-approved retrospective reader study recruited nine breast radiologists from a single academic institution [name withheld] to interpret 150 screening mammograms performed between December 1, 2008, and December 31, 2015 under two different reading conditions, as follows: (1) uninterrupted batch reading and (2) interrupted reading. The 150 cases consisted of 125 normal mammograms and 25 mammograms with subtle breast cancers. Cases were divided into two groups of 75 cases each (cohort 1 and cohort 2), with a comparable distribution of cancer cases. Four rounds of 75 cases each were conducted with a 6-week washout period between rounds 2 and 3. After completing each interpretation session, readers completed a seven-question survey, assessing perceptions of mental and physical effort, level of frustration, and performance satisfaction. Clinical performance metrics (reading time, recall rate, sensitivity, specificity, accuracy, and positive predictive value 1) were calculated.

RESULTS

Recall rates were significantly (P = .04) higher during interrupted reading sessions (35.4%) than they were during uninterrupted batch reading sessions (31.4%). Accuracy was significantly (P = .049) worse in the interrupted reading sessions (69.5%), compared with uninterrupted sessions (73.6%). Differences in overall image interpretation times were not statistically significant (P = .065). Compared with uninterrupted batch reading sessions, readers during interrupted sessions reported feeling busier (P < .001), encountered higher levels of cognitive demand (P = .005), experienced elevated levels of physical fatigue (P = .004), and expressed lower levels of satisfaction with their performance (P = .041).

CONCLUSION

Interruptions during interpretation of screening mammography have deleterious effects on physician performance and their sense of well-being.

Should I Stay, or Should I Go? Early Phase Instrument Development of Workforce Movement-A Pilot Study with Breast Radiologists

OBJECTIVE

The goal of this study was to develop a psychometrically valid survey on workplace satisfaction and examine predictors of workforce movement among breast radiologists.

METHODS

Actively practicing members of the Society of Breast Imaging were invited to complete a survey on workplace satisfaction. Radiologists also indicated whether they had recently left their practice or were thinking of leaving their practice.

RESULTS

In total, 228 breast radiologists provided valid responses (8.7% response rate); 45% were thinking of leaving or had left their practice. Factor analysis yielded five factors, and discriminant function analysis found six main aspects associated with workforce movement in breast radiologists: (1) not enough work-life balance; (2) salary too low; (3) not feeling valued; (4) wanting a different challenge and/or more growth opportunity; (5) safety concerns; and (6) not feeling respected by physician leadership.

CONCLUSIONS

Pending further validation in larger and different cohorts, the survey created here can be administered by radiology practices to predict when breast radiologists are vulnerable to quitting. Atlhough this measure was designed for breast radiologists specifically, it could be adapted for other subspecialties.

Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports

PURPOSE

In this preliminary study, we aimed to evaluate the potential of the generative pre-trained transformer (GPT) series for generating radiology reports from concise imaging findings and compare its performance with radiologist-generated reports.

METHODS

This retrospective study involved 28 patients who underwent computed tomography (CT) scans and had a diagnosed disease with typical imaging findings. Radiology reports were generated using GPT-2, GPT-3.5, and GPT-4 based on the patient's age, gender, disease site, and imaging findings. We calculated the top-1, top-5 accuracy, and mean average precision (MAP) of differential diagnoses for GPT-2, GPT-3.5, GPT-4, and radiologists. Two board-certified radiologists evaluated the grammar and readability, image findings, impression, differential diagnosis, and overall quality of all reports using a 4-point scale.

RESULTS

Top-1 and Top-5 accuracies for the different diagnoses were highest for radiologists, followed by GPT-4, GPT-3.5, and GPT-2, in that order (Top-1: 1.00, 0.54, 0.54, and 0.21, respectively; Top-5: 1.00, 0.96, 0.89, and 0.54, respectively). There were no significant differences in qualitative scores about grammar and readability, image findings, and overall quality between radiologists and GPT-3.5 or GPT-4 (p > 0.05). However, qualitative scores of the GPT series in impression and differential diagnosis scores were significantly lower than those of radiologists (p < 0.05).

CONCLUSIONS

Our preliminary study suggests that GPT-3.5 and GPT-4 have the possibility to generate radiology reports with high readability and reasonable image findings from very short keywords; however, concerns persist regarding the accuracy of impressions and differential diagnoses, thereby requiring verification by radiologists.

Imaging Stewardship: Triage for Neuroradiology MR During Limited-Resource Hours

OBJECTIVES

To decrease call burden on pediatric neuroradiologists, we developed guidelines for appropriate use of MR overnight. These guidelines were implemented using triage by in-house generalist pediatric radiologists. Process measures and balancing measures were assessed during implementation.

METHODS

For this improvement project, interdepartmental consensus guidelines were developed using exploratory mixed-methods design. Implementation of triage used plan-do-study-act cycles. Process measures included reduction in the number of telephone calls, frequency of calls, triage decisions, and number and type of examinations ordered. Balancing measures included burden of time and effort to the generalist radiologists. Differences in examination orders between implementation intervals was assessed using Kruskal-Wallis, with significance at P < .05.

RESULTS

Consensus defined MR requests as "do," "defer," or "divert" (to CT). Guidelines decreased neuroradiologist calls 74% while adding minimal burden to the generalist radiologists. Most nights had zero or one triage request and the most common triage decision was "do," and the most common examination was routine brain MR. Number of MR ordered and completed overnight did not significantly change with triage.

DISCUSSION

Multidisciplinary consensus for use of pediatric neurological MR during limited resource hours overnight is an example of imaging stewardship that decreased the burden of calls and burnout for neuroradiologists while maintaining a comparable level of service to the ordering clinicians.

Improving traumatic fracture detection on radiographs with artificial intelligence support: a multi-reader study

Objectives

The aim of this study was to evaluate the diagnostic performance of nonspecialist readers with and without the use of an artificial intelligence (AI) support tool to detect traumatic fractures on radiographs of the appendicular skeleton.

Methods

The design was a retrospective, fully crossed multi-reader, multi-case study on a balanced dataset of patients (≥2 years of age) with an AI tool as a diagnostic intervention. Fifteen readers assessed 340 radiographic exams, with and without the AI tool in 2 different sessions and the time spent was automatically recorded. Reference standard was established by 3 consultant radiologists. Sensitivity, specificity, and false positives per patient were calculated.

Results

Patient-wise sensitivity increased from 72% to 80% (P < .05) and patient-wise specificity increased from 81% to 85% (P < .05) in exams aided by the AI tool compared to the unaided exams. The increase in sensitivity resulted in a relative reduction of missed fractures of 29%. The average rate of false positives per patient decreased from 0.16 to 0.14, corresponding to a relative reduction of 21%. There was no significant difference in average reading time spent per exam. The largest gain in fracture detection performance, with AI support, across all readers, was on nonobvious fractures with a significant increase in sensitivity of 11 percentage points (pp) (60%-71%).

Conclusions

The diagnostic performance for detection of traumatic fractures on radiographs of the appendicular skeleton improved among nonspecialist readers tested AI fracture detection support tool showed an overall reader improvement in sensitivity and specificity when supported by an AI tool. Improvement was seen in both sensitivity and specificity without negatively affecting the interpretation time.

Advances in knowledge

The division and analysis of obvious and nonobvious fractures are novel in AI reader comparison studies like this.

Incidence and factors associated with burnout in radiologists: A systematic review

Rationale and objectives

Burnout among physicians has a prevalence rate exceeding 50%. The radiology department is not immune to the burnout epidemic. Understanding and addressing burnout among radiologists has been a subject of recent interest. Thus, our study aims to systematically review studies reporting the prevalence of burnout in physicians in the radiology department while providing an overview of the factors associated with burnout among radiologists.

Materials and methods

The search was conducted from inception until November 13th, 2022, in PubMed, Embase, Education Resources Information Center, PsycINFO, and psycArticles. Studies reporting the prevalence of burnout or any subdimensions among radiology physicians, including residents, fellows, consultants, and attendings, were included. Data on study characteristics and estimates of burnout syndrome or any of its subdimensions were collected and summarized.

Results

After screening 6379 studies, 23 studies from seven countries were eligible. The number of participants ranged from 26 to 460 (median, 162; interquartile range, 91-264). In all, 18 studies (78.3%) employed a form of the Maslach Burnout Inventory. In comparison, four studies (17.4%) used the Stanford Professional Fulfillment Index, and one study (4.3%) used a single-item measure derived from the Zero Burnout Program survey. Overall burnout prevalence estimates were reported by 14 studies (60.9%) and varied from 33% to 88%. High burnout prevalence estimates were reported by only five studies (21.7%) and ranged from 5% to 62%. Emotional exhaustion and depersonalization prevalence estimates were reported by 16 studies (69.6%) and ranged from 11%-100% and 4%-97%, respectively. Furthermore, 15 studies (65.2%) reported low personal accomplishment prevalence, ranging from 14.7% to 84%. There were at least seven definitions for overall burnout and high burnout among the included studies, and there was high heterogeneity among the cutoff scores used for the burnout subdimensions.

Conclusion

Burnout in radiology is increasing globally, with prevalence estimates reaching 88% and 62% for overall and high burnout, respectively. A myriad of factors has been identified as contributing to the increased prevalence. Our data demonstrated significant variability in burnout prevalence estimates among radiologists and major disparities in burnout criteria, instrument tools, and study quality.

A pre-post study of stressors and burnout affecting breast radiologists before and during the COVID-19 pandemic

Rationale and objective

To compare burnout and stressors of breast radiologists prior to and during the COVID-19 pandemic.

Materials and methods

Members of the Society of Breast Imaging were emailed an IRB-approved survey in January 2021 during the COVID-19 pandemic. Survey included questions from the Maslach Burnout Inventory and specific stressors including work pace, work-life balance, care of dependents, and financial strain. Data were compared to previous surveys prior to the pandemic.

Results

The response rate was 25% (261/1061) for those who opened the email. Of the respondents, 74% (194/261) were female, 82% (214/261) were white, 73% (191/261) were full time, 71% (185/261) were fellowship trained, 41% (106/261) had more than 20 years of experience, and 30% (79/261) were in academic practice.Respondents in 2021 reported frequent levels of depersonalization (2.2) and emotional exhaustion (3.4) while reporting frequent levels of personal accomplishment (5.3), a protective factor. These values were nearly identical before the pandemic in 2020: (2.2, 3.5, 5.3, respectively, p = .9). Respondents rated practicing faster than they would like as the highest stressor; however, 5 of the 6 stressors improved after the pandemic onset (p < .05). Conversely, participants perceived these stresses had gotten slightly worse since the pandemic (p < .01). Almost 50% of respondents reported they were considering leaving their practice; the most common reason was work/life balance.

Conclusion

Burnout in breast radiologists remains frequent but unchanged during the COVID-19 pandemic. While participants perceived that some stressors were worse during the pandemic, there was slight improvement in most stressors between the pre-pandemic and pandemic cohorts.

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach

Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers derived from abdominopelvic computed tomography (CT) correlate with IHD risk, they are impractical to measure manually. Here, in a retrospective cohort of 8139 contrast-enhanced abdominopelvic CT examinations undergoing up to 5 years of follow-up, we developed multimodal opportunistic risk assessment models for IHD by automatically extracting BC features from abdominal CT images and integrating these with features from each patient's electronic medical record (EMR). Our predictive methods match and, in some cases, outperform clinical risk scores currently used in IHD risk assessment. We provide clinical interpretability of our model using a new method of determining tissue-level contributions from CT along with weightings of EMR features contributing to IHD risk. We conclude that such a multimodal approach, which automatically integrates BC biomarkers and EMR data, can enhance IHD risk assessment and aid primary prevention efforts for IHD. To further promote research, we release the Opportunistic L3 Ischemic heart disease (OL3I) dataset, the first public multimodal dataset for opportunistic CT prediction of IHD.

New trend in artificial intelligence-based assistive technology for thoracic imaging

Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggered by improvements in computing power, algorithm development, and the use of big data. In recent years, the application and development of AI technology in the medical field have intensified internationally. There is no doubt that AI will be used in clinical practice to assist in diagnostic imaging in the future. In qualitative diagnosis, it is desirable to develop an explainable AI that at least represents the basis of the diagnostic process. However, it must be kept in mind that AI is a physician-assistant system, and the final decision should be made by the physician while understanding the limitations of AI. The aim of this article is to review the application of AI technology in diagnostic imaging from PubMed database while particularly focusing on diagnostic imaging in thorax such as lesion detection and qualitative diagnosis in order to help radiologists and clinicians to become more familiar with AI in thorax.

Evaluating Health Disparities in Radiology Practices in New Jersey: Exploring Radiologist Geographical Distribution

OBJECTIVE

This study aimed to determine if a disproportionate number of radiologists practice in high-income versus low-income counties in New Jersey (NJ), identify which vulnerable populations are most in need of more radiologists, and discuss how these relative differences can ultimately influence health outcomes.

METHODS

The NJ Health Care Profile, a database overseen and maintained by the Division of Consumer Affairs, was queried for all actively practicing radiologists within the state of NJ. These results were grouped into diagnostic and interventional radiologists followed by further stratification of physicians based on the counties where they currently practice. The median household income and population size of each county for 2021 were obtained from the US Census database. The ratio of the population size of each county over the number of radiologists in that county was used as a surrogate marker for disparities in patient care within the state and was compared between counties grouped by levels of income.

RESULTS

Of the 1,186 board-certified radiologists actively practicing within the state of NJ, 86% are solely diagnostic radiologists and 14% are interventional radiologists. About 44% of radiologists practice within counties that are within the top one-third of median household income in NJ, 25% practice within counties in the middle one-third, and 31% practice within counties in the bottom one-third.

CONCLUSIONS

There is a disproportionate number of radiologists practicing in high-income counties as opposed to lower-income counties. A contradiction to this trend was noted in three low-income counties: Essex, Camden, and Atlantic County, all of which exhibited low numbers of individuals per radiologist that rivaled those of higher-income counties. This finding is a concrete measure of successful radiologist recruitment efforts within these counties during the past few years to combat the increased prevalence of disease and associated complications that historically marginalized communities tend to disproportionately exhibit. Other low-income counties should look to what Essex, Camden, and Atlantic County have done to increase radiologist recruitment to levels that rival those of high-income areas.

Prevalence of Burnout of Radiologists in Private Practice

PURPOSE

The aim of this study was to evaluate the prevalence and demographic factors associated with both burnout and fulfillment of private practice radiologists within the largest coalition of independent wholly physician-owned diagnostic radiology practices within the United States.

METHODS

The study cohort included practicing radiologists within the largest coalition of wholly radiologist-owned, independently practicing diagnostic radiology groups within the United States. Practicing radiologists within all 31 radiology private practices within the organization were electronically mailed a web link to a confidential institutional review board-approved survey in August and September 2021. The survey included validated questions from the Stanford Professional Fulfillment Index, individual and practice demographics, and self-care. Radiologists were classified as being burned out and professionally fulfilled on the basis of established cutoffs from the Professional Fulfillment Index.

RESULTS

The overall response rate was 20.6% (254 of 1,235). The overall rate of radiologist burnout was 46% (Cronbach's α = 0.92), and professional fulfillment was 26.7% (Cronbach's α = 0.91). The inverse association between professional fulfillment and burnout was highly significant (r = -0.66, P < .0001) on the basis of average scores. Radiologists who took call (evenings, overnight, and weekends) were statistically most likely to be burned out. Older radiologists were less likely to experience burnout. Factors statistically significantly associated with professional fulfillment were eating nutritious meals and exercising at least four times per week. No statistically significant association was seen between either burnout or fulfillment with gender, ethnicity, practice geography, or practice size.

CONCLUSIONS

In the largest coalition of independent wholly physician-owned diagnostic radiology practices across the United States, about one-half of radiologists were burned out, and just over one-quarter were professionally fulfilled. Taking call was significantly associated with radiologist burnout. Self-care habits were associated with professional fulfillment.

Leadership: Causing and Curing Burnout in Radiology

Burnout in US radiology has reached crisis proportions. Leaders play critical roles in both causing and preventing burnout. This article will review the current state of the crisis and how leaders can work to stop causing burnout as well as developing proactive strategies for preventing and mitigating burnout.

Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review

Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning systems to assist clinicians and improve interpretation accuracy. An understanding of the capabilities and limitations of modern machine learning systems is necessary for clinicians as these tools begin to permeate practice. This systematic review aimed to provide an overview of machine learning applications designed to facilitate CXR interpretation. A systematic search strategy was executed to identify research into machine learning algorithms capable of detecting >2 radiographic findings on CXRs published between January 2020 and September 2022. Model details and study characteristics, including risk of bias and quality, were summarized. Initially, 2248 articles were retrieved, with 46 included in the final review. Published models demonstrated strong standalone performance and were typically as accurate, or more accurate, than radiologists or non-radiologist clinicians. Multiple studies demonstrated an improvement in the clinical finding classification performance of clinicians when models acted as a diagnostic assistance device. Device performance was compared with that of clinicians in 30% of studies, while effects on clinical perception and diagnosis were evaluated in 19%. Only one study was prospectively run. On average, 128,662 images were used to train and validate models. Most classified less than eight clinical findings, while the three most comprehensive models classified 54, 72, and 124 findings. This review suggests that machine learning devices designed to facilitate CXR interpretation perform strongly, improve the detection performance of clinicians, and improve the efficiency of radiology workflow. Several limitations were identified, and clinician involvement and expertise will be key to driving the safe implementation of quality CXR machine learning systems.

Imaging Service Navigators: An Approach Toward More Efficient and Effective Communications

PURPOSE

Many practices have implemented support services to assist radiologists with noninterpretive tasks; however, little research has been performed to assess the overall effect of these services. The purpose of this study was to evaluate the effect of a team of imaging service navigators (ISNs) incorporated into a practice on (1) number of communications, (2) time saved by radiologists, and (3) radiologist satisfaction with the service.

METHODS

The numbers and types of reports dictated by radiologists were captured for 6-month periods before and after ISN implementation. Communication rates before and after implementation were then calculated. The amount of perceived time savings using the ISN team and satisfaction with the service were assessed through pre- and postimplementation surveys of participating radiologists. Mean and median time savings and satisfaction rates were calculated.

RESULTS

The overall communication rate increased from 2.196% before ISNs to 3.278% after ISNs (49% increase; 95% confidence interval, 47%-52%). Communication rates increased among all communication subtypes (critical, urgent, routine, and actionable), with the highest increases in urgent (94%) and actionable (75%) findings. Before implementation, radiologists reported spending 39 min on average per day on communications tasks, with only 33% of radiologists indicating that the communication process was efficient. After implementation, radiologists reported mean time savings of 28 min (95% confidence interval, 19.9-35.1), and 82% of radiologists indicated a positive or highly positive view of the ISN service.

CONCLUSIONS

After ISN implementation, communication rates increased and radiologists reported spending less time performing communications. Most radiologists were satisfied with the service.

Work From Home in Academic Radiology Departments: Advantages, Disadvantages and Strategies for the Future

To achieve necessary social distancing during the Covid-19 pandemic, working from home was introduced at most if not all academic radiology departments. Although initially thought to be a temporary adaptation, the popularity of working from home among faculty has made it likely that it will remain a component of radiology departments for the long term. This paper will review the potential advantages and disadvantages of working from home for an academic radiology department and suggest strategies to try to preserve the advantages and minimize the disadvantages.

Utilizing advanced practice providers in the paracentesis/thoracentesis clinic

In an era of increasing radiology volumes, including image-guided procedures, as well as decreased reimbursements, radiology practices are seeking ways to become more efficient to prevent radiologist burnout. One such strategy involves the employment of advanced practice providers to perform certain procedures. We describe steps departments can pursue to involve advanced practice providers within the radiology workforce, specifically in implementing an advance practice provider-driven paracentesis and thoracentesis clinic.

Burnout, Professional Fulfillment, Intention to Leave, and Sleep-Related Impairment among Radiology Trainees across the United States (US): A Multisite Epidemiologic Study

OBJECTIVE

To examine the prevalence of burnout among radiology trainees in the United States, and to study the relationships between burnout and professional fulfillment (PF), intent-to-leave (ITL), sleep-related impairment and self-compassion by gender.

METHODS

This cross-sectional study was conducted via an anonymous electronic survey sent to 11 large academic medical centers (Physician Wellness Academic Consortium) between January 2017 and September 2018. The survey included the Professional Fulfillment Index (PFI) and an abbreviated form of the PROMIS Sleep-related impairment (SRI) scale. Two-sample t-tests and chi-square exact tests were used for analysis (p < 0.05).

RESULTS

Two hundred forty-seven radiology residents responded to the survey. Out of these, 36.2% reported burnout, 37.4% endorsed PF, 64.8% reported sleep-related impairment, 7.6% expressed ITL. There were no significant differences between genders. Burnout was associated with reduced PF, increased sleep-impairment (p < 0.001 for both) and increased ITL (p = 0.02). Lower PF, peer support, perceived appreciation for and meaningfulness in work, alignment of organizational and personal values, self-compassion, and higher sleep impairment were associated with burnout (p < 0.001 for all). Burnout was associated with perceptions of less support from department leaders (p = 0.003), control over schedules (p = 0.001) and helpfulness of electronic health record systems (p = 0.01). ITL was associated with reduced PF, perceived work appreciation, and leadership support (p = 0.03, p = 0.04, and p = 0.007, respectively).

DISCUSSION

Burnout is prevalent among radiology residents. Many demonstrate sleep-impairment and reduced professional fulfillment, with a lesser fraction desiring to leave their institution. Key factors to burnout included peer and organizational support, electronic health record systems helpfulness, and personal factors like self-compassion and work appreciation.

Burnout amongst radiologists: A bibliometric study from 1993 to 2020

BACKGROUND

Burnout amongst radiologists is common in many different institutions and is increasing day by day. To battle burnout, we have to address the root causes already recognized in published literature. Therefore, it is crucial to examine and discern important publications.

AIM

To provide evidence-based data and trends related to burnout in radiologists so that researchers can work on it further and develop preventive strategies to overcome this problem.

METHODS

Bibliometric analysis conducted by two independent reviewers separately used Scopus Library for data extraction by using medical subject heading and International Classification of Diseases keywords. Forty-nine articles were selected for analysis after an extensive scrutiny. Statistical Package for the Social Sciences version 20 was used for analysis. Pearson correlation coefficient, Kruskal Wallis test, and Mann-Whitney U test were applied.

RESULTS

The most productive period with regards to the number of publications was between 2017 and 2019. A total of 160 authors contributed to the topic burnout among radiologists, with an average of 3.26 authors per paper. About 41.68% of the authors were female, whilst 35% of them were first authors. The co-citation analysis by author involved 188 cited authors, 13 of whom were cited at least 70 times. Only six out of forty-nine studies were funded by various government institutions and non-governmental organizations.

CONCLUSION

Current analysis casts a spotlight on important trends being witnessed in regard to the mental health of radiologists, including lack of funding for mental health research, narrowing of female vs male citation gap, as well as authorship and citation trends.

It Takes a Village: A Multimodal Approach to Addressing Radiologist Burnout

Burnout is a significant issue confronting the medical profession, to which radiology is no exception. Addressing burnout demands a full-spectrum response, in keeping with its complexity, prevalence, and significance. This manuscript brings together key techniques at the individual, peer, and institutional levels to offer a multifaceted approach to ameliorating radiologist burnout. Such an approach would begin by equipping physicians with the skillset necessary to identify signs of burnout in themselves and others. Institutions can work to validate the radiologists they employ and work toward mitigating the impact of occupational stressors. Lastly, engaging in conversations about burnout throughout the course of one's medical career can affect a sea change in the way burnout is envisioned, and treated.

Lessons learned from radiology mentors

As in any field, radiologists may face a number of challenges as they navigate their early careers. Because with experience comes wisdom, early-career radiologists may find helpful the advice and perspectives of mid- and late-career radiologists. The Society of Abdominal Radiology recognizes the value of this pool of knowledge and experience, prompting the establishment of the Early Career Committee. This group is designed to support early-career radiologists by sharing the experiences and insights of leaders in the field. In this series, the authors interview trailblazers Matthew S. Davenport, MD; Jonathan B. Kruskal, MD, PhD; Katherine E. Maturen, MD, MS; David B. Larson, MD, MBA; and Desiree E. Morgan, MD. This perspective explores a wide range of subjects, including personal values in medicine, the role of teleradiology, diversity of backgrounds in radiology, how to navigate workplace conflict, and lifelong learning in medicine. Beyond conveying these pearls of wisdom, the aim of this perspective is to highlight for early-career radiologists the value that mid- and late-career mentors can provide in navigating careers in medicine.

Gender of Department Chair and Paid Parental Leave Benefits in Academic Radiology Residency Programs

RATIONALE AND OBJECTIVES

Residency training often overlaps with prime childbearing years, yet variability in availability and duration of parental leave in residency can complicate the decision to become parents. Gender disparities in attitudes towards parenthood in residency is well recognized, with females generally reporting more concerns surrounding prolonged training, hindrance of future career plans, and negative perception from peers. However, gender of the department chair has not yet been examined as a factor influencing parental leave policies for residents in Radiology.

MATERIALS AND METHODS

The gender of the department chair and parental leave policies for residents in 209 ACGME accredited diagnostic radiology programs across the United States were procured from their websites. These programs were stratified into 6 geographical regions to identify regional differences. Chi-squared analyses were used to compare availability of paid parental benefits with the gender of department chairs.

RESULTS

Seventy-seven percent of diagnostic radiology program department chairs were male. 34 of 49 programs (69%) with female department chairs advertised paid parental benefits, compared to 61 of 160 programs (38%) chaired by males (P < 0.001). When stratified by region, this gender difference remained statistically significant in the mid-Atlantic and New England.

CONCLUSION

Female gender of the department chair was associated with the increased availability of paid parental leave benefits for residents, yet females hold fewer academic leadership positions than males. Future discussions regarding parental leave policies for residents will have to consider the unique challenges in residency such as length of training and burden on coresidents.

Burnout: A Mindful Framework for the Radiologist

Burnout, the outcome of prolonged stress or frustration, manifests as both mental and physical fatigue affecting over half of healthcare workers. This article will discuss the etiologies, problems, and potential solutions to burnout related issues that are impacting radiologists. Factors placing radiologists at risk for burnout as well the impact of burnout upon the radiologist, the department, staff, and patients they serve will also be discussed. An emphasis will also be placed upon recognition, solutions, and a collective response to burnout. Readers should be able to perform a self-assessment of their own risk for burnout and understand what can be done to dissolve and prevent burnout amongst their colleagues. In doing so, our hope is that radiologists will develop greater insight, awareness, and ultimately empathy for the unique challenges that others in the radiology community may face.

Physician Burnout in Radiology: Perspectives From the Field

Physician burnout is increasingly recognized as a public health crisis given the impact of burnout on physicians, their families, patients, communities, and population health. The COVID-19 pandemic has superimposed a new set of challenges for physicians to navigate, including unique challenges presented to radiologists. Radiologists from a diversity of backgrounds, practice settings, and career stages were asked for their perspectives on burnout.

How Radiology Leaders Can Address Burnout

The 2018 Annual Workforce Survey conducted by the ACR Commission on Human Resources demonstrated that, although the majority of radiology practice leaders acknowledge radiologist burnout as a significant problem, only about one in five leaders responded that their practices were either extremely or very effective at addressing physician burnout. Moving forward, leaders will be increasingly held accountable and expected to describe to their teams their reasons for not addressing burnout. In this article, common misperceptions that may contribute to radiology practice leaders not addressing burnout are described, followed by outlining practical skills that leaders should develop to effectively address burnout.

Best Practices and Critical Factors in a Successful Private Practice

Independent private practice has historically been the predominant practice model in radiology. In the last two decades, this model has faced increasing pressures on both a micro and macro level, which threatens its existence. In the current health care environment, how does a practice stay independent? The authors address some of the critical factors needed for a successful practice. These factors are derived from the collective experience of the authors who are in private practice as well as best practices described in the literature. Strengths that already exist in the practice, opportunities that can be capitalized on, and looming or existing threats to the independence of a private group are discussed. Recommendations are provided on how to optimize an individual practice and reduce the risk of alternative practice penetration.

What Causes the Most Stress in Breast Radiology Practice? A Survey of Members of the Society of Breast Imaging

OBJECTIVE

The objective of this study is to determine the major stressors affecting practicing breast radiologists.

METHODS

All members of the Society of Breast Imaging within the United States received an email invitation to complete an anonymous survey evaluating stressors that may contribute to physician burnout. Stressors evaluated included pace at work, work-life balance, care of dependents, job security, financial strain, decreasing reimbursement, new regulations, delivering bad news, fear of getting sued, and dealing with difficult patients, radiologists, and administrators.

RESULTS

The overall response rate was 13.5% (312/2308). For those who opened the email, response rate was 24.6% (312/1269). The most prevalent stressors reported were working too fast (222/312, 71.2%), balancing demands of work with personal life (209/312, 70.0%), fear of getting sued (164/312, 52.6%), and dealing with difficult administrators (156/312, 50%). Prevalence of stress related to new regulation requirements, job security, financial strain, decreased reimbursement, dependent care, call, delivering bad news, and dealing with difficult patients, difficult referrers, and difficult radiologists were present in fewer than 50% of respondents.

CONCLUSION

The most prevalent sources of stress in breast imaging radiologists relate to working too fast and balancing demands of work with time needed for personal life.

Implementation of a Software Distribution Intervention to Improve Workload Balance in an Academic Pediatric Radiology Department

In our pediatric radiology department, radiographs (XR) are the shared responsibility of the body section and interpreted in addition to modality or site-specific assignments. Given an unequal contribution amongst radiologists to the XR workload, a software solution was developed to distribute radiographs and improve workload balance. Metrics to evaluate the intervention's effectiveness were compared before and after the intervention. Data was retrieved from the radiology analytics platform, scheduling software, and the peer learning database. Metrics were compared 12 months pre (March 2018-February 2019) and 6 months post (March 2019-August 2019) intervention on non-holiday weekdays, 7 am-5 pm. To evaluate the intervention's effectiveness, variance between radiologists' contributions to XR volume was assessed using Levene's and Fisher's tests. Changes in turnaround times (TATs) and error rates pre- and post-intervention were evaluated as secondary metrics. Following the intervention, the average number of XR interpreted on target rotations increased by 8.9% (p = 0.011) while the departmental volume of radiographs increased only 4.5%. The variance between radiologists' daily XR contribution was 21.3% (p < 0.0001) higher prior to the intervention. Days where target rotations read fewer than 5 XR decreased from 17.8 to 1.1% (p < 0.0001) after the intervention. Days in which more than 75% of all XR had a TAT less than 60 min improved from 26.8 to 39.7% (p = 0.017) after the intervention. There was no statistically significant difference in error frequency (error rate 2.49% pre and 2.72% post, p = 0.636). In conclusion, the software intervention improved XR workload contribution with decreased variability. Despite increased volumes, there was an improvement in turnaround times with no effect on error rates.

Radiologist-Practice Separation: Recent Trends and Characteristics

PURPOSE

To assess recent trends and characteristics in radiologist-practice separation across the United States.

METHODS

Using the Medicare Physician Compare and Medicare Physician and Other Supplier Public Use File data sets, we linked all radiologists to associated group practices annually between 2014 and 2018 and assessed radiologist-practice separation over a variety of physician and group characteristics. Multivariate logistic regression modeling was used to estimate the likelihood of radiologist-practice separation.

RESULTS

Of 25,228 unique radiologists associated with 4,381 unique group practices, 41.1% separated from at least one group practice between 2014 and 2018, and annual separation rates increased 38.4% over time (13.8% from 2014 to 2015 to 19.2% from 2017 to 2018). Radiologist-practice separation rates ranged from 57.4% in Utah to 26.3% in Virginia. Separation rates were 42.8% for general radiologists versus 38.2% for subspecialty radiologists. Among subspecialists, separation rates ranged from 43.0% for breast imagers to 33.5% for cardiothoracic radiologists. Early career status (odds ratio [OR] = 1.286) and late (OR = 1.554) career status were both independent positive predictors of radiologist-practice separation (both P < .001). Larger practice size (OR = 0.795), radiology-only (versus multispecialty) group (OR = 0.468), academic (versus nonacademic) practice (OR = 0.709), and abdominal (OR = 0.820), musculoskeletal (OR = 0.659), and neuroradiology (OR = 0.895) subspecialization were independent negative predictors (all P < .05).

CONCLUSIONS

With over 40% of radiologists separating from at least one practice in recent years, the US radiologist workforce is highly and increasingly mobile. Because reasons for separation (eg, resignation, practice acquisition) cannot be assessed using administrative data, further attention is warranted given the manifold financial, operational, and patient care implications.

Optimizing Radiology Reading Room Design: The Eudaimonia Radiology Machine

Physical and mental stressors on radiologists can result in burnout. Although current efforts seek to target the issues of burnout and stress for radiologists, the impact of their physical workspace is often overlooked. By combining evidence-based design, human factors, and the architectural concept of the Eudaimonia Machine, we have developed a redesign of the radiology reading room that aims to create an optimal workspace for the radiologist. Informed by classical principles of well-being and contemporary work theory, Eudaimonia integrates concerns for individual wellness and efficiency to create an environment that fosters productivity. This layout arranges a work environment into purposeful spaces, each hosting tasks of varying degrees of intensity. The improved design addresses the radiologist's work requirements while also alleviating cognitive and physical stress, fatigue, and burnout. This new layout organizes the reading room into separate areas, each with a distinct purpose intended to support the range of radiologists' work, from consultation with other health care providers to reading images without interruption. The scientific principles that undergird evidence-based design and human factors considerations ensure that the Eudaimonia Radiology Machine is best suited to support the work of the radiologists and the entire radiology department.

Unsustainable: COVID-19 Demands Increased Support for Radiologists

Life is sometimes described as a complex tapestry and progress is not linear, but twisted like stitches, contributing to the final fabric. When tension arises, the most recent stitches unravel first. The COVID-19 pandemic is pulling back the thread of humanity's progress. Those disproportionately affected by the pandemic's tension are those whose progress is most recent and, therefore most tenuous, including women in medicine. The profession of radiology, recently acknowledged by practice leaders as experiencing burnout as a very significant problem (Parikh et al., 2020 [1]), is rapidly facing an untenable situation.

Lessons learned: A single academic department's unique approach to preventing physician burnout

Physician burnout is a recognized problem within medicine and its prevalence appears to be increasing. The symptoms include three major components; exhaustion, depersonalization and feeling a lack of accomplishment. The presence of burnout can have major professional and personal consequences. While there has been much commentary on the impact of burnout, little has been published addressing ways to prevent and resolve the issue. Our department has taken a novel and individualized approach to lower burnout. This includes allowing faculty to personalize their schedules as demonstrated by the perspectives of four breast imaging faculty. We as physicians are as diverse as the patient population we treat which needs to be recognized when addressing solutions to burnout. We propose that most practices and departments can find meaningful ways to allow physicians to increase their sense of autonomy through flexibility and control in scheduling. Having leadership open to unique and sometimes unconventional approaches enables a mutually beneficial culture of respect, productivity, and wellness.

Prevalence of Burnout in Breast Imaging Radiologists

OBJECTIVE

Burnout is defined as a psychological syndrome arising as a response to chronic prolonged interpersonal job-related stress. Physician burnout has been increasingly recognized over the past decade as an epidemic within the United States. The goal of this study was to ascertain the prevalence of burnout amongst practicing breast imaging radiologists.

METHODS

A survey contained demographic questions based on workforce surveys carried out by the American College of Radiology and a validated condensed version of the Maslach Burnout Inventory (MBI) evaluating the three aspects of burnout. The radiologist members of the Society of Breast Imaging (SBI) received the survey internally from the SBI as a weekly e-mail with a web link to the survey from February 19, 2019, to March 13, 2019. The link allowed respondents to complete the survey anonymously. The authors were blinded to the SBI mailing list and the SBI was blinded to the responses.

RESULTS

A total of 370 breast imaging radiologists from the SBI responded to the survey. Overall, 290 out of 370 (78.4%) were highly burned out in at least 1 measured dimension of burnout; 197 out of 362 (54.4%) were highly burned out in at least 2 dimensions of burnout; and 27 out of 362 (7.5%) were highly burned out in all 3 dimensions of burnout. However, rates of personal accomplishment were high, with only 8.8% experiencing high burnout in the dimension of personal accomplishment.

CONCLUSION

Our study demonstrates a high prevalence of burnout amongst breast imaging radiologists. Burnout rates were highest in the youngest breast imaging radiologists.

Physician Stress and Burnout

Tens (or hundreds) of thousands of Americans die each year as a result of preventable medical errors. Changes in the practice and business of medicine have caused some to question whether burnout among physicians and other healthcare providers may adversely affect patient outcomes. A clear consensus supports the contention that burnout affects patients, albeit with low-quality objective data. The psychological and physical impact on physicians and other providers is quite clear, however, and the impact on the physician workforce (where large shortages are projected) is yet another cause for concern. We have all heard the airplane safety announcement remind us to "Please put on your own oxygen mask first before assisting others." Unfortunately, like many airline passengers (very few of whom use oxygen masks correctly when they are needed), physicians often do not recognize symptoms of burnout or depression, and even less often do they seek help. We detail the causes and consequences of physician burnout and propose solutions to increase physician work satisfaction.