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Interprofessional teamwork among students in simulated codes: a quasi-experimental study.


AIM The purpose of this study was to evaluate the efficacy of using crisis resource management (CRM) principles and high-fidelity human patient simulation (HFHPS) for interprofessional (IP) team training of students from undergraduate nursing, nurse anesthesia, medical, and respiratory therapy.

BACKGROUND IP education using simulation-based training has the potential to transform education by improving teamwork and communication and breaking down silos in education.

METHOD This one-year study used a quasi-experimental design to evaluate students' acquisition and retention of teamwork and communication skills. A convenience sample consisted of 52 students in the fall semester, with 40 students returning in the spring.

RESULTS Mean scores increased after training, and skills were retained fairly well. Any loss was regained with repeat training in the spring.

CONCLUSION The results suggest that using CRM and HFHPS is an effective pedagogy for teaching communication and teamwork skills to IP student teams.


When interprofessional (IP) communication fails in health care, it often results from team members' fears of appearing incompetent or of being embarrassed or reprimanded (Reader, Flin, Mearns, & Cuthbertson, 2007). Traditionally, education in nursing, medicine, and the allied health professions has involved didactic, clinical, and simulation activities that take place separately. Recently, the importance of IP education, specifically in the areas of teamwork and communication, has been emphasized by, among others, the Institute of Medicine (IOM) in the Future of Nursing report (2011), the Joint Commission (2013), the National League for Nursing (2013), and the American Association of Colleges of Nursing (2013).

Many health care professions have used simulation to teach technical as well as communication skills. Crisis-resource management (CRM) training involves four categories of behavioral markers: communication, leadership, situational awareness, and decision-making. We sought to evaluate the use of CRM principles in IP education through the use of high-fidelity simulation with teams of students from various schools within a health sciences center.


Although seen as an essential element of patient safety, teamwork is often less than ideal. From the intensive care unit (Thomas, Sexton, & Helmreich, 2003) to the operating room (Carney, West, Nelly, Mills, & Bagian, 2010), physicians and nurses hold diverging views on the quality of communication and collaboration among team members. Too often, IP teams are plagued by poor team interaction (Sexton, Thomas, & Helmreich, 2000), communication breakdowns (Lingard et al., 2004), and role confusion (Donohue & Endacott, 2010). Even with the increasing awareness of these deficiencies among health care teams, they persist (Halverson et al., 2011; Wauben et al., 2011).

Given the link between well-functioning teams and "high-reliability organizations" (those with exceptional safety records) (Wilson, Burke, Priest, & Salas, 2005), improving team function in health care has become a priority. The IOM identified IP teamwork as a core competency for all health care providers in 2003 and further delineated the importance of teamwork and IP education in their 2011 report. An expert panel from six professional organizations, including nursing, medicine, dental, public health, pharmacy, and osteopathic medicine, established core competencies for IP collaborative practice, of which teamwork and communication are two of the four competency domains that students learn from pre-licensure through practice (Interprofessional Education Collaborative, 2011). Miller, Crandall, and McLaughlin (2012) stated that failure of teamwork and communication are important factors in adverse events highlighted by IOM reports. Effective communication is a key component of patient safety (Aebersold, Tschannen, & Sculli, 2013; Kilner & Sheppard, 2010; Liaw, Zhou, Lau, Siau, & Chan (in press). Ineffective communication is the root cause of medical errors (Aebersold et al.; Brock et al., 2013). The Joint Commission (2013) ranked ineffective communication between the first and third leading cause for most sentinel events through 2012.

A poor work culture can contribute to team dysfunction in health care. Frequently, this culture is characterized by friction between professions and the "silo mentality" (Bleakley, Boyden, Hobbs, Walsh, & Allard, 2006). As a result, team members tend to favor multiprofessional rather than IP interaction (Bleakley et al.). Also, hierarchical educational and professional structures can stunt communication and hamper collaboration (Haldet & Stein, 2006), possibly exerting a subtle but powerful influence on students in clinical rotations and perpetuating poor collaboration.

Counteracting such influence remains a challenge to educators. The Lucian Leape Institute, a think tank within the National Patient Safety Foundation, has called for IP education using simulation-based training to give students the skills for effective teamwork and to spur health care redesign (Leape et al., 2009). Such an approach has many attractions. First, simulation-based training allows students to transfer what they have learned to the clinical environment (Fernandez et al., 2008; Fisher & King, 2013). Second, team training promotes highly reliable team functioning and, in doing so, can potentially affect client care and patient safety (Stevens et al., 2012; Wilson et al., 2005). Finally, when high-fidelity techniques are employed, simulation-based training gives students a realistic, safe environment to encounter high-risk situations and to learn from their errors (Fisher & King; Hobgood et al., 2010).

Although the use of high-fidelity simulation-based training in IP education has been shown to improve students' attitudes about teamwork (Dillon, Noble, & Kaplan, 2009; Fisher & King, 2013; Hobgood et al., 2010), few studies have evaluated both the acquisition and retention of team-based skills over time (e.g., Garbee et al., 2013; Miller et al., 2012). This study investigates this issue using an emergency room code scenario to train IP student teams over the course of an academic year.


A quasi-experimental design was used to evaluate teamwork and communication skills of health care students on an IP team in a high-fidelity simulation. This design was selected to allow all students an opportunity to participate in the learning activity, instead of having some excluded due to randomization. All students received the same educational interventions and evaluation. Institutional review board (IRB) approval was obtained by expedited review with waiver of informed consent.


Study participants were selected from a convenience sample of undergraduate baccalaureate students in nursing and respiratory therapy, and graduate-level nurse anesthesia and medical students. All students attended the same health sciences center in the southeastern United States. Students volunteered after a recruitment email was sent to all eligible student groups. On the day of the simulation, two graduate nurse anesthesia students distributed and read an IRB-approved statement containing elements of informed consent. Students were given the option to opt out of photographs, videos, and/or the research portion of the educational activity. They were required to complete the evaluation tools. A total of 52 students participated in the fall of 2009, with 40 students returning in spring 2010.


Tools used to measure team performance included the Communication and Teamwork Skills (CATS) assessment instrument, designed to measure health care team performance (Frankel, Gardner, Maynard, & Kelly, 2007); the Teamwork Assessment Scale (TAS), a modification of a previously employed Operating Room Teamwork Assessment Scale (ORTAS) having both a multisource and overall team-based evaluative component (Paige, Aaron, Yang, Howell, & Chauvin, 2009); and the Mayo High Performance Teamwork Scale (MHPTS), designed to measure and evaluate team CRM skills (Malec et al., 2007).

The CATS tool has a weighted scoring system for 18 observed behaviors. The behaviors fall into the categories of Coordination, Cooperation, Communication (seven behaviors each), and Situational Awareness (two behaviors). Trained observers mark each time specific behaviors occur and grade their quality. Behaviors are rated as observed and good = 1, variation in quality = 0.5, and expected but not observed = 0. A score is then calculated for each subscale adjusted to a 100-point scale. The CATS has high inter-rater reliability scores: global Team Performance Assessment intraclass correlation = 0.84 for four judges and total CATS score intraclass correlation = 0.73 for four judges (Gardner, 2010). Further, correlation between total and global scores indicated concurrent validity. The TAS was successfully used as a 360-degree teamwork assessment scale with research in a clinical setting using CRM and IP team training at a rural clinical site (Paige et al., 2008); it was found to have face validity and content validity and underwent validation through factor analysis (Paige et al., 2009). In addition, it demonstrated a degree of convergent validity as a multisource evaluative instrument and observation tool in an IP student team-training setting (Garbee et al., 2013).

The TAS has three subscales that evaluate team-based behavior (TBB), shared mental model (SMM), and adaptive communication and response (ACR). TBBs get a 360-degree evaluation of each participant and member of the team. The subscales measure teamwork competencies such as communication, role clarity, flattened hierarchy, mental rehearsal, situational awareness, cross-monitoring, resource management, shared mental model (often referred to as "on the same page" in a situation), and anticipatory response (Paige et al., 2009). All items are scored on a six-point Likert-type scale, with scores ranging from 1 (definitely no) to 6 (definitely yes). The TAS rates team interactions and individual performance by specialty (physician, nurse anesthetist, nurse, and respiratory therapist).

The MHPTS consists of 18 items; the first eight items are team qualities and are scored as 0 = never or rarely, 1 = inconsistently, or 3 = consistently; the remaining items are crisis situations that may occur during the simulation. According to Malec et al. (2007), MHPTS showed satisfactory internal consistency and construct validity by Rasch (person reliability = .77; person separation = 1.85; item reliability =.96; item separation = 5.04) and traditional psychometric indicators (Cronbach's alpha = .85).

Data Collection

In the fall, IP teams that included at least one but not more than two students from each professional program participated in two high-fidelity simulations of code scenarios set in an emergency room (Scenario 1, unstable atrial fibrillation; Scenario 2, tension pneumothorax). Each scenario began with nursing students receiving a report on the "patient." When the patient's condition deteriorated, students sought help as appropriate from respiratory therapy, medical, or anesthesia students. During simulations, trained observers scored performance using the CATS and the TAS. At the end of each simulation, participants rated overall team performance using the TAS and the MHPTS. A structured debriefing then followed that stimulated reflection on teamwork and communication and served as training in these skills. The second scenario was conducted using the same format. These same procedures were followed in the spring.

Data Analyses

The data were analyzed using the Statistical Package for the Social Sciences (SPSS) 17.0. The three outcome variables analyzed were teamwork as measured by trained observers using the CATS and the TAS, teamwork as measured by student self-report using the TAS and the MHPTS (comparing performance on the first and second scenarios), and retention of teamwork and communication skills as measured by CATS, TAS, and MHPTS scores (comparing spring and fall session scores). Descriptive statistics were used for demographic data. Paired samples t-tests were calculated to compare mean scores between scenarios. The statistical significance was set at p < .05.


The convenience sample consisted of fourth-year medical students, senior nurse anesthesia students, senior undergraduate nursing students, and junior respiratory therapy students. There were 52 participants in the fall semester, with 40 participants returning in the spring. The majority of participants in the fall semester were female (n = 34, 65.4 percent), white (n = 39, 75 percent), and from either the undergraduate nursing or the nurse anesthetist program (n = 28, 53.8 percent); other races and ethnicities represented were Asian (n = 7, 13.5 percent), African American (n = 3, 5.8 percent), Hispanic/Latino (n = 3, 5.7 percent). Medical students accounted for 21 percent of participants (n = 11); respiratory therapy students accounted for 25 percent (n = 13). Although some participants did not return for the spring simulations, demographics remained similar, with the exception of medical students, who decreased to 17 percent (n = 7).

Mean scores on the TAS and the MHPTS were compared using paired samples t-tests (Table 1). Significant increases were found in the fall from Scenario 1 to Scenario 2 in TBB, t(857) = -14.07, p < .05; SMM, t(154) = -8.64, p < .05; and ACR, t(155) - -9.60, p < .05). Mean scores on the MHPTS also showed a significant increase, t(43) = -4.87, p < .05).

In the spring, the mean student scores showed significant increases from Scenario 1 to Scenario 2 in TAS subscales of TBB, t(671) = -8.84, p < .05, and SMM, t(116) = -2.12, p < .05. Mean scores increased on ACR, though not significantly: t(116) = -1.70, p > .05. Analysis of mean MHPTS scores also showed a significant increase in the spring, t(38) = -4.17, p < .05.

A comparison of fall observer data using paired samples t-tests revealed significant increases in scores from the first to the second scenario on TBB, t(256) = -31.32, p < .05, and significant increases in scores on SMM, t(155) = -26.22, p < .05, and ACR, t(155) = -29.25, p < .05. Also, from Scenario 1 to Scenario 2, mean scores on the CATS increased significantly in all four subscales: Coordination, Situational Awareness, Cooperation, and Communication. Similarly, to compare mean TAS and CATS scores, paired samples t-tests were calculated on observer data for the spring semester. From Scenario 1 to Scenario 2, a significant increase was found on TBB, t(193) = -19.60, p < .05, as well as SMM, t(65) = -6.82, p < .05, and ACR, t(64) = -5.04, p < .05. Although mean scores on the CATS increased in all subscales, only the mean scores on Situational Awareness and Cooperation showed a significant difference.

To assess retention from the fall to spring semester, paired samples t-tests were calculated on participant and observer mean scores for Scenario 2 in the fail to Scenario 1 in the spring. Although participant mean scores decreased slightly in the spring, only mean scores on TBB showed a significant difference, t(684) = 5.64, p < .05 (Table 1). Similarly, a significant decrease in mean observer scores was found for TBB, (192) = 3.35, p < .05, as well as SMM, t(82) = 3.42, p < .05, and ACR, t(81) = 5.78, p < .05 (Table 2). Further, mean CATS scores on Coordination and Cooperation were higher in the spring on Scenario 1 than in the fall on Scenario 2, while Situational Awareness and Communication scores showed decreases, with the largest loss in Communication. Nonetheless, the CATS mean observer scores for Scenario 1 in the spring were not significantly different than scores in the fail on Scenario 2 (p > .05) (Table 2).

To assess overall gain from training in the fall and spring semesters, paired samples t-tests were calculated to compare mean scores for Scenario 1 (fall) and Scenario 2 (spring). Significant increases were found in participant scores on TBB, SMM, ACR, and MHPTS (p < .05) and observer scores on TBB, SMM, ACR, and all subscales of CATS (p < .05).


Participant and observer scores showed significant improvements in the areas of TBB, SMM, and ACR. Observer mean scores showed improvement in Communication, Cooperation, Coordination, and Situational Awareness during the study, with only small losses in skill retention during the five months between sinmlations in the fall and the spring. These findings support those of other studies in the use of high-fidelity simulation in IP education (Bender & Buckner, 2005; Dillon et al., 2009; Issenberg, McGahie, Petrusa, Gordon, & Scales, 2005; Leighton & Scholl, 2009; Miller et al., 2012; Worzala, Glaser, & McGinley, 2006).

This study involved four preprofessional student groups from a health sciences center, offering unique insights on IP interaction. Many IP studies use only two student groups, mainly medicine and nursing (Dillon et al., 2009; Hobgood et al., 2010: Robertson et al., 2010; Worzala et al., 2006). Although different assessment instruments were used, studies have found significant improvements in team collaboration (Aebersold et al., 2013: Dillon et al., 2009; Kilner & Sheppard, 2010: Liaw et al., in press; Worzala et al., 2006), attitudes and knowledge (Hobgood et al., 2010; Robertson et al., 2010), and recognition of quality team skills in video vignettes (Robertson et al.).


Our small sample size and the attrition due to scheduling conflicts seen between semesters limit the generalizability of our findings. Dillon et al. (2009) and Worzala et al. (2006) reported small sample sizes that highlighted the difficulty in scheduling between the different professional schools, which was a challenge in our study as well. Worzala and colleagues reported attrition between pretest and posttest, losing half of student participants.

Larger sample sizes were achieved with all-day team training (Hobgood et al., 2010; Robertson et al., 2010) and involvement of students from two universities (Hobgood et al.). However, Robertson and colleagues used 40 facilitators for team training, whereas our team training consisted of seven faculty for observation and debriefing.


This study adds to the literature on the feasibility and efficacy of simulation-based training with students in four professional programs. It is significant for IP education that medical, nursing, nurse anesthesia, and respiratory therapy students worked together in a patient crisis and valued the contributions of each profession. The findings suggest that a CRM model of IP team training can be utilized with preprofessional students in high-fidelity simulation of patients in code scenarios. Also, the findings suggest the benefit of repeat team training.

Enhancing quality and safety in health care is a complex goal. Use of high-fidelity simulations creates a realistic environment for teaching IP teamwork and communication skills. These methods overcome the silo effect and develop a better understanding of the roles of each team member. Although new skills can be quickly learned in a simulated environment, repeated experiences are needed to produce steady changes in behavior and attitude.


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The authors are affiliated with Louisiana State University Health Sciences Center, New Orleans. Deborah D. Garbee, PhD, APRN, ACNS-BC, is an adult health clinical nurse specialist. John Z Paige MD, is a general surgeon and director, American College of Surgeons Accredited Education Institute LSUHSC-NO School of Medicine Learning Center. Kendra Barrier MSN, RN, # a nurse educator, Valeriy, V. Kozmenko, MD, is a resident in anesthesiology. Lyubov Kozmenko, BSN, RN, is a simulation lab instructor. John B. Zamjahn, PhD, RRT, is a respiratory, therapist. Laura Bonanno, DNP. CRNA, is a nurse anesthetist. Jean E. Cefalu, MSN, APRN, ANP-C, GNP-C. CWOCN, CFCN, is an adult-gerontology nurse practitioner. The authors are grateful to the NLN for funding support of this study, withh a 2009 NLN Nursing Education Research Grant. They thank Kaycee Keller, CRNA, and Claire Fahre, CRNA, for assistance with data collection, and Joseph Hagan, ScD, MSPH, for assitance with data analysis. For more information, contact Dr. Garbee at
Table 1: Participant Mean Scores

Instrument Subscale M [+ or -] SD M [+ or -] SD

 Fall 2009 Fall 2009
 Scenario 1 Scenario 2

TAS TBB 4.84 [+ or -] 1.13 5.45 [+ or -] 0.67
 SMM 4.56 [+ or -] 1.17 5.37 [+ or -] 0.60
 ACR 4.09 [+ or -] 1.41 5.25 [+ or -] 0.77
MHPTS N/A 19.98 [+ or -] 5.01 25.36 [+ or -] 4.65

 Spring 2010 Spring 2010
 Scenario 1 Scenario 2

TAS TB13 5.22 [+ or -] 0.87 5.58 [+ or -] 0.65
 SMM 5.23 [+ or -] 0.81 5.41 [+ or -] 0.68
 ACR 5.18 [+ or -] 0.94 5.35 [+ or -] 0.83
MHPTS N/A 22.95 [+ or -] 6.16 26.69 [+ or -] 4.80

 Fall 2009 Spring 2010
 Scenario 2 Scenario 1

TAS TBB 5.45 [+ or -] 0.64 5.22 [+ or -] 0.87
 SMM 5.38 [+ or -] 0.58 5.23 [+ or -] 0.81
 ACR 5.32 [+ or -] 0.69 5.18 [+ or -] 0.94
MHPTS N/A 25.21 [+ or -] 4.67 22.95 [+ or -] 6.16

 Score p
Instrument Subscale Change Value

TAS TBB 0.61 *
 SMM 0.81 *
 ACR 1.16 *
MHPTS N/A 5.38 *

TAS TB13 0.36 *
 SMM 0.18 *
 ACR 0.17 NS
MHPTS N/A 3.74 *

TAS TBB -0.23 *
 SMM -0.15 NS
 ACR -0.14 NS
MHPTS N/A -2.26 NS

Note: ACR = Adaptive Communication and Response, M = Mean, MHPTS =
Mayo High Performance Teamwork Scale, NS = not significant, SD =
Standard Deviation, SMM = Shared Mental Model, TAS = Modified
Operating Room Teamwork Assessment Scale, TBB = Team-Based
Behaviors. * p = <.05.

Table 2: Observer Mean Scores Evaluating Retention

Instrument Subscale M [+ or -] SD

 Fall 2009
 Scenario 2

TAS TBB 4.39 [+ or -] 0.44

 SMM 4.61 [+ or -] 0.32

 ACR 4.71 [+ or -] 0.26

CATS Coordination 19.98 [+ or -] 5.01

 Situational 92.38 [+ or -] 9.93

 Cooperation 89.14 [+ or -] 9.00

 Communication 91.22 [+ or -] 10.28

 Score p
Instrument Subscale M [+ or -] SD Change Value

 Spring 2010
 Scenario 1

TAS TBB 4.24 [+ or -] 0.50 -0.15 *

 SMM 4.18 [+ or -] 1.03 -0.43 *

 ACR 3.96 [+ or -] 1.13 -0.75 *

CATS Coordination 25.36 [+ or -] 4.65 6.40 NS

 Situational 91.85 [+ or -] 10.54 -0.53 NS

 Cooperation 91.10 [+ or -] 10.40 1.96 NS

 Communication 85.36 [+ or -] 13.16 -5.86 NS

Note: ACR =Adaptive Communication and Response, CATS =
Communication and Teamwork Scale, M = Mean, NS = not significant,
SD = Standard Deviation, SMM = Shared Mental Model, TAS = Modified
Operating Room Teamwork Assessment Scale, TBB = Team-Based
Behaviors. * p = <.05.
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Author:Garbee, Deborah D.; Paige, John; Barrier, Kendra; Kozmenko, Valeriy; Kozmenko, Lyubov; Zamjahn, John
Publication:Nursing Education Perspectives
Article Type:Report
Date:Sep 1, 2013
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