Background: Patient monitoring is indispensable in any operating room to follow the patient’s current health state based on measured physiological parameters. Reducing workload helps to free cognitive resources and thus influences human performance, which ultimately improves the quality of care. Among the many methods available to assess perceived workload, the National Aeronautics and Space Administration Task Load Index (NASA-TLX) provides the most widely accepted tool. However, only few studies have investigated the validity of the NASA-TLX in the health care sector. Objective: This study aimed to validate a modified version of the raw NASA-TLX in patient monitoring tasks by investigating its correspondence with expected lower and higher workload situations and its robustness against nonworkload-related covariates. This defines criterion validity. Methods: In this pooled analysis, we evaluated raw NASA-TLX scores collected after performing patient monitoring tasks in four different investigator-initiated, computer-based, prospective, multicenter studies. All of them were conducted in three hospitals with a high standard of care in central Europe. In these already published studies, we compared conventional patient monitoring with two newly developed situation awareness–oriented monitoring technologies called Visual Patient and Visual Clot. The participants were resident and staff anesthesia and intensive care physicians, and nurse anesthetists with completed specialization qualification. We analyzed the raw NASA-TLX scores by fitting mixed linear regression models and univariate models with different covariates. Results: We assessed a total of 1160 raw NASA-TLX questionnaires after performing specific patient monitoring tasks. Good test performance and higher self-rated diagnostic confidence correlated significantly with lower raw NASA-TLX scores and the subscores (all P<.001). Staff physicians rated significantly lower workload scores than residents (P=.001), whereas nurse anesthetists did not show any difference in the same comparison (P=.83). Standardized distraction resulted in higher rated total raw NASA-TLX scores (P<.001) and subscores. There was no gender difference regarding perceived workload (P=.26). The new visualization technologies Visual Patient and Visual Clot resulted in significantly lower total raw NASA-TLX scores and all subscores, including high self-rated performance, when compared with conventional monitoring (all P<.001). Conclusions: This study validated a modified raw NASA-TLX questionnaire for patient monitoring tasks. The scores obtained correctly represented the assumed influences of the examined covariates on the perceived workload. We reported high criterion validity. The NASA-TLX questionnaire appears to be a reliable tool for measuring subjective workload. Further research should focus on its applicability in a clinical setting.

This review provides a comprehensive and up-to-date overview of point-of-care (POC) devices most commonly used for coagulation analyses in the acute settings. Fast and reliable assessment of hemostasis is essential for the management of trauma and other bleeding patients. Routine coagulation assays are not designed to visualize the process of clot formation, and their results are obtained only after 30–90 m due to the requirements of sample preparation and the analytical process. POC devices such as viscoelastic coagulation tests, platelet function tests, blood gas analysis and other coagulometers provide new options for the assessment of hemostasis, and are important tools for an individualized, goal-directed, and factor-based substitution therapy. We give a detailed overview of the related tests, their characteristics and clinical implications. This review emphasizes the evident advantages of the speed and predictive power of POC clot measurement in the context of a goal-directed and algorithm-based therapy to improve the patient’s outcome. Interpretation of viscoelastic tests is facilitated by a new visualization technology.

Background: Dementia and mild cognitive impairment (MCI) are underrecognized in community settings. This may be due in part to the lack of brief dementia screening tools available to clinicians. We compared 2 brief, informant-based screening tests: the AD8 and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) in a community-based neurology practice in the midwestern United States. Methods: We examined 186 consecutive patients (44 controls, 13 with MCI, and 129 with dementia). Receiver operator characteristic curves were used to examine the ability of AD8 and IQCODE to discriminate between controls and MCI or dementia. Sensitivity, specificity, predictive values, and likelihood ratios were reported. Results: AD8 differentiated healthy controls from MCI (P<0.001) or dementia (P<0.001), and MCI from dementia (P=0.008). The IQCODE differentiated controls and MCI from dementia (both P<0.001), and between controls and MCI (P=0.002). Both AD8 (AUC=0.953; 95% confidence interval, 0.92-0.99) and IQCODE (AUC=0.930, 95% confidence interval, 0.88-0.97) provided discrimination between controls and patients with dementia; however, the AD8 had superior sensitivity detecting dementia (99.2%) and MCI (100%) compared with the IQCODE (79.1% for dementia, 46.1% for MCI) with nonoverlapping confidence intervals. Using published cut-offs (AD8≥2, IQCODE≥3.4), only 1 case of dementia was missed with the AD8, whereas the IQCODE failed to detect dementia in 27 individuals. The AD8 detected MCI in all 13 individuals, whereas the IQCODE misclassified 7 individuals. Conclusions: Both the AD8 and IQCODE were able to detect dementia in a community setting. The AD8, however, was more successful than IQCODE in detecting MCI. If simple and efficient screening for early cognitive impairment is the goal, particularly in the early stages (eg, for prevention trials or public screening), the combination of an informant interview (the AD8) and a brief performance measure could be considered as they meet the basic requirements of the Personalized Prevention Plan for Medicare beneficiaries.

Visual Patient technology is a situation awareness-oriented visualization technology that translates numerical and waveform patient monitoring data into a new user-centered visual language. Vital sign values are converted into colors, shapes, and rhythmic movements—a language humans can easily perceive and interpret—on a patient avatar model in real time. In this review, we summarize the current state of the research on the Visual Patient, including the technology, its history, and its scientific context. We also provide a summary of our primary research and a brief overview of research work on similar user-centered visualizations in medicine. In several computer-based studies under various experimental conditions, Visual Patient transferred more information per unit time, increased perceived diagnostic certainty, and lowered perceived workload. Eye tracking showed the technology worked because of the way it synthesizes and transforms vital sign information into new and logical forms corresponding to the real phenomena. The technology could be particularly useful for improving situation awareness in settings with high cognitive demand or when users must make quick decisions. This comprehensive review of Visual Patient research is the foundation for an evaluation of the technology in clinical applications, starting with a high-fidelity simulation study in early 2020.