A growing body of research aims at understanding how medical harm can be prevented.1–8 This is particularly relevant for highly dynamic medical settings such as anesthesia in which health care professionals work together in varying compositions for short time periods in so-called action teams.9–11 A remarkable finding of research on medical action teams is that something seemingly trivial such as communication is a major factor contributing to medical errors.12–20 In surgery, for example, it is even the second major source of error after lack of competence.12 Even if these teams have excellent preconditions, such as highly skilled and motivated team members, they may suffer from breakdowns in teamwork, e.g., due to miscommunication and a resulting lack of mutual “sense-making.”10,21–24
One prominent communication error is the failure to speak up. In a tragic example of unsuccessful speaking up resulting in the death of a patient, a nurse observed very experienced senior anesthesiologists during the induction of general anesthesia unsuccessfully attempting to intubate a patient scheduled for a routine operation. After the patient’s lungs had not been ventilated for several minutes, the nurse fetched a tracheotomy set but did not attract sufficient attention to this promising problem solution from the doctors to change their course of action.25 That is, junior doctors or nurses may communicate an important observation only implicitly, leading to a lack of effect on the procedure.25 This communication problem is well known in many work environments, particularly in aviation.26–30 In medicine, the potential risks of not speaking up are increasingly acknowledged; speaking up is increasingly considered essential for error prevention and quality of care.25,26,31,32
In accordance with the literature, we define speaking up as explicitly communicating task-relevant observations, requesting clarification, or explicitly challenging or correcting a task-relevant decision or a procedure.30 We assume that speaking up is particularly crucial in intense, dynamic health care contexts such as anesthesia in which nonroutine events require rapid information processing and decision making.33 However, this assumption has not yet been formally tested. Medical research has investigated the perceived barriers to speaking up (e.g., repercussion, social rejection) and the training of how to speak up (e.g., using the 2-challenge rule) using surveys and evaluating training interventions.34–36 An interview study found that the perceived ease of speaking up was correlated with the success of implementing a new technology for minimally invasive cardiac surgery.21 Yet, empirical evidence for positive effects of speaking-up behavior on technical team performance has yet to be established. Addressing this research gap was the main goal of our study, i.e., we investigated the empirical relationship between observed speaking up and technical team performance. As secondary aims, we also explored the effects of speaking-up behavior on immediate team interaction and its development during different phases of teamwork.
First, on the basis of the literature suggesting that speaking up is crucial for high quality of care, we assumed that team members’ (i.e., resident physicians’ and nurses’) higher levels of speaking up are related to higher technical team performance (hypothesis 1). Second, we were interested in the effects of speaking up on team interaction. By investigating teammates’ immediate reactions to speaking up, we aimed to reveal the mechanism of why speaking up may be beneficial for performance. In line with the definition of speaking up, we assumed that team members would most likely react to it by either clarifying their procedure or initiating a procedural change (hypothesis 2). Third, we investigated the development of speaking up over the course of 2 distinct induction phases.37,38 Previous research has shown that expressing opinions, similar to remaining silent, can become self-reinforcing.39 Thus, we assumed that higher levels of speaking up during an earlier phase of teamwork (i.e., before intubation) would lead to higher levels of speaking up during a later phase (i.e., during intubation; hypothesis 3).
Testing our hypotheses implied 2 methodological requirements: (a) observing the actual level of speaking up and (b) using reliable markers for technical team performance. We incorporated both requirements in this observation study.
METHODS
The study was approved by the Ethics Committee of the Canton Zurich, Switzerland. Written consent was obtained from study participants. The study was registered at ClinicalTrial.gov (NCT00706108).
Study Design
The 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 in Switzerland. We chose the simulator setting to ensure standardization of the case. An advanced cardiac life support training mannequin (MegaCode®, Laerdal, Stavanger, Norway) allowing cardiac arrhythmia simulation was extended by a noninvasive blood pressure (NIBP) and a pulse oximetry (Spo2) simulator to be used for simulation of induction of general anesthesia. Video and vital variable recordings were obtained using a setup allowing synchronized recording and playback of video, monitor, and ventilator data. The simulation scenario was standardized and designed as a straightforward induction of anesthesia according to local standards and took place in an actual operating room (OR). To design the simulated scenario as realistically as possible, we simulated 8 nonroutine events, which are typical for inductions, within each scenario in the following order40: (1) Cefazolin, a cephalosporin, planned as prophylactic antibiotic on OR schedule for a patient allergic to cephalosporin (noted in the patient chart), (2) handwriting on anesthesia preoperative chart partly illegible, (3) patient moans during induction, (4) hypotension, (NIBP decreases to 60/30 mm Hg), (5) bradycardia (40 per minute), (6) airway obstruction (high airway pressure and decreased breath sounds over left chest after intubation), (7) desaturation (Spo2 decreases to 88%), and (8) hypertension (NIBP increases to 200/150 mm Hg).
Participants
The required sample size was estimated by a priori power analysis using G*Power.41 Because all participants were volunteers, our possible sample size was limited. Assuming a large effect size (f2 = 0.35) for linear multiple regression with 2 predictors (α = 0.05, power = 0.80), the total required sample size was 31 teams.41 Participants were 64 staff members (32 registered anesthesia nurses, 32 resident physicians) organized in 32 teams performing a simulated induction of general anesthesia with the resident performing intubation while being assisted by the nurse. Each team consisted of 1 nurse and 1 resident (the resident at the intubating position, nurse assisting). A consultant anesthesiologist was immediately available, if requested. Participants were only included if they had at least 3 months’ clinical experience to assure sufficient familiarity with the anesthesia procedures and equipment. Participants were explicitly informed that they could withdraw from the simulation at any time. One team made use of this opportunity after the simulation, thereby reducing the final sample to 31 teams.
Team Communication and Coordination Behavior Coding
Testing hypotheses 1 and 3 required the coding of team members’ speaking up. Additionally, testing hypothesis 2 required coding of further team communication and coordination behaviors to investigate how team members reacted to speaking up. We used a coding scheme capturing verbal and nonverbal interactions with 12 distinct categories (Table 1).42 Applying an event sampling procedure, we classified each behavior according to its code (e.g., speaking up), its timing (i.e., beginning, end, duration), and the team member role (e.g., anesthesia nurse). Specifically, speaking up was coded when a team member questioned a current decision or procedure, corrected the task-relevant behavior of the other team member, or asked for a task-relevant clarification.
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Table 1: Mean Frequency and Standard Deviations of Study Variables for Nurses and Residents
Coding was performed by 2 observers with a background in psychology and training in use of the coding instrument, both blinded to our hypotheses, using specialized software for behavioral observation (Interact, Mangold International, Arnstorf, Germany). Watching the videotape, the observers marked the beginning (e.g., defining the onset time when a nurse asked for task-relevant clarification) and ending of a code (e.g., when the nurse was finished asking for task-relevant clarification). For determining interrater reliability, 10% of the data were independently coded by both coders. Cohen’s kappa for speaking up was 0.80; the overall Cohen’s kappa was 0.77. Both values represent substantial agreement.43
Technical Team Performance Assessment
Because a simulated setting precludes assessment of real patient outcomes, we assessed the practical result of the anesthesia team’s efforts during anesthesia induction in terms of technical team performance. Acknowledging that standards reflect an institution’s accepted best practice implementing both current scientific evidence and institutional experience, we quantified technical team performance using a measure that assessed the level of agreement of team actions with the respective institutional standards for induction of general anesthesia. For this purpose, a checklist was Delphi-validated37 by repeated assessment by experienced staff anesthesiologists. The resulting checklist included items representing (a) steps of an ideal standard anesthesia induction and for preventing errors (e.g., checking correct position of tube by auscultation), as well as (b) monitoring and reacting to adequate target values (e.g., SaO2 > 95%). The complete performance checklist can be found in Appendix 1. Very similar checklists have already been used to assess technical team performance in anesthesia.44–47 The performance measure was applied by 2 experienced staff anesthesiologists, blinded to our hypotheses, who reviewed video, monitor, and ventilator data. Each score was compared to the respective maximum score to obtain an adjusted measure of team performance ranging between 1 and 100. A score of 100 would indicate that the team conducted the induction perfectly according to the standard and dealt optimally with the simulated nonroutine events. To establish interrater reliability, we evaluated 3 randomly selected videotapes by both raters. Interrater reliability was subsequently calculated using the ICC coefficient, which was 0.98, indicating high reliability.48
Appendix 1: Technical Team Performance Measure for Anesthesia Induction (Adapted for Simulated Inductions)
Statistical Analyses
In accordance with comparable studies, teamwork measures were defined as the time spent on the respective teamwork category in relation to induction duration.20,23,37,38 For example, if an anesthesia nurse spent 1 minute of a 20-minute induction on speaking up, the speaking-up score was 5%. These relative durations allowed for controlling for variation in duration of the induction. The percentage of team communication and coordination behavior was arcsine-transformed, as recommended for proportional data.49
All hypotheses were tested separately for residents and nurses, that is, residents’ and nurses’ speaking-up behavior was not aggregated. After visually inspecting the data by means of data scatter plots revealed no indications for nonlinear relationships, hypotheses 1 and 3 were tested using linear regression analysis (PASW Statistics 18, SPSS Inc., Chicago, IL). Specifically, hypothesis 1 was tested with speaking up as predictor and technical team performance as criterion. Testing hypothesis 3 included speaking up before intubation as predictor and speaking up during intubation as criterion. Hypothesis 2—proposing that team members would most likely react to speaking up by either clarifying their procedure or initiating a procedural change—was analyzed via lag sequential analysis to determine whether speaking up was significantly more or less often than expected followed by one of the other 11 categories.50 Of those 11 categories, “information request,” “information evaluation,” and “providing information upon request” are clarifying the procedure, whereas “instruction,” “planning,” and “provide assistance” are initiating procedural change. The lag sequential analysis is explained in Appendix 2. Its results are Z scores: significant positive Z scores indicate that a specific behavior of one team member is followed significantly more often by a specific behavior of the other team member. By contrast, negative Z scores indicate that a specific behavior of one team member is followed significantly less often by a specific behavior of the other team member.
Appendix 2: Performing the Lag Sequential Analysis
RESULTS
Duration of the 31 simulations ranged from 18 to 33 minutes (M = 21, SD = 4). In total, 28,883 distinct team communication and coordination behaviors were coded. Table 1 shows the descriptive statistics of the study variables; Table 2 shows the intercorrelations among technical team performance and speaking up. Residents’ and nurses’ levels of speaking up were not significantly correlated (r = 0.18; P = 0.17), and nurses showed higher levels of speaking up than residents.
Table 2: Intercorrelations Among Technical Team Performance and Speaking Up
Speaking Up and Technical Team Performance
Hypothesis 1, which stated that team members’ (i.e., resident physicians’ and nurses’) higher levels of speaking up are related to higher technical team performance, was tested with a hierarchical linear regression. This regression modela is shown in Table 3 (n = 31 teams). In step 1, we entered nurses’ levels of speaking up as predictor of technical team performance in the regression term because they had the highest levels of speaking up. Nurses’ levels of speaking up significantly predicted technical team performance (R2 = 0.18, P = 0.017). The value of 0.43 indicates that as speaking up from nurses increased by one standard deviation (SDarcsine = 0.009), technical team performance (SD = 9.99) increased by 0.43 standard deviations, i.e., by 4.229. Table 4 shows respective examples of nurses’ levels of speaking up in the highest-, medium-, and lowest-performing teams.
Table 4: Examples of Technical Team Performance and Nurses’ Level of Speaking Up in the Highest, Medium, and Lowest Performing Team
Table 3: Linear Regression of Speaking Up on Technical Team Performance
In step 2, we entered residents’ levels of speaking up as predictors of technical team performance in the regression term to determine the additional predictive value of the residents’ levels of speaking up. Although this regression model yielded a trend for the proposed assumption, it was not statistically significant (R2 = 0.19, P = 0.053).
That is, technical team performance could be predicted by the level of speaking up from nurses but not from residents.
Immediate Effects of Speaking Up on Team Interaction
Hypothesis 2 proposed that team members would react to speaking up with either clarifying the procedure or initiating a procedural change. Applying lag sequential analysis (Appendix 2), we explored the team members’ immediate reactions to speaking up. Residents reacted to speaking up with clarifying the procedure by providing information (Z = 18.08, P < 0.001), with initiating procedural change by giving instructions (Z = 4.74, P < 0.001), and also with team member monitoring (Z = 3, P = 0.0013). Likewise, nurses reacted with clarifying the procedure by providing information (Z = 16.09, P < 0.001) and information evaluation (Z = 3.72, P < 0.001) and with initiating procedural change by providing assistance (Z = 0.57, P < 0.001) but not by giving instructions (Table 5). These results support hypothesis 2.
Table 5: Values for the Criteria Speaking up for Lag 1
Development of Speaking Up
Hypothesis 3, which stated that higher levels of speaking up in an earlier phase of the induction (before intubation) are related to higher levels of speaking up in a later phase (intubation), was tested with 2 linear regressions. Both regression models are shown in Table 6.
Table 6: Linear Regression of Speaking Up Before Intubation on Speaking Up During Intubation
In the first regression we predicted nurses’ speaking up during intubation. In step 1 we entered nurses’ levels of speaking up before intubation. This model yielded a trend for the proposed assumption, but was not statistically significant when applying the Bonferroni correction for 2 comparisons (R2 = 0.15, P = 0.034). In step 2 we entered residents’ levels of speaking up before intubation. This model was not statistically significant (R2 = 0.15, P = 0.096).
In the second regression we predicted residents’ speaking up during intubation. In step 1 we entered residents’ levels of speaking up before intubation. This model was not statistically significant (R2 = 0.09, P = 0.099). In step 2 we entered nurses’ levels of speaking up before intubation. This model was not significant (R2 = 0.13, P = 0.13) either.
In summary, we found a trend indicating that nurses’ previous level of speaking up, not the level of their respective colleague, predicted later occurrence of speaking up.
DISCUSSION
Three significant findings resulted from our simulation-based observational study. The first and main finding was a significant positive association between nurses’ overall level of speaking up and technical team performance. Second, further analyses of team interaction by means of lag sequential analysis showed that speaking up by nurses as well as by residents resulted in clarifications of the procedure (e.g., providing and evaluating information) and initiated procedural change (e.g., residents gave instructions, nurses provided assistance). Third, because there was a tendency for the nurses’ level of speaking up before intubation to be associated with their level of speaking up during subsequent intubation, our results also point to the potential value of early speaking up.
Empirical Evidence for Positive Effects of Speaking Up on Team Performance
Our findings are a meaningful contribution to research on improving communication and preventing medical harm in anesthesia because they provide the first empirical evidence for the positive relationship between actual speaking-up behavior and technical team performance. Moreover, they also show how speaking up affects immediate team interaction and how it develops over the course of anesthesia induction. Previous literature has focused on (a) explaining why speaking up is essential for preventing medical harm and ensuring good quality of care,25,31,32,52 (b) investigating the perceived barriers of speaking up,34,35,53–55 (c) the impact of the perceived ease of speaking up on performance,21 and (d) the training of how to speak up,36 but not on the effects of training on patient outcomes. The positive effects of the actual speaking-up behavior on performance had been suggested but not been formally studied. Through observing the level of naturally occurring speaking up and using quantifiable markers for technical team performance, our study provides empirical evidence for an association of speaking up with better technical team performance and suggests possible explanations for its effects on, and development during, teamwork. Specifically, our data suggest that it is the level of speaking up by the assisting nurses that matters for team performance.
The particular importance of nurses’ speaking up might not only reflect their more extensive work experience in our study population (Table 1) but also their functional role-behavior adapted to the specific conditions of a teaching hospital OR setting. In the investigated setting, resident physicians were performing simulated clinical procedures while being assisted by nurses. That allowed the assisting person to monitor the overall situation, which was a precondition for speaking up.56 Possibly, if a nurse had performed the intubation while being assisted by a resident, the speaking up levels of the resident would have been similarly relevant for performance. Alternatively, in case of a more complex scenario (e.g., cannot intubate, cannot ventilate), which mostly requires an attending physician to monitor or assist the team, his or her levels of speaking up would probably have also been relevant to performance.
The results of the lag sequential analyses enhance our understanding of the mechanism through which speaking up has an impact on technical team performance, i.e., it results in clarifications of the procedure and initiates procedural change. Residents also reacted with monitoring, indicating that speaking up can result in observing the other team member. Some responses to speaking up were identical for residents and nurses; others were different. Residents reacted with monitoring and giving instructions, whereas nurses reacted with providing assistance. The latter result again reflects the functional work roles in anesthesia teams. Residents held the responsibility for the intubation and were manually involved and thus very concentrated on performing the laryngoscopy. This may have narrowed their range of possible responses to nurses’ speaking up. Whereas providing assistance may not have been possible for residents, monitoring and giving instructions were. Nurses, on the other hand, monitored the resident during intubation and were thus able to respond to residents’ speaking up with providing assistance.
With respect to the development of speaking up, the trends resulting from regression analysis suggest that it can be important for nurses to start speaking up early because speaking up before intubation was associated with speaking up during intubation. This result could indicate that speaking up early may set the stage for being more at ease and likely to apply this technique later on. With regard to training, these results could indicate that anesthesia teams should be encouraged to get comfortable with speaking up early instead of waiting until the first attempt to speak up until a potentially critical situation occurs. In the clinical work environment, speaking up could already be initiated explicitly during the World Health Organization (WHO) Surgical Safety Checklist–based “time out” during which the OR team has the chance to assemble and to discuss anticipated critical patient issues before skin incision.57 However, because our study only found a trend for the importance of earlier speaking up by conservative interpretation, further research is needed to draw a more robust conclusion.
Strengths and Limitations of the Study
This is a prospective observational study that directly assessed dynamic team processes instead of relying on team members’ self-reports, which provide only static snapshots.52 Through observing the actual level of speaking up and by using quantifiable markers for technical team performance, our study provides empirical results on the association between speaking up and performance. The sequential analysis of team interaction provided insights in the immediate effects of speaking up.
Our study has several limitations. First, our findings on speaking up during a simulated induction cannot be generalized to speaking-up behavior in real clinical settings. Although observations of simulated cases are a good opportunity to assess the nature of people’s behavior in environments similar to their work and to provide a certain degree of standardization, we cannot exclude that our study participants may have behaved differently if the simulated nonroutine situations had happened during real clinical intubations. For example, knowing that no real patient was potentially at risk may have influenced the participants’ motivation to speak up. Second, the correlational design does neither allow for conclusions about causal relationships between speaking up and team performance nor allow for conclusions about the preconditions for speaking up. Given that nurses were more experienced than residents and only nurses’ levels of speaking up were positively related to performance, the role of work experience as a potential precondition for effective speaking up should be explored in further studies. Third, to perform the statistical analysis reported here, we quantified speaking up as the time spent with questioning a current decision or procedure, correcting task-relevant behavior, or asking for a task-relevant clarification in relation to induction duration. Although only task-relevant behaviors were coded, some of them may have been more important than others, and some shorter speaking-up behaviors may have been more important than longer ones. Finally, the limited sample size in combination with resident participants (instead of senior anesthesiologists to whom the nurses may have been more reluctant to speak up to) may have further reduced the generalizability of our findings and prevented us from analyzing the potential causal link among speaking up, team interaction, and team performance by means of statistical mediation analysis.
Implications for Future Research
Our study offers directions for future research on speaking up. First, as we tested our hypotheses in a simulated setting, further research should investigate whether our findings can be replicated in the clinical setting, ideally including larger sample sizes from several hospitals. This would allow for relating interaction patterns to further organizational variables such as psychological safety, that is, the shared belief held by team members that they are safe for interpersonal risk taking.58 This would increase our understanding of what organizations must provide to anesthesia team members to feel at ease with speaking up. Second, interventional studies should test the effects of “trainable” speaking up on performance—also with respect to optimal amount, timing, and quality—in a simulated setting using a randomized control group design. This would allow us to draw causal conclusions on the impact of speaking up on performance. Third, the aforementioned interventional studies should be followed by comparable studies in clinical settings to examine the transferability of the respective findings into clinical practice and the impact on real patient outcomes.
CONCLUSION
We think that by providing empirical evidence for the positive association of speaking up with team performance and by showing some of the mechanisms that might explain this association, the current research contributes to the understanding of the impact of speaking up in anesthesia. We hope that our work will inspire additional research and application of speaking up to help expand its utility for patient safety.
DISCLOSURES
Name: Michaela Kolbe, PhD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Michaela Kolbe has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.
Name: Michael J. Burtscher, PhD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Michael J. Burtscher has seen the original study data, partly reviewed the analysis of the data, and approved the final manuscript.
Name: Johannes Wacker, MD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Johannes Wacker has seen the original study data and approved the final manuscript.
Name: Bastian Grande, MD.
Contribution: This author helped conduct the study.
Attestation: Bastian Grande approved the final manuscript.
Name: Renata Nohynkova, MD.
Contribution: This author helped conduct the study.
Attestation: Renata Nohynkova approved the final manuscript.
Name: Tanja Manser, PhD.
Contribution: This author helped design the study and write the manuscript.
Attestation: Tanja Manser approved the final manuscript.
Name: Donat R Spahn, MD, FRCA.
Contribution: This author helped write the manuscript.
Attestation: Donat R. Spahn approved the final manuscript.
Name: Gudela Grote, PhD.
Contribution: This author helped design the study and write the manuscript.
Attestation: Gudela Grote approved the final manuscript.
This manuscript was handled by: Sorin J. Brull, MD, FCARCSI (Hon).
CURRENT AFFILIATIONS
Michael J. Burtscher is currently affiliated with Institute of Psychology, University of Zurich, Zurich, Switzerland. Johannes Wacker is currently affiliated with Institute of Physicians for Anaesthesia and Intensive Care, Klinik Hirslanden Zurich, Zurich, Switzerland. Tanja Manser is currently affiliated with Département de Psychologie, Industrial Psychology and Human Factors, University Fribourg, Fribourg, Switzerland.
ACKNOWLEDGMENTS
We would like to thank Sonja Sollberger and Raphael Agosti for behavioral coding, and Daniel B. Raemer, PhD, Burkhardt Seifert, PhD, and Carl Schick for their helpful comments on an earlier version of this paper.
a There was no multicollinearity within our data (VIF values ranging from 1.00 to 1.032; tolerance statistics ranging from 0.969 to 1.00). The assumption of independent errors was met (value of Durbin–Watson statistic = 2.3).51
Cited Here
REFERENCES
1. Haynes AB, Weiser TG, Berry WR, Lipsitz SR, Breizat AS, Dellinger EP, Herbosa T, Joseph S, Kibatala PL, Lapitan MCM, Merry AF, Moorthy K, Reznick RK, Taylor B, Gawande AA. A surgical safety checklist to reduce morbidity and mortality in global population. N Engl J Med. 2009;360:491–9
2. de Vries EN, Prins HA, Crolla RMPH, den Outer AJ, van Andel G, van Helden SH, Schlack WS, van Putten MAs, Gouma DJ, Dijkgraaf MGW, Smorenburg SM, Boermeester MA. Effect of a comprehensive surgical safety system on patient outcomes. N Engl J Med. 2010;363:1928–37
3. Flin R, Patey R. Improving patient safety through training in non-technical skills. BMJ. 2009:339
4. Gaba DM. Anaesthesiology as a model for patient safety in health care. BMJ. 2000;320:785–88
5. Cooper JB, Blum RH, Carroll JS, Dershwitz M, Feinstein DM, Gaba DM, Morey JC, Singla AK. Differences in safety climate among hospital anesthesia departments and the effect of a realistic simulation-based training program. Anesth Analg. 2008;106:574–84
6. Manser T, Harrison TK, Gaba DM, Howard SK. Coordination patterns related to high clinical performance in a simulated anesthetic crisis. Anesth Analg. 2009;108:1606–15
7. Martinez EA, Thompson DA, Errett NA, Kim GR, Bauer L, Lubomski LH, Gurses AP, Marsteller JA, Mohit B, Goeschel CA, Pronovost PJ. High stakes and high risk: a focused qualitative review of hazards during cardiac surgery. Anesth Analg. 2011;112:1061–74
8. Sanderson PM, Watson MO, Russell WJ, Jenkins S, Liu D, Green N, Llewelyn K, Cole P, Shek V, Krupenia SS. Advanced auditory displays and head-mounted displays: advantages and disadvantages for monitoring by the distracted anesthesiologist. Anesth Analg. 2008;106:1787–97
9. Sundstrom E, de Meuse KP, Futrell D. Work teams. Applications and effectiveness. Am Psychol. 1990;45:120–33
10. Manser T. Teamwork and patient safety in dynamic domains of healthcare: a review of the literature. Acta Anaesthesiol Scand. 2009;53:143–51
11. Tschan F, Semmer NK, Hunziker PR, Marsch SCUDuffy VG. Decisive action vs. joint deliberation: different medical tasks imply different coordination requirements. In: Advances in Human Factors and Ergonomics in Healthcare. 2011 Boca Raton Taylor & Francis:191–200
12. Gawande AA, Studdert DM, Orav EJ, Brennan TA, Zinner MJ. Risk factors for retained instruments and sponges after surgery. N Engl J Med. 2003;348:229–35
13. Greenberg CC, Regenbogen SE, Studdert DM, Lipsitz SR, Rogers SO, Zinner MJ, Gawande AA. Patterns of communication breakdowns resulting in injury to surgical patients. J Am Coll Surg. 2007;204:533–40
14. Lingard L, Espin S, Whyte S, Regehr G, Baker GR, Reznick R, Bohnen J, Orser B, Doran D, Grober E. Communication failures in the operating room: an observational classification of recurrent types and effects. Qual Saf Health Care. 2004;13:330–4
15. Arbous MS, Grobee DE, van Kleef JW, de Lange JJ, Spoormans HHAJM, Touw P, Werner FM, Meursing AEE. Mortality associated with anaesthesia: a qualitative analysis to identify risk factors. Anaesthesia. 2001;56:1141–53
16. Vincent C. Understanding and responding to adverse events. N Engl J Med. 2003;348:1051–6
17. Baker DP, Salas E, Barach P, Battles J, King HCarayon P. The relation between teamwork and patient safety. In: Handbook of Human Factors and Ergonomics in Healthcare and Patient Safety. 2006 Hillsdale Erlbaum:259–71
18. Campion EW. A death at Duke. N Engl J Med. 2003;348:1083–4
19. Frankel A, Vecchio P. Commonly used, easily confused: let’s eliminate hyper and hypo. BMJ. 2010:341
20. Burtscher MJ, Manser T, Kolbe M, Grote G, Grande B, Spahn DR, Wacker J. Adaptation in anaesthesia team coordination in response to a simulated critical event and its relationship to clinical performance. Br J Anaesth. 2011;10:801–6
21. Edmondson AC. Speaking up in the operating room: how team leaders promote learning in interdisciplinary action teams. J Manage Studies. 2003;40:1419–52
22. Nagpal K, Vats A, Lamb B, Ashrafan H, Sevdalis N, Vincent C, Moorthy K. Information transfer and communication in surgery. A systematic review. Ann Surg. 2010;252:225–39
23. Williams AL, Lasky RE, Dannemiller JL, Andrei AM, Thomas EJ. Teamwork behaviours and errors during neonatal resuscitation. Qual Saf Health Care. 2010;19:60–4
24. Cooper JB, Newbower RS, Long CD, McPeek B. Preventable anesthesia mishaps: a study of human factors. Qual Saf Health Care. 2002;11:277–83
25. Reynard J, Reynolds J, Stevenson P. Practical patient safety. 2009 Oxford Oxford University Press
26. Jentsch F, Smith-Jentsch KASalas E, Bowers CA, Edens E. Assertiveness and team performance: more than “just say no.” In: Improving Teamwork in Organizations. Applications of Resource Management Training. 2001 Mahwah, NJ Erlbaum:73–94
27. Ginnett RCWiener EL, Kanki BG, Helmreich RL. Crews as groups: their formation and their leadership. In: Cockpit Resource Management. 1993 San Diego, CA Academic Press:71–98
28. Morrison EW, Milliken FJ. Speaking up, remaining silent: the dynamics of voice and silence in organizations. J Manage Studies. 2003;40:1353–8
29. National Transportation Safety Board. . A review of flightcrew-involved, major accidents of U.S. air carriers, 1978 through 1990 (Safety Study NTSB/SS-94/01). 1994 Washington, DC
30. Morrison EW. Employee voice behavior: integration and directions for future research. Acad Manag Ann. 2011;5:373–412
31. Dwyer J. Primum non tacere. An ethics of speaking up. Hastings Cent Rep. 1994;24:13–8
32. Henriksen K, Dayton E. Organizational silence and hidden threats to patient safety. Health Serv Res. 2006;41:1539–54
33. Weinger MB, Slagle J. Human factors research in anesthesia patient safety: techniques to elucidate factors affecting clinical task performance and decision making. J Am Inform Assoc. 2002;9:S58–63
34. Sexton JB, Thomas EJ, Helmreich RL. Error, stress, and teamwork in medicine and aviation: cross sectional surveys. BMJ. 2000;320:745–9
35. Kobayashi H, Pian-Smith M, Sato M, Sawa R, Takeshita T, Raemer D. A cross-cultural survey of residents’ perceived barriers in questioning/challenging authority. Qual Saf Health Care. 2006;15:277–83
36. Pian-Smith MCM, Simon R, Minehart RD, Podraza M, Rudolph J, Walzer T, Raemer D. Teaching residents the Two-Challenge Rule: a simulation-based approach to improve education and patient safety. Simul Healthcare. 2009;4:84–91
37. Burtscher MJ, Wacker J, Grote G, Manser T. Managing non-routine events in anesthesia: the role of adaptive coordination. Hum Factors. 2010;52:282–94
38. Künzle B, Zala-Mezö E, Wacker J, Kolbe M, Grote G. Leadership in anaesthesia teams: the most effective leadership is shared. Qual Saf Health Care. 2010;19:1–6
39. Bowen F, Blackmon K. Spirals of silence: the dynamics of diversity on organizational voice. J Manage Studies. 2003;40:1393–417
40. Wacker J, Kleeb B, Künzle B, Leisinger E, Kobler A, Kolbe M, Manser T, Burtscher M, Spahn DR, Grote G. High incidence of non-routine events during standard anesthesia inductions: a prospective analysis of synchronized video and vital parameter recordings. Abstract presented at the Annual Conference of the Swiss Society of Anaesthesiology and Reanimation, Fribourg, Switzerland, 2008. Swiss Med Wkly 2008;138(suppl 166):9S
41. Faul F, Erdfelder E, Lang A-G, Buchner A. G*Power 3: a flexible statistical power program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;41:175–91
42. Kolbe M, Burtscher M, Manser T. CoMeT: analyzing communication to understand how healthcare action teams coordinate. Paper presented at the 5th International Workshop on Behavioural Science Applied to Acute Care Teams. 2011 Zurich, Switzerland
43. Landis JR, Koch GG. The measurement of observers agreement for categorial data. Biometrics. 1977;33:159–74
44. Burtscher MJ, Kolbe M, Wacker J, Manser T. Interactions of team mental models and monitoring behaviors predict team performance in simulated anesthesia inductions. J Exp Psychol Appl. 2011;17:257–69
45. Scavone BM, Sproviero MT, McCarthy RJ, Wong CA, Sullivan JT, Siddall VJ, Wade LD. Development of an objective scoring system for measurement of resident performance on the human patient simulator. Anesthesiology. 2006;105:260–6
46. Forrest FC, Taylor MA, Postlethwaite K, Aspinall R. Use of a high-fidelity simulator to develop testing of the technical performance of novice anaesthetists. Br J Anaesth. 2002;88:338–44
47. Donoghue A, Nishisaki A, Sutton R, Hales R, Boulet J. Reliability and validity of a scoring instrument for clinical performance during Pediatric Advanced Life Support simulation scenarios. Resuscitation. 2010;81:331–6
48. Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med. 1998;26:217–38
49. Fleiss JL. Statistical methods for rates and proportions. 19812nd ed New York Wiley
50. Bakeman R, Gottman JM. Observing Interaction: An Introduction to Sequential Analysis. 1986 Cambridge Cambridge University Press
51. Field A. Discovering Statistics Using SPSS. 20052nd ed London, UK Sage
52. Weingart LR. How did they do that? The ways and means of studying group process. Res Organ Behav. 1997;19:189–239
53. Detert JR, Trevino LK. Speaking up to higher-ups: how supervisors and skip-level leaders influence employee voice. Organ Sci. 2010;21:249–70
54. Detert JR, Edmondson A. Implicit voice theories: taken-for-granted rules of self-censorship at work. Acad Manage J. 2011;54:461–88
55. Morrison EW, Wheeler-Smith S, Kamdar D. Speaking up in groups: a cross-level study of group voice climate and voice. J Appl Psychol. 2011;96:183–91
56. Kolbe M, Künzle B, Zala-Mezö E, Burtscher MJ, Wacker J, Spahn DR, Grote G.. The functions of team monitoring, and ’talking to the room’ for performance in anesthesia teams. In: Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting.. 2010 Santa Monica, CA Human Factors and Ergonomics Society:857–61
57. World Alliance for Patient Safety. . World Health Organizations Surgical Safety Checklist. 20081st ed Geneva World Health Organizations
58. Edmondson A. Psychological safety and learning behavior in work teams. Adm Sci Q. 1999;44:350–83
