RESUMEN
Medical technology innovation has improved patient monitoring in perioperative and intensive care medicine and continuous improvement in the technology is now a central focus in this field. Because data density increases with the number of parameters captured by patient-monitoring devices, its interpretation has become more challenging. Therefore, it is necessary to support clinicians in managing information overload while improving their awareness and understanding about the patient's health status. Patient monitoring has almost exclusively operated on the single-sensor-single-indicator principle-a technology-centered way of presenting data in which specific parameters are measured and displayed individually as separate numbers and waves. An alternative is user-centered medical visualization technology, which integrates multiple pieces of information (e.g., vital signs), derived from multiple sensors into a single indicator-an avatar-based visualization-that is a meaningful representation of the real-world situation. Data are presented as changing shapes, colors, and animation frequencies, which can be perceived, integrated, and interpreted much more efficiently than other formats (e.g., numbers). The beneficial effects of these technologies have been confirmed in computer-based simulation studies; visualization technologies improved clinicians' situation awareness by helping them effectively perceive and verbalize the underlying medical issue, while improving diagnostic confidence and reducing workload. This review presents an overview of the scientific results and the evidence for the validity of these technologies.
Asunto(s)
Unidades de Cuidados Intensivos , Monitoreo Fisiológico , Tecnología , Humanos , Monitoreo Fisiológico/tendencias , Tecnología/tendencias , Seguridad del Paciente , Medicina Perioperatoria , ConcienciaciónRESUMEN
BACKGROUND: Cognitive ergonomics design of patient monitoring may reduce human factor errors in high-stress environments. Eye-tracking is a suitable tool to gain insight into the distribution of visual attention of healthcare professionals with patient monitors, which may facilitate their further development. METHODS: This prospective, exploratory, high-fidelity simulation study compared anesthesia personnel's visual attention (fixation count and dwell-time) to 15 areas of interest on the patient monitor during non-critical and critical anesthesia situations. Furthermore, we examined the extent to which participants' experience influenced visual attention and which vital signs displayed on the patient monitor received the most visual attention. We used mixed zero-inflated Poisson regression and mixed linear models to analyze the data. RESULTS: Analyzing 23 ten-minute scenarios, we found significantly more fixations to the areas of interest on the patient monitor during critical than non-critical situations (rate ratio of 1.45; 95% CI 1.33 to 1.59; p < 0.001). However, the dwell-time on the areas of interest did not significantly differ between the non-critical and critical situations (coefficient of - 1.667; 95% CI - 4.549 to 1.229; p = 0.27). The professional experience did not significantly influence the visual attention (fixation: rate ratio of 0.88; 95% CI 0.54 to 1.43; p = 0.61 and dwell-time: coefficient of 0.889; 95% CI - 1.465 to 3.229; p = 0.27). Over all situations, anesthesia personnel paid the most attention to the vital signs blood pressure (fixation: mean [SD] of 108 [74.83]; dwell-time: mean [SD] of 27 [15.90] seconds), end-expiratory carbon dioxide (fixation: mean [SD] of 59 [47.39]; dwell-time: mean [SD] of 30 [21.51] seconds), and the electrocardiogram (fixation: mean [SD] of 58 [64.70]; dwell-time: mean [SD] of 15 [14.95] seconds). CONCLUSIONS: Critical anesthesia situations increased anesthesia personnel's visual interaction with the patient monitor. Furthermore, we found that their visual attention focused mainly on a few vital signs. To assist clinicians in critical situations, manufacturers should optimize monitors to convey necessary information as easily and quickly as possible and optimize the visibility of less frequently observed but equally critical vital signs, especially when they are in an abnormal range.
Asunto(s)
Anestesia , Anestesiología , Tecnología de Seguimiento Ocular , Humanos , Monitoreo Fisiológico , Estudios ProspectivosRESUMEN
Acute bleeding during surgery or after trauma harms patients, and challenges involved physicians. Protocols and cognitive aids can help in such situations. This dual-centre study investigated physicians' opinions regarding two ways to present cognitive aids, graphic 'Haemostasis Traffic Light' and text-based, using the example of a coagulation management algorithm to identify the strengths and limitations of both presentation modalities. Using qualitative research methods, we identified recurring answer patterns and derived major topics and subthemes through inductive coding. Eighty-four physicians participated. We assigned each half randomly to one of the cognitive aids (graphic/text-based) and determined 447 usable statements. We qualitatively deduced the importance of having a cognitive aid for physicians. Furthermore, it is noticeable that the graphic group made more positive comments (154 of 242 (64%) statements), while the text-based participants made more negative annotations (126 of 205 (61%) statements), suggesting a generally stronger approval of this cognitive aid. Practitioner summary: This qualitative study provides an overview of physicians` positive and negative perceptions regarding two presentation ways for a coagulation management algorithm. Participants perceived the graphic method created according to user-centred design principles more positively. The analysis reveals components that an ideal algorithm should have to help streamline the decision-making process.
Asunto(s)
Recursos Audiovisuales , Médicos , Algoritmos , Humanos , Investigación CualitativaRESUMEN
BACKGROUND: Failures in situation awareness cause two-thirds of anaesthesia complications. Avatar-based patient monitoring may promote situation awareness in critical situations. METHODS: We conducted a prospective, randomised, high-fidelity simulation study powered for non-inferiority. We used video analysis to grade anaesthesia teams managing three 10 min emergency scenarios using three randomly assigned monitoring modalities: only conventional, only avatar, and split-screen showing both modalities side by side. The primary outcome was time to performance of critical tasks. Secondary outcomes were time to verbalisation of vital sign deviations and the correct cause of the emergency, perceived workload, and usability. We used mixed Cox and linear regression models adjusted for various potential confounders. The non-inferiority margin was 10%, or hazard ratio (HR) 0.9. RESULTS: We analysed 52 teams performing 154 simulations. For performance of critical tasks during a scenario, split-screen was non-inferior to conventional (HR=1.13; 95% confidence interval [CI], 0.96-1.33; not significant in test for superiority); the result for avatar was inconclusive (HR=0.98; 95% CI, 0.83-1.15). Avatar was associated with a higher probability for verbalisation of the cause of the emergency (HR=1.78; 95% CI, 1.13-2.81; P=0.012). We found no evidence for a monitor effect on perceived workload. Perceived usability was lower for avatar (coefficient=-23.0; 95% CI, -27.2 to -18.8; P<0.0001) and split-screen (-6.7; 95% CI, -10.9 to -2.4; P=0.002) compared with conventional. CONCLUSIONS: This study showed non-inferiority of split-screen compared with conventional monitoring for performance of critical tasks during anaesthesia crisis situations. The patient avatar improved verbalisation of the correct cause of the emergency. These results should be interpreted considering participants' minimal avatar but extensive conventional monitoring experience.
Asunto(s)
Anestesia/métodos , Enseñanza Mediante Simulación de Alta Fidelidad/métodos , Monitoreo Intraoperatorio/métodos , Interfaz Usuario-Computador , Anestesia/efectos adversos , Concienciación , Femenino , Humanos , Masculino , Estudios Prospectivos , Carga de TrabajoRESUMEN
BACKGROUND: Acoustic alarms in medical devices are vital for patient safety. State-of-the-art patient monitoring alarms are indistinguishable and contribute to alarm fatigue. There are two promising new sound modalities for vital sign alarms. Auditory icons convey alarms as brief metaphorical sounds, and voice alerts transmit information using a clear-spoken language. We compared how reliably healthcare professionals identified alarms using these two modalities. METHODS: This investigator-initiated computer-based multicentre simulation study included 28 anaesthesia providers who were asked to identify vital sign alarms in randomised order, once with voice alerts and once with auditory icons. We further assessed time to decision, diagnostic confidence, and perceived helpfulness. We analysed the results using mixed models, adjusted for possible confounders. RESULTS: We assessed 14 alarms for each modality, resulting in 392 comparisons across all participants. Compared with auditory icons, healthcare providers had 58 times higher odds of correctly identifying alarms using voice alerts (odds ratio 58.0; 95% confidence interval [CI]: 25.1-133.6; P<0.001), made their decisions about 14 s faster (coefficient -13.9; 95% CI: -15.8 to -12.1 s; P<0.001), perceived higher diagnostic confidence (100% [392 of 392] vs 43% [169 of 392; P<0.001]), and rated voice alerts as more helpful (odds ratio 138.2; 95% CI: 64.9-294.1; P<0.001). The participants were able to identify significantly higher proportions of alarms with voice alerts (98.5%; P<0.001) and auditory icons (54.1%; P<0.001) compared with state-of-the-art alarms (17.9%). CONCLUSIONS: Voice alerts were superior to auditory icons, and both were superior to current state-of-the-art auditory alarms. These findings demonstrate the potential that voice alerts hold for patient monitoring.
Asunto(s)
Acústica , Alarmas Clínicas , Monitoreo Fisiológico/métodos , Voz , Adulto , Percepción Auditiva , Simulación por Computador , Toma de Decisiones , Diseño de Equipo , Femenino , Personal de Salud/estadística & datos numéricos , Humanos , Masculino , Factores de TiempoRESUMEN
BACKGROUND: Acute bleeding is an omnipresent challenge for all physicians. Uncontrolled hemorrhage is the most common preventable cause of death after trauma worldwide. In different surgical disciplines, hemorrhage represents an independent risk factor for increased postoperative morbimortality, directly affecting patients' outcomes. This study asked anesthesiologists about their personal perceived challenges when treating bleeding patients. METHODS: This investigator-initiated, prospective, international, dual-center, mixed qualitative and quantitative study interrogated anesthesiologists about what they found easy and what difficult in treating acutely bleeding patients. Following the template approach for qualitative research, we identified major and minor topics through free inductive coding and word count. In a second step, we derived ten statements from the participants' answers. Using a field survey, we then asked the participants to rate their level of agreement with the derived statements. We analyzed the answers using one sample Wilcoxon test and the Mann-Whitney test. RESULTS: We included a total of 84 physicians in the qualitative interrogations and a different group of 42 anesthesiologists in the quantitative part. We identified 11 major topics and 19 associated subtopics. The main topics and the degree of agreement (here as agree or strongly agree) were as follows: "Complexity of the topic" (52.4% agreed to find the topic complex), "Cognitive aids" (92.9% agreed to find them helpful), "Time management" (64.3% agreed to feeling time pressure), "Human factors" (95.2% agreed that human factors are essential), "Resources" (95.2% agreed that resources are essential), "Experience" and "Low frequency of cases" (57.1% agreed to lack practice), "Diagnostic methods" (31.0% agreed that the interpretation of test results is difficult), "Anticoagulation" (85.7% agreed to it being difficult), "Treatment" (81.0% agreed to knowing the first therapeutic steps), and "Nothing". CONCLUSIONS: Anesthesiologists in two large tertiary care facilities in different parts of the world found coagulation management, especially in anticoagulated patients, complex. We identified the delayed diagnostic test results and their interpretation as challenges. Resources, treatment protocols and human factors such as team communication were perceived to facilitate management. Future studies should explore the challenges in smaller hospitals and other parts of the world and test new technologies addressing the identified difficulties.
Asunto(s)
Anestesiólogos/estadística & datos numéricos , Actitud del Personal de Salud , Hemorragia/terapia , Encuestas y Cuestionarios/estadística & datos numéricos , Enfermedad Aguda , Anestesiólogos/psicología , Argentina , Hemorragia/psicología , Humanos , Médicos/estadística & datos numéricos , Estudios Prospectivos , Investigación Cualitativa , SuizaRESUMEN
BACKGROUND: Viscoelastic hemostatic assays, such as rotational thromboelastometry (ROTEM) or thromboelastography, enable prompt diagnosis and accelerate targeted treatment. However, the complex interpretation of the results remains challenging. Visual Clot-a situation awareness-based visualization technology-was developed to assist clinicians in interpreting viscoelastic tests. OBJECTIVE: Following a previous high-fidelity simulation study, we analyzed users' perceptions of the technology, to identify its strengths and limitations from clinicians' perspectives. METHODS: This is a mixed qualitative-quantitative study consisting of interviews and a survey. After solving coagulation scenarios using Visual Clot in high-fidelity simulations, we interviewed anesthesia personnel about the perceived advantages and disadvantages of the new tool. We used a template approach to identify dominant themes in interview responses. From these themes, we defined 5 statements, which were then rated on Likert scales in a questionnaire. RESULTS: We interviewed 77 participants and 23 completed the survey. We identified 9 frequently mentioned topics by analyzing the interview responses. The most common themes were "positive design features," "intuitive and easy to learn," and "lack of a quantitative component." In the survey, 21 respondents agreed that Visual Clot is easy to learn and 16 respondents stated that a combination of Visual Clot and ROTEM would help them manage complex hemostatic situations. CONCLUSIONS: A group of anesthesia care providers found Visual Clot well-designed, intuitive, and easy to learn. Participants highlighted its usefulness in emergencies, especially for clinicians inexperienced in coagulation management. However, the lack of quantitative information is an area for improvement.
Asunto(s)
Anestesia , Hemostáticos , Enseñanza Mediante Simulación de Alta Fidelidad , Trombosis , Humanos , Coagulación Sanguínea , ClotrimazolRESUMEN
Patient monitoring is crucial in critical care medicine. Perceiving and interpreting multiple vital signs requires a high workload that can lead to decreased situation awareness and consequently inattentional blindness, defined as impaired perception of unexpectedly changing data. To facilitate information transfer, we developed and validated the Visual-Patient avatar. Generated by numerical data, the animation displays the status of vital signs and patient installations according to a user-centered design to improve situation awareness. As a surrogate parameter for information transfer in patient monitoring, we recorded visual attention using eye-tracking data. In this computer-based study, we compared the correlation of visually perceived and correctly interpreted vital signs between a Visual-Patient-avatar ICU and conventional patient monitoring. A total of 50 recruited study participants (25 nurses, 25 physicians) from five European study centers completed five randomized scenarios in both modalities. Using a stationary eye tracker as the primary endpoint, we recorded how long different areas of interest of the two monitoring modalities were viewed. In addition, we tested for a possible association between the length of time an area of interest was viewed and the correctness of the corresponding question. With the conventional monitor, participants looked at the installation site the longest (median 2.13-2.51 s). With the Visual-Patient-avatar ICU, gaze distribution was balanced; no area of interest was viewed for particularly long. For both modalities, the longer an area was viewed, the more likely the associated question was answered incorrectly (OR 0.97, 95% CI 0.95-0.99, p = 0.008). The Visual-Patient-avatar ICU facilitates and improves information transfer through its visualizations, especially with written information. The longer an area of interest was viewed, the more likely the associated question was answered incorrectly.
RESUMEN
BACKGROUND: Machine learning can analyze vast amounts of data and make predictions for events in the future. Our group created machine learning models for vital sign predictions. To transport the information of these predictions without numbers and numerical values and make them easily usable for human caregivers, we aimed to integrate them into the Philips Visual-Patient-avatar, an avatar-based visualization of patient monitoring. METHODS: We conducted a computer-based simulation study with 70 participants in 3 European university hospitals. We validated the vital sign prediction visualizations by testing their identification by anesthesiologists and intensivists. Each prediction visualization consisted of a condition (e.g., low blood pressure) and an urgency (a visual indication of the timespan in which the condition is expected to occur). To obtain qualitative user feedback, we also conducted standardized interviews and derived statements that participants later rated in an online survey. RESULTS: The mixed logistic regression model showed 77.9% (95% CI 73.2-82.0%) correct identification of prediction visualizations (i.e., condition and urgency both correctly identified) and 93.8% (95% CI 93.7-93.8%) for conditions only (i.e., without considering urgencies). A total of 49 out of 70 participants completed the online survey. The online survey participants agreed that the prediction visualizations were fun to use (32/49, 65.3%), and that they could imagine working with them in the future (30/49, 61.2%). They also agreed that identifying the urgencies was difficult (32/49, 65.3%). CONCLUSIONS: This study found that care providers correctly identified >90% of the conditions (i.e., without considering urgencies). The accuracy of identification decreased when considering urgencies in addition to conditions. Therefore, in future development of the technology, we will focus on either only displaying conditions (without urgencies) or improving the visualizations of urgency to enhance usability for human users.
RESUMEN
Artificial intelligence (AI) is predicted to play an increasingly important role in perioperative medicine in the very near future. However, little is known about what anesthesiologists know and think about AI in this context. This is important because the successful introduction of new technologies depends on the understanding and cooperation of end users. We sought to investigate how much anesthesiologists know about AI and what they think about the introduction of AI-based technologies into the clinical setting. In order to better understand what anesthesiologists think of AI, we recruited 21 anesthesiologists from 2 university hospitals for face-to-face structured interviews. The interview transcripts were subdivided sentence-by-sentence into discrete statements, and statements were then grouped into key themes. Subsequently, a survey of closed questions based on these themes was sent to 70 anesthesiologists from 3 university hospitals for rating. In the interviews, the base level of knowledge of AI was good at 86 of 90 statements (96%), although awareness of the potential applications of AI in anesthesia was poor at only 7 of 42 statements (17%). Regarding the implementation of AI in anesthesia, statements were split roughly evenly between pros (46 of 105, 44%) and cons (59 of 105, 56%). Interviewees considered that AI could usefully be used in diverse tasks such as risk stratification, the prediction of vital sign changes, or as a treatment guide. The validity of these themes was probed in a follow-up survey of 70 anesthesiologists with a response rate of 70%, which confirmed an overall positive view of AI in this group. Anesthesiologists hold a range of opinions, both positive and negative, regarding the application of AI in their field of work. Survey-based studies do not always uncover the full breadth of nuance of opinion amongst clinicians. Engagement with specific concerns, both technical and ethical, will prove important as this technology moves from research to the clinic.
RESUMEN
Acid-base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants' ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers' ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00-5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67-2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of -3.2 (95%CI -3.77 to -2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians' ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers' decision-making and may improve patient care.
RESUMEN
Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial blood gas (ABG) printouts. We presented six scenarios to anaesthesiologists, once with Visual Blood and once with the conventional ABG printout. The primary outcome was ABG parameter perception. The secondary outcomes included correct clinical diagnoses, perceived diagnostic confidence, and perceived workload. To analyse the results, we used mixed models and matched odds ratios. Analysing 300 within-subject cases, we showed noninferiority of Visual Blood compared to ABG printouts concerning the rate of correctly perceived ABG parameters (rate ratio, 0.96; 95% CI, 0.92-1.00; p = 0.06). Additionally, the study revealed two times higher odds of making the correct clinical diagnosis using Visual Blood (OR, 2.16; 95% CI, 1.42-3.29; p < 0.001) than using ABG printouts. There was no or, respectively, weak evidence for a difference in diagnostic confidence (OR, 0.84; 95% CI, 0.58-1.21; p = 0.34) and perceived workload (Coefficient, 2.44; 95% CI, -0.09-4.98; p = 0.06). This study showed that participants did not perceive the ABG parameters better, but using Visual Blood resulted in more correct clinical diagnoses than using conventional ABG printouts. This suggests that Visual Blood allows for a higher level of situation awareness beyond individual parameters' perception. However, the study also highlighted the limitations of today's virtual reality headsets and Visual Blood.
RESUMEN
Viscoelastic point-of-care haemostatic resuscitation methods, such as ROTEM or TEG, are crucial in deciding on time-efficient personalised coagulation interventions. International transfusion guidelines emphasise increased patient safety and reduced treatment costs. We analysed care providers' perceptions of ROTEM to identify perceived strengths and areas for improvement. We conducted a single-centre, mixed qualitative-quantitative study consisting of interviews followed by an online survey. Using a template approach, we first identified themes in the responses given by care providers about ROTEM. Later, the participants rated six statements based on the identified themes on five-point Likert scales in an online questionnaire. Seventy-seven participants were interviewed, and 52 completed the online survey. By analysing user perceptions, we identified ten themes. The most common positive theme was "high accuracy". The most common negative theme was "need for training". In the online survey, 94% of participants agreed that monitoring the real-time ROTEM temograms helps to initiate targeted treatment more quickly and 81% agreed that recurrent ROTEM training would be beneficial. Anaesthesia care providers found ROTEM to be accurate and quickly available to support decision-making in dynamic and complex haemostatic situations. However, clinicians identified that interpreting ROTEM is a complex and cognitively demanding task that requires significant training needs.
RESUMEN
Blood gas analysis plays a central role in modern medicine. Advances in technology have expanded the range of available parameters and increased the complexity of their interpretation. By applying user-centered design principles, it is possible to reduce the cognitive load associated with interpreting blood gas analysis. In this international, multicenter study, we explored anesthesiologists' perspectives on Visual Blood, a novel visualization technique for presenting blood gas analysis results. We conducted interviews with participants following two computer-based simulation studies, the first utilizing virtual reality (VR) (50 participants) and the second without VR (70 participants). Employing the template approach, we identified key themes in the interview responses and formulated six statements, which were rated using Likert scales from 1 (strongly disagree) to 5 (strongly agree) in an online questionnaire. The most frequently mentioned theme was the positive usability features of Visual Blood. The online survey revealed that participants found Visual Blood to be an intuitive method for interpreting blood gas analysis (median 4, interquartile range (IQR) 4-4, p < 0.001). Participants noted that minimal training was required to effectively learn how to interpret Visual Blood (median 4, IQR 4-4, p < 0.001). However, adjustments are necessary to reduce visual overload (median 4, IQR 2-4, p < 0.001). Overall, Visual Blood received a favorable response. The strengths and weaknesses derived from these data will help optimize future versions of Visual Blood to improve the presentation of blood gas analysis results.
RESUMEN
Background: In case of bleeding patients and in acute care, the assessment of residual direct oral anticoagulant (DOAC) activity is essential for evaluating the potential impact on hemostasis, especially when a timely decision on urgent surgery or intervention is required. Viscoelastic tests are crucial in a modern goal-directed coagulation management to assess patients' coagulation status. However, the role of viscoelastic test to detect and quantify residual DOAC plasma levels is controversially discussed. The aim of this review was to systematically summarize the evidence of viscoelastic tests for the assessment of residual DOAC activity. Method: PubMed, Embase, Scopus, and the Cochrane Library were searched for original articles investigating the effect of rivaroxaban, apixaban, edoxaban, or dabigatran plasma levels on different viscoelastic tests of the adult population from database inception to December 31, 2021. Results: We included 53 studies from which 31 assessed rivaroxaban, 22 apixaban, six edoxaban, and 29 dabigatran. The performance of viscoelastic tests varied across DOACs and assays. DOAC specific assays are more sensitive than unspecific assays. The plasma concentration of rivaroxaban and dabigatran correlates strongly with the ROTEM EXTEM, ClotPro RVV-test or ECA-test clotting time (CT) and TEG 6s anti-factor Xa (AFXa) or direct thrombin inhibitor (DTI) channel reaction time (R). Results of clotting time (CT) and reaction time (R) within the normal range do not reliable exclude relevant residual DOAC plasma levels limiting the clinical utility of viscoelastic assays in this context. Conclusion: Viscoelastic test assays can provide fast and essential point-of-care information regarding DOAC activity, especially DOAC specific assays. The identification and quantification of residual DOAC plasma concentration with DOAC unspecific viscoelastic assays are not sensitive enough, compared to recommended anti-Xa activity laboratory measurements. Systematic review registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=320629], identifier [CRD42022320629].
RESUMEN
BACKGROUND: Inadequate situational awareness accounts for two-thirds of preventable complications in anesthesia. An essential tool for situational awareness in the perioperative setting is the patient monitor. However, the conventional monitor has several weaknesses. Avatar-based patient monitoring may address these shortcomings and promote situation awareness, a prerequisite for good decision making. OBJECTIVE: The spatial distribution of visual attention is a fundamental process for achieving adequate situation awareness and thus a potential quantifiable surrogate for situation awareness. Moreover, measuring visual attention with a head-mounted eye-tracker may provide insights into usage and acceptance of the new avatar-based patient monitoring modality. METHODS: This prospective eye-tracking study compared anesthesia providers' visual attention on conventional and avatar-based patient monitors during simulated critical anesthesia events. We defined visual attention, measured as fixation count and dwell time, as our primary outcome. We correlated visual attention with the potential confounders: performance in managing simulated critical anesthesia events (task performance), work experience, and profession. We used mixed linear models to analyze the results. RESULTS: Fifty-two teams performed 156 simulations. After a manual quality check of the eye-tracking footage, we excluded 57 simulations due to technical problems and quality issues. Participants had a median of 198 (IQR 92.5-317.5) fixations on the patient monitor with a median dwell time of 30.2 (IQR 14.9-51.3) seconds. We found no significant difference in participants' visual attention when using avatar-based patient monitoring or conventional patient monitoring. However, we found that with each percentage point of better task performance, the number of fixations decreased by about 1.39 (coefficient -1.39; 95% CI -2.44 to -0.34; P=.02), and the dwell time diminished by 0.23 seconds (coefficient -0.23; 95% CI: -0.4 to -0.06; P=.01). CONCLUSIONS: Using eye tracking, we found no significant difference in visual attention when anesthesia providers used avatar-based monitoring or conventional patient monitoring in simulated critical anesthesia events. However, we identified visual attention in conjunction with task performance as a surrogate for situational awareness.
RESUMEN
Visual-Patient-avatar, an avatar-based visualisation of patient monitoring, is a newly developed technology aiming to promote situation awareness through user-centred design. Before the technology's introduction into clinical practice, the initial design used to validate the concept had to undergo thorough examination and adjustments where necessary. This mixed qualitative and quantitative study, consisting of three different study parts, aimed to create a design with high user acceptance regarding perceived professionalism and potential for identification while maintaining its original functionality. The first qualitative part was based on structured interviews and explored anaesthesia personnel's first impressions regarding the original design. Recurrent topics were identified using inductive coding, participants' interpretations of the vital sign visualisations analysed and design modifications derived. The second study part consisted of a redesign process, in which the visualisations were adapted according to the results of the first part. In a third, quantitative study part, participants rated Likert scales about Visual-Patient-avatar's appearance and interpreted displayed vital signs in a computer-based survey. The first, qualitative study part included 51 structured interviews. Twenty-eight of 51 (55%) participants mentioned the appearance of Visual-Patient-avatar. In 23 of 51 (45%) interviews, 26 statements about the general impression were identified with a balanced count of positive (14 of 26) and negative (12 of 26) comments. The analysis of vital sign visualisations showed deficits in several vital sign visualisations, especially central venous pressure. These findings were incorporated into part two, the redesign of Visual-Patient-avatar. In the subsequent quantitative analysis of study for part three, 20 of 30 (67%) new participants agreed that the avatar looks professional enough for medical use. Finally, the participants identified 73% (435 of 600 cases) of all vital sign visualisations intuitively correctly without prior instruction. This study succeeded in improving the original design with good user acceptance and a reasonable degree of intuitiveness of the new, revised design. Furthermore, the study identified aspects relevant for the release of Visual-Patient-avatar, such as the requirement for providing at least some training, despite the design's intuitiveness. The results of this study will guide further research and improvement of the technology. The study provides a link between Visual-Patient-avatar as a scientific concept and as an actual product from a cognitive engineering point of view, and may serve as an example of methods to study the designs of technologies in similar contexts.
RESUMEN
Decision confidencethe subjective belief to have made the right decisionis central in planning actions in a complex environment such as the medical field. It is unclear by which factors it is influenced. We analyzed a pooled data set of eight studies and performed a multicenter online survey assessing anesthesiologists' opinions on decision confidence. By applying mixed models and using multiple imputation to determine the effect of missing values from the dataset on the results, we investigated how task performance, perceived workload, the utilization of user-centered medical diagnostic devices, job, work experience, and gender affected decision confidence. The odds of being confident increased with better task performance (OR: 1.27, 95% CI: 0.94 to 1.7; p = 0.12; after multiple imputation OR: 3.19, 95% CI: 2.29 to 4.45; p < 0.001) and when user-centered medical devices were used (OR: 5.01, 95% CI: 3.67 to 6.85; p < 0.001; after multiple imputation OR: 3.58, 95% CI: 2.65 to 4.85; p < 0.001). The odds of being confident decreased with higher perceived workload (OR: 0.94, 95% CI: 0.93 to 0.95; p < 0.001; after multiple imputation, OR: 0.94, 95% CI: 0.93 to 0.95; p < 0.001). Other factors, such as gender, job, or professional experience, did not affect decision confidence. Most anesthesiologists who participated in the online survey agreed that task performance (25 of 30; 83%), perceived workload (24 of 30; 80%), work experience (28 of 30; 93%), and job (21 of 30; 70%) influence decision confidence. Improved task performance, lower perceived workload, and user-centered design in medical equipment enhanced the decision confidence of anesthesia providers.