Michael J. Burtscher

Speaking up is related to better team performance in simulated anesthesia inductions: an observational study.

BACKGROUND:Our goal in this study was to test the relationship between speaking up—i.e., questioning, correcting, or clarifying a current procedure—and technical team performance in anesthesia. Hypothesis 1: team members’ higher levels of speaking up are related to higher levels of technical team performance. Hypothesis 2: team members will react to speaking up by either clarifying their procedure or initiating a procedural change. Hypothesis 3: higher levels of speaking up during an earlier phase of teamwork will be related to higher levels of speaking up during a later phase. METHODS:This prospective observational study involved 2-person ad hoc anesthesia teams performing simulated inductions of general anesthesia with minor nonroutine events (e.g., bradycardia) in a large teaching hospital. Subjects were registered anesthesia nurses and residents. Each team consisted of 1 nurse and 1 resident. Synchronized video and vital parameter recordings were obtained. Two trained observers blinded to the hypotheses coded speaking up and further team communication and coordination behavior on the basis of 12 distinct categories. All teamwork measures were quantified as percentage of total time spent on the respective teamwork category. Two experienced staff anesthesiologists blinded to the hypotheses evaluated technical team performance using a Delphi-validated rating checklist. Hypotheses 1 and 3 were tested using linear regression with residents’ and nurses’ levels of speaking up as 2 separate predictor variables. Hypothesis 2 was analyzed using lag sequential analysis, resulting in Z values representing the extent to which the observed value for a conditional transition significantly differs from its unconditional value. RESULTS:Thirty-one nurses and 31 residents participated. Technical team performance could be predicted by the level of speaking up from nurses (R2 = 0.18, P = 0.017) but not from residents (R2 = 0.19, P = 0.053); this result supports Hypothesis 1 for nurses. Supporting Hypothesis 2, residents reacted to speaking up with clarifying the procedure by providing information (Z = 18.08, P < 0.001), initiating procedural change by giving instructions (Z = 4.74, P < 0.001) and team member monitoring (Z = 3, P = 0.0013). Likewise, nurses reacted with clarifying the procedure by providing or evaluating information (Z = 16.09, P < 0.001; Z = 3.72, P < 0.001) and initiating procedural change by providing assistance (Z = 0.57, P < 0.001). Indicating a trend for Hypothesis 3, nurses’ level of speaking up before intubation predicted their level of speaking up during intubation (R2 = 0.15, P = 0.034), although this did not reach the Bonferroni-corrected significance level of P = 0.025. No respective relationship was found for residents (R2 = 0.15, P = 0.096). CONCLUSIONS:This study provides empirical evidence and shows mechanisms for the positive relationship between speaking-up behavior and technical team performance.

Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team mental model properties. Thirty-one two-person teams consisting of anesthesia resident and anesthesia nurse were videotaped during a simulated anesthesia induction of general anesthesia. Team mental models were assessed with a newly developed measurement tool based on the concept-mapping technique. Monitoring behavior was coded by two organizational psychologists using a structured observation system. Team performance was rated by two expert anesthetists using a performance-checklist. Moderated multiple regression analysis revealed that team mental model similarity moderated the relationship between team monitoring and performance; a higher level of team monitoring in the absence of a similar team mental model had a negative effect on performance. Furthermore, team mental model similarity and accuracy interacted to predict team performance. Our findings provide new insights on factors influencing the relationship between team processes and team performance in health care. When investigating the effectiveness of a specific team coordination behavior, team cognition has to be taken into account. This represents a necessary and compelling extension of the popular process-outcome relationship on which previous teamwork research in health care has focused. Moreover, the current study adds further external validity to the concept of team mental models by highlighting its usefulness in health care.

Managing Nonroutine Events in Anesthesia: The Role of Adaptive Coordination

Objective: This field study aimed at examining the role of anesthesia teams’ adaptive coordination in managing changing situational demands, such as in nonroutine events (NREs). Background: Medical teams’ ability to adapt their teamwork (e.g., their coordination activities) to changing situational demands is crucial to team performance and, thus, to patient safety. Whereas the majority of previous studies on the matter have focused on critical but rare events, it has recently been pointed out that the effective management of NREs is a key challenge to medical teams. Hence this study investigated the relationship between coordination activities, NRE occurrence, and team performance. Method: We videotaped 22 anesthesia teams during standard anesthesia induction and recorded data from the vital signs monitor and the ventilator. Coordination was coded by a trained observer using a structured observation system. NREs were recorded by an experienced staff anesthesiologist using all three video streams. Checklist-based team performance assessment was also performed by an experienced staff anesthesiologist. Results: We found that anesthesia teams adapt their coordination activities to changing situational demands. In particular, the increased occurrence of NREs caused an increase in the time the teams spent on task management. A stronger increase in the teams’ task management (i.e., more adaptive coordination) was related to their performance. Conclusion: Our results emphasize the importance of adaptive coordination in managing NREs effectively. Application: This study provides valuable information for developing novel team training programs in health care that focus on adaptation to changing task requirements, for example, when faced with NREs.

Adaptation in anaesthesia team coordination in response to a simulated critical event and its relationship to clinical performance

BACKGROUND Recent studies in anaesthesia and intensive care indicate that a teams ability to adapt its coordination activities to changing situational demands is crucial for effective teamwork and thus, safe patient care. This study addresses the relationship between adaptation of team coordination and markers of clinical performance in response to a critical event, particularly regarding which types of coordination activities are used and which team member engages in those coordination activities. METHODS Video recordings of 15 two-person anaesthesia teams (anaesthesia trainee plus anaesthesia nurse) performing a simulated induction of general anaesthesia were coded, using a structured observation system for coordination activities. The simulation involved a critical event-asystole during laryngoscopy. Clinical performance was assessed using two separate reaction times related to the critical event. RESULTS Analyses of variance revealed a significant effect of the critical event on team coordination: after the occurrence of the asystole, team members adapted their coordination activities by spending more time on information management-a specific type of coordination activity (F(1,28)=15.17, P=0.001). No significant effect was found for task management. The increase in information management was related to faster decisions regarding how to respond to the critical event, but only for trainees and not for nurses. CONCLUSIONS Our findings support the claim that adaptation of coordination activities is related to improved team performance in healthcare. Moreover, adaptation and its relationship to team performance were found to vary with regard to type of coordination activities and team member.

Monitoring and talking to the room: autochthonous coordination patterns in team interaction and performance

This paper builds on and extends theory on team functioning in high-risk environments. We examined 2 implicit coordination behaviors that tend to emerge autochthonously within high-risk teams: team member monitoring and talking to the room. Focusing on nonrandom patterns of behavior, we examined sequential patterns of team member monitoring and talking to the room in higher- and lower-performing action teams working in a high-risk health care environment. Using behavior observation methods, we coded verbal and nonverbal behaviors of 27 anesthesia teams performing an induction of general anesthesia in a natural setting and assessed team performance with a Delphi-validated checklist-based performance measure. Lag sequential analyses revealed that higher-performing teams were characterized by patterns in which team member monitoring was followed by speaking up, providing assistance, and giving instructions and by patterns in which talking to the room was followed by further talking to the room and not followed by instructions. Higher- and lower-performing teams did not differ with respect to the frequency of team member monitoring and talking to the room occurrence. The results illustrate the importance of patterns of autochthonous coordination behaviors and demonstrate that the interaction patterns, as opposed to the behavior frequencies, discriminated higher- from lower-performing teams. Implications for future research and for team training are included. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Co-ACT—a framework for observing coordination behaviour in acute care teams

Background Acute care teams (ACTs) represent action teams, that is, teams in which members with specialised roles must coordinate their actions during intense situations, often under high time pressure and with unstable team membership. Using behaviour observation, patient safety research has been focusing on defining teamwork behaviours—particularly coordination—that are critical for patient safety during these intense situations. As one result of this divergent research landscape, the number, scope and variety of applied behaviour observation taxonomies are growing, making comparison and convergent integration of research findings difficult. Aim To facilitate future ACT research by presenting a framework that provides a shared language of teamwork behaviours, allows for comparing previous and future ACT research and offers a measurement tool for ACT observation. Method Based on teamwork theory and empirical evidence, we developed Co-ACT—the Framework for Observing Coordination Behaviour in ACT. Integrating two previous, extensive taxonomies into Co-ACT, we also suggested 12 behavioural codes for which we determined inter-rater reliability by analysing the teamwork of videotaped anaesthesia teams in the clinical setting. Results The Co-ACT framework consists of four quadrants organised along two dimensions (explicit vs implicit coordination; action vs information coordination). Each quadrant provides three categories for which Cohens κ overall value was substantial; but values for single categories varied considerably. Conclusions Co-ACT provides a framework for organising behaviour codes and offers respective categories for succinctly measuring teamwork in ACTs. Furthermore, it has the potential to allow for guiding and comparing ACTs study results. Future work using Co-ACT in different research and training settings will show how well it can generally be applied across ACTs.

CoenoFire: monitoring performance indicators of firefighters in real-world missions using smartphones

Firefighting is a dangerous task and many research projects have aimed at supporting firefighters during missions by developing new and often costly equipment. In contrast to previous approaches, we use the smartphone to monitor firefighters during real-world missions in order to provide objective data that can be used in post-incident briefings and trainings. In this paper, we present CoenoFire, a smartphone based sensing system aimed at monitoring temporal and behavioral performance indicators of firefighting missions. We validate the performance metrics showing that they can indicate why certain teams performed faster than others in a training scenario conducted by 16 firefighting teams. Furthermore, we deployed CoenoFire over a period of six weeks in a professional fire brigade. In total, 71 firefighters participated in our study and the collected data includes 76 real-world missions totaling to over 148 hours of mission data. Additionally, we visualize real-world mission data and show how mission feedback is supported by the data.

Sensing group proximity dynamics of firefighting teams using smartphones

Firefighters work in dangerous and unfamiliar situations under a high degree of time pressure and thus team work is of utmost importance. Relying on trained automatisms, firefighters coordinate their actions implicitly by observing the actions of their team members. To support training instructors with objective mission data, we aim to automatically detect when a firefighter is in-sight with other firefighters and to visualize the proximity dynamics of firefighting missions. In our approach, we equip firefighters with smartphones and use the built-in ANT protocol, a low-power communication radio, to measure proximity to other firefighters. In a second step, we cluster the proximity data to detect moving sub-groups. To evaluate our method, we recorded proximity data of 16 professional firefighting teams performing a real-life training scenario. We manually labeled six training sessions, involving 51 firefighters, to obtain 79 minutes of ground truth data. On average, our algorithm assigns each group member to the correct ground truth cluster with 80% accuracy. Considering height information derived from atmospheric pressure signals increases group assignment accuracy to 95%.

Promoting good decisions: How regulatory focus affects group information processing and decision-making

Decision-making groups often fail to exploit their full potential because they do not integrate all relevant information. We propose to address this issue by interpreting group information processing as a motivational process that is influenced by group goal structure. In line with this approach, we apply regulatory focus theory to decision-making groups. Specifically, we investigate the effects of a promotion versus a prevention focus framing on group decision quality and information processing. Sixty-three-person groups solved five decision-making tasks based on the “stranded in the desert” scenario. Regulatory focus was manipulated via pay-off schemes and group interactions were videotaped. We found that groups in a promotion focus solved more tasks correctly than groups in a prevention focus. This effect on decision quality was mediated by group information processing. Finally, we show that regulatory focus influences group interaction patterns, which represents an important extension of regulatory focus research in groups.

The Role of Coordination in Preventing Harm in Healthcare Groups: Research Examples from Anaesthesia and an Integrated Model of Coordination for Action Teams in Health Care

In this chapter we discuss the role of group coordination as a means of preventing iatrogenic harm in health care using anaesthesia teams as our forum of research. Applying the inclusive model of group coordination in Chap. 2 (see Fig. 2.5), we outline that (1) clinical performance and patient safety are functions of group coordination, (2) information and actions are key input entities of group coordination, (3) adaptation to situational demands serves as a critical coordination process, and (4) explicit and implicit coordination are essential coordination mechanisms. We will present recent findings regarding the role of each of these concepts for teamwork in health care. Combining theoretical considerations and empirical results, we will offer an integrated model of coordination for action teams in health care. The core idea of this model is that coordination can be classified along two independent dimensions (1) mechanisms such as explicit vs. implicit coordination, and (2) input entities such as behaviours (e.g. actions) and meanings (e.g. information). We suggest that the usefulness of team coordination should hence be considered with regard to this distinction.