Toward a better understanding of task demands, workload, and performance during physician-computer interactions

OBJECTIVE: To assess the relationship between (1) task demands and workload, (2) task demands and performance, and (3) workload and performance, all during physician-computer interactions in a simulated environment. METHODS: Two experiments were performed in 2 different electronic medical record (EMR) environments: WebCIS (n = 12) and Epic (n = 17). Each participant was instructed to complete a set of prespecified tasks on 3 routine clinical EMR-based scenarios: urinary tract infection (UTI), pneumonia (PN), and heart failure (HF). Task demands were quantified using behavioral responses (click and time analysis). At the end of each scenario, subjective workload was measured using the NASA-Task-Load Index (NASA-TLX). Physiological workload was measured using pupillary dilation and electroencephalography (EEG) data collected throughout the scenarios. Performance was quantified based on the maximum severity of omission errors. RESULTS: Data analysis indicated that the PN and HF scenarios were significantly more demanding than the UTI scenario for participants using WebCIS (P < .01), and that the PN scenario was significantly more demanding than the UTI and HF scenarios for participants using Epic (P < .01). In both experiments, the regression analysis indicated a significant relationship only between task demands and performance (P < .01). DISCUSSION: Results suggest that task demands as experienced by participants are related to participants' performance. Future work may support the notion that task demands could be used as a quality metric that is likely representative of performance, and perhaps patient outcomes. CONCLUSION: The present study is a reasonable next step in a systematic assessment of how task demands and workload are related to performance in EMR-evolving environments

Use of a Checklist to Facilitate the Recognition of a Transfusion Associated Adverse Event

Transfusions are the most common procedure that hospitalized patients undergo. One of the risks associated with a transfusion is a transfusion related adverse event (TAAE). Transfusion associated adverse events can occur in any patient receiving a transfusion. Some patients are at risk of certain TAAEs (e.g., heart failure patients at risk of transfusion associated circulatory overload) while other events (e.g., allergic reactions) cannot always be anticipated. The severity of a TAAE can range from mildly uncomfortable to life threatening. Nurses need to be able to identify the signs and symptoms of a possible TAAE and intervene immediately by stopping the infusion of the blood product, taking immediate action to stabilize the patient and contacting the provider and transfusion medicine services/blood bank. This experimental study describes how the use of a transfusion checklist could facilitate the recognition and management of TAAEs for all clinicians and in particular, student nurses

Emergency department crowding and provider workload

This observational field study attempted to quantify the objective task load imposed on emergency department (ED) providers, determine the degree of subjective workload they experience, and to correlate these data with ED operational metrics, mainly ED crowding metrics. Participants were a convenience sample of 10 emergency care providers; the 3 female and 7 male participants represented a variety of provider levels (6 physicians, 3 physician assistants, and 1 nurse practitioner). Forty-two hours of data were collected. ED variables were obtained from the hospital\u27s existing information system each hour and included the Emergency Severity Index (ESI), number of people in the waiting room, patient/doctor ratio, patient/nurse ratio, number of patients assigned, number of providers on duty and crowding variables; Emergency Department Work Index (EDWIN) and occupancy level. Providers were shadowed and observed each hour by a researcher who recorded the type of tasks they performed, the number of tasks they performed, the time they spent on each task and the number of times they were interrupted. Subjective workload ratings (NASA-TLX) were obtained from providers at the end of each hour of observation. Correlations were performed to evaluate the relation of observed, subjective and hospital variables. Overall objective task load was quantified using time-on-task data and task difficulty weightings to achieve a single standardized value for overall objective workload (OTLX). OTLX scores were regressed against ED crowding measures of occupancy and EDWIN score. Structured interviews were conducted with each participant following the observation sessions. Results from the study revealed that providers spent 75 percent of their time performing tasks related to communication with staff, direct patient care, and paperwork. The other 25 percent of their time was spent checking test results, admitting patients to the hospital, taking breaks, looking for supplies, checking the electronic whiteboard, and other job-related tasks. ED occupancy was positively correlated to subjective workload and predicted 30 percent of the variance in subjective workload. The EDWIN score, on the other hand, only predicted 9 percent of the variance in subjective workload. This study revealed no correlation between ED crowding and objective task load and ED crowding predicted less than 4 percent of the variance in OTLX scores. In accordance with Occam\u27s razor , ED occupancy may provide an advantage over more complex compound measures of ED crowding such as the EDWIN score in predicting provider subjective workload and may be more useful in making ED staffing and scheduling decisions. In addition to collected and recorded variables, valuable insights were obtained from ED providers regarding issues of ED crowding, time-pressure and workload. It is apparent from their responses that, in the absence of observable changes in task load, the quantity and status of the unseen patient weighs heavily on their minds. Future research should assess the number of patients waiting or the number of patients who have left without being seen (LWBS) not only as a metric of ED crowding but as a predictor of ED provider workload

An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment

One of the key goals of Pedagogy is to assess learning. Various paradigms exist and one of this is Cognitivism. It essentially sees a human learner as an information processor and the mind as a black box with limited capacity that should be understood and studied. With respect to this, an approach is to employ the construct of cognitive load to assess a learner\u27s experience and in turn design instructions better aligned to the human mind. However, cognitive load assessment is not an easy activity, especially in a traditional classroom setting. This research proposes a novel method for evaluating learning both employing subjective cognitive load assessment and natural language processing. It makes use of primary, empirical and deductive methods. In details, on one hand, cognitive load assessment is performed using well-known self-reporting instruments, borrowed from Human Factors, namely the Nasa Task Load Index and the Workload Profile. On the other hand, Natural Language Processing techniques, borrowed from Artificial Intelligence, are employed to calculate semantic similarity of textual information, provided by learners after attending a typical third-level class, and the content of the class itself. Subsequently, an investigation of the relationship of cognitive load assessment and textual similarity is performed to assess learning

A novel methodology for evaluating user interfaces in health care

A pilot study is reported to identify an improved method of evaluating digital user interfaces in health care. Experience and developments from the aviation industry and the NASA-TLX mental workload assessment tools are applied in conjunction with Nielsen heuristics for evaluating an Electronic Health Record System in an Irish hospital. The NASA-TLX performs subjective workload assessments on operators working with various human-computer systems. Results suggest that depending on the cognitive workload and the working context of users, the usability will differ for the same digital interface. We conclude that incorporating the NASA-TLX with Nielsen\u27s heuristics offers a more reliable method in design and evaluation of digital user interfaces in clinical environments, since the healthcare work context is taken into account. Improved interfaces can be expected to reduce medical errors and improve patient care

Optimizing assessors’ mental workload in rater-based assessment: a critical narrative review

Introduction Rater-based assessment has resulted in high cognitive demands for assessors within the education of health professionals. Rating quality may be influenced by the mental workload required of assessors to complete rating tasks. The objective of this review was to explore interventions or strategies aimed at measuring and reducing mental workload for improvement in assessment outcomes in health professions education. Methods A critical narrative review was conducted for English-language articles using the databases PubMed, EMBASE, and Google Scholar from conception until November 2018. To be included, articles were eligible if they reported results of interventions aimed at measuring or reducing mental workload in rater-based assessment. Results A total of six articles were included in the review. All studies were conducted in simulation settings (OSCEs or videotaped interactions). Of the four studies that measured mental workload, none found any reduction in mental workload as demonstrated by objective secondary task performance after interventions of assessor training or reductions in competency dimension assessment. Reductions in competency dimensions, however, did result in improvements in assessment quality across three studies. Discussion The concept of mental workload in assessment in medical education needs further exploration, including investigation into valid measures of assessors’ mental workload. It appears that adjusting raters’ focus may be a valid strategy to improve assessment outcomes. Future research should be designed to inform how to best reduce load in assessments to improve quality, while balancing the type and quantity of data needed for judgments.Scopu

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 133)

This special bibliography lists 276 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in September 1974

The impact of pandemics on healthcare providers\u27 workloads: A scoping review

Aims: To review and synthesize available evidence exploring the impact of pandemics on direct healthcare providers\u27 workloads in the acute care setting. Design: Scoping review. Data Sources: A review of English research articles published up to August 2022 that examined the impact of pandemics on healthcare providers’ workloads was undertaken. Studies were identified by searching four electronic databases: Medline (EBSCO), CINAHL (EBSCO), Web of Science and PsychInfo (EBSCO). Fifty-five studies met the inclusion criteria. Review Methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses Scoping Review checklist. Results: Healthcare workers experience an increase in workload pressures during a pandemic. This included patients requiring more care, undertaking non-normal work activities, increase in work content including changes to documentation, increase in demand and skills required, an increase in overtime and hours of work per week and higher patient-to-nurse ratios. The review also highlighted changes to the work environment and worsened work environments, including staffing shortages. Conclusion: Focused efforts from health organizations to prioritize supportive conditions, policies focused on improved work environments, staffing adequacy and fair and reasonable workloads will enhance retention of the current workforce and future planning for pandemics. Impact: Understanding workload challenges faced by frontline health professionals during the pandemic can improve planning, including policies and procedures, and resource allocation for future pandemic or emergency situations. In addition, extended periods of high workloads can impact staff retention. As many countries return to life after COVID-19, it is important that healthcare organizations examine staff pressures and identify ways to support staff moving forward. This will be vital for the future sustainability of the workforce. Patient or Public Contribution: No patient or public contribution