BACKGROUND: The world's population is progressively ageing, and this trend imposes several challenges to society and governments. The aim of this study was to investigate the burden generated by the hospitalisation of older (60 years) compared with non-older population, as well as the epidemiology of these hospital admissions.
METHODS: Using the Brazilian Unified Health System (known as 'Sistema Único de Saúde' (SUS)), an analysis of all hospital admissions of adult patients in the SUS from 2009 to 2015 was undertaken. The following indicators were used: hospital admission rate, intensive care unit (ICU) admission rate, average length of hospital and ICU stay, hospital mortality and average reimbursement per hospitalisation.
RESULTS: A total of 61 958 959 admissions during the 7-year period, were analysed, encompassing 17 893 392 (28.9%) older patients. Elderly represent 15% (n=21 294 950) of the Brazilian adult population, but are responsible for 29% (n=17 893 392) of hospitalisations, 52% (n=1 731 299) of ICU admissions and 66% (n=1 885 291) of hospital mortality. Among the adults, elderly represents 39% of the total reimbursement made related to admission/hospitalisation. For 2009 to 2015, while the older population increased 27%, ICU admission rate increased 20%; the average length of ICU stay was 12% higher in 2015 (6.5 days) compared with 2009 (5.8 days); and the hospital mortality increased from 9.8% to 11.2%.
CONCLUSION: These findings illustrate the current panorama of the burden due to hospitalisation of older people in the Brazilian public health system, and evidence the consolidation of the epidemiological transition toward the predominance of non-communicable diseases as the main cause of hospitalisation among the elderly in Brazil.
Cognitive Engineering is focused on how humans can cope and master the complexity of processes and technological environments. In cardiothoracic surgery, the goal is to support safe and effective human performance by preventing medical errors. Strategies derived from cognitive engineering research could be introduced in cardiothoracic surgery practice in the near future to enhance patient safety and outcomes.
PURPOSE: Intensive care unit (ICU) admission triage occurs frequently and often involves highly subjective decisions that may lead to potentially inappropriate ICU admissions. In this study, we evaluated the effect of implementing a decision-aid tool for ICU triage on ICU admission decisions.
METHODS: This was a prospective, before-after study. Urgent ICU referrals to ten ICUs in a tertiary hospital in Brazil were assessed before and after the implementation of the decision-aid tool. Our primary outcome was the proportion of potentially inappropriate ICU referrals (defined as priority 4B or 5 referrals, accordingly to the Society of Critical Care Medicine guidelines of 1999 and 2016, respectively) admitted to the ICU within 48 h. We conducted multivariate analyses to adjust for potential confounders and evaluated the interaction between phase and triage priority.
RESULTS: Of the 2201 patients analyzed, 1184 (53.8%) patients were admitted to the ICU. After adjustment for confounders, implementation of the decision-aid tool was associated with a reduction in potentially inappropriate ICU admissions using either the 1999 [adjOR (95% CI) = 0.36 (0.13-0.97)] or 2016 [adjOR (95%CI) = 0.35 (0.13-0.96)] definitions.
CONCLUSION: Implementation of a decision-aid tool for ICU triage was associated with a reduction in potentially inappropriate ICU admissions.
MINI: In this study we identified a total of 137 unique cognitive processes related to the intraoperative phase of coronary artery bypass grafting procedures. This study advances the current body of knowledge by elucidating cognitive processes involved during the intraoperative phase of cardiac surgery from the perspective of multiple operating room team members.
OBJECTIVE: The aim of this study was to elucidate the cognitive processes involved in surgical procedures from the perspective of different team roles (surgeon, anesthesiologist, and perfusionist) and provide a comprehensive compilation of intraoperative cognitive processes.
SUMMARY BACKGROUND DATA: Nontechnical skills play a crucial role in surgical team performance and understanding the cognitive processes underlying the intraoperative phase of surgery is essential to improve patient safety in the operating room (OR).
METHODS: A mixed-methods approach encompassing semistructured interviews with 9 subject-matter experts. A cognitive task analysis was built upon a hierarchical segmentation of coronary artery bypass grafting procedures and a cued-recall protocol using video vignettes was used.
RESULTS: A total of 137 unique surgical cognitive processes were identified, including 33 decision points, 23 critical communications, 43 pitfalls, and 38 strategies. Self-report cognitive workload varied substantially, depending on team role and surgical step. A web-based dashboard was developed, providing an integrated visualization of team cognitive processes in the OR that allows readers to intuitively interact with the study findings.
CONCLUSIONS: This study advances the current body of knowledge by making explicit relevant cognitive processes involved during the intraoperative phase of cardiac surgery from the perspective of multiple OR team members. By displaying the research findings in an interactive dashboard, we provide trainees with new knowledge in an innovative fashion that could be used to enhance learning outcomes. In addition, the approach used in the present study can be used to deeply understand the cognitive factors underlying surgical adverse events and errors in the OR.
Healthcare organizations rely on simulations of complex processes to provide the training required for individuals and teams to evolve their skills and maintain high levels of competence in medical domains. Inherent in this process is the belief, generally founded on macro-scale measures such as observations and workplace-based assessments, that simulations provide the degree of psychological fidelity needed to accomplish this goal. A paradigm shift is underway toward a more dynamic perspective of teamwork to include psycho-physiological measures which will shape the creation of new forms of simulations, performance measures, and practices.Initially it is expected that these dynamic understandings will be derived from simulation studies. However, it is currently unknown at the neural / physiologic/ cognitive level how well simulation training elicits the types of dynamic thinking that is actually used by operating room teams during live-patient surgery, i.e. the ecological validity of simulation environments is unknown for dynamic neural and physiologic measures of team performance. This panel will describe efforts to address this question.Among the questions the panel will consider are:• To what extent do neurodynamic behaviors seen during simulations diverge from those in the operating room?• What are the implications for improving patient safety when communication, cognitive, and neurodynamic analysis become real-time?• Can biometric and communication measures better inform root cause analyses and best practices during live-patient encounters?The topics discussed anticipate the time when dynamic biometric data can contribute to our understanding of how to rapidly determine a team’s functional status, and how to use this information to optimize outcomes and training. The rapid, dynamic and task neutral measures will make the lessons learned in healthcare applicable to other complex group and team environments. They will also provide a foundation for incorporating these models into machines to support the training and performance of teams.
The operating room (OR) is a high-risk and complex environment, where multiple specialized professionals work as a team to effectively care for patients in need of surgical interventions. Surgical tasks impose high cognitive demands on OR staff and cognitive overload may have deleterious effects on team performance and patient safety. The aim of the present study was to investigate the feasibility and describe a novel methodological approach to characterize dynamic changes in team cognitive load by measuring synchronization and entropy of heart rate variability parameters during real-life cardiac surgery. Cognitive load was measured by capturing interbeat intervals (IBI) from three team members (surgeon, anesthesiologist and perfusionist) using an unobtrusive wearable heart rate sensor and transmitted in real-time to a smartphone application. Clinical data and operating room audio/video recordings were also collected to provide behavioral and contextual information. We developed symbolic representations of the transient cognitive state of individual team members (Individual Cognitive State - ICS), and overall team (Team Cognitive State - TCS) by comparing IBI data from each team member with themselves and with others. The distribution of TCS symbols during surgery enabled us to display and analyze temporal states and dynamic changes of team cognitive load. Shannon's entropy was calculated to estimate the changing levels of team organization and to detect fluctuations resulting from a variety of cognitive demands and/or specific situations (e.g. medical error, emergency, flow disruptions). An illustrative example from a real cardiac surgery team shows how cognitive load patterns shifted rapidly after an actual near-miss medication event, leading the team to a more organized and synchronized state. The methodological approach described in this study provides a measurement technique for the assessment of team physiological synchronization, which can be applied to many other team-based environments. Future research should gather additional validity evidence to support the proposed methods for team cognitive load measurement.
The cardiac operating room (OR) is a high-risk environment where several specialized providers work as team to provide care for patients undergoing complex surgical pro-cedures. Cardiac surgery can be conceptualized as a team-based sociotechnical system with critical requirements for communication and coordination. Contemporary research in this realm has moved away from the individual as the unit of cognitive analysis, and a new focus on the activity system (human actors, their tools and the environment) has been proposed; this framework has been referred to as “distributed cognition”. To execute highly specialized tasks, resources are distributed throughout the OR team, as well as the cognitive demands imposed by the surgical tasks. Furthermore, the dynam-ics of team activities may provide relevant information for understanding the multitude of factors that impact surgical performance and patient safety outcomes. Previous research has shown that certain patterns extracted from team members’ position and motion data can predict team coordination and cohesion.. In this pilot study, we de-scribe a novel integrative approach that captures objective measures of team cognitive load (heart rate variability), as well as position and motion metrics from multiple OR team members generated by a computer vision system. Our aim was to investigate the feasibility of using this novel approach to integrate and visualize team dynamics and cognitive load metrics gathered from the OR team during a real-life cardiac surgery.
Cognitive workload data of members of the cardiac surgery team can be measured intraoperatively and stored for later analysis. We present a case of a near-miss (medication error) that underwent root cause analysis using workload data. Heart rate variability data, representing workload levels, were collected from the attending surgeon, attending anesthesiologist, and lead perfusionist using wireless heart rate monitors. An episode of cognitive overload of the anesthesiologist due to a distractor was associated with the preventable error. Additional studies are needed to better understand the role of psychophysiological data in enhancing surgical patient safety.
Procedural flow disruptions secondary to interruptions play a key role in error occurrence during complex medical procedures, mainly because they increase mental workload among team members, negatively impacting team performance and patient safety. Since certain types of interruptions are unavoidable, and consequently the need for multitasking is inherent to complex procedural care, this field can benefit from an intelligent system capable of identifying in which moment flow interference is appropriate without generating disruptions. In the present study we describe a novel approach for the identification of tasks imposing low cognitive load and tasks that demand high cognitive effort during real-life cardiac surgeries. We used heart rate variability analysis as an objective measure of cognitive load, capturing data in a real-time and unobtrusive manner from multiple team members (surgeon, anesthesiologist and perfusionist) simultaneously. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the identification of specific steps, substeps and tasks that impose low cognitive load. An interruption management system can use these low demand situations to guide the surgical team in terms of the appropriateness of flow interruptions. The described approach also enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies) or in situations that are prone to errors. An in-depth understanding of the relationship between cognitive overload states, task demands, and error occurrence will drive the development of cognitive supporting systems that recognize and mitigate errors efficiently and proactively during high complex procedures.
To address the, currently unmet, need for intra-operative safety-critical cognitive support in cardiac surgery, we have developed, validated, and implemented a series of customized checklists to address intra-operative emergencies, using a simulated operative setting. These crisis checklists are designed to provide cognitive and communication support to the operative team to reduce the likelihood of adverse events and improve adherence to best-practice guidelines. We recruited a number of content specialists including members of the hospital safety network and intraoperative cardiac surgery team members, and utilized a Delphi consensus method to develop procedure-specific guidelines for select intraoperative crises. Cardiac surgery team members were subsequently trained on utilizing the developed checklists, performed operative simulations, and were surveyed to determine checklist facility and effectiveness. We developed and validated five checklists for the following cardiac surgery crisis scenarios: (a) Cardiopulmonary Bypass Failure; (b) Systemic Air Embolism; (c) Venous Air Lock; (d) Protamine Reaction; Heparin Resistance. Upon initiation of the crisis management, a crew resource management approach was triggered. A member of the operative team was designated as the "reader" for each scenario to guide the team through the process. After training, 89% of operative team members surveyed indicated that they would like the crisis checklist to be used if they had one of these events occurring to them. Crisis management challenges members of the cardiac surgery team in reasoning accurately and according to best practice during periods of high cognitive workload and psychological stress. These crisis checklists were developed, validated, and simulated with the goal of supporting human performance and shared mental models in the clinical setting.
In the surgical setting, team members constantly deal with a high-demand operative environment that requires simultaneously processing a large amount of information. In certain situations, high demands imposed by surgical tasks and other sources may exceed team member's cognitive capacity, leading to cognitive overload which may place patient safety at risk. In the present study, we describe a novel approach to integrate an objective measure of team member's cognitive load with procedural, behavioral and contextual data from real-life cardiac surgeries. We used heart rate variability analysis, capturing data simultaneously from multiple team members (surgeon, anesthesiologist and perfusionist) in a real-time and unobtrusive manner. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the analysis of the cognitive load imposed by specific steps, substeps and/or tasks. The described approach enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies, teaching) and in situations that are prone to errors. This in-depth understanding of the relationship between cognitive load, task demands and error occurrence is essential for the development of cognitive support systems to recognize and mitigate errors during complex surgical care in the operating room.
OBJECTIVES: Prognostication is an essential ability to clinicians. Nevertheless, it has been shown to be quite variable in acutely ill patients, potentially leading to inappropriate care. We aimed to assess the accuracy of physician's prediction of hospital mortality in acutely deteriorating patients referred for urgent intensive care unit (ICU) admission. METHODS: Prospective cohort of acutely ill patients referred for urgent ICU admission in an academic, tertiary hospital. Physicians' prognosis assessments were recorded at ICU referral. Prognosis was assessed as survival without severe disabilities, survival with severe disabilities or no survival. Prognosis was further dichotomised in good prognosis (survival without severe disabilities) or poor prognosis (survival with severe disabilities or no survival) for prediction of hospital mortality. RESULTS: There were 2374 analysed referrals, with 2103 (88.6%) patients with complete data on mortality and physicians' prognosis. There were 593 (34.4%), 215 (66.4%) and 51 (94.4%) deaths in the groups ascribed a prognosis of survival without disabilities, survival with severe disabilities or no survival, respectively (p<0.001). Sensitivity was 31%, specificity was 91% and the area under the receiver operating characteristic curve was 0.61 for prediction of mortality. After multivariable analysis, severity of illness, performance status and ICU admission were associated with an increased likelihood of incorrect classification, while worse predicted prognosis was associated with a lower chance of incorrect classification. CONCLUSIONS: Physician's prediction was associated with hospital mortality, but overall accuracy was poor, mainly due to low sensitivity to detect risk of poor prognosis.
PURPOSE: To identify the different machine learning (ML) techniques that have been applied to automate physician competence assessment and evaluate how these techniques can be used to assess different competence domains in several medical specialties. METHOD: In May 2017, MEDLINE, EMBASE, PsycINFO, Web of Science, ACM Digital Library, IEEE Xplore Digital Library, PROSPERO, and Cochrane Database of Systematic Reviews were searched for articles published from inception to April 30, 2017. Studies were included if they applied at least one ML technique to assess medical students', residents', fellows', or attending physicians' competence. Information on sample size, participants, study setting and design, medical specialty, ML techniques, competence domains, outcomes, and methodological quality was extracted. MERSQI was used to evaluate quality, and a qualitative narrative synthesis of the medical specialties, ML techniques, and competence domains was conducted. RESULTS: Of 4,953 initial articles, 69 met inclusion criteria. General surgery (24, 34.8%) and radiology (15, 21.7%) were the most studied specialties; natural language processing (24, 34.8%), support vector machine (15, 21.7%), and hidden Markov models (14, 20.3%) were the ML techniques most often applied; and patient care (63, 91.3%) and medical knowledge (45, 65.2%) were the most assessed competence domains. CONCLUSIONS: A growing number of studies have attempted to apply ML techniques to physician competence assessment. Although many studies have investigated the feasibility of certain techniques, more validation research is needed. The use of ML techniques may have the potential to integrate and analyze pragmatic information that could be used in real-time assessments and interventions.
This paper summarizes the accomplishments and recent directions of our medical safety project. Our process-based approach uses a detailed, rigorously-defined, and carefully validated process model to provide a dynamically updated, context-aware and thus, "Smart" Checklist to help process performers understand and manage their pending tasks . This paper focuses on support for teams of performers, working independently as well as in close collaboration, in stressful situations that are life critical. Our recent work has three main thrusts: provide effective real-time guidance for closely collaborating teams; develop and evaluate techniques for measuring cognitive load based on biometric observations and human surveys; and, using these measurements plus analysis and discrete event process simulation, predict cognitive load throughout the process model and propose process modifications to help performers better manage high cognitive load situations. This project is a collaboration among software engineers, surgical team members, human factors researchers, and medical equipment instrumentation experts. Experimental prototype capabilities are being built and evaluated based upon process models of two cardiovascular surgery processes, Aortic Valve Replacement (AVR) and Coronary Artery Bypass Grafting (CABG). In this paper we describe our approach for each of the three research thrusts by illustrating our work for heparinization, a common subprocess of both AVR and CABG. Heparinization is a high-risk error-prone procedure that involves complex team interactions and thus highlights the importance of this work for improving patient outcomes.
OBJECTIVE: Our main objective was to assess patient and family members' perception of bad news communication in the emergency department (ED) and compare these with physicians' perceptions. METHODS: This is a cross-sectional study carried out at the ED of a tertiary teaching hospital. To compare physicians' and receivers' (patient and/or family member) perceptions, we created a survey based on the six attributes derived from the SPIKES protocol. The surveys were applied immediately after communication of bad news occurred in the ED. We analyzed agreement among participants using κ-statistics and the χ-test to compare proportions. RESULTS: A total of 73 bad news communication encounters were analyzed. The survey respondents were 73 physicians, 69 family members, and four patients. In general, there is a low level of agreement between physicians' and receivers' perceptions of how breaking bad news transpired. The satisfaction level of receivers, in terms of breaking bad news by doctors, presented a mean of 3.7±0.6 points. In contrast, the physicians' perception of the communication was worse (2.9±0.6 points), with P value less than 0.001. CONCLUSION: Doctors and receivers disagree in relation to what transpired throughout bad news communications. Discrepancies were more evident in issues involving emotion, invitation, and privacy. An important agreement between perceptions was found in technical and knowledge-related aspects of the communication.
BACKGROUND: Surgeons in the operating theatre deal constantly with high-demand tasks that require simultaneous processing of a large amount of information. In certain situations, high cognitive load occurs, which may impact negatively on a surgeon's performance. This systematic review aims to provide a comprehensive understanding of the different methods used to assess surgeons' cognitive load, and a critique of the reliability and validity of current assessment metrics. METHODS: A search strategy encompassing MEDLINE, Embase, Web of Science, PsycINFO, ACM Digital Library, IEEE Xplore, PROSPERO and the Cochrane database was developed to identify peer-reviewed articles published from inception to November 2016. Quality was assessed by using the Medical Education Research Study Quality Instrument (MERSQI). A summary table was created to describe study design, setting, specialty, participants, cognitive load measures and MERSQI score. RESULTS: Of 391 articles retrieved, 84 met the inclusion criteria, totalling 2053 unique participants. Most studies were carried out in a simulated setting (59 studies, 70 per cent). Sixty studies (71 per cent) used self-reporting methods, of which the NASA Task Load Index (NASA-TLX) was the most commonly applied tool (44 studies, 52 per cent). Heart rate variability analysis was the most used real-time method (11 studies, 13 per cent). CONCLUSION: Self-report instruments are valuable when the aim is to assess the overall cognitive load in different surgical procedures and assess learning curves within competence-based surgical education. When the aim is to assess cognitive load related to specific operative stages, real-time tools should be used, as they allow capture of cognitive load fluctuation. A combination of both subjective and objective methods might provide optimal measurement of surgeons' cognition.
Providing care for simulated emergency patients may induce considerable acute stress in physicians. However, the acute stress provoked in a real-life emergency room (ER) is not well known. Our aim was to assess acute stress responses in residents during real emergency care and investigate the related personal and situational factors. A cross-sectional observational study was carried out at an emergency department of a tertiary teaching hospital. All second-year internal medicine residents were invited to voluntarily participate in this study. Acute stress markers were assessed at baseline (T1), before residents started their ER shift, and immediately after an emergency situation (T2), using heart rate, systolic, and diastolic blood pressure, salivary α-amylase activity, salivary interleukin-1 β, and the State-Trait Anxiety Inventory (STAI-s and STAI-t). Twenty-four residents were assessed during 40 emergency situations. All stress markers presented a statistically significant increase between T1 and T2. IL-1 β presented the highest percent increase (141.0%, p < .001), followed by AA (99.0%, p = .002), HR (81.0%, p < .001), DBP (8.0%, p < .001), and SBP (3.0%, p < .001). In the multivariable analysis, time of residency had a negative correlation with HR during the emergency (adjusted R-square = .168; F = 8.69; p = .006), SBP response (adjusted R-square = .210; F = 6.19; p = .005) and DBP response (adjusted R-square = .293; F = 9.09; p = .001). Trait anxiety (STAI-t) was positively correlated with STAI-s (adjusted R-square = .326; F = 19.9; p < .001), and number of procedures performed during emergency care had a positive association with HR response (adjusted R-square = .241; F = 5.02; p = .005). In the present study, emergency care provoked substantial acute stress in residents. Resident experience, trait anxiety, and number of emergency procedures were independently associated with acute stress response.
Objectives: To investigate acute stress response in residents playing nurse and physician roles during emergency simulations.
Methods: Sixteen second-year internal medicine residents participated in teams of four (two playing physician roles and two playing nurse roles). Stress markers were assessed in 24 simulations at baseline (T1) and immediately after the scenario (T2), using heart rate, systolic and diastolic blood pressure, salivary α-amylase, salivary cortisol and salivary interleukin-1β. The State-Trait Anxiety Inventory was applied at T2. Continuous data were summarized for the median (1st-3rd interquartile ranges), and the Mann-Whitney U Test was used to compare the groups.
Results: The percent variations of the stress markers in the physician and nurse roles, respectively, were the following: heart rate: 70.5% (46.0-136.5) versus 53.0% (29.5-117.0), U=89.00, p=0.35; systolic blood pressure: 3.0% (0.0-10.0) versus 2.0% (-2.0-9.0), U=59.50, p=0.46; diastolic blood pressure: 5.5% (0.0-13.5) versus 0.0% (0.0-11.5), U=91.50, p=0.27; α-amylase: -5.35% (-62.70-73.90) versus 42.3% (12.4-133.8), U=23.00, p=0.08; cortisol: 35.3% (22.2-83.5) versus 42.3% (12.4-133.8), U=64.00, p=0.08); and interleukin-1β: 54.4% (21.9-109.3) versus 112.55% (29.7-263.3), U= 24.00, p=0.277. For the physician and nurse roles, respectively, the average heart rate was 101.5 (92.0-104.0) versus 91.0 (83.0-99.5) beats per minute, U=96.50, p=0.160; and the state anxiety inventory score was 44.0 (40.0-50.0) versus 42.0 (37.50-48.0) points, U= 89.50, p=0.319.
Conclusions: Different roles during emergency simulations evoked similar participants' engagement, as indicated by acute stress levels. Role-play strategies can provide high psychological fidelity for simulation-based training, and these results reinforce the potential of role-play methodologies in medical education.
OBJECTIVE: The use of palliative care (PC) screening criteria to trigger PC consultations may optimize the utilization of PC services, improve patient comfort, and reduce invasive and futile end-of-life care. The aim of the present study was to assess the criterion validity and inter-rater reliability of a PC screening tool for patients admitted to an emergency department intensive care unit (ED-ICU).
METHOD: Observational retrospective study evaluating PC screening criteria based on the presence of advanced diagnosis and the use of two "surprise questions" (traditional and modified). Patients were classified at ED-ICU admission in four categories according to the proposed algorithm. Result A total of 510 patients were included in the analysis. From these, 337 (66.1%) were category 1, 0 (0.0%) category 2, 63 (12.4%) category 3, and 110 (21.6%) category 4. Severity of illness (Simplified Acute Physiology Score III score and mechanical ventilation), mortality (ED-ICU and intrahospital), and PC-related measures (order for a PC consultation, time between admission and PC consultation, and transfer to a PC bed) were significantly different across groups, more evidently between categories 4 and 1. Category 3 patients presented similar outcomes to patients in category 1 for severity of illness and mortality. However, category 3 patients had a PC consultation ordered more frequently than did category 1 patients. The screening criteria were assessed by two independent raters (n = 100), and a substantial interrater reliability was found, with 80% of agreement and a kappa coefficient of 0.75 (95% confidence interval = 0.62, 0.88). Significance of results This study is the first step toward the implementation of a PC screening tool in the ED-ICU. The tool was able to discriminate three groups of patients within a spectrum of increasing severity of illness, risk of death, and PC needs, presenting substantial inter-rater reliability. Future research should investigate the implementation of these screening criteria into routine practice of an ED-ICU.
INTRODUCTION: Nontechnical skills (NTS) such as teamwork and communication play an important role in preventing adverse outcomes in the operating room (OR). Simulation-based OR team training focused on these skills provides an environment where team members can learn with and from one another. We sought to conduct a systematic review to identify simulation-based approaches to NTS training for surgical teams.
MATERIALS AND METHODS: We conducted a systematic search of PubMed, ERIC, and the Cochrane Database using keywords and MeSH terms for studies describing simulation-based training for OR teams, including members from surgery, anesthesia, and nursing in September 2016. Information on the simulations, participants, and NTS assessments were abstracted from the articles meeting our search criteria.
RESULTS: We identified 10 published articles describing simulation-based OR team-training programs focused on NTS. The primary focus of these programs was on communication, teamwork, leadership, and situation awareness. Only four of the programs used a validated instrument to assess the NTS of the individuals or teams participating in the simulations.
DISCUSSION: Simulation-based OR team-training programs provide opportunities for NTS development and reflection by participants. Future programs could benefit from involving the full range of disciplines and professions that compose an OR team, as well as increased use of validated assessment instruments.