User Perceptions of Visual Clot in a High-Fidelity Simulation Study: Mixed Qualitative-Quantitative Study

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.

The Visual Patient Avatar ICU Facilitates Information Transfer of Written Information by Visualization: A Multicenter Comparative Eye-Tracking Study

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.

Using Visual Patient to Show Vital Sign Predictions, a Computer-Based Mixed Quantitative and Qualitative Simulation Study

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.

User Perceptions of Visual Blood: An International Mixed Methods Study on Novel Blood Gas Analysis Visualization

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.

Human-centered visualization technologies for patient monitoring are the future: a narrative review

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.

User Perceptions of ROTEM-Guided Haemostatic Resuscitation: A Mixed Qualitative-Quantitative Study

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.

Visual Blood, Visualisation of Blood Gas Analysis in Virtual Reality, Leads to More Correct Diagnoses: A Computer-Based, Multicentre, Simulation Study

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.

Attitudes of Anesthesiologists toward Artificial Intelligence in Anesthesia: A Multicenter, Mixed Qualitative-Quantitative Study

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.

The impact of direct oral anticoagulants on viscoelastic testing - A systematic review

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].

Physicians' perceptions of two ways of algorithm presentation: graphic versus text-based approach

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.

Improved Task Performance, Low Workload, and User-Centered Design in Medical Diagnostic Equipment Enhance Decision Confidence of Anesthesia Providers: A Meta-Analysis and a Multicenter Online Survey

Decision confidence—the subjective belief to have made the right decision—is 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.

Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study

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.

Anesthesia providers' visual attention in simulated anesthesia emergencies using conventional number-based and avatar-based patient monitoring: a prospective, eye-tracking study

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.

CLINICALTRIAL

Business Management System for Ethics Committees Number Req-2020-00059.

Voice alerting as a medical alarm modality for next-generation patient monitoring: a randomised international multicentre trial

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.

Physicians' perceptions regarding acute bleeding management: an international mixed qualitative quantitative study

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12871-021-01269-x.

The Haemostasis Traffic Light, a user-centred coagulation management tool for acute bleeding situations: a simulation-based randomised dual-centre trial

The Haemostasis Traffic Light is a cognitive aid with a user-centred design to enhance and simplify situation awareness and decision-making during peri-operative bleeding. Its structure helps to prioritise therapeutic interventions according to the pathophysiology and the severity of the bleeding. This investigator-initiated, randomised, prospective, international, dual-centre study aimed to validate the Haemostasis Traffic Light by adapting it to the local coagulation protocols of two university hospitals. Between 9 January and 12 May 2020, we recruited 84 participants at the University Hospital Zurich, Switzerland, and the Italian Hospital of Buenos Aires, Argentina. Each centre included 21 resident and 21 staff anaesthetists. Participants were randomly allocated to either the text-based algorithm or the Haemostasis Traffic Light. All participants managed six bleeding scenarios using the same algorithm. In simulated bleeding scenarios, the design of the Haemostasis Traffic Light algorithm enabled more correctly solved cases, OR (95%CI) 7.23 (3.82-13.68), p < 0.001, and faster therapeutic decisions, HR (95%CI) 1.97 (1.18-3.29, p = 0.010). In addition, the tool improved therapeutic confidence, OR (95%CI) 4.31 (1.67-11.11, p = 0.003), and reduced perceived work-load coefficient (95%CI) -6.1 (-10.98 to -1.22), p = 0.020). This study provides empirical evidence for the importance of user-centred design in the development of haemostatic management protocols.