Feasibility of Wearable Sensors to Assess Cognitive Load During Clinical Performance: Lessons Learned and Blueprint for Success.

INTRODUCTION: Cognitive load (CogL) is increasingly recognized as an important resource underlying operative performance. Current innovations in surgery aim to develop objective performance metrics via physiological monitoring from wearable digital sensors. Surgeons have access to consumer technology that could measure CogL but need guidance regarding device selection and implementation. To realize the benefits of surgical performance improvement these methods must be feasible, incorporating human factors usability and design principles. This paper aims to evaluate the feasibility of using wearable sensors to assess CogL, identify the benefits and challenges of implementing devices, and develop guidance for surgeons planning to implement wearable devices in their research or practice. METHODS: We examined the feasibility of wearable sensors from a series of empirical studies that measured aspects of clinical performance relating to CogL. Across four studies, 84 participants and five sensors were involved in the following clinical settings: (i) real intraoperative surgery; (ii) simulated laparoscopic surgery; and (iii) medical team performance outside the hospital. RESULTS: Wearable devices worn on the wrist and chest were found to be comfortable. After a learning curve, electrodermal activity data were easily and reliably collected. Devices using photoplethysmography to determine heart rate variability were significantly limited by movement artifact. There was variable success with electroencephalography devices regarding connectivity, comfort, and usability. CONCLUSIONS: It is feasible to use wearable sensors across various clinical settings, including surgery. There are some limitations, and their implementation is context and device dependent. To scale sensor use in clinical research, surgeons must embrace human factors principles to optimize wearability, usability, reliability, and data security.

Exploring Intraoperative Cognitive Biases in Cardiac Surgery Teams.

This study focuses on understanding the influence of cognitive biases in the intra-operative decision-making process within cardiac surgery teams, recognizing the complexity and high-stakes nature of such environments. We aimed to investigate the perceived prevalence and impact of cognitive biases among cardiac surgery teams, and how these biases may affect intraoperative decisions and patient safety and outcomes. A mixed-methods approach was utilized, combining quantitative ratings across 32 different cognitive biases (0 to 100 visual analogue scale), regarding their "likelihood of occurring" and "potential for patient harm" during the intraoperative phase of cardiac surgery. Based on these ratings, we collected qualitative insights on the most-rated cognitive biases from semi-structured interviews with surgeons, anaesthesiologists, and perfusionists who work in a cardiac operating room. A total of 16 participants, including cardiac surgery researchers and clinicians, took part in the study. We found a significant presence of cognitive biases, particularly confirmation bias and overconfidence, which influenced decision-making processes and had the potential for patient harm. Of 32 cognitive biases, 6 were rated above the 75th percentile for both criteria (potential for patient harm, likelihood of occurring). Our preliminary findings provide a first step toward a deeper understanding of the complex cognitive mechanisms that underlie clinical reasoning and decision-making in the operating room. Future studies should further explore this topic, especially the relationship between the occurrence of intraoperative cognitive biases and postoperative surgical outcomes. Additionally, the impact of metacognition strategies (e.g. debiasing training) on reducing the impact of cognitive bias and improving intraoperative performance should also be investigated.

A novel multimodal, intraoperative cognitive workload assessment of cardiac surgery team members.

OBJECTIVE: To characterize cognitive workload (CWL) of cardiac surgery team members in a real-world setting during coronary artery bypass grafting (CABG) surgery using providers' heart rate variability (HRV) data as a surrogate measure of CWL. METHODS: HRV was collected from the surgeon, anesthesiologist, perfusionist, and scrub nurse, and audio/video recordings were made during isolated, nonemergency CABG surgeries (n = 27). Eight surgical phases were annotated by trained researchers, and HRV was calculated for each phase. RESULTS: Significant differences in CWL were observed within a given role across surgical phases. Results are reported as predicted probability (95% confidence interval [CI]). CWL was significantly higher for anesthesiologists during "preparation and induction" (0.57; 95% CI, 0.42-0.71) and "anastomoses" (0.44; 95% CI, 0.30-0.58) compared to other phases, and the same held for nurses during the "opening" (0.51; 95% CI, 0.37-0.65) and "postoperative" (0.68; 95% CI, 0.42-0.86) phases. Additional significant differences were observed between roles within a given surgical phase. For example, surgeons had significantly higher CWL during "anastomoses" (0.81; 95% CI, 0.69-0.89) compared to all other phases, and the same was true of perfusionists during the "opening" (0.79; 95% CI, 0.66-0.88) and "prebypass preparation" (0.50; 95% CI, 0.36-0.64) phases. CONCLUSIONS: Our innovative analysis demonstrates that CWL fluctuates across surgical procedures by role and phase, which may reflect the distribution of primary tasks. This corroborates earlier findings from self-report measures. The data suggest that team-wide, peak CWL during a phase decreases from early phases of surgery through initiation of cardiopumonary bypass (CPB), rises during anastomosis, and decreases after termination of CPB. Knowledge of these trends could encourage the adoption of behaviors to enhance team dynamics and performance.

Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills.

Importance: Assessing nontechnical skills in operating rooms (ORs) is crucial for enhancing surgical performance and patient safety. However, automated and real-time evaluation of these skills remains challenging. Objective: To explore the feasibility of using motion features extracted from surgical video recordings to automatically assess nontechnical skills during cardiac surgical procedures. Design, Setting, and Participants: This cross-sectional study used video recordings of cardiac surgical procedures at a tertiary academic US hospital collected from January 2021 through May 2022. The OpenPose library was used to analyze videos to extract body pose estimations of team members and compute various team motion features. The Non-Technical Skills for Surgeons (NOTSS) assessment tool was employed for rating the OR team's nontechnical skills by 3 expert raters. Main Outcomes and Measures: NOTSS overall score, with motion features extracted from surgical videos as measures. Results: A total of 30 complete cardiac surgery procedures were included: 26 (86.6%) were on-pump coronary artery bypass graft procedures and 4 (13.4%) were aortic valve replacement or repair procedures. All patients were male, and the mean (SD) age was 72 (6.3) years. All surgical teams were composed of 4 key roles (attending surgeon, attending anesthesiologist, primary perfusionist, and scrub nurse) with additional supporting roles. NOTSS scores correlated significantly with trajectory (r = 0.51, P = .005), acceleration (r = 0.48, P = .008), and entropy (r = -0.52, P = .004) of team displacement. Multiple linear regression, adjusted for patient factors, showed average team trajectory (adjusted R2 = 0.335; coefficient, 10.51 [95% CI, 8.81-12.21]; P = .004) and team displacement entropy (adjusted R2 = 0.304; coefficient, -12.64 [95% CI, -20.54 to -4.74]; P = .003) were associated with NOTSS scores. Conclusions and Relevance: This study suggests a significant link between OR team movements and nontechnical skills ratings by NOTSS during cardiac surgical procedures, suggesting automated surgical video analysis could enhance nontechnical skills assessment. Further investigation across different hospitals and specialties is necessary to validate these findings.

Adapting the World Health Organization's Surgical Safety Checklist to High-Income Settings: A Hybrid Effectiveness-Implementation Trial Protocol.

Objectives: The proposed study aims to assess users' perceptions of a surgical safety checklist (SSC) reimplementation toolkit and its impact on SSC attitudes and operating room (OR) culture, meaningful checklist use, measures of surgical safety, and OR efficiency at 3 different hospital sites. Background: The High-Performance Checklist toolkit (toolkit) assists surgical teams in modifying and implementing or reimplementing the World Health Organization's SSC. Through the explore, prepare, implement, and sustain implementation framework, the toolkit provides a process and set of tools to facilitate surgical teams' modification, implementation, training on, and evaluation of the SSC. Methods: A pre-post intervention design will be used to assess the impact of the modified SSC on surgical processes, team culture, patient experience, and safety. This mixed-methods study includes quantitative and qualitative data derived from surveys, semi-structured interviews, patient focus groups, and SSC performance observations. Additionally, patient outcome and OR efficiency data will be collected from the study sites' health surveillance systems. Data analysis: Statistical data will be analyzed using Statistical Product and Service Solutions, while qualitative data will be analyzed thematically using NVivo. Furthermore, interview data will be analyzed using the Consolidated Framework for Implementation Research and reach, effectiveness, adoption, implementation, maintenance implementation frameworks. Setting: The toolkit will be introduced at 3 diverse surgical sites in Alberta, Canada: an urban hospital, university hospital, and small regional hospital. Anticipated impact: We anticipate the results of this study will optimize SSC usage at the participating surgical sites, help shape and refine the toolkit, and improve its usability and application at future sites.

Space Ultrasound: A Proposal for Competency-based Ultrasound Training for In-flight Space Medicine.

Space travel has transformed in the past several years. Given the burgeoning market for space tourism, in-flight medical emergencies are likely to be expected. Ultrasound is one of the few diagnostic and therapeutic modalities available for astronauts in space. However, while point-of-care ultrasound (POCUS) is available, there is no current standard of training for astronaut preparation. We suggest an organized and structured methodology by which astronauts should best prepare for space with the medical equipment available on board. As technology continues to evolve, the assistance of other artificial intelligence and augmented reality systems are likely to facilitate training and dynamic real-time needs during space emergencies. Summary: As space tourism continues to evolve, an organized methodology for POCUS use is advised to best prepare astronauts for space.

Data-driven coaching to improve statewide outcomes in CABG: before and after interventional study.

BACKGROUND: The impact of quality improvement initiatives program (QIP) on coronary artery bypass grafting surgery (CABG) remains scarce, despite improved outcomes in other surgical areas. This study aims to evaluate the impact of a package of QIP on mortality rates among patients undergoing CABG. MATERIALS AND METHODS: This prospective cohort study utilized data from the multicenter database Registro Paulista de Cirurgia Cardiovascular II (REPLICCAR II), spanning from July 2017 to June 2019. Data from 4018 isolated CABG adult patients were collected and analyzed in three phases: before-implementation, implementation, and after-implementation of the intervention (which comprised QIP training for the hospital team). Propensity Score Matching was used to balance the groups of 2170 patients each for a comparative analysis of the following outcomes: reoperation, deep sternal wound infection/mediastinitis ≤30 days, cerebrovascular accident, acute kidney injury, ventilation time >24 h, length of stay <6 days, length of stay >14 days, morbidity and mortality, and operative mortality. A multiple regression model was constructed to predict mortality outcomes. RESULTS: Following implementation, there was a significant reduction of operative mortality (61.7%, P =0.046), as well as deep sternal wound infection/mediastinitis ( P <0.001), sepsis ( P =0.002), ventilation time in hours ( P <0.001), prolonged ventilation time ( P =0.009), postoperative peak blood glucose ( P <0.001), total length of hospital stay ( P <0.001). Additionally, there was a greater use of arterial grafts, including internal thoracic ( P <0.001) and radial ( P =0.038), along with a higher rate of skeletonized dissection of the internal thoracic artery. CONCLUSIONS: QIP was associated with a 61.7% reduction in operative mortality following CABG. Although not all complications exhibited a decline, the reduction in mortality suggests a possible decrease in failure to rescue during the after-implementation period.

Surgical Sabermetrics: A Scoping Review of Technology-enhanced Assessment of Nontechnical Skills in the Operating Room.

OBJECTIVE: To evaluate the current evidence for surgical sabermetrics: digital methods of assessing surgical nontechnical skills and investigate the implications for enhancing surgical performance. BACKGROUND: Surgeons need high-quality, objective, and timely feedback to optimize performance and patient safety. Digital tools to assess nontechnical skills have the potential to reduce human bias and aid scalability. However, we do not fully understand which of the myriad of digital metrics of performance assessment have efficacy for surgeons. METHODS: A systematic review was conducted by searching PubMed, EMBASE, CINAHL, and PSYCINFO databases following PRISMA-ScR guidelines. MeSH terms and keywords included "Assessment," "Surgeons," and "Technology". Eligible studies included a digital assessment of nontechnical skills for surgeons, residents, and/or medical students within an operative context. RESULTS: From 19,229 articles screened, 81 articles met the inclusion criteria. The studies varied in surgical specialties, settings, and outcome measurements. A total of 122 distinct objective, digital metrics were utilized. Studies digitally measured at least 1 category of surgical nontechnical skill using a single (n=54) or multiple objective measures (n=27). The majority of studies utilized simulation (n=48) over live operative settings (n=32). Surgical Sabermetrics has been demonstrated to be beneficial in measuring cognitive load (n=57), situation awareness (n=24), communication (n=3), teamwork (n=13), and leadership (n=2). No studies measured intraoperative decision-making. CONCLUSIONS: The literature detailing the intersection between surgical data science and operative nontechnical skills is diverse and growing rapidly. Surgical Sabermetrics may provide a promising modifiable technique to achieve desirable outcomes for both the surgeon and the patient. This study identifies a diverse array of measurements possible with sensor devices and highlights research gaps, including the need for objective assessment of decision-making. Future studies may advance the integration of physiological sensors to provide a holistic assessment of surgical performance.

Implementing ultrasound-guided nerve blocks in the emergency department: A low-cost, low-fidelity training approach.

Background: Managing acute pain is a common challenge in the emergency department (ED). Though widely used in perioperative settings, ED-based ultrasound-guided nerve blocks (UGNBs) have been slow to gain traction. Here, we develop a low-cost, low-fidelity, simulation-based training curriculum in UGNBs for emergency physicians to improve procedural competence and confidence. Methods: In this pre-/postintervention study, ED physicians were enrolled to participate in a 2-h, in-person simulation training session composed of a didactic session followed by rotation through stations using handmade pork-based UGNB models. Learner confidence with performing and supervising UGNBs as well as knowledge and procedural-based competence were assessed pre- and posttraining via electronic survey quizzes. One-way repeated-measures ANOVAs and pairwise comparisons were conducted. The numbers of nerve blocks performed clinically in the department pre- and postintervention were compared. Results: In total, 36 participants enrolled in training sessions, eight participants completed surveys at all three data collection time points. Of enrolled participants, 56% were trainees, 39% were faculty, 56% were female, and 53% self-identified as White. Knowledge and competency scores increased immediately postintervention (mean ± SD t0 score 66.9 ± 8.9 vs. t1 score 90.4 ± 11.7; p < 0.001), and decreased 3 months postintervention but remained elevated above baseline (t2 scores 77.2 ± 11.5, compared to t0; p = 0.03). Self-reported confidence in performing UGNBs increased posttraining (t0 5.0 ± 2.3 compared to t1 score 7.1 ± 1.5; p = 0.002) but decreased to baseline levels 3 months postintervention (t2 = 6.0 ± 1.9, compared to t0; p = 0.30). Conclusions: A low-cost, low-fidelity simulation curriculum can improve ED provider procedural-based competence and confidence in performing UGNBs in the short term, with a trend toward sustained improvement in knowledge and confidence. Curriculum adjustments to achieve sustained improvement in confidence performing and supervising UGNBs long term are key to increased ED-based UGNB use.

Nontechnical Skills for Intraoperative Team Members.

Nontechnical skills, defined as the set of cognitive and social skills used by individuals and teams to reduce error and improve performance in complex systems, have become increasingly recognized as a key contributor to patient safety. Efforts to characterize, quantify, and teach nontechnical skills in the context of perioperative care continue to evolve. This review article summarizes the essential behaviors for safety, described in taxonomies for nontechnical skills assessments developed for intraoperative clinical team members (eg, surgeons, anesthesiologists, scrub practitioners, perfusionists). Furthermore, the authors describe emerging methods to advance understanding of the impact of nontechnical skills on perioperative outcomes.

Drying, Physical, Nutritional and Bioactive Characteristics of Apple Peel Flour Subjected to Blanching and Ultrasound Pretreatments.

The aim of this work was to study the effect of blanching and ultrasound pretreatments on drying and quality characteristics of apple peel. Blanching was conducted in boiling water, ultrasound in a water bath, and drying in a batch tray dryer. The product obtained was ground into a flour, and assessed for color, water activity, proximate composition, sugars, and bioactive compounds. Results showed that effective moisture diffusivity increases with a decrease in product moisture content, being such dependence well described by a second order polynomial model. Average drying rate was higher and product moisture content was lower for blanched and sonicated flour, especially for the former. Such result suggests that blanching and ultrasound enhance water removal during drying of apple peel. Physical properties were significantly affected by pretreatments, being more intense red color and lower water activity obtained for sonicated flour. Nutritional and bioactive properties were also significantly affected by pretreatments, being lower sugar, higher protein, fiber, catechin and epicatechin content observed for blanched flour. Summarizing, blanching and ultrasound pretreatments improve drying of apple peel, both regarding process efficiency and product quality.

Using Digital Biomarkers for Objective Assessment of Perfusionists' Workload and Acute Stress During Cardiac Surgery.

The cardiac operating room (OR) is a high-risk, high-stakes environment inserted into a complex socio-technical healthcare system. During cardiopulmonary bypass (CPB), the most critical phase of cardiac surgery, the perfusionist has a crucial role within the interprofessional OR team, being responsible for optimizing patient perfusion while coordinating other tasks with the surgeon, anesthesiologist, and nurses. The aim of this study was to investigate objective digital biomarkers of perfusionists' workload and stress derived from heart rate variability (HRV) metrics captured via a wearable physiological sensor in a real cardiac OR. We explored the relationships between several HRV parameters and validated self-report measures of surgical task workload (SURG-TLX) and acute stress (STAI-SF), as well as surgical processes and outcome measures. We found that the frequency-domain HRV parameter HF relative power - FFT (%) presented the strongest association with task workload (correlation coefficient: -0.491, p-value: 0.003). We also found that the time-domain HRV parameter RMSSD (ms) presented the strongest correlation with perfusionists' acute stress (correlation coefficient: -0.489, p-value: 0.005). A few workload and stress biomarkers were also associated with bypass time and patient length of stay in the hospital. The findings from this study will inform future research regarding which HRV-based biomarkers are best suited for the development of cognitive support systems capable of monitoring surgical workload and stress in real time.

Generative Adversarial Networks in Medicine: Important Considerations for this Emerging Innovation in Artificial Intelligence.

The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations. With these powerful applications, there is a necessity for framework regulations to ensure equitable and safe deployment of technology. Generative Adversarial Networks (GANs) are emerging ML techniques that have immense applications in medical imaging due to their ability to produce synthetic medical images and aid in medical AI training. Producing accurate synthetic images with GANs can address current limitations in AI development for medical imaging and overcome current dataset type and size constraints. Offsetting these constraints can dramatically improve the development and implementation of AI medical imaging and restructure the practice of medicine. As observed with its other AI predecessors, considerations must be taken into place to help regulate its development for clinical use. In this paper, we discuss the legal, ethical, and technical challenges for future safe integration of this technology in the healthcare sector.

The impact of a smartphone-based cognitive aid on clinical performance during cardiac arrest simulations: A randomized controlled trial.

Objectives: In-hospital cardiac arrests are common and associated with high mortality. Smartphone applications offer quick access to algorithms and timers but often lack real-time guidance. This study assesses the impact of the Code Blue Leader application on the performance of providers leading cardiac arrest simulations. Methods: This open-label randomized controlled trial included Advanced Cardiac Life Support (ACLS)-trained medical doctors (MD) and registered nurses (RN). Participants were randomized to lead the same ACLS simulation with or without the app. The primary outcome, "performance score," was assessed by a trained rater using a validated ACLS scoring system. Secondary outcomes included percentage of critical actions performed, number of incorrect actions, and chest compression fraction (percentage of time spent performing chest compressions). A sample size of 30 participants was calculated to detect a difference of 20% at the 0.05 alpha level with 90% power. Results: Fifteen MDs and 15 RNs underwent stratified randomization. The median (interquartile range) performance score in the app group was 95.3% (93.0%-100.0%) compared to 81.4% (60.5%-88.4%) in the control group, demonstrating an effect size of r = 0.69 (Z = -3.78, r = 0.69, p = 0.0002). The percentage of critical actions performed in the app group was 100% (96.2%-100.0%) compared to 85.0% (74.1%-92.4%) in the control group. The number of incorrect actions performed in the app group was 1 (1) compared to 4 (3-5) in the control group. Chest compression fraction in the app group was 75.5% (73.0%-84.0%) compared to 75.0% (72.0%-85.0%) in the control group. Conclusions: The Code Blue Leader smartphone app significantly improved the performance of ACLS-trained providers in cardiac arrest simulations.

An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring.

Clinical alarm and decision support systems that lack clinical context may create non-actionable nuisance alarms that are not clinically relevant and can cause distractions during the most difficult moments of a surgery. We present a novel, interoperable, real-time system for adding contextual awareness to clinical systems by monitoring the heart-rate variability (HRV) of clinical team members. We designed an architecture for real-time capture, analysis, and presentation of HRV data from multiple clinicians and implemented this architecture as an application and device interfaces on the open-source OpenICE interoperability platform. In this work, we extend OpenICE with new capabilities to support the needs of the context-aware OR including a modularized data pipeline for simultaneously processing real-time electrocardiographic (ECG) waveforms from multiple clinicians to create estimates of their individual cognitive load. The system is built with standardized interfaces that allow for free interchange of software and hardware components including sensor devices, ECG filtering and beat detection algorithms, HRV metric calculations, and individual and team alerts based on changes in metrics. By integrating contextual cues and team member state into a unified process model, we believe future clinical applications will be able to emulate some of these behaviors to provide context-aware information to improve the safety and quality of surgical interventions.

Extended Reality Applications for Space Health.

INTRODUCTION: Spaceflight has detrimental effects on human health, imposing significant and unique risks to crewmembers due to physiological adaptations, exposure to physical and psychological stressors, and limited capabilities to provide medical care. Previous research has proposed and evaluated several strategies to support and mitigate the risks related to astronauts' health and medical exploration capabilities. Among these, extended reality (XR) technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (MR) have increasingly been adopted for training, real-time clinical, and operational support in both terrestrial and aerospace settings, and only a few studies have reported research results on the applications of XR technologies for improving space health. This study aims to systematically review the scientific literature that has explored the application of XR technologies in the space health field. We also discuss the methodological and design characteristics of the existing studies in this realm, informing future research and development efforts on applying XR technologies to improve space health and enhance crew safety and performance.Ebnali M, Paladugu P, Miccile C, Park SH, Burian B, Yule S, Dias RD. Extended reality applications for space health. Aerosp Med Hum Perform. 2023; 94(3):122-130.

Protocol for a scoping review on 'surgical sabermetrics:' technology-enhanced measurement of operative non-technical skills.

INTRODUCTION: Surgeons need high fidelity, high quality, objective, non-judgemental and quantitative feedback to measure their performance in order to optimise their performance and improve patient safety. This can be provided through surgical sabermetrics, defined as 'advanced analytics of digitally recorded surgical training and operative procedures to enhance insight, support professional development and optimise clinical and safety outcomes'. The aim of this scoping review is to investigate the assessment of surgeon's non-technical skills using sabermetrics principles, focusing on digital, automated measurements that do not require a human observer. METHODS AND ANALYSIS: To investigate the current methods of digital, automated measurements of surgeons' non-technical skills, a systematic scoping review will be conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, using databases from medicine and other fields. Covidence software is used for screening of potential studies. A data extraction tool will be developed specifically for this study to evaluate the methods of measurement. Quality assurance will be assessed using Quality Assessment Tool for Diverse Designs. Multiple reviewers will be responsible for screening of studies and data extraction. ETHICS AND DISSEMINATION: This is a review study, not using primary data, and therefore, ethical approval is not required. A range of methods will be employed for dissemination of the results of this study, including publication in journals and conference presentations.