Análisis de la carga laboral en tiempo médico en función del grado de complejidad de las muestras y propuesta de algoritmo para la distribución equitativa del trabajo asistencial en un servicio de anatomía patológica / Analysis of the workload in medical time according to the degree of complexity of the samples and proposal of an algorithm for the equitable distribution of the workload in an anatomic pathology department

Introducción: En un servicio de anatomía patológica se analiza la carga laboral en tiempo médico en función de la complejidad de las muestras recibidas, y se valora su distribución entre los patólogos, presentado un nuevo algoritmo informático que favorece una distribución equitativa. Métodos: Siguiendo las directrices para la «Estimación de la carga de trabajo en citopatología e histopatología (tiempo médico) atendiendo al catálogo de muestras y procedimientos de la SEAP-IAP (2.ª edición)» se determinan las unidades de carga laboral (UCL) por patólogo y UCL global del servicio, la carga media laboral que soporta el servicio (factor MU), el tiempo de dedicación de cada patólogo a la actividad asistencial y el número de patólogos óptimo según la carga laboral del servicio. Resultados: Determinamos 12.197 UCL totales anuales para el patólogo jefe de servicio, así como 14.702 y 13.842 para los patólogos adjuntos, con una UCL global del servicio de 40.742. El factor MU calculado es 4,97. El jefe ha dedicado el 72,25% de su jornada a la asistencia y los adjuntos el 87,09 y 82,01%. El número de patólogos óptimo para el servicio es de 3,55. Conclusiones: Todos los resultados obtenidos demuestran la sobrecarga laboral médica, y la distribución de las UCL entre los patólogos no resulta equitativa. Se propone un algoritmo informático capaz de distribuir la carga laboral de manera equitativa, asociado al sistema de información del laboratorio, y que tenga en cuenta el tipo de muestra, su complejidad y la dedicación asistencial de cada patólogo.(AU)

Introduction: In a pathological anatomy service, the workload in medical time is analyzed based on the complexity of the samples received and its distribution among pathologists is assessed, presenting a new computer algorithm that favors an equitable distribution. Methods: Following the second edition of the Spanish guidelines for the estimation of workload in cytopathology and histopathology (medical time) according to the Spanish Pathology Society-International Academy of Pathology (SEAP-IAP) catalog of samples and procedures, we determined the workload units (UCL) per pathologist and the overall UCL of the service, the average workload of the service (MU factor), the time dedicated by each pathologist to healthcare activity and the optimal number of pathologists according to the workload of the service. Results: We determined 12 197 total annual UCL for the chief pathologist, as well as 14 702 and 13 842 UCL for associate pathologists, with an overall of 40 742 UCL for the whole service. The calculated MU factor is 4.97. The chief pathologist devoted 72.25% of his working day to healthcare activity while associate pathologists dedicated 87.09% and 82.01% of their working hours. The optimal number of pathologists for the service is found to be 3.55. Conclusions: The results demonstrate medical work overload and a non-equitable distribution of UCLs among pathologists. We propose a computer algorithm capable of distributing the workload in an equitable manner. It would be associated with the laboratory information system and take into account the type of specimen, its complexity and the dedication of each pathologist to healthcare activity.(AU)

You Cannot Function in "Overwhelm": Helping Primary Care Navigate the Slow End of the Pandemic.

GOAL: This study was developed to explicate underlying organizational factors contributing to the deterioration of primary care clinicians' mental health during the COVID-19 pandemic. METHODS: Using data from the Larry A. Green Center for the Advancement of Primary Health Care for the Public Good's national survey of primary care clinicians from March 2020 to March 2022, a multidisciplinary team analyzed more than 11,150 open-ended comments. Phase 1 of the analysis happened in real-time as surveys were returned, using deductive and inductive coding. Phase 2 used grounded theory to identify emergent themes. Qualitative findings were triangulated with the survey's quantitative data. PRINCIPAL FINDINGS: The clinicians shifted from feelings of anxiety and uncertainty at the start of the pandemic to isolation, lack of fulfillment, moral injury, and plans to leave the profession. The frequency with which they spoke of depression, burnout, and moral injury was striking. The contributors to this distress included crushing workloads, worsening staff shortages, and insufficient reimbursement. Consequences, both felt and anticipated, included fatigue and demoralization from the inability to manage escalating workloads. Survey findings identified responses that could alleviate the mental health crisis, namely: (1) measuring and customizing workloads based on work capacity; (2) quantifying resources needed to return to sufficient staffing levels; (3) promoting state and federal support for sustainable practice infrastructures with less administrative burden; and (4) creating patient visits of different lengths to rebuild relationships and trust and facilitate more accurate diagnoses. PRACTICAL APPLICATIONS: Attention to clinicians' mental health should be rapidly directed to on-demand, confidential mental health support so they can receive the care they need and not worry about any stigma or loss of license for accepting that help. Interventions that address work-life balance, workload, and resources can improve care, support retention of the critically important primary care workforce, and attract more trainees to primary care careers.

An examination of the usefulness of a quantitative appraisal method in nursing human resource management in primary hospital operating rooms: An example of integrated collaborative scheduling.

In recent years, China medical and health services have made great development. However, the management of nursing human resources in operating room of primary hospitals still faces a series of challenges. In the nursing work of operating room, high-quality nursing human resource management is important for improving the efficiency of operating room and ensuring the safety of patients. From January 2022 to December 2022, comprehensive collaborative scheduling and quantitative scoring evaluation methods were carried out in our hospital, and relevant data were collected. The flexible scheduling combined quantitative scoring performance appraisal system and the traditional scheduling plus average distribution performance appraisal system were statistically analyzed and compared in terms of annual surgical cases, annual overtime hours, annual back work hours, annual compensatory rest hours, and average daily working hours. This study was based on 30 medical staff (27 females and 3 males) in the operating room of a primary hospital. The annual operation volume increased by 387 cases compared with before, and the attitudes of patients to the service attitude and preoperative waiting time were significantly improved, reaching more than 95%. In addition, in the survey of surgeons, it was found that their satisfaction with preoperative preparation and operation time was significantly higher than that of the traditional scheduling method, and reached more than 95%. In the survey of nursing staff, it was found that the satisfaction with the traditional scheduling method was about 80%, and the satisfaction directly reached 100% after the comprehensive collaborative scheduling system. Based on the above survey, the satisfaction of nurses, doctors and patients with the new comprehensive collaborative scheduling system has improved compared with before. After the implementation of the comprehensive collaborative scheduling system, the annual surgical volume has increased significantly, and the average daily working hours of nursing staff have decreased. Comprehensive collaborative scheduling is an effective method of nursing human resource management in operating room, which can effectively improve the work efficiency of nurses and the satisfaction of patients, doctors and nurses. In practice, this method needs to be continuously explored and refined to adapt to different application scenarios and requirements.

Calibrated to drive: Measuring self-assessed driving ability and perceived workload after prolonged sitting and sleep restriction.

Self-assessed driving ability may differ from actual driving performance, leading to poor calibration (i.e., differences between self-assessed driving ability and actual performance), increased risk of accidents and unsafe driving behaviour. Factors such as sleep restriction and sedentary behaviour can impact driver workload, which influences driver calibration. This study aims to investigate how sleep restriction and prolonged sitting impact driver workload and driver calibration to identify strategies that can lead to safer and better calibrated drivers. Participants (n = 84, mean age = 23.5 ± 4.8, 49 % female) undertook a 7-day laboratory study and were randomly allocated to a condition: sitting 9-h sleep opportunity (Sit9), breaking up sitting 9-h sleep opportunity (Break9), sitting 5-h sleep opportunity (Sit5) and breaking up sitting 5-h sleep opportunity (Break5). Break9 and Break5 conditions completed 3-min of light-intensity walking on a treadmill every 30 min between 09:00-17:00 h, while participants in Sit9 and Sit5 conditions remained seated. Each participant completed a 20-min simulated commute in the morning and afternoon each day and completed subjective assessments of driving ability and perceived workload before and after each commute. Objective driving performance was assessed using a driving simulator measuring speed and lane performance metrics. Driver calibration was analysed using a single component and 3-component Brier Score. Correlational matrices were conducted as an exploratory analysis to understand the strength and direction of the relationship between subjective and objective driving outcomes. Analyses revealed participants in Sit9 and Break9 were significantly better calibrated for lane variability, lane position and safe zone-lane parameters at both time points (p < 0.0001) compared to Sit5 and Break5. Break5 participants were better calibrated for safe zone-speed and combined safe zone parameters (p < 0.0001) and speed variability at both time points (p = 0.005) compared to all other conditions. Analyses revealed lower perceived workload scores at both time points for Sit9 and Break9 participants compared to Sit5 and Break5 (p = <0.001). Breaking up sitting during the day may reduce calibration errors compared to sitting during the day for speed keeping parameters. Future studies should investigate if different physical activity frequency and intensity can reduce calibration errors, and better align a driver's self-assessment with their actual performance.

Nurse Staffing, Work Hours, Mandatory Overtime, and Turnover in Acute Care Hospitals Affect Nurse Job Satisfaction, Intent to Leave, and Burnout: A Cross-Sectional Study.

Objectives: This study examined the impact of nurse staffing, working hours, mandatory overtime, and turnover on nurse outcomes in acute care hospitals. Previous studies have focused on the single characteristics of sub-optimal nurse staffing but have not considered them comprehensively. Methods: Data were collected in July-September 2022 using convenience sampling and an online survey (N = 397). For the analysis, 264 nurses working as staff nurses at 28 hospitals met the inclusion criteria. Univariate analysis and multivariable generalized estimating equation (GEE) were performed. Results: Both nurse staffing (ß = -0.036, standard error [SE] = 0.011) and turnover (ß = -0.006, SE = 0.003) were significant factors affecting job satisfaction. In the multivariable GEE, only mandatory overtime (ß = 0.395, SE = 0.116) was significantly related to intent to leave. Nurse staffing, work hours, mandatory overtime, and turnover were not significantly related to burnout. Subjective health status and workload were significantly associated with burnout. Conclusion: Nurse staffing policies and improvement programs in hospitals should be implemented to improve nurses' job satisfaction. Labor policy should ban mandatory overtime.

Gender Difference of Burnout in Physicians Working in Tertiary Care Hospital: A Cross-Sectional Study.

Burnout and emotional exhaustion are becoming common among health workers in the busy teaching hospitals due to increased workload and the dearth of human resource. This study aimed to determine the causes of burnout among doctors and across gender differences. This was a descriptive cross-sectional study conducted in the Fauji Foundation Hospital, Rawalpindi, Pakistan, from 1st July to 30th September 2022. Two hundred and forty-five randomly recruited doctors who filled out self-administered questionnaires were included in the study. Independent samples t-test was used for comparison of the mean emotional burnout score. Female doctors felt more emotionally drained, more fatigued, and more worn out from work than male doctors (p < 0.05). Overall emotional exhaustion was also higher in female doctors (p < 0.05). This situation was more serious during the COVID-19 pandemic. Gender-sensitive environments, workplace policies, and necessary interventions will save physicians' burnout and brain drain. Emotional burnout is greater in female doctors as compared to their male counterparts. This evidence not only calls for prevention and treatment but also certain service-related reforms to facilitate female physicians to balance out their work and family lives more effectively. Key Words: Physicians, Emotional exhaustion, Burnout, Gender difference, Pakistan.

Chapitre 1. La charge professionnelle du télétravailleur.

The organization of work through the remote practice of professional activity maintains a strong link with the notion of workload, given the implications that can be generated in terms of duration, work intensification and therefore overload for the teleworker. The legal mobilization of this notion is developing with the very expansion of the practice of telecommuting. Under the banner of the employer’s general safety obligation, case law and legislation are likely to evolve (by reinforcing the obligation to control and monitor workloads), as is the case with the « forfait en jours » system, another flexible work organization method.

Clinical Full-Time Equivalent in PICUs: Survey of the U.S. Pediatric Critical Care Chiefs Network, 2020-2022.

OBJECTIVES: To inform workforce planning for pediatric critical care (PCC) physicians, it is important to understand current staffing models and the spectrum of clinical responsibilities of physicians. Our objective was to describe the expected workload associated with a clinical full-time equivalent (cFTE) in PICUs across the U.S. Pediatric Critical Care Chiefs Network (PC3N). DESIGN: Cross-sectional survey. SETTING: PICUs participating in the PC3N. SUBJECTS: PICU division chiefs or designees participating in the PC3N from 2020 to 2022. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A series of three surveys were used to capture unit characteristics and clinical responsibilities for an estimated 1.0 cFTE intensivist. Out of a total of 156 PICUs in the PC3N, the response rate was 46 (30%) to all three distributed surveys. Respondents used one of four models to describe the construction of a cFTE-total clinical hours, total clinical shifts, total weeks of service, or % full-time equivalent. Results were stratified by unit size. The model used for construction of a cFTE did not vary significantly by the total number of faculty nor the total number of beds. The median (interquartile range) of clinical responsibilities annually for a 1.0 cFTE were: total clinical hours 1750 (1483-1858), total clinical shifts 142 (129-177); total weeks of service 13.0 (11.3-16.0); and total night shifts 52 (36-60). When stratified by unit size, larger units had fewer nights or overnight hours, but covered more beds per shift. CONCLUSIONS: This survey of the PC3N (2020-2022) provides the most contemporary description of clinical responsibilities associated with a cFTE physician in PCC. A 1.0 cFTE varies depending on unit size. There is no correlation between the model used to construct a cFTE and the associated clinical responsibilities.

Optimizing Human-Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis.

The transition to Industry 4.0 and 5.0 underscores the need for integrating humans into manufacturing processes, shifting the focus towards customization and personalization rather than traditional mass production. However, human performance during task execution may vary. To ensure high human-robot teaming (HRT) performance, it is crucial to predict performance without negatively affecting task execution. Therefore, to predict performance indirectly, significant factors affecting human performance, such as engagement and task load (i.e., amount of cognitive, physical, and/or sensory resources required to perform a particular task), must be considered. Hence, we propose a framework to predict and maximize the HRT performance. For the prediction of task performance during the development phase, our methodology employs features extracted from physiological data as inputs. The labels for these predictions-categorized as accurate performance or inaccurate performance due to high/low task load-are meticulously crafted using a combination of the NASA TLX questionnaire, records of human performance in quality control tasks, and the application of Q-Learning to derive task-specific weights for the task load indices. This structured approach enables the deployment of our model to exclusively rely on physiological data for predicting performance, thereby achieving an accuracy rate of 95.45% in forecasting HRT performance. To maintain optimized HRT performance, this study further introduces a method of dynamically adjusting the robot's speed in the case of low performance. This strategic adjustment is designed to effectively balance the task load, thereby enhancing the efficiency of human-robot collaboration.

The Impact of Various Cockpit Display Interfaces on Novice Pilots' Mental Workload and Situational Awareness: A Comparative Study.

Future airspace is expected to become more congested with additional in-service cargo and commercial flights. Pilots will face additional burdens in such an environment, given the increasing number of factors that they must simultaneously consider while completing their work activities. Therefore, care and attention must be paid to the mental workload (MWL) experienced by operating pilots. If left unaddressed, a state of mental overload could affect the pilot's ability to complete his or her work activities in a safe and correct manner. This study examines the impact of two different cockpit display interfaces (CDIs), the Steam Gauge panel and the G1000 Glass panel, on novice pilots' MWL and situational awareness (SA) in a flight simulator-based setting. A combination of objective (EEG and HRV) and subjective (NASA-TLX) assessments is used to assess novice pilots' cognitive states during this study. Our results indicate that the gauge design of the CDI affects novice pilots' SA and MWL, with the G1000 Glass panel being more effective in reducing the MWL and improving SA compared with the Steam Gauge panel. The results of this study have implications for the design of future flight deck interfaces and the training of future pilots.

Adjunct Preceptor Perceptions of Motivation, Understanding, and Support for the Precepting Role.

OBJECTIVE: To determine adjunct pharmacist preceptor perceptions of their precepting role related to three domains: motivation to precept, understanding the precepting role, and support for precepting. METHODS: An online cross-sectional survey of 2429 adjunct preceptors for four schools of pharmacy was conducted. Participants ranked their agreement with 81 statements regarding the three domains, including eleven subdomains. RESULTS: Mean scores for the three domains were slightly below the positive response level, with lower scores found for the subdomains of workload, precepting norms, and extrinsic benefits/rewards. Individual statements indicated increased workload due to precepting, need for more preceptor recognition and appreciation, perceptions that precepting was stressful or draining, and a preference for one concurrent learner. More frequent need for extra coaching for APPE students negatively impacted all domains, including nine subdomains. CONCLUSION: This study provides a formal evaluation of adjunct preceptor perceptions of their precepting role. Compared to previous studies, these results may indicate lower satisfaction with precepting, suggesting opportunities exist to improve the adjunct precepting experience. Actions by schools/colleges of pharmacy are necessary to ensure experiential education capacity including addressing workload concerns, increasing preceptor recognition and appreciation, and supporting preceptors when students need extra coaching.

Gaze entropy metrics for mental workload estimation are heterogenous during hands-off level 2 automation.

As the level of vehicle automation increases, drivers are more likely to engage in non-driving related tasks which take their hands, eyes, and/or mind away from the driving task. Consequently, there has been increased interest in creating Driver Monitoring Systems (DMS) that are valid and reliable for detecting elements of driver state. Workload is one element of driver state that has remained elusive within the literature. Whilst there has been promising work in estimating mental workload using gaze-based metrics, the literature has placed too much emphasis on point estimate differences. Whilst these are useful for establishing whether effects exist, they ignore the inherent variability within individuals and between different drivers. The current work builds on this by using a Bayesian distributional modelling approach to quantify the within and between participants variability in Information Theoretical gaze metrics. Drivers (N = 38) undertook two experimental drives in hands-off Level 2 automation with their hands and feet away from operational controls. During both drives, their priority was to monitor the road before a critical takeover. During one drive participants had to complete a secondary cognitive task (2-back) during the hands-off Level 2 automation. Changes in Stationary Gaze Entropy and Gaze Transition Entropy were assessed for conditions with and without the 2-back to investigate whether consistent differences between workload conditions could be found across the sample. Stationary Gaze Entropy proved a reliable indicator of mental workload; 92 % of the population were predicted to show a decrease when completing 2-back during hands-off Level 2 automated driving. Conversely, Gaze Transition Entropy showed substantial heterogeneity; only 66 % of the population were predicted to have similar decreases. Furthermore, age was a strong predictor of the heterogeneity of the average causal effect that high mental workload had on eye movements. These results indicate that, whilst certain elements of Information Theoretic metrics can be used to estimate mental workload by DMS, future research needs to focus on the heterogeneity of these processes. Understanding this heterogeneity has important implications toward the design of future DMS and thus the safety of drivers using automated vehicle functions. It must be ensured that metrics used to detect mental workload are valid (accurately detecting a particular driver state) as well as reliable (consistently detecting this driver state across a population).

Work-, lifestyle-, and health-related factors among women and men working in the emergency medical services.

Objectives. This study aimed to describe work-, lifestyle-, and health-related factors among ambulance personnel, and to analyse differences between women and men. Methods. The cross-sectional study (N = 106) included self-reported and objective measures of work, lifestyle, and health in 10 Swedish ambulance stations. The data collection comprised clinical health examination, blood samples, tests of physical capacity, and questionnaires. Results. A high proportion of the ambulance personnel reported heavy lifting, risk of accidents, threats and violence at work. A low level of smoking and alcohol use, and a high level of leisure-time physical activity were reported. The ambulance personnel had, on average, good self-rated health, high work ability and high physical capacity. However, the results also showed high proportions with risk factors for cardiovascular disease (CVD), e.g., high blood pressure, and high levels of blood lipids. More women than men reported high work demands. Furthermore, women performed better in tests of physical capacity and had a lower level of CVD risk factors. Conclusions. Exposure to work-related factors that might affect health was common among ambulance personnel. Lifestyle- and health-related factors were somewhat contradictory, with a low proportion reporting lifestyle-related risk factors, but a high proportion having risk factors for CVD.

Investigating learning burnout and academic performance among management students: a longitudinal study in English courses.

This study aims to move away from the cross-sectional approach related to burnout and conduct a longitudinal study to explore the factors influencing learning burnout among management students. The study primarily adopts a questionnaire survey, with students majoring in business management. Descriptive statistics and structural equation modeling (SEM) are used to analyze the data and validate the hypotheses. The findings are: (1) There is a significant negative relationship between English anxiety and self-efficacy and a significant positive relationship between past English learning performance and self-efficacy. (2) The changes in self-efficacy are negatively related to the changes in burnout, while the changes in workload are positively related to the changes in burnout. Additionally, there is a positive relationship between English anxiety and learning burnout. (3) There is a significant negative relationship between English learning performance and burnout. The direct impact of self-efficacy on English learning performance is not supported, but it has an indirect effect through the mediating role of burnout. The study proposes strategies to improve student outcomes and well-being: (1) making English courses more engaging to boost performance and confidence, reducing learning burnout; (2) encouraging and supporting students to enhance self-efficacy and motivation; (3) assigning tasks seen as useful and interesting to lessen perceived workload and emotional exhaustion; (4) and considering English anxiety in admissions to decrease learning burnout, especially as schools gain more autonomy in their policies.

Classification of mental workload using brain connectivity and machine learning on electroencephalogram data.

Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess mental workload from EEG data that use effective brain connectivity for the purpose of extracting features, a hierarchical feature selection algorithm to select the most significant features, and finally machine learning models. We have used the Simultaneous Task EEG Workload (STEW) dataset, an open-access collection of raw EEG data from 48 subjects. We extracted brain-effective connectivities by the direct directed transfer function and then selected the top 30 connectivities for each standard frequency band. Then we applied three feature selection algorithms (forward feature selection, Relief-F, and minimum-redundancy-maximum-relevance) on the top 150 features from all frequencies. Finally, we applied sevenfold cross-validation on four machine learning models (support vector machine (SVM), linear discriminant analysis, random forest, and decision tree). The results revealed that SVM as the machine learning model and forward feature selection as the feature selection method work better than others and could classify the mental workload levels with accuracy equal to 89.53% (± 1.36).

A qualitative study on the adoption of the new duty hour regulations among medical residents and faculty in Korea.

Duty hour regulations (DHRs) were enforced in 2017 in Korea to prevent the detrimental effects of excessively prolonged working hours among medical residents. We investigated the adoption of and implications of the new DHRs among medical residents and faculty members. Semi-structured interviews were conducted with 15 medical residents and 9 faculty members across general surgery, internal medicine, obstetrics-gynecology, and pediatrics departments at Chonnam National University Hospital. Based on the constructivist grounded theory, we developed themes from the data by concurrent coding and analysis with theoretical sampling until data saturation. In addition, respondent validation was used to ensure accuracy, and all authors remained reflexive throughout the study to improve validity. The methods of DHRs adoption among residents and faculty members included the following 4 themes: DHRs improved work schedule, residents have more time to learn on their own, clinical departments have come to distribute work, organization members have strived to improve patient safety. Residents have undertaken initial steps towards creating a balance between personal life and work. Teamwork and shift within the same team are the transitions that minimize discontinuity of patient care considering patient safety. Teaching hospitals, including faculty members, should ensure that residents' work and education are balanced with appropriate clinical experience and competency-based training.