ABSTRACT
No standard tool to measure pathologist workload currently exists. An accurate measure of workload is needed for determining the number of pathologists to be hired, distributing the workload fairly among pathologists, and assessing the overall cost of pathology consults. Initially, simple tools such as counting cases or slides were used to give an estimate of the workload. More recently, multiple workload models, including relative value units (RVUs), the Royal College of Pathologists (RCP) point system, Level 4 Equivalent (L4E), Work2Quality (W2Q), and the University of Washington, Seattle (UW) slide count method, have been developed. There is no "ideal" model that is universally accepted. The main differences among the models come from the weights assigned to different specimen types, differential calculations for organs, and the capture of additional tasks needed for safe and timely patient care. Academic centers tend to see more complex cases that require extensive sampling and additional testing, while community-based and private laboratories deal more with biopsies. Additionally, some systems do not account for teaching, participation in multidisciplinary rounds, quality assurance activities, and medical oversight. A successful workload model needs to be continually updated to reflect the current state of practice.Awareness about physician burnout has gained attention in recent years and has been added to the World Health Organization's International Classification of Diseases (World Health Organization, WHO) as an occupational phenomenon. However, the extent to which this affects pathologists is not well understood. According to the WHO, burnout syndrome is diagnosed by the presence of three components: emotional exhaustion, depersonalization from one's work (cynicism related to one's job), and a low sense of personal achievement or accomplishment. Three drivers of burnout are the demand for productivity, lack of recognition, and electronic health records. Prominent consequences of physician burnout are economic and personal costs to the public and to the providers.Wellness is physical and mental well-being that allows individuals to manage stress effectively and to thrive in both their professional and personal lives. To achieve wellness, it is necessary to understand the root causes of burnout, including over-work and working under stressful conditions. Wellness is more than the absence of stress or burnout, and the responsibility of wellness should be shared by pathologists themselves, their healthcare organization, and governing bodies. Each pathologist needs to take their own path to achieve wellness.
Subject(s)
Burnout, Professional , Pathologists , Workload , HumansABSTRACT
Background Retrospective studies have suggested that using artificial intelligence (AI) may decrease the workload of radiologists while preserving mammography screening performance. Purpose To compare workload and screening performance for two cohorts of women who underwent screening before and after AI system implementation. Materials and Methods This retrospective study included 50-69-year-old women who underwent biennial mammography screening in the Capital Region of Denmark. Before AI system implementation (October 1, 2020, to November 17, 2021), all screenings involved double reading. For screenings conducted after AI system implementation (November 18, 2021, to October 17, 2022), likely normal screenings (AI examination score ≤5 before May 3, 2022, or ≤7 on or after May 3, 2022) were single read by one of 19 senior full-time breast radiologists. The remaining screenings were read by two radiologists with AI-assisted decision support. Biopsy and surgical outcomes were retrieved between October 1, 2020, and April 15, 2023, ensuring at least 180 days of follow-up. Screening metrics were compared using the χ2 test. Reading workload reduction was measured as saved screening reads. Results In total, 60 751 and 58 246 women were screened before and after AI system implementation, respectively (median age, 58 years [IQR, 54-64 years] for both cohorts), with a median screening interval before AI of 845 days (IQR, 820-878 days) and with AI of 993 days (IQR, 968-1013 days; P < .001). After AI system implementation, the recall rate decreased by 20.5% (3.09% before AI [1875 of 60 751] vs 2.46% with AI [1430 of 58 246]; P < .001), the cancer detection rate increased (0.70% [423 of 60 751] vs 0.82% [480 of 58 246]; P = .01), the false-positive rate decreased (2.39% [1452 of 60 751] vs 1.63% [950 of 58 246]; P < .001), the positive predictive value increased (22.6% [423 of 1875] vs 33.6% [480 of 1430]; P < .001), the rate of small cancers (≤1 cm) increased (36.6% [127 of 347] vs 44.9% [164 of 365]; P = .02), the rate of node-negative cancers was unchanged (76.7% [253 of 330] vs 77.8% [273 of 351]; P = .73), and the rate of invasive cancers decreased (84.9% [359 of 423] vs 79.6% [382 of 480]; P = .04). The reading workload was reduced by 33.5% (38 977 of 116 492 reads). Conclusion In a population-based mammography screening program, using AI reduced the overall workload of breast radiologists while improving screening performance. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Lee and Friedewald in this issue.
Subject(s)
Artificial Intelligence , Breast Neoplasms , Early Detection of Cancer , Mammography , Workload , Humans , Female , Mammography/methods , Breast Neoplasms/diagnostic imaging , Middle Aged , Retrospective Studies , Aged , Early Detection of Cancer/methods , Workload/statistics & numerical data , Denmark , Mass Screening/methodsABSTRACT
OBJECTIVES: COVID-19 pandemic surges strained hospitals globally. We performed a systematic review to examine measures of pandemic caseload surge and its impact on mortality of hospitalized patients. DATA SOURCES: PubMed, Embase, and Web of Science. STUDY SELECTION: English-language studies published between December 1, 2019, and November 22, 2023, which reported the association between pandemic "surge"-related measures and mortality in hospitalized patients. DATA EXTRACTION: Three authors independently screened studies, extracted data, and assessed individual study risk of bias. We assessed measures of surge qualitatively across included studies. Given multidomain heterogeneity, we semiquantitatively aggregated surge-mortality associations. DATA SYNTHESIS: Of 17,831 citations, we included 39 studies, 17 of which specifically described surge effects in ICU settings. The majority of studies were from high-income countries ( n = 35 studies) and included patients with COVID-19 ( n = 31). There were 37 different surge metrics which were mapped into four broad themes, incorporating caseloads either directly as unadjusted counts ( n = 11), nested in occupancy ( n = 14), including additional factors (e.g., resource needs, speed of occupancy; n = 10), or using indirect proxies (e.g., altered staffing ratios, alternative care settings; n = 4). Notwithstanding metric heterogeneity, 32 of 39 studies (82%) reported detrimental adjusted odds/hazard ratio for caseload surge-mortality outcomes, reporting point estimates of up to four-fold increased risk of mortality. This signal persisted among study subgroups categorized by publication year, patient types, clinical settings, and country income status. CONCLUSIONS: Pandemic caseload surge was associated with lower survival across most studies regardless of jurisdiction, timing, and population. Markedly variable surge strain measures precluded meta-analysis and findings have uncertain generalizability to lower-middle-income countries (LMICs). These findings underscore the need for establishing a consensus surge metric that is sensitive to capturing harms in everyday fluctuations and future pandemics and is scalable to LMICs.
Subject(s)
COVID-19 , COVID-19/epidemiology , Humans , Hospital Mortality , Pandemics , Surge Capacity , Intensive Care Units/statistics & numerical data , Intensive Care Units/organization & administration , SARS-CoV-2 , Workload/statistics & numerical dataABSTRACT
PURPOSE: The heart is a highly aerobic organ consuming most of the oxygen the body in supporting heart function. Quantitative imaging of myocardial oxygen metabolism and perfusion is essential for studying cardiac physiopathology in vivo. Here, we report a new imaging method that can simultaneously assess myocardial oxygen metabolism and blood flow in the rat heart. METHODS: This novel method is based on the 17 O-MRSI combined with brief inhalation of 17 O-isotope labeled oxygen gas for quantitative imaging of myocardial metabolic rate of oxygen consumption (MVO2 ), myocardial blood flow (MBF), and oxygen extraction fraction (OEF). We demonstrate this imaging method under basal and high workload conditions in rat hearts at 9.4 T. RESULTS: We show that this 17 O MRSI-based approach can directly measure and image MVO2 (1.35-4.06 µmol/g/min), MBF (0.49-1.38 mL/g/min), and OEF (0.33-0.44) in the heart of anesthetized rat under basal and high workload (21.6 × 103 -56.7 × 103 mmHg ⢠bpm) conditions. Under high workload condition, MVO2 and MBF values in healthy rats approximately doubled, whereas OEF remained unchanged, indicating a strong coupling between myocardial oxygen metabolic demand and supply through blood perfusion. CONCLUSION: The 17 O-MRSI method has been used to simultaneously image the myocardial metabolic rate of oxygen consumption, blood flow, and oxygen extraction fraction in small animal hearts, which are sensitive to the physiological changes induced by high workload. This approach could provide comprehensive measures that are critical for studying myocardial function in normal and diseased states and has a potential for translation.
Subject(s)
Oxygen , Workload , Rats , Animals , Coronary Circulation , Myocardium/metabolism , Heart/diagnostic imaging , Oxygen ConsumptionABSTRACT
PURPOSE: Genome sequencing (GS) enables comprehensive molecular analysis of tumors and identification of hereditary cancer predisposition. According to guidelines, directly determining pathogenic germline variants (PGVs) requires pretest genetic counseling, which is cost-ineffective. Referral for genetic counseling based on tumor variants alone could miss relevant PGVs and/or result in unnecessary referrals. METHODS: We validated GS for detection of germline variants and simulated 3 strategies using paired tumor-normal GS data of 937 metastatic patients. In strategy-1, genetic counseling before tumor testing allowed direct PGV analysis. In strategy-2 and -3, germline testing and referral for post-test genetic counseling is based on tumor variants using Dutch (strategy-2) or Europen Society for Medical Oncology (ESMO) Precision Medicine Working Group (strategy-3) guidelines. RESULTS: In strategy-1, PGVs would be detected in 50 patients (number-needed-to counsel; NTC = 18.7). In strategy-2, 86 patients would have been referred for genetic counseling and 43 would have PGVs (NTC = 2). In strategy-3, 94 patients would have been referred for genetic counseling and 32 would have PGVs (NTC = 2.9). Hence, 43 and 62 patients, respectively, were unnecessarily referred based on a somatic variant. CONCLUSION: Both post-tumor test counseling strategies (2 and 3) had significantly lower NTC, and strategy-2 had the highest PGV yield. Combining pre-tumor test mainstreaming and post-tumor test counseling may maximize the clinically relevant PGV yield and minimize unnecessary referrals.
Subject(s)
Genetic Counseling , Neoplasms , Humans , Genetic Testing , Workload , Neoplasms/diagnosis , Neoplasms/genetics , Genetic Predisposition to Disease , Germ-Line Mutation/geneticsABSTRACT
PURPOSE: Lower urinary tract symptoms (LUTS) are a challenge to the healthy nursing workforce. Nurses confront various objective and subjective nursing workloads which contribute to their LUTS, but less is known about how nursing workloads influence their LUTS. This study is designed to test hypotheses that delayed voiding behaviors mediate the relationships between nursing workloads and LUTS in female nurses. MATERIALS AND METHODS: This study analyzed the baseline data collected from an ongoing cohort study named Nurse Urinary Related Health Study in China. LUTS of nurses in 20 tertiary hospitals were assessed with the International Consultation on Incontinence QuestionnaireâFemale Lower Urinary Tract Symptoms. Objective nursing workloads including working environment, working hours, and working schedule were collected, and perceived stress, the proxy of the subjective nursing workload, was assessed with the Perceived Stress Scale. Delayed voiding behaviors were assessed with 3 questions adapted from the Taiwan Nurse Bladder Survey. Structural equation modeling was used to run the mediation model. RESULTS: More than half (51%) of 13,191 female nurses had LUTS. Median age was 31 years (IQR 27-37). When delayed voiding behaviors served as a mediator, the direct effects of subjective nursing workload rather than objective nursing workloads on LUTS were significant. CONCLUSIONS: Nursing workloads influence nurses' LUTS via delayed voiding behaviors. Strategies tailored to delayed voiding behaviors should be developed, and these may work with stress-reducing strategies as the gatekeepers for nurses' bladder health.
Subject(s)
Lower Urinary Tract Symptoms , Psychological Tests , Self Report , Workload , Humans , Female , Adult , Cohort Studies , Lower Urinary Tract Symptoms/epidemiology , Surveys and Questionnaires , China/epidemiologyABSTRACT
OBJECTIVE: Vascular surgeons have one of the highest rates of burnout among surgical specialties, often attributed to high patient acuity and clinical workload. Acute Care Surgery models are a potential solution used among general and trauma surgeons. METHODS: This is a retrospective analysis of prospectively collected Accreditation Council for Graduate Medical Education survey results from faculty and residents before and after implementation of a vascular Acute Care Surgery (VACS) model. The VACS model assigns a weekly rotation of an attending surgeon with no elective cases or clinic responsibilities and a monthly rotating resident team. Residents and attendings are in-house to cover all urgent and emergent vascular daytime consultations and procedures, whereas nights and weekend coverage remain a typical rotating schedule. Survey question results were binned into domains consistent with the Maslach Burnout Inventory. RESULTS: Both residents and faculty reported an increase in median scores in Maslach Burnout Inventory domains of emotional exhaustion (Faculty: 2.9 vs 3.4; P < .001; Residents: 3.1 vs 3.6; P < .001) and faculty reported higher personal accomplishment scores (Faculty: 3.3 vs 3.8; P = .005) after the VACS model implementation. CONCLUSIONS: A VACS model is a tangible practice change that can address a major problem for current vascular surgeons, as it is associated with decreased burnout for faculty and residents through improvement in both emotional exhaustion and personal accomplishment. Improved longitudinal assessment of resident and faculty burnout is needed and future work should identify specific practice patterns related to decreased burnout.
Subject(s)
Acute Care Surgery , Burnout, Professional , Internship and Residency , Surgeons , Vascular Surgical Procedures , Workload , Female , Humans , Male , Acute Care Surgery/organization & administration , Attitude of Health Personnel , Burnout, Professional/psychology , Burnout, Professional/epidemiology , Burnout, Professional/prevention & control , Education, Medical, Graduate , Emotions , Faculty, Medical/psychology , Job Satisfaction , Models, Organizational , Personnel Staffing and Scheduling , Retrospective Studies , Surgeons/psychology , Surgeons/statistics & numerical data , Surveys and QuestionnairesABSTRACT
OBJECTIVE: Vascular surgeons work long, unpredictable hours with repeated exposure to high-stress situations. Inspired by general surgery acute care surgery models, we sought to organize the care of vascular emergencies with the implementation of a vascular acute care surgery (VACS) model. Within this model, a surgeon is in-house without elective cases and assigned for consultations and urgent operative cases on a weekly basis. This study examined the impact of a VACS model on postoperative mortality and surgeon efficiency. METHODS: This was a retrospective cohort analysis of institutional Vascular Quality Initiative data from July 2014 to July 2023. Patients undergoing lower extremity bypass, peripheral vascular intervention, or amputation were included. There was a washout period from January 2020 to January 2022 to account for COVID-19 pandemic practice abnormalities. Patients were separated into pre- or post-VACS groups. The primary clinical outcomes were 30-day and 2-year mortality. Secondary clinical outcomes included 30-day complications and 30-day and 1-year major adverse limb events (MALE). Separate analyses of operating room data from July 2017 to February 2024 and fiscal data from fiscal year 2019 to fiscal year 2024 were conducted. A washout period from January 2020 to January 2022 was applied. Efficiency outcomes included monthly relative value units (RVUs) per clinical fraction full-time equivalent (cFTE) and daytime (0730-1700, Monday-Friday) operating room minutes. Patient factors and operative efficiency were compared using appropriate statistical tests. Regression modeling was performed for the primary outcomes. RESULTS: There were 972 and 257 patients in the pre- and post-VACS groups, respectively. Pre-VACS patients were younger (66.8 ± 12.0 vs 68.7 ± 12.7 years; P = .03) with higher rates of coronary artery disease (34.6% vs 14.8%; P < .01), hypertension (88.4% vs 82.2%; P = .01), and tobacco history (84.4% vs 78.2%; P = .02). Thirty-day mortality (2.4% pre-vs 0.8% post-VACS; P = .18) and Kaplan-Meier estimation of 2-year mortality remained stable after VACS (P = .07). VACS implementation was not associated with 30-day mortality but was associated with lower 2-year mortality hazard on multivariable Cox regression (hazard ratio [HR], 0.5; 95% confidence interval [CI], 0.3-0.9; P = .01). Operative efficiency improved post-VACS (median, 850.0; interquartile range [IQR], 765.7-916.3 vs median, 918.0; IQR, 881.0-951.1 RVU/cFTE-month; P = .03). Daytime operating minutes increased (469.1 ± 287.5 vs 908.2 ± 386.2 minutes; P < .01), whereas non-daytime minutes (420.0; IQR, 266.0-654.0 vs 469.5; IQR, 242.0-738.3 minutes; P = .40) and weekend minutes (129.0; IQR, 0.0-298.0 vs 113.5; IQR, 0.0-279.5 minutes; P = .59) remained stable. CONCLUSIONS: A VACS model leads to improvement in surgeon operative efficiency while maintaining patient safety. The adoption of a vascular acute care model has a positive impact on the delivery of comprehensive vascular care.
Subject(s)
Acute Care Surgery , Lower Extremity , Vascular Surgical Procedures , Aged , Female , Humans , Male , Middle Aged , Acute Care Surgery/organization & administration , Acute Care Surgery/statistics & numerical data , Amputation, Surgical , Efficiency, Organizational , Lower Extremity/blood supply , Lower Extremity/surgery , Peripheral Arterial Disease/mortality , Peripheral Arterial Disease/surgery , Peripheral Arterial Disease/diagnosis , Postoperative Complications/mortality , Retrospective Studies , Risk Factors , Surgeons , Time Factors , Vascular Surgical Procedures/adverse effects , Vascular Surgical Procedures/mortality , Vascular Surgical Procedures/statistics & numerical data , Workload/statistics & numerical dataABSTRACT
BACKGROUND: As patient-initiated messaging rises, identifying variation in message volume and its relationship to clinician workload is essential. OBJECTIVE: To describe the association between variation in message volume over time and time spent on the electronic health record (EHR) outside of scheduled hours. DESIGN: Retrospective cohort study. PARTICIPANTS: Primary care clinicians at Cleveland Clinic Health System. MAIN MEASURES: We categorized clinicians according to their number of quarterly incoming medical advice messages (i.e., message volume) between January 2019 and December 2021 using group-based trajectory modeling. We assessed change in quarterly messages and outpatient visits between October-December 2019 (Q4) and October-December 2021 (Q12). The primary outcome was time outside of scheduled hours spent on the EHR. We used mixed effects logistic regression to describe the association between incoming portal messages and time spent on the EHR by clinician messaging group and at the clinician level. KEY RESULTS: Among the 150 clinicians, 31% were in the low-volume group (206 messages per quarter per clinician), 47% were in the moderate-volume group (505 messages), and 22% were in the high-volume group (840 messages). Mean quarterly messages increased from 340 to 695 (p < 0.001) between Q4 and Q12; mean quarterly outpatient visits fell from 711 to 575 (p = 0.005). While time spent on the EHR outside of scheduled hours increased modestly for all clinicians, this did not significantly differ by message group. Across all clinicians, each additional 10 messages was associated with an average of 12 min per quarter of additional time spent on the EHR (p < 0.001). CONCLUSIONS: Message volume increased substantially over the study period and varied by group. While messages were associated with additional time spent on the EHR outside of scheduled hours, there was no significant difference in time spent on the EHR between the high and low message volume groups.
Subject(s)
Electronic Health Records , Patient Portals , Humans , Retrospective Studies , Workload , Primary Health CareABSTRACT
It has been widely accepted that dopamine (DA) plays a major role in motivation, yet the specific contribution of DA signaling at D1-like receptor (D1R) and D2-like receptor (D2R) to cost-benefit trade-off remains unclear. Here, by combining pharmacological manipulation of DA receptors (DARs) and positron emission tomography (PET) imaging, we assessed the relationship between the degree of D1R/D2R blockade and changes in benefit- and cost-based motivation for goal-directed behavior of macaque monkeys. We found that the degree of blockade of either D1R or D2R was associated with a reduction of the positive impact of reward amount and increasing delay discounting. Workload discounting was selectively increased by D2R antagonism. In addition, blocking both D1R and D2R had a synergistic effect on delay discounting but an antagonist effect on workload discounting. These results provide fundamental insight into the distinct mechanisms of DA action in the regulation of the benefit- and cost-based motivation, which have important implications for motivational alterations in both neurological and psychiatric disorders.
Subject(s)
Cost-Benefit Analysis , Dopamine/metabolism , Macaca mulatta/physiology , Motivation , Receptors, Dopamine D1/physiology , Receptors, Dopamine D2/physiology , Animals , Delay Discounting , Dopamine Antagonists/pharmacology , Macaca fuscata , Male , Positron-Emission Tomography , Receptors, Dopamine D1/drug effects , Receptors, Dopamine D2/drug effects , WorkloadABSTRACT
OBJECTIVES: Gender differences have been reported to influence medical training. We investigated gender differences encountered during training in interventional radiology maneuvers. METHODS: Catheter handling was analyzed under standardized conditions in 64 participants naïve to endovascular procedures (26 women, 38 men). Objective (e.g., catheter pathway, catheter movements, required time) and subjective parameters (stress level) were recorded. The NASA-Task Load Index (NASA-TLX; 1-20 points) was used to assess participants' stress levels and perceived workload. RESULTS: In the easier tasks, no significant differences between male and female participants regarding catheter handling were observed. In the most complex task, female participants took themselves more time (688 ± 363 vs. 501 ± 230 s; p = 0.02), asked for help more frequently (n = 19 vs. n = 8) and earlier than men (203 ± 94 vs. 305 ± 142 s; p = 0.049), whereas men stood out by more agitated catheter handling (6.0 ± 1.8 vs. 4.8 ± 1.6 movements/s; p = 0.005). Overall, female participants perceived tasks to be more difficult (11.5 ± 4.2 vs. 9.6 ± 3.3; p = 0.016), perceived higher stress levels (8.9 ± 4.9 vs. 6.3 ± 4.4; p = 0.037), and rated their own performance lower (9.12 ± 3.3 vs. 11.3 ± 3.3; p = 0.009). However, female participants were able to correlate self-assessed with objective parameters correctly (r between -0.555 and -0.469; p = 0.004-0.018), whereas male participants failed to correctly rate their performance (p between 0.34 and 0.73). Stress levels correlated with objective parameters in males (r between 0.4 and 0.587; p < 0.005), but not in female participants. CONCLUSION: Perceived stress levels, self-evaluation skills, and catheter handling differ greatly between untrained male and female participants trying to solve interventional radiological tasks. These gender-specific differences should be considered in interventional radiology training. CLINICAL RELEVANCE STATEMENT: As psychological aspects may influence individual working strategies gender-specific differences in self-perception while learning interventional radiology maneuvers could be essential regarding success in teaching and treatment outcomes. KEY POINTS: ⢠After performing standardized training, 38 male and 26 female volunteers showed significant differences regarding objective and self-assessed performance, as well as in perceived workload while performing simulated endovascular catheter maneuvers. ⢠After solving simulated endovascular radiological tasks, female participants were able to self-assess their objective performance much more accurately than male participants. ⢠Women took more time to solve simulated endovascular tasks and asked earlier and more frequently for help than men.
Subject(s)
Endovascular Procedures , Radiology, Interventional , Humans , Male , Female , Sex Factors , Workload/psychology , LearningABSTRACT
OBJECTIVES: To evaluate whether deep learning-based detection algorithms (DLD)-based triaging can reduce outpatient chest radiograph interpretation workload while maintaining noninferior sensitivity. METHODS: This retrospective study included patients who underwent initial chest radiography at the outpatient clinic between June 1 and June 30, 2017. Readers interpreted radiographs with/without a commercially available DLD that detects nine radiologic findings (atelectasis, calcification, cardiomegaly, consolidation, fibrosis, nodules, pneumothorax, pleural effusion, and pneumoperitoneum). The reading order was determined in a randomized, crossover manner. The radiographs were classified into negative and positive examinations. In a 50% worklist reduction scenario, radiographs were sorted in descending order of probability scores: the lower half was regarded as negative exams, while the remaining were read with DLD by radiologists. The primary analysis evaluated noninferiority in sensitivity between radiologists reading all radiographs and simulating a 50% worklist reduction, with the inferiority margin of 5%. The specificities were compared using McNemar's test. RESULTS: The study included 1964 patients (median age [interquartile range], 55 years [40-67 years]). The sensitivity was 82.6% (195 of 236; 95% CI: 77.5%, 87.3%) when readers interpreted all chest radiographs without DLD and 83.5% (197 of 236; 95% CI: 78.8%, 88.1%) in the 50% worklist reduction scenario. The difference in sensitivity was 0.8% (95% CI: - 3.8%, 5.5%), establishing noninferiority of 50% worklist reduction (p = 0.01). The specificity increased from 86.7% (1498 of 1728) to 90.4% (1562 of 1728) (p < 0.001) with DLD-based triage. CONCLUSION: Deep learning-based triaging may substantially reduce workload without lowering sensitivity while improving specificity. CLINICAL RELEVANCE STATEMENT: Substantial workload reduction without lowering sensitivity was feasible using deep learning-based triaging of outpatient chest radiograph; however, the legal responsibility for incorrect diagnoses based on AI-standalone interpretation remains an issue that should be defined before clinical implementation. KEY POINTS: ⢠A 50% workload reduction simulation using deep learning-based detection algorithm maintained noninferior sensitivity while improving specificity. ⢠The CT recommendation rate significantly decreased in the disease-negative patients, whereas it slightly increased in the disease-positive group without statistical significance. ⢠In the exploratory analysis, the noninferiority of sensitivity was maintained until 70% of the workload was reduced; the difference in sensitivity was 0%.
Subject(s)
Artificial Intelligence , Deep Learning , Humans , Middle Aged , Radiography , Radiography, Thoracic , Radiologists , Retrospective Studies , Sensitivity and Specificity , Triage , Workload , Adult , AgedABSTRACT
OBJECTIVES: The current study aimed to explore the moderating role of psychological resilience in the association between workload and depressive symptoms among radiology residents during standardized residency training (SRT) in China. METHODS: A nationwide cross-sectional online survey was conducted among radiology residents in China. Workload was measured by working hours per week and the frequency of frontline nightwork in the last month. Resilience was assessed by the 2-item Connor-Davidson Resilience Scale. Depressive symptoms were measured by the Depression Anxiety Stress Scales. The hierarchical regression and simple slope analyses were performed to examine the moderating effect of resilience. RESULTS: Among 3666 radiology residents, the mean age was 27.3 years (SD = 2.6) and 58% were female. About 24.4% of the participants reported medium to severe depressive symptoms. The hierarchical regression showed that working hours (ba = 0.11, 95%CI: 0.08, 0.14) and having frontline nightwork more than once (ba = 1.22, 95%CI: 0.67, 1.78) were positively associated with depressive symptoms; the moderating effect of resilience was significant in the association of depressive symptoms with working hours (ba = - 0.02, 95%CI: - 0.03, - 0.01) and having frontline nightwork more than once (ba = - 0.28, 95%CI: - 0.49, - 0.07). The simple slope test showed the association between workload-related variables and depressive symptoms was only significant in those with a relatively lower level of resilience. CONCLUSIONS: The study found that resilience was an important modifier buffering the positive association between workload and depressive symptoms among radiology residents in China. Future medical training programs are suggested to include effective intervention components to increase personal resilience. CLINICAL RELEVANCE STATEMENT: Heavy workload in clinical setting may pose adverse effect on mental health and job performance of radiology residents. The study investigated whether psychological resilience would mitigate the association between workload and depressive symptoms among Chinese radiology residents. KEY POINTS: ⢠Radiology residents with a heavier workload presented a higher level of depressive symptoms in China. ⢠Psychological resilience mitigated the positive association between workload and depressive symptoms. ⢠The association between workload and depressive symptoms was only statistically significant in radiology residents with a relatively lower level of resilience.
Subject(s)
Psychological Tests , Radiology , Resilience, Psychological , Humans , Female , Adult , Male , Workload , Depression/epidemiology , Cross-Sectional Studies , China/epidemiologyABSTRACT
OBJECTIVES: In the presence of escalating global concerns regarding physician burnout, this study aims to analyze the prevalence and associated factors of burnout among radiologists in Germany. METHODS: A comprehensive online survey, inclusive of 73 targeted questions including a German-modified version of the Maslach Burnout Inventory, was distributed among all members of the German Radiological Society and the German Interventional Radiological Society between May and August 2023. The survey encompassed aspects of employment, workload, well-being, and coping mechanisms. Data from 172 completed surveys were analyzed, with correlations explored via crosstabs and the Pearson-chi-square test. RESULTS: In total, 76.7% of participating radiologists were identified to be burnt out. The prevalence was significantly associated with increased workload, reduced sleep quality, suboptimal working conditions, reduced job satisfaction, and the negative interplay between work, family life, and health. Median work satisfaction was described as "satisfied" while median workload was assessed as "frequently overwhelming of work." A total of 41.9% of respondents noted facing daily time pressure. Radiologists' concerns about work interfering with private family life were voiced by approximately 70%, and 73.3% highlighted the perceived negative effects on their health. CONCLUSION: The pronounced prevalence of burnout among German radiologists demonstrates an urgent, unmet need for comprehensive interventions and systemic changes. Our findings act as a catalyst for initiating targeted, multifaceted strategies and dialogs, essential for fostering a resilient and effective healthcare ecosystem. Further large-scale systematic studies should follow to analyze the findings in broad. CLINICAL RELEVANCE STATEMENT: Consistent with other countries, there is a high prevalence of burnout among radiologists in Germany. A call for further investigation is recommended to help mitigate adverse outcomes associated with physician burnout. KEY POINTS: ⢠The prevalence of burnout has yet not been evaluated for German radiologists. ⢠German radiologists have a high prevalence of burnout. ⢠Steps must be implemented to engage this problem to prevent worsening.
Subject(s)
Burnout, Professional , Job Satisfaction , Radiologists , Workload , Burnout, Professional/epidemiology , Humans , Germany/epidemiology , Radiologists/psychology , Prevalence , Female , Male , Surveys and Questionnaires , Middle Aged , AdultABSTRACT
OBJECTIVES: We aimed to evaluate the early-detection capabilities of AI in a screening program over its duration, with a specific focus on the detection of interval cancers, the early detection of cancers with the assistance of AI from prior visits, and its impact on workload for various reading scenarios. MATERIALS AND METHODS: The study included 22,621 mammograms of 8825 women within a 10-year biennial two-reader screening program. The statistical analysis focused on 5136 mammograms from 4282 women due to data retrieval issues, among whom 105 were diagnosed with breast cancer. The AI software assigned scores from 1 to 100. Histopathology results determined the ground truth, and Youden's index was used to establish a threshold. Tumor characteristics were analyzed with ANOVA and chi-squared test, and different workflow scenarios were evaluated using bootstrapping. RESULTS: The AI software achieved an AUC of 89.6% (86.1-93.2%, 95% CI). The optimal threshold was 30.44, yielding 72.38% sensitivity and 92.86% specificity. Initially, AI identified 57 screening-detected cancers (83.82%), 15 interval cancers (51.72%), and 4 missed cancers (50%). AI as a second reader could have led to earlier diagnosis in 24 patients (average 29.92 ± 19.67 months earlier). No significant differences were found in cancer-characteristics groups. A hybrid triage workflow scenario showed a potential 69.5% reduction in workload and a 30.5% increase in accuracy. CONCLUSION: This AI system exhibits high sensitivity and specificity in screening mammograms, effectively identifying interval and missed cancers and identifying 23% of cancers earlier in prior mammograms. Adopting AI as a triage mechanism has the potential to reduce workload by nearly 70%. CLINICAL RELEVANCE STATEMENT: The study proposes a more efficient method for screening programs, both in terms of workload and accuracy. KEY POINTS: ⢠Incorporating AI as a triage tool in screening workflow improves sensitivity (72.38%) and specificity (92.86%), enhancing detection rates for interval and missed cancers. ⢠AI-assisted triaging is effective in differentiating low and high-risk cases, reduces radiologist workload, and potentially enables broader screening coverage. ⢠AI has the potential to facilitate early diagnosis compared to human reading.
Subject(s)
Artificial Intelligence , Breast Neoplasms , Early Detection of Cancer , Mammography , Sensitivity and Specificity , Humans , Breast Neoplasms/diagnostic imaging , Female , Early Detection of Cancer/methods , Mammography/methods , Middle Aged , Aged , Workload/statistics & numerical data , Mass Screening/methods , Radiographic Image Interpretation, Computer-Assisted/methodsABSTRACT
INTRODUCTION: There has been widespread international implementation of duration-hour restrictions to prevent surgical resident burnout and promote patient safety and wellbeing of doctors. A variety of Extended-Duration Work Shifts (EDWS) have been implemented, with a variety of studies examining the effect of shift systems on both surgical performance and the stress response unestablished in the literature. METHODS: This was a systematic review evaluating the impact of extended working hours on surgical performance, cognitive impairment, and physiological stress responses. The review used PubMed, Ovid Medline, Embase, and Google Scholar search engines between September and October 2021 in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Filters including studies carried out after 2002 and published in the English language were applied. RESULTS: In total, 30 studies were included for analysis. General surgery was the most commonly studied rotation, with Neurosurgical, Orthopedic, and ear, nose and throat specialties also included. The majority of studies found no difference or a significant improvement in post-EDWS on simulated performance. EDWS appeared to have the greatest impact on physiological stress markers in junior surgical trainees. CONCLUSIONS: Experience appears to confer a protective element in the postcall period, with preservation of skill demonstrated. More experienced clinicians yielded lower levels of physiological markers of stress, although variability in hierarchical workload should be considered. Heterogeneity of findings across physiological, cognitive, and psychomotor assessments highlights the need for robust research on the optimum shift pattern prevents worker burnout and promotes patient safety. Future research to evaluate correlation between stress, on-call workload, and performance in the postcall period is warranted.
Subject(s)
Internship and Residency , Physicians , Specialties, Surgical , Humans , Workload/psychology , Physicians/psychologyABSTRACT
PURPOSE: To propose a research method for identifying "practicing interventional radiologists" using 2 national claims data sets. MATERIALS AND METHODS: The 2015-2019 100% Medicare Part B data and 2015-2019 private insurance claims from Optum's Clinformatics Data Mart (CDM) database were used to rank-order radiologists' interventional radiology (IR)-related work as a percentage of total billed work relative value units (RVUs). Characteristics were analyzed at various threshold percentages. External validation used Medicare self-designated specialty with Society of Interventional Radiology (SIR) membership records; Youden index evaluated sensitivity and specificity. Multivariate logistic regression assessed practicing IR characteristics. RESULTS: In the Medicare data, above a 10% IR-related work threshold, only 23.8% of selected practicing interventional radiologists were designated as interventional radiologists; above 50% and 90% thresholds, this percentage increased to 42.0% and 47.5%, respectively. The mean percentage of IR-related work among practicing interventional radiologists was 45%, 84%, and 96% of total work RVUs for the 10%, 50%, and 90% thresholds, respectively. At these thresholds, the CDM practicing interventional radiologists included 21.2%, 35.2%, and 38.4% designated interventional radiologists, and evaluation and management services comprised relatively more total work RVUs. Practicing interventional radiologists were more likely to be males, metropolitan, and earlier in their careers than other radiologists at all thresholds. CONCLUSIONS: Most radiologists performing IR-related work are designated in claims data as diagnostic radiologists, indicating insufficiency of specialty designation for IR identification. The proposed method to identify practicing interventional radiologists by percent IR-related work effort could improve generalizability and comparability across claims-based IR studies.
Subject(s)
Databases, Factual , Radiologists , Radiology, Interventional , Humans , United States , Male , Female , Medicare Part B , Relative Value Scales , Workload , Radiography, Interventional , Data Mining , Insurance Claim Review , Job Description , Practice Patterns, Physicians'ABSTRACT
PURPOSE: The purpose of this study is to evaluate recent trends in primary care physician (PCP) electronic health record (EHR) workload. METHODS: This longitudinal study observed the EHR use of 141 academic PCPs over 4 years (May 2019 to March 2023). Ambulatory full-time equivalency (aFTE), visit volume, and panel size were evaluated. Electronic health record time and inbox message volume were measured per 8 hours of scheduled clinic appointments. RESULTS: From the pre-COVID-19 pandemic year (May 2019 to February 2020) to the most recent study year (April 2022 to March 2023), the average time PCPs spent in the EHR per 8 hours of scheduled clinic appointments increased (+28.4 minutes, 7.8%), as did time in orders (+23.1 minutes, 58.9%), inbox (+14.0 minutes, 24.4%), chart review (+7.2 minutes, 13.0%), notes (+2.9 minutes, 2.3%), outside scheduled hours on days with scheduled appointments (+6.4 minutes, 8.2%), and on unscheduled days (+13.6 minutes, 19.9%). Primary care physicians received more patient medical advice requests (+5.4 messages, 55.5%) and prescription messages (+2.3, 19.5%) per 8 hours of scheduled clinic appointments, but fewer patient calls (-2.8, -10.5%) and results messages (-0.3, -2.7%). While total time in the EHR continued to increase in the final study year (+7.7 minutes, 2.0%), inbox time decreased slightly from the year prior (-2.2 minutes, -3.0%). Primary care physicians' average aFTE decreased 5.2% from 0.66 to 0.63 over 4 years. CONCLUSIONS: Primary care physicians' time in the EHR continues to grow. While PCPs' inbox time may be stabilizing, it is still substantially higher than pre-pandemic levels. It is imperative health systems develop strategies to change the EHR workload trajectory to minimize PCPs' occupational stress and mitigate unnecessary reductions in effective physician workforce resulting from the increased EHR burden.
Subject(s)
Electronic Health Records , Physicians, Primary Care , Humans , Longitudinal Studies , Pandemics , WorkloadABSTRACT
OBJECTIVES: Despite the fact that team manual handling is common in different working environments, the previous studies in this regard, particularly those with a physiological approach are quite limited. The present study is an attempt to model the heart rate (HR) of individual and team manual handling with one hand. METHODS: Twenty-five young men (aged 21.24±1.42 year) volunteered for this study. The experiments included individual and two-person handling of the load with three different weights with and without height difference. The participants' HR was registered at the end of the route by a chest-strap pulse monitor and a polar watch according to the manufacturer's recommendation. A multivariate Generalized Additive Mixed Model (MGAMM) was used for modeling heart rate based on explanatory variables of workload, carry method, HRrest, body weight, height, knee height, shoulder height, elbow height, and hand height. The significance level of the tests was considered as <0.05. RESULTS: Based on the MGAMM, the average HR (bpm) of participants increased as the workload increased (P<0.001). Handling the load with a taller person increased the HR compared to shorter partner (P<0.001). Moreover, the nonlinear associations of the resting HR (P<0.001), body weight (P<0.001), height (P<0.001), and the height of elbow, hand and knee (P<0.001) were statistically significant. The adjusted R2 of the model was 0.89 indicating that about 90 percent of the variations observed in HR could be explained by the variables in the model. This was greater than the model considering only linear effects (R2 =0.60). CONCLUSION: The model obtained in this study can predict the heart rate of individual and team one-handed handling with high validity. The MGAMM can be used in modeling heart rate in manual handling.
Subject(s)
Workload , Male , Humans , Heart Rate , Body WeightABSTRACT
The current radiology landscape has an imbalance between the rising demand for radiology services and the national radiologist workforce available. More vacant radiology positions exist than graduating radiology trainees. The origins of this problem are complex and require long-term solutions. Rather than working longer and/or faster, radiologists can work smarter. In this article, we present multiple short-term strategies to increase the effective radiologist workforce and/or increase workforce efficiency, to alleviate the current workload challenges. These strategies are derived from an analysis of possible practice-level changes in personnel, process, and physical plant. The impacts of the potential changes are estimated. No single change addresses the mismatch between supply and demand for radiology services. By creating an inventory of potential solutions, practices can choose the potential mechanism(s) to address the workforce shortage that best fit their needs and local environment.