The red hat - designating leadership using visual and verbal cues: a mixed-methods study.

BACKGROUND: During a critical event in the labor and delivery operating room, it is crucial for team members responding to the situation to be aware of the designated leaders. Visual and verbal cues have been utilized to designate leadership in various healthcare settings; however, previous research has indicated mixed results using visual cues for role designation. METHODS: The purpose of this study was to explore the use of the red surgical hat as a visual cue of leadership during obstetric emergency simulation training. We used a mixed-methods design to analyze simulation-based education video and debriefing transcripts. RESULTS: There was a statistically significant difference in the proportion of participants who declared leadership vs. those who donned the red hat. Participants were more likely to visually declare leadership utilizing a red surgical bouffant hat than to verbally declare leadership. Most participants indicated that observing the red hat to detect leadership in the operating room was more effective than when leaders used a verbal declaration to inform others who was leading. CONCLUSIONS: Our findings suggest that utilizing a visual cue of leadership with the red surgical bouffant hat improves participant perceptions of communication of the surgical team during an obstetrical critical event in a simulation environment.

A novel model for real-time risk evaluation of vehicle-pedestrian interactions at intersections.

Safety decisions for vehicles at an intersection rely on real-time, objective and continuous assessment of risks in vehicle-pedestrian interactions. Existing surrogate safety models, constrained by ideal assumptions of constant current speed and reliant on interaction points, often misjudge risks, and show inefficiency, inaccuracy and discontinuity. This work proposes a novel model for evaluation of those risks in vehicle-pedestrian interactions at intersections, which abstracts the pedestrian distribution density around a vehicle into a generalized model of driver-pedestrian interaction preferences. The introduction of two conceptions: 'driving risk index' and 'driving risk gradient,' facilitates the delineation of driving spaces for identifying safety-critical events. By means of the trajectory data from three intersections, model parameters are calibrated and a multidimensional vehicle-pedestrian interaction risk (VPIR) model is proposed to adapt the complex and dynamic characteristics of vehicle-pedestrian interactions at intersections. Commonly used surrogate safety models, such as Time to Collision (TTC), are selected as benchmark models. Results show that the proposed model overcomes the limitations of the existing interaction-point-based models, and offers a ideal assessment of driving risks at intersections. Finally, the model is illustrated with a case study that assesses the risks in vehicle-pedestrian interactions in varied scenarios and the case study indicates that the VPIR model works well in evaluating vehicle-pedestrian interaction risks. This work can facilitate humanoid learning in the autonomous driving domain, and achieve an ideal evaluation of vehicle-pedestrian interaction risks for safe and efficient vehicle navigation through an intersection.

The relationship between young college students' recognition of national COVID-19 crisis governance capabilities and the improvement of national identity: the mediating role of online participation in public health critical events.

Background: Improving the young college students' national identity is crucial for ensuring social stability and fostering development during public health critical events such as COVID-19. Young college students' recognition of national COVID-19 crisis governance capabilities can influence their national identity, and online participation in public health criticalevents may serve as a crucial role in shaping this intricate relationship. To investigate this possibility, the present study established an intermediary model to examine the impact of online participation in public health critical events on young college students' recognition of national COVID-19 crisis governance capabilities and improvement of national identity. Methods: This cross-sectional survey study employed a convenience sampling method to investigate a total of 3041 young college students in China. The correlations between study variables were analyzed using Spearman's rank correlation. The mediation model was established using PROCESS Model 4 with 5000 bootstrap samples in SPSS. The bias-corrected bootstrap method provided statistical efficacy and identification interval estimation. Results: Young college students' recognition of national COVID-19 crisis governance capabilities (r=0.729, P<0.001) and online participation in public health critical events (r=0.609, P<0.001) were positively correlated with improvement of their national identity. The relationship between these two factors was partially mediated by online participation in public health critical events (Indirect effect estimate=0.196, P<0.001). Conclusion: Online participation in public health critical events played a mediating role in the association between college students' recognition of national COVID-19 crisis governance capabilities and the improvement of national identity. Our findings provide a novel intervention strategy for improving college students' national identity, which is to encourage their online participation in public health critical events.

Getting back in the loop: Does autonomous driving duration affect driver's takeover performance?

The level 3 autonomous driving function allows the driver to perform non-driving-related tasks such as watching movies or reading while the system manages the driving task. However, when a difficult situation arises, the driver is requested to return to the loop of control. This switching from driver to passenger then back to driver may modify the driving paradigm, potentially causing an out-of-the-loop state. We tested the hypothesis of a linear (progressive) impact of various autonomous driving durations: the longer the level 3 autonomous function is used, the poorer the driver's takeover performance. Fifty-two participants were divided into 4 groups, each group being assigned a specific period of autonomous driving (5, 15, 45, or 60 min), followed by a takeover request with a time budget of 8.3 s. Takeover performance was assessed over two successive drives via reaction times and manual driving metrics (trajectories). The initial hypothesis (linearity) was not confirmed: there was a nonlinear relationship between autonomous driving duration and takeover performance, with one duration (15 min) appearing safer overall and mixed performance within groups. Repetition induced a major change in performance during the second drive, indicating rapid adaptation to the situation. The non-driving-related task appears critical in several respects (dynamics, content, driver interest) to proper use of level 3 automation. All this supports previous research prompting reservations about the prospect of car driving becoming like train travel.

Critical Event Debriefing: Impacts on Clinical Practice and Implications for Oncology Nurses.

BACKGROUND: The complexity of caring for patients with cancer has a direct impact on oncology nurses. When a patient with cancer experiences a critical health event, oncology nurses may have concerns about their ability to provide high-quality care for patients in the current healthcare environment. These concerns can negatively affect nurses' emotional well-being and lead to compassion fatigue and burnout. OBJECTIVES: This article aims to examine critical event debriefing and identify ways oncology nurses can implement a critical event debriefing framework into their clinical practice. METHODS: A literature search was conducted in CINAHL® and PubMed® databases for articles related to critical event debriefing and compassion fatigue and burnout among oncology nurses. A case study demonstrates the use of critical event debriefing on an oncology unit. FINDINGS: Critical event debriefing frameworks can enhance teamwork, help initiate process improvements, and offer psychological support to improve emotional well-being. Additional research is needed about the use of critical event debriefing as a solution to compassion fatigue and burnout among oncology nurses.

How do people experience innocent suffering?

Introduction: The paper examines the psychological facet of innocent suffering. One can find a description of this phenomenon in social psychology as a factor that affects the belief in a just world, but there is a lack of qualitative scientific data about related psychological features, processes, copings, and consequences on the personality level. Methods: To study innocent suffering, semi-structured in-depth interview was conducted (31 respondents, ~223 minutes per respondent, 6,924 min in total) aimed to gather data about the experiences of innocent sufferings happened to participants. For the analysis of texts, a narrative and content analysis are used within the framework of grounded theory. The reliability of the results is based on expert assessment. Results and discussion: As a result, six essential properties of innocent sufferings were identified: complexity, stability, distress, injustice, casual incoherence, and breaks of integrity of a life story. The most "popular" life domains, in which participants reported about innocent sufferings, are violence, abuse (physical and psychological), and quitting romantic relationships. It is proposed a scientific definition of innocent suffering and the prototype of the phenomenon.

[Increasing the Accuracy of Extracorporeal Membrane Oxygenation Critical Event Management in the Medical Intensive Care Unit].

BACKGROUND & PROBLEMS: Extracorporeal membrane oxygenation (ECMO) is an intervention that replaces cardiopulmonary function temporarily to reduce injury to vital organs. As important members of the ECMO medical team, intensive care unit nurses must be well trained and alert to possible critical events. Failure to troubleshoot and manage ECMO promptly and correctly significantly increases the risk of mortality. A previous ECMO critical event in our unit resulted in lingering concerns and stress among nurses related to implementing this intervention. A survey conducted among our medical intensive care unit (MICU) nurses identified an implementation accuracy level for ECMO critical event management of only 59.1%. This poor result was attributed to a lack of technical assessment standards, in-service training, clinical experience, and instruction materials and the failure to offer online courses. PURPOSE: This study was designed to increase the accuracy of ECMO critical event management implementation among intensive care unit nurses to >86%. RESOLUTIONS: We conducted a problem-based training project to improve ECMO critical event management that: introduced a technical assessment sheet and technical simulation exercise, organized in-service training, implemented irregular simulation exercises, and produced multiple different instructional materials. RESULTS: The accuracy of ECMO critical event management implementation among the intensive care unit nurses increased from 59.1% pretest to 95.9% posttest. CONCLUSIONS: This project improved the ECMO care ability of MICU nurses in our hospital significantly, resulting in increased ECMO critical event management implementation accuracy, better patient care, higher nursing staff confidence, and lower perceived stress among nursing staff.

Practice of debriefing of critical events: a survey-based cross-sectional study of Portuguese anesthesiologists.

Debriefing is an essential procedure for identifying medical errors, improving communication, reviewing team performance, and providing emotional support after a critical event. This study aimed to describe the current practice and limitations of debriefing and gauge opinions on the best timing, effectiveness, need for training, use of established format, and expected goals of debriefing among Portuguese anesthesiologists. Methods: We performed a national cross-sectional online survey exploring the practice of anesthesiologists' debriefing practice after critical events in Portuguese hospitals. The questionnaire was distributed using a snowball sampling technique from July to September 2021. Data were descriptively and comparatively analyzed. Results: We had replies from 186 anesthesiologists (11.3% of the Portuguese pool). Acute respiratory event was the most reported type of critical event (96%). Debriefing occurred rarely or never in 53% of cases, 59% of respondents needed more training in debriefing, and only 4% reported having specific tools in their institutions to carry it out. There was no statistical association between having a debriefing protocol and the occurrence of critical events (P=.474) or having trained personnel (P=.95). The existence of protocols was associated with lower frequencies of debriefing (P=.017). Conclusions: Portuguese anesthesiologists know that debriefing is an essential process that increases patient safety, but among those surveyed, there is a need for an adequate debriefing culture or practice. Trial registration: Research registry 7741 (https://www.researchregistry.com/browse-the-registry#home).

Integrating simulation and interpretive description to explore operating room leadership: critical event continuing education.

In Obstetrics and Gynecologic operating room emergencies, the surgeon cannot both operate and lead a suddenly expanded and redirected team response. However, one of the most often used approaches to interprofessional continuing education designed to improve teams' ability to respond to unanticipated critical events still emphasizes surgeon leadership. We developed Explicit Anesthesia and Nurse Distributed (EXPAND) Leadership to imagine a workflow that might better distribute emergency leadership task responsibilities and practices. The purpose of this exploratory study was to investigate teams' responses to distributing leadership during an interprofessional continuing education simulated obstetrical emergency. We used interpretive descriptive design in a secondary analysis of teams' post-simulation reflective debriefings. One-hundred sixty providers participated, including OB-Gyn surgeons, anesthesiologists, CRNAs, scrub technicians, and nurses. Using reflective thematic analysis, we identified three core themes: 1) The surgeon is focused on the surgical field, 2) Explicit leadership initiates a nurse transition from follower to leader in a hierarchical environment, and 3) Explicit distributed leadership enhances teamwork and taskwork. Continuing education which uses distributed leadership to improve teams' ability to respond to an obstetric emergency is perceived to enhance team members' response to the critical event . The potential for nurses' career growth and professional transformation was an unexpected finding associated with this continuing education which used distributed leadership. Our findings suggest that healthcare educators should consider ways in which distributed leadership may improve teams' response to critical events in the operating room.

The resident experience with psychological safety during interprofessional critical event debriefings.

Objectives: Interprofessional feedback and teamwork skills training are important in graduate medical education. Critical event debriefing is a unique interprofessional team training opportunity in the emergency department. While potentially educational, these varied, high-stakes events can threaten psychological safety for learners. This is a qualitative study of emergency medicine resident physicians' experience of interprofessional feedback during critical event debriefing to characterize factors that impact their psychological safety. Methods: The authors conduced semistructured interviews with resident physicians who were the physician team leader during a critical event debriefing. Interviews were coded and themes were generated using a general inductive approach and concepts from social ecological theory. Results: Eight residents were interviewed. The findings suggest that cultivating a safe learning environment for residents during debriefings involves the following: (1) allowing space for validating statements, (2) supporting strong interprofessional relationships, (3) providing structured opportunities for interprofessional learning, (4) encouraging attendings to model vulnerability, (5) standardizing the process of debriefing, (6) rejecting unprofessional behavior, and (7) creating the time and space for the process in the workplace. Conclusions: Given the numerous intrapersonal, interpersonal, and institutional factors at play, educators should be sensitive to times when a resident cannot engage due to unaddressed threats to their psychological safety. Educators can address these threats in real time and over the course of a resident's training to enhance psychological safety and the potential educational impact of critical event debriefing.

Comparison of machine learning methods with logistic regression analysis in creating predictive models for risk of critical in-hospital events in COVID-19 patients on hospital admission.

BACKGROUND: Machine learning (ML) algorithms have been trained to early predict critical in-hospital events from COVID-19 using patient data at admission, but little is known on how their performance compares with each other and/or with statistical logistic regression (LR). This prospective multicentre cohort study compares the performance of a LR and five ML models on the contribution of influencing predictors and predictor-to-event relationships on prediction model´s performance. METHODS: We used 25 baseline variables of 490 COVID-19 patients admitted to 8 hospitals in Germany (March-November 2020) to develop and validate (75/25 random-split) 3 linear (L1 and L2 penalty, elastic net [EN]) and 2 non-linear (support vector machine [SVM] with radial kernel, random forest [RF]) ML approaches for predicting critical events defined by intensive care unit transfer, invasive ventilation and/or death (composite end-point: 181 patients). Models were compared for performance (area-under-the-receiver-operating characteristic-curve [AUC], Brier score) and predictor importance (performance-loss metrics, partial-dependence profiles). RESULTS: Models performed close with a small benefit for LR (utilizing restricted cubic splines for non-linearity) and RF (AUC means: 0.763-0.731 [RF-L1]); Brier scores: 0.184-0.197 [LR-L1]). Top ranked predictor variables (consistently highest importance: C-reactive protein) were largely identical across models, except creatinine, which exhibited marginal (L1, L2, EN, SVM) or high/non-linear effects (LR, RF) on events. CONCLUSIONS: Although the LR and ML models analysed showed no strong differences in performance and the most influencing predictors for COVID-19-related event prediction, our results indicate a predictive benefit from taking account for non-linear predictor-to-event relationships and effects. Future efforts should focus on leveraging data-driven ML technologies from static towards dynamic modelling solutions that continuously learn and adapt to changes in data environments during the evolving pandemic. TRIAL REGISTRATION NUMBER: NCT04659187.

Efficiency performance and safety evaluation of the responsibility-sensitive safety in freeway car-following scenarios using automated longitudinal controls.

The Responsibility-Sensitive Safety (RSS) model was proposed by Mobileye as a mathematical model that defines the real-time safety distance that the automated vehicle (AV) needs to maintain from surrounding vehicles. However, RSS strategy tends to be overly conservative. This research made modifications to the RSS safe distance to reduce its conservativeness without affecting safety, and evaluated the modified (RSS_X) and original RSS (RSS_O) in freeway car-following scenarios extracted from the Shanghai Naturalistic Driving Study (SH-NDS). The modifications were replacing the maximum acceleration with the positive previous time-step acceleration and adding standstill gap. In this study, 6,146 car-following scenarios were extracted and divided into two groups, normal scenarios (5,923) and safety-critical events (SCEs, near crashes) (223), to evaluate the efficiency and safety performance of RSS. The RSS_O and RSS_X were then embedded into the intelligent driver model (IDM) and model predictive control (MPC), but because the RSS modifications caused a few acceleration stability problems, the IDM and MPC were also modified to accommodate the RSS_X. The efficiency performance results showed that the modified models (IDM + RSS_X, MPC + RSS_X) performed better than the originals (IDM + RSS_O, MPC + RSS_O) in that they had higher average speeds, more comfortable acceleration pattern, and smaller longitudinal clearance between vehicles, which leads to less conservativeness. To evaluate safety, human drivers were compared with the original and modified models. RSS reduced the severity of at least 80 % of the human driver SCEs. MPC + RSS_X increased the mean minimum time to collision (TTC) for the majority of SCEs from 1.65 s to 4.08 s, and IDM + RSS_X increased the mean minimum TTC for the majority of SCEs from 1.53 s to 3.44 s.

Developing an improved automatic preventive braking system based on safety-critical car-following events from naturalistic driving study data.

In public road tests of autonomous vehicles in California, rear-end crashes have been the most common type of crash. Collision avoidance systems, such as autonomous emergency braking (AEB), have provided an effective way for autonomous vehicles to avoid collisions with the lead vehicle, but to avert false alarms, AEB tends to apply late and hard brake only if a collision becomes unavoidable. Automatic preventive braking (APB) is a new collision avoidance method used in Mobileye's Responsibility-Sensitive Safety (RSS) model that aims to reduce crashes with a milder brake and decreased impact on traffic flow, but APB's safety performance is inferior to that of AEB. This study therefore proposes three safety improvement strategies for APB, the addition of response time, safety buffer, and minimum following distance; and combines them in different ways into four improved APB systems, IP1-IP4. Simulating car-following safety-critical events (SCEs) extracted from the Shanghai Naturalistic Driving Study in MATLAB's Simulink, the safety performance, conservativeness, and driving comfort of the four systems were evaluated and compared with the original APB system, two AEB systems, and human drivers. The results show that 1) IP4, the system that integrated all three strategies, outperformed the baseline APB and IP1-IP3 and prevented all SCEs from becoming crashes; 2) IP4 was slightly more conservative than AEB, but less conservative than RSS; 3) APB's jerk-bounded braking profile improved driving comfort; and 4) higher deceleration was found in the two AEB systems (both 8.1 m/s2) than in IP4 (6.7 m/s2), but they failed to prevent all crashes. Our proposed APB system, IP4, can provide safe, efficient, and comfortable braking for AVs in car-following SCEs, and has the potential to be practically applied in vehicle collision avoidance systems.

Predictive Monitoring of Shake Flask Cultures with Online Estimated Growth Models.

Simplicity renders shake flasks ideal for strain selection and substrate optimization in biotechnology. Uncertainty during initial experiments may, however, cause adverse growth conditions and mislead conclusions. Using growth models for online predictions of future biomass (BM) and the arrival of critical events like low dissolved oxygen (DO) levels or when to harvest is hence important to optimize protocols. Established knowledge that unfavorable metabolites of growing microorganisms interfere with the substrate suggests that growth dynamics and, as a consequence, the growth model parameters may vary in the course of an experiment. Predictive monitoring of shake flask cultures will therefore benefit from estimating growth model parameters in an online and adaptive manner. This paper evaluates a newly developed particle filter (PF) which is specifically tailored to the requirements of biotechnological shake flask experiments. By combining stationary accuracy with fast adaptation to change the proposed PF estimates time-varying growth model parameters from iteratively measured BM and DO sensor signals in an optimal manner. Such proposition of inferring time varying parameters of Gompertz and Logistic growth models is to our best knowledge novel and here for the first time assessed for predictive monitoring of Escherichia coli (E. coli) shake flask experiments. Assessments that mimic real-time predictions of BM and DO levels under previously untested growth conditions demonstrate the efficacy of the approach. After allowing for an initialization phase where the PF learns appropriate model parameters, we obtain accurate predictions of future BM and DO levels and important temporal characteristics like when to harvest. Statically parameterized growth models that represent the dynamics of a specific setting will in general provide poor characterizations of the dynamics when we change strain or substrate. The proposed approach is thus an important innovation for scientists working on strain characterization and substrate optimization as providing accurate forecasts will improve reproducibility and efficiency in early-stage bioprocess development.

Student Nurses' Experiences of Critical Events in the Clinical Setting: A Grounded Theory.

BACKGROUND: Nursing students often experience critical events in the clinical setting and clinical instructors may not be prepared to adequately support them. These students often feel alone and abandoned, increasing their risk of psychological distress. PURPOSE: A grounded theory study was conducted to explore pre-licensure nursing students' experiences of critical events in the clinical setting. Specific attention was paid to understanding how they are prepared for and supported before, during, and after critical events, and their experiences of psychological distress and psychological recovery. METHOD: Strauss and Corbin's Grounded Theory methodology was used for this study. RESULTS: Fourteen undergraduate student nurses from universities in the western United States were interviewed. Ten concepts were identified, and a theory of Student Nurses' Experiences of Critical Events in the Clinical Setting emerged. CONCLUSION: Findings indicate that student nurses need active instructor and/or staff support during critical events, and pre-briefing whenever possible. Debriefing positively affected students' post-event stress response and lack of debrief was associated with post-event psychological distress. Support for students exposed to critical events during clinical experiences should continue in the days, weeks, and months following the event; clinical instructors need to be prepared to provide this support. All faculty members should monitor students for signs of psychological distress and better support students' mental health and emotional wellbeing.

The PATH to patient safety.

Communication is critical to safe patient care. In this issue of the British Journal of Anaesthesia, Jaulin and colleagues show that use of a Post-Anaesthesia Team Handover (PATH) checklist is associated with fewer hypoxaemia events in the PACU, reduced handover interruptions, and other important metrics related to improved communication. The PATH checklist provides a link within a broader chain of safety checklists and other interventions that comprise a perioperative chain of survival.

Mining patterns of near-crash events with and without secondary tasks.

The engagement of secondary tasks, like using a phone or talking to passengers while driving, could introduce considerable risks to driving safety. This study utilizes a near-crash dataset extracted from a naturalistic driving study to explore the patterns of near-crash events with or without the involvement of secondary tasks as a surrogate approach to understand the impact of these behaviors on traffic safety. The dataset contains information about driver behaviors, such as secondary tasks, vehicle maneuvers, other conflict vehicles' maneuvers before and during near-crash events, and the driving environment. The patterns for near-crashes with or without the involvement of secondary tasks are mined by adopting the apriori association rule algorithm. Finally, the mined rules for the near-crash events with or without the involvement of the secondary tasks are analyzed and compared. The results demonstrate that near-crashes with the involvement of secondary tasks often occur with drivers in a relatively stable and presumably predictable environment, such as an interstate highway with a constant speed. This type of near-crash is highly associated with the leading vehicle's sudden slowing or stopping since there is no expectation of any interruptions for these drivers performing the secondary tasks. The most common evasive maneuver in this kind of emergency is braking. Near-crashes without the involvement of secondary tasks is often associated with lane-changing behavior and sideswipe incidents. With shorter reaction time and awareness of the driving environment, the drivers in this type of near-crash can often make more complex maneuvers, like braking and steering, to avoid a collision. Understanding the patterns of these two types of near-crash incidents could help safety researchers, traffic engineers, and even vehicle designers/engineers develop countermeasures for minimizing potential collisions caused by secondary tasks or improper lane changing behaviors.

Avatar-based patient monitoring in critical anaesthesia events: a randomised high-fidelity simulation study.

BACKGROUND: Failures in situation awareness cause two-thirds of anaesthesia complications. Avatar-based patient monitoring may promote situation awareness in critical situations. METHODS: We conducted a prospective, randomised, high-fidelity simulation study powered for non-inferiority. We used video analysis to grade anaesthesia teams managing three 10 min emergency scenarios using three randomly assigned monitoring modalities: only conventional, only avatar, and split-screen showing both modalities side by side. The primary outcome was time to performance of critical tasks. Secondary outcomes were time to verbalisation of vital sign deviations and the correct cause of the emergency, perceived workload, and usability. We used mixed Cox and linear regression models adjusted for various potential confounders. The non-inferiority margin was 10%, or hazard ratio (HR) 0.9. RESULTS: We analysed 52 teams performing 154 simulations. For performance of critical tasks during a scenario, split-screen was non-inferior to conventional (HR=1.13; 95% confidence interval [CI], 0.96-1.33; not significant in test for superiority); the result for avatar was inconclusive (HR=0.98; 95% CI, 0.83-1.15). Avatar was associated with a higher probability for verbalisation of the cause of the emergency (HR=1.78; 95% CI, 1.13-2.81; P=0.012). We found no evidence for a monitor effect on perceived workload. Perceived usability was lower for avatar (coefficient=-23.0; 95% CI, -27.2 to -18.8; P<0.0001) and split-screen (-6.7; 95% CI, -10.9 to -2.4; P=0.002) compared with conventional. CONCLUSIONS: This study showed non-inferiority of split-screen compared with conventional monitoring for performance of critical tasks during anaesthesia crisis situations. The patient avatar improved verbalisation of the correct cause of the emergency. These results should be interpreted considering participants' minimal avatar but extensive conventional monitoring experience.

Clinical debriefing: A concept analysis.

AIMS AND OBJECTIVES: The purpose of this paper is to enhance nursing and collaborative practice by presenting a concept analysis of clinical debriefing and introducing an operational definition. BACKGROUND: Debriefing has taken many forms, using a variety of approaches. Variations and inconsistencies in clinical debriefing, and its related terms, still exist in the clinical setting. DESIGN: Concept analysis. METHODS: Walker and Avant's eight-step approach to concept analysis. RESULTS: The defining attributes of clinical debriefing identified in this analysis are described as the five E's: educated/experienced facilitator, environment, education, evaluation and emotions. Antecedents identified in this analysis include the critical event, the desire or need to review such an event and the organizational awareness to execute clinical debriefs. The consequences of clinical debriefings are primarily advantageous and positively impact involved nurses, healthcare teams, patients and organizations. Empirical referents of clinical debriefing are complex and multifactorial. The productivity of a clinical debrief can be enhanced through a series of proposed questions. Together, the defining attributes, antecedents and consequences shape a proposed operational definition of clinical debriefing. CONCLUSION: Clinical debriefing is a valuable tool within healthcare organizations. Debriefing can be a holistic, interprofessional, collaborative experience when all five defining attributes are present. Further investigation is required to standardise debriefing practices in clinical settings. RELEVANCE TO CLINICAL PRACTICE: A concept analysis on clinical debriefing promotes uniformity of debriefing practices, reflective practice among nurses and healthcare teams, and contributes to nursing science by creating a platform for the development of practice standards, research and theory development.