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)

[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]. / 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.

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.

Workload reduction through automated documentation in intensive and intermediate care - a monocentric observational study.

OBJECTIVE: The global coronavirus pandemic has placed an unprecedented and enormous burden on health systems worldwide. In addition to a shortage of resources, nurses were also confronted with high levels of sick leave and an increasing exodus from the profession. Automating documentation obligations is an effective way of reducing the burden on the workplace. PATIENTS AND METHODS: The study was conducted at a tertiary university hospital. The time required for the manual documentation of administered medication and dose changes of syringe and infusion pumps was recorded using the patient data management system (PDMS) representing all intensive and intermediate care wards (n = 6). Subsequently, all medication administration - grouped into five classes - was evaluated from January 1st, 2019, until December 31st, 2022. RESULTS: A total of 1,373,340 drug applications were studied, treating 32,499 patients. Data were obtained from ICUs (68%) and IMC wards (32%). This corresponds to an overall time of 2,901 ± 233 hours per year. Based on publicly known national rates for intensive care nurses, an annual financial expenditure of approximately 83,300 € (~ USD 89,300) per year was estimated. CONCLUSIONS: A non-negligible part of the daily working time in the medical sector is spent on documentation duties. This aggravates the high workload, which has increased in recent years. Automated documentation systems can lead to considerable relief and the possibility of focusing primarily on the patient and on other core competencies and activities. This is even more important, as available staff will be a key resource in patient care for the foreseeable future.

The development and implementation of the district nursing Welsh Levels of Care Tool.

District nurses provide a vital service to individuals and their families and carers in the community. With increasing complexity of care and changes in the needs of the UK population, developing evidence-based workforce and workload tools which are fit for purpose is essential. This article describes the development, piloting and implementation of the District Nursing Welsh Levels of Care (DN WLoC), acuity and dependency tool which has been designed to be used alongside nurses professional judgment, to evidence the acuity and dependency of patients, and to help inform decisions of nurse staffing requirements in district nursing services. The initial pilot successfully achieved its objective and demonstrated that the draft DN WLoC tool is applicable in practice by district nurses across Wales, with limited but positive findings in the reliability and validity of the WLoC tool when applied in clinical practice.

How Transformational Leadership Affects the Off-work Recovery of Daily Personal Energy Resources via Work Engagement: Resource and Demand-based Pathways.

This study focuses on the transformational leadership-work engagement relationship by investigating resource and demand pathways for daily off-work recovery and employee wellbeing (EWB). While previous research highlighted how transformational leadership energizes employees to engage at work, energy is a finite resource requiring daily restoration for EWB. Yet, how the leader's energizing effect relates to daily employees' recovery remains unknown. Following job demands-resource-recovery theory, we test two pathways that relate the transformational leadership-work engagement relationship to daily employee recovery: (a) Resource-based via resource-building, (b) demand-based via increased demands. Utilizing a 10-day, two daily measurement (N = 88) study, multilevel path analyses revealed: transformational leadership predicted via work engagement (b = .17, p < .05) role clarity (b = .56, p < .01), then positive (b = .39, p < .01), and negative work-nonwork spillover (b = -.38, p < .01). Positive work-nonwork spillover predicted recovery positively (b = .25, p < .01), negative work-nonwork spillover negatively (b = -.40, p < .01). Recovery predicted EWB for positive (b = .38, p < .01) and for negative (b = -.43, p < .01) affect. Work engagement predicted workload (b = .35, p < .01), further negative (b = .33, p < .01) and positive work-nonwork spillover (b = -.16, p < .01), hampering EWB. As one pathway effect might cancel the other, the main effect of transformational leadership on EWB was not significant in the integrative model (p > .05). Results highlight dark and bright sides of the transformational leadership-work engagement relationship regarding daily recovery.

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.

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).

Validating the Effectiveness of the Patient-Centered Cancer Care Framework by Assessing the Impact of Work System Factors on Patient-Centered Care and Quality of Care: Interview Study With Newly Diagnosed Cancer Patients.

BACKGROUND: Patients with cancer who have recently been diagnosed have distinct requirements compared to cancer survivors. It is crucial to take into account their unique needs to ensure that they make informed decisions and are receptive to the care provided. OBJECTIVE: This study suggested a framework titled Effectiveness of Patient-Centered Cancer Care that considers the needs of newly diagnosed patients with cancer and related work system factors. This study investigated how work system factors influence the perceptions of patient-centered care, quality of care, and associated outcomes among newly diagnosed patients with cancer. Patient-centered care is defined in terms of workload and communication considerations, whereas the quality of care is assessed through indicators such as trust in physicians, satisfaction with care, and perceptions of technology. METHODS: This study used qualitative data collected through interviews with newly diagnosed patients with cancer (N=20) right after their first visits with their physicians. Thematic analysis was conducted to validate the 5 hypotheses of the framework, mapping the interactions among quality of care, patient-centered care, and work system factors. RESULTS: We found that workload and patient-centered communication impact the quality of care and that the work system elements impact the patient-centeredness (workload and communication) and the quality of care (trust in physicians, satisfaction with care, and perception of technology use). CONCLUSIONS: Qualitatively validating the proposed Effectiveness of Patient-Centered Cancer Care framework, this study demonstrated its efficacy in elucidating the interplay of various factors. The framework holds promise for informing interventions geared toward enhancing patients' experiences during their initial visits after diagnosis. There is a pressing need for heightened attention to the organizational design, patient processes, and collaborative efforts among diverse stakeholders and providers to optimize the overall patient experience.

Interruptions in a dental setting and evaluating the efficacy of an intervention: A pilot study.

INTRODUCTION: Interruptions during dental treatment are frequent, and often impact provider satisfaction and processing times We investigate the source and duration of such interruptions at a German dental clinic. METHODS: A pre-post approach was adopted at this dental clinic. This included direct observations of 3 dentists and 3 dental hygienists, and a survey of providers. Following that, an intervention (switchable 'Do Not Enter' sign) was chosen, and a pilot study was conducted to evaluate if the chosen intervention can reduce processing time and improve provider satisfaction. Additional observations and surveys were performed afterwards. RESULTS: Pre-intervention data indicated that interruptions have the highest negative impact on provider satisfaction at this clinic as well as on processing time during longer and more complex treatments, where a minor error due to an interruption could lead to rework of 30 minutes and more. The total number of interruptions dropped by 72.5% after the intervention, short interruptions (< 1min) by 86%. Provider survey indicated improvement due to the intervention in perceived workload, provider work satisfaction, patient safety and stress. CONCLUSIONS: This study demonstrates that a switchable sign can substantially reduce the number of interruptions in this dental clinic. It also shows the potential of improving the work environment by reducing interruptions to the dental providers.

Salud mental asociada a la pandemia de COVID-19 en estudiantes de fisioterapia de la Universidad Nacional Autónoma de México / Mental health associated with the COVID-19 pandemic in physiotherapy students at the National Autonomous University of Mexico

Antecedentes y objetivo: A nivel mundial la pandemia por el COVID-19 ha interrumpido el aprendizaje de más de mil millones de estudiantes, quienes reportan alteraciones en la salud mental, niveles altos de estrés académico y carga de trabajo. En la Licenciatura en Fisioterapia de la Universidad Nacional Autónoma de México, 331 estudiantes dejaron de asistir a clases presenciales indispensables para su formación académica y, tras un año de confinamiento, se desconoce el impacto psicológico y académico en esta población. El objetivo fue evaluar la salud mental, carga de trabajo y estrés académico de los estudiantes e identificar la asociación entre variables. Materiales y métodos: Se aplicó el Cuestionario de Salud Emocional por la Pandemia de COVID-19 - Fisioterapia, la escala de carga de trabajo UNIPSICO Battery y el Cuestionario de estrés estudiantil COVID-19. Se incluyeron los alumnos inscritos entre el primer y cuarto año de la Licenciatura en Fisioterapia de la Universidad Nacional Autónoma de México mayores de 18 años que contestaron la encuesta vía online y otorgaron su consentimiento informado. Resultados: El 62,7% de los estudiantes reportaron ansiedad, el 61,8% reportaron depresión, el 51,0% indicaron una percepción moderada del estrés académico y el 42,2% percibieron una carga de trabajo alta. La ansiedad y depresión tuvieron una asociación estadísticamente significativa con el estrés académico y carga de trabajo (p<0,05). Conclusiones: El estudio evidencia los efectos psicológicos y académicos derivados de la pandemia del COVID-19 en estudiantes de fisioterapia, que amerita medidas de intervención fisioterapéuticas y académicas que mitiguen los efectos del confinamiento.(AU)

Background and objective: Worldwide, the COVID-19 pandemic has disrupted the learning of over a billion students, who report mental health disorders, high levels of academic stress, and workload. In the bachelor's degree in physical therapy at the National Autonomous University of Mexico, 331 students stopped attending essential face-to-face classes for their academic training, and after a year of confinement, the psychological and academic impact on this population is unknown. The objective was to evaluate the mental health, workload, and academic stress of students in the bachelor's degree and identify the association between variables. Materials and methods: The Emotional Health Questionnaire for the COVID-19 pandemic – physical therapy was applied, including the UNIPSICO battery workload scale and the COVID-19 student stress questionnaire. Students enrolled between the first and fourth year of the Bachelor's degree in Physical Therapy at the National Autonomous University of Mexico over 18 years old who completed the survey online and provided informed consent were included. Results: 62.7% of students reported anxiety, 61.8% reported depression, 51.0% indicated a moderate perception of academic stress, and 42.2% perceived a high workload. Anxiety and depression had a statistically significant association with academic stress and workload (P<.05). Conclusions: The study demonstrates the psychological and academic effects of the COVID-19 pandemic on physical therapy students, which warrants physiotherapeutic and academic intervention measures to mitigate the effects of confinement.(AU)

Nurses' workload during the COVID-19 pandemic: potential for experiences of moral distress.

OBJECTIVES: to understand nurses' experiences of moral distress related to work overload during the COVID-19 pandemic in Brazil. METHODS: qualitative research, whose data collection occurred through individual interviews with 19 nurses who worked on the front line of COVID-19 in health services in southeastern Brazil. Data were analyzed using thematic content analysis. RESULTS: work overload proved to be a powerful source of experiences of moral distress due to excessive working hours during vaccination, double working hours, a troubled relationship due to pressure from managers and the population and physical and mental exhaustion, which prevented nurses from act according to their judgment. FINAL CONSIDERATIONS: nurses' work overload reflects on quality patient care and prevents nurses from acting in accordance with their moral principles, generating moral distress in nurses.

Factors related to Nursing workload in the Oncology assistance provided to hospitalized women.

OBJECTIVE: to evaluate the Nursing workload and its related factors in the assistance provided to hospitalized women with gynecological and breast cancers, according to the Nursing Activities Scores adapted for cancer patients. METHOD: a cross-sectional and epidemiological study. The participants were women with gynecological and/or breast cancer, over 18 years of age, and hospitalized for a minimum period of 24 hours. The following was collected from the medical records: sociodemographic and clinical data, Karnofsky Performance Status and workload, according to the adapted Nursing Activities Score. The factors related to workload were analyzed by means of multiple linear regression. RESULTS: the mean Nursing Activities Scores was 29.3%, denoting seven hours of daily care per patient. The factors related to workload differed according to the breast or gynecological cancer diagnosis (ß=-0.01; p<0.001), clinical or surgical treatment (ß=-0.03; p<0.001) and functional capacity at admission (ß=0.07; p<0.001), as per the Karnofsky Performance Status. CONCLUSION: there was greater workload for the care of women with gynecological cancer undergoing clinical treatment and with lower functional capacity at admission. The findings reveal directions for optimization of resources and improvements in work processes and flows, in order to promote a favorable work environment and good quality assistance. BACKGROUND: (1) A pioneer study in using the NAS instrument, adapted for Hospital Oncology. BACKGROUND: (2) The clinical treatment of gynecological/breast cancer demands a greater workload. BACKGROUND: (3) Functional capacity at the admission of women with cancer influences workload. BACKGROUND: (4) Gynecological cancer demands a greater Nursing workload than breast cancer.

A Review of the Use of Gaze and Pupil Metrics to Assess Mental Workload in Gamified and Simulated Sensorimotor Tasks.

Gaze and pupil metrics are used to represent higher cognitive processes in a variety of contexts. One growing area of research is the real-time assessment of workload and corresponding effort in gamified or simulated cognitive and motor tasks, which will be reviewed in this paper. While some measurements are consistent across studies, others vary and are likely dependent on the nature of the effort required by the task and the resulting changes in arousal. Pupil diameter is shown to consistently increase with task effort and arousal; however, the valence of arousal must be considered. In many cases, measures of pupil diameter were sensitive to both excessive and insufficient challenge. Overall, it is evident that gaze and pupil metrics are valuable to assess the cognitive state during gamified and simulated tasks, and further research is indicated regarding their use in clinical populations in rehabilitation to inform optimally engaging interventions.

Evaluating Technicians' Workload and Performance in Diagnosis for Corrective Maintenance.

The advancement in digital technology is transforming the world. It enables smart product-service systems that improve productivity by changing tasks, processes, and the ways we work. There are great opportunities in maintenance because many tasks require physical and cognitive work, but are still carried out manually. However, the interaction between a human and a smart system is inevitable, since not all tasks in maintenance can be fully automated. Therefore, we conducted a controlled laboratory experiment to investigate the impact on technicians' workload and performance due to the introduction of smart technology. Especially, we focused on the effects of different diagnosis support systems on technicians during maintenance activity. We experimented with a model that replicates the key components of a computer numerical control (CNC) machine with a proximity sensor, a component that requires frequent maintenance. Forty-five participants were evenly assigned to three groups: a group that used a Fault-Tree diagnosis support system (FTd-system), a group that used an artificial intelligence diagnosis support system (AId-system), and a group that used neither of the diagnosis support systems. The results show that the group that used the FTd-system completed the task 15% faster than the group that used the AId-system. There was no significant difference in the workload between groups. Further analysis using the NGOMSL model implied that the difference in time to complete was probably due to the difference in system interfaces. In summary, the experimental results and further analysis imply that adopting the new diagnosis support system may improve maintenance productivity by reducing the number of diagnosis attempts without burdening technicians with new workloads. Estimates indicate that the maintenance time and the cognitive load can be reduced by 8.4 s and 15% if only two options are shown in the user interface.

Determining Cognitive Workload Using Physiological Measurements: Pupillometry and Heart-Rate Variability.

The adoption of Industry 4.0 technologies in manufacturing systems has accelerated in recent years, with a shift towards understanding operators' well-being and resilience within the context of creating a human-centric manufacturing environment. In addition to measuring physical workload, monitoring operators' cognitive workload is becoming a key element in maintaining a healthy and high-performing working environment in future digitalized manufacturing systems. The current approaches to the measurement of cognitive workload may be inadequate when human operators are faced with a series of new digitalized technologies, where their impact on operators' mental workload and performance needs to be better understood. Therefore, a new method for measuring and determining the cognitive workload is required. Here, we propose a new method for determining cognitive-workload indices in a human-centric environment. The approach provides a method to define and verify the relationships between the factors of task complexity, cognitive workload, operators' level of expertise, and indirectly, the operator performance level in a highly digitalized manufacturing environment. Our strategy is tested in a series of experiments where operators perform assembly tasks on a Wankel Engine block. The physiological signals from heart-rate variability and pupillometry bio-markers of 17 operators were captured and analysed using eye-tracking and electrocardiogram sensors. The experimental results demonstrate statistically significant differences in both cardiac and pupillometry-based cognitive load indices across the four task complexity levels (rest, low, medium, and high). Notably, these developed indices also provide better indications of cognitive load responding to changes in complexity compared to other measures. Additionally, while experts appear to exhibit lower cognitive loads across all complexity levels, further analysis is required to confirm statistically significant differences. In conclusion, the results from both measurement sensors are found to be compatible and in support of the proposed new approach. Our strategy should be useful for designing and optimizing workplace environments based on the cognitive load experienced by operators.

Position-specific workload of professional rugby union players during tactical periodization training.

The positional workload characteristics in rugby union on three acquisition days (i.e. strength, endurance, and speed days) of tactical periodization are still relatively unknown. Therefore, the primary aim of this study was to shed light on the positional external workload variables (10 Hz Global Positioning System and accelerometer microtechnology) and internal workload indicators (the session rating of perceived exertion) of players in a professional rugby union team by utilizing and comparing two tactical periodization models. Twenty-six male players (15 forwards and 11 backs) were recruited from a French second-division rugby club. Data were obtained over 10 weeks of in-season home games: a total of 780 observations were analyzed. Student's t-test observed different external workload profiles between positions among acquisition days. Mean external workload values, except PlayerLoadslow, were significantly higher (p≤0.01; effect size: 0.41-1.93) for backs than forwards for all acquisition days. Moreover, forwards perceived a higher internal workload than backs on the strength day of both models. The findings demonstrate that applying these two tactical periodization models could result in effective rugby union training. Validating external and internal workload characteristics on tactical periodization acquisition days enables extensive analysis of training load monitoring data; these data can be utilized to discover the unique characteristics of each position and design position-specific acquisition days to improve performance.