[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.

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.

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.

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.

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 systematic review of the types, workload, and supervision mechanism of community health workers: lessons learned for Indonesia.

BACKGROUND: Community health workers (CHWs) have demonstrated capability to improve various health indicators, however, many programmes require support in meeting their objectives due to subpar performance and a high rate of CHW attrition. This systematic review investigated the types of CHWs, their workloads, and supervision practices that contribute to their performance in different countries. METHODS: The search was carried out in November 2022 in Medline, Embase, and Neliti for studies published in Indonesian or English between 1986 and 2022 that reported public health services delivered by CHWs who live and serve the community where they live but are not considered health professionals. The findings were synthesised using a thematic analysis to assess key factors influencing the performance of CHWs. RESULTS: Sixty eligible articles were included in this review. CHWs were responsible for more than two diseases (n = 35) and up to fifteen, with more than eighteen activities. Their roles covered the human life cycle, from preparation for pregnancy, care for newborns, health for children, adolescents, and productive age to elderly individuals. They were also involved in improving environmental health, community empowerment, and other social issues hindering access to health services. They carried out promotive, preventive, and curative interventions. The CHW-population ratio varied from eight to tens of thousands of people. Some CHWs did not have a clear supervision system. Challenges that were often faced by CHWs included inappropriate incentives, inadequate facilities, insufficient mentoring, and supervision, many roles, and a broad catchment area. Many studies revealed that CHWs felt overburdened and stressed. They needed help to balance their significant work and domestic tasks. CONCLUSIONS: Effective planning that considered the scope of work of CHWs in proportion to their responsibilities and the provision of necessary facilities were crucial factors in improving the performance of CHWs. Supportive supervision and peer-supervision methods are promising, however, any CHW supervision required a detailed protocol. This systematic review emphasised the opportunity for CHW management system improvement in Indonesia.

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.

User Experience Evaluation of a Spinal Surgery Robot: Workload, Usability, and Satisfaction Study.

BACKGROUND: Robotic spine surgery has continued to evolve since its US Food and Drug Administration approval in 2004, with products now including real-time video guidance and navigation during surgery. As the market for robotic surgical devices evolves, it is important to consider usability factors. OBJECTIVE: The primary objective of this study was to determine the user experience of a surgical-assistive robotic device. The secondary objective was to evaluate workload, usability, the After-Scenario Questionnaire (ASQ), and the System Usability Scale (SUS). In addition, this study compares the workload, usability, and satisfaction survey of the device among different occupational groups using the device. METHODS: Doctors (n=15) and nurses (n=15), the intended users of the surgical assistant robot, participated in the usability evaluation. Participants performed essential scenarios for the surgical assistant robot and provided scenario-specific satisfaction (ASQ), workload (NASA Task Load Index), and usability (SUS) scores. RESULTS: Both doctors and nurses had task success rates of 85% or higher for each scenario. ASQ results showed that both doctors and nurses were least satisfied with ease of completing the task of registration (group 1: mean 4.73, SD 1.57 and group 2: mean 4.47, SD 1.8), amount of time it took (group 1: mean 4.47, SD 1.63 and group 2: mean 4.40, SD 2.09), and support information satisfaction (group 1: mean 5.13, SD 1.50 and group 2: mean 5.13, SD 1.89). All participants had low workloads, and the overall Task Load Index score had a P value of .77, which is greater than .05. The SUS results showed that the overall usability mean for doctors was 64.17 (SD 16.52) and the mean for nurses was 61.67 (SD 19.18), with a P value of .84, which is greater than .05, indicating no difference between the 2 groups. CONCLUSIONS: In this study, doctors and nurses evaluated the interaction of the device in a simulated environment, the operating room. By evaluating the use experience and usability of the device with real intended users, we can develop a more effective and convenient user interface.

On the impact of on-road partially-automated driving on drivers' cognitive workload and attention allocation.

The use of partially-automated or SAE level-2 vehicles is expected to change the role of the human driver from operator to supervisor, which may have an effect on the driver's workload and visual attention. In this study, 30 Ontario drivers operated a vehicle in manual and partially-automated mode. Cognitive workload was measured by means of the Detection Response Task, and visual attention was measured by means of coding glances on and off the forward roadway. No difference in cognitive workload was found between driving modes. However, drivers spent less time glancing at the forward roadway, and more time glancing at the vehicle's touchscreen. These data add to our knowledge of how vehicle automation affects cognitive workload and attention allocation, and show potential safety risks associated with the adoption of partially-automated driving.

Nonintubated spontaneous ventilation versus intubated mechanical ventilation anesthesia for video-assisted thoracic surgery in terms of perioperative complications and practitioners' workload assessments: a pilot randomized control study.

BACKGROUND: The use of nonintubated video-assisted thoracoscopic surgery (NI-VATS) has been increasingly reported to yield favourable outcomes. However, this technology has not been routinely used because its advantages and safety have not been fully confirmed. The aim of this study was to assess the safety and feasibility of nonintubated spontaneous ventilation (NI-SV) anesthesia compared to intubated mechanical ventilation (I-MV) anesthesia in VATS by evaluating of perioperative complications and practitioners' workloads. METHODS: Patients who underwent uniportal VATS were randomly assigned at a 1:1 ratio to receive NI-SV or I-MV anesthesia. The primary outcome was the occurrence of intraoperative airway intervention events, including transient MV, conversion to intubation and repositioning of the double-lumen tube. The secondary outcomes included perioperative complications and modified National Aeronautics and Space Administration Task Load Index (NASA-TLX) scores from anesthesiologists and surgeons. RESULTS: Thirty-five patients in each group were enrolled in the intention-to-treat analysis. The incidence of intraoperative airway intervention events was greater in the NI-SV group than in the I-MV group (12 [34.3%] vs. 3 [8.6%]; OR = 0.180; 95% CI = 0.045-0.710; p = 0.009). No significant difference was found in the postoperative pulmonary complications between the groups (p > 0.05). The median of the anesthesiologists' overall NASA-TLX score was 37.5 (29-52) when administering the NI-SV, which was greater than the 25 (19-34.5) when the I-MV was administered (p < 0.001). The surgeons' overall NASA-TLX score was comparable between the two ventilation strategies (28 [21-38.5] vs. 27 [20.5-38.5], p = 0.814). CONCLUSION: The NI-SV anesthesia was feasible for VATS in the selected patients, with a greater incidence of intraoperative airway intervention events than I-MV anesthesia, and with more surgical effort required by anesthesiologists. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2200055427. https://www.chictr.org.cn/showproj.html?proj=147872 was registered on January 09, 2022.

Workplace digitalization and workload: changes and reciprocal relations across 3 years.

This article reports the results of a 33-wave longitudinal study of changes in, and reciprocal relations between, workplace digitalization and workload. Monthly data were collected between April 2020 and December 2022 from n = 1661 employees in Germany. Based on theoretical models of workplace information and communication technology use, stress, and coping, we hypothesized both positive and negative within-person effects of digitalization on workload, and vice versa. Results of an autoregressive latent trajectory model with structured residuals (ALT-SR) showed on-average positive linear trajectories in digitalization, but not in workload over time. Moreover, higher digitalization was associated with subsequently higher levels of workload, and vice versa. This pattern of results suggests a dynamic, reciprocal process wherein positive deviations from one's average trajectory of digitalization (workload) are associated with subsequently higher levels of workload (digitalization). We additionally find evidence for linear trends in these within-person processes, suggesting that the strength of the within-person effects of digitalization on workload, and of workload on digitalization, becomes more strongly positive over time. Practitioners developing work design interventions could focus on ways to reduce the detrimental impact of digitalization on increased workload, while simultaneously encouraging the potential of digitalization to help employees cope effectively with their workload.

Non-invasive stress estimation in simulative endoscopy setting: literature review.

One of the most common stressors is so-called "occupational stress." It is defined as the sum of physical, mental and physiological responses to work in situations where the workload or stress associated with it intensifies for an extended period of time. It is a gradual process in which individual cognitive assessments of occupational stressors generate adverse health events and may lead to burnout. Since it has become a major problem in the medical field, studying, measuring and limiting it have been set as goals for the future.

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

OBJECTIVES: To assess whether a deep learning-based system (DLS) with black-blood imaging for brain metastasis (BM) improves the diagnostic workflow in a multi-center setting. MATERIALS AND METHODS: In this retrospective study, a DLS was developed in 101 patients and validated on 264 consecutive patients (with lung cancer) having newly developed BM from two tertiary university hospitals, which performed black-blood imaging between January 2020 and April 2021. Four neuroradiologists independently evaluated BM either with segmented masks and BM counts provided (with DLS) or not provided (without DLS) on a clinical trial imaging management system (CTIMS). To assess reading reproducibility, BM count agreement between the readers and the reference standard were calculated using limits of agreement (LoA). Readers' workload was assessed with reading time, which was automatically measured on CTIMS, and were compared between with and without DLS using linear mixed models considering the imaging center. RESULTS: In the validation cohort, the detection sensitivity and positive predictive value of the DLS were 90.2% (95% confidence interval [CI]: 88.1-92.2) and 88.2% (95% CI: 85.7-90.4), respectively. The difference between the readers and the reference counts was larger without DLS (LoA: -0.281, 95% CI: -2.888, 2.325) than with DLS (LoA: -0.163, 95% CI: -2.692, 2.367). The reading time was reduced from mean 66.9 s (interquartile range: 43.2-90.6) to 57.3 s (interquartile range: 33.6-81.0) (P <.001) in the with DLS group, regardless of the imaging center. CONCLUSION: Deep learning-based BM detection and counting with black-blood imaging improved reproducibility and reduced reading time, on multi-center validation.