Megan E. Gregory

Saving lives: A meta-analysis of team training in healthcare.

As the nature of work becomes more complex, teams have become necessary to ensure effective functioning within organizations. The healthcare industry is no exception. As such, the prevalence of training interventions designed to optimize teamwork in this industry has increased substantially over the last 10 years (Weaver, Dy, & Rosen, 2014). Using Kirkpatricks (1956, 1996) training evaluation framework, we conducted a meta-analytic examination of healthcare team training to quantify its effectiveness and understand the conditions under which it is most successful. Results demonstrate that healthcare team training improves each of Kirkpatricks criteria (reactions, learning, transfer, results; d = .37 to .89). Second, findings indicate that healthcare team training is largely robust to trainee composition, training strategy, and characteristics of the work environment, with the only exception being the reduced effectiveness of team training programs that involve feedback. As a tertiary goal, we proposed and found empirical support for a sequential model of healthcare team training where team training affects results via learning, which leads to transfer, which increases results. We find support for this sequential model in the healthcare industry (i.e., the current meta-analysis) and in training across all industries (i.e., using meta-analytic estimates from Arthur, Bennett, Edens, & Bell, 2003), suggesting the sequential benefits of training are not unique to medical teams. Ultimately, this meta-analysis supports the expanded use of team training and points toward recommendations for optimizing its effectiveness within healthcare settings. (PsycINFO Database Record

The cognitive underpinnings of adaptive team performance in ill-defined task situations A closer look at team cognition

As the nature of work changes due to technology, organizational restructuring, and globalization, complex tasks have emerged that necessitate the use of teams. Oftentimes, teams complete tasks that have more than one plausible solution or engage in performance episodes under uncertain circumstances. Therefore, teams are called upon to be highly adaptable to these ill-defined tasks by responding to continuous changes in the task environment. We propose that dimensions of team cognition (i.e., shared mental models and transactive memory systems) help drive adaptation. In recognition of the additional cognitive demands placed upon teams who must be highly adaptable, we believe much can be gained from taking a closer look at the facets of team-level cognitive variables. The current effort aims to provide a more comprehensive explanation of emergent cognitive states, and how they interact to drive adaptive team performance, especially within the context of ill-defined problems.

Enhancing the Effectiveness of Team Debriefings in Medical Simulation: More Best Practices

BACKGROUND Teamwork is a vital component of optimal patient care. In both clinical settings and medical education, a variety of approaches are used for the development of teamwork skills. Yet, for team members to receive the full educational benefit of these experiential learning opportunities, postsimulation feedback regarding the teams performance must be incorporated. Debriefings are among the most widely used form of feedback regarding team performance. A team debriefing is a facilitated or guided dialogue that takes place between team members following an action period to review and reflect on team performance. Team members discuss their perceptions of what occurred, why it occurred, and how they can enhance their performance. Simulation debriefing allows for greater control and planning than are logistically feasible for on-the-job performance. It is also unique in that facilitators of simulation-based training are generally individuals external to the team, whereas debriefing on the job is commonly led by an internal team member or conducted without a specified facilitator. Consequently, there is greater opportunity for selecting and training facilitators for team simulation events. Thirteen Best Practices: The 13 best practices, extracted from existing training and debriefing research, are organized under three general categories: (1) preparing for debriefing, (2) facilitator responsibilities during debriefing, and (3) considerations for debriefing content. For each best practice, considerations and practical implications are provided to facilitate the implementation of the recommended practices. CONCLUSION The 13 best practices presented in this article should help health care organizations by guiding team simulation administrators, self-directed medical teams, and debriefing facilitators in the optimization of debriefing to support learning for all team members.

A Systematic Review of Team Training in Health Care: Ten Questions

BACKGROUND As a result of the recent proliferation of health care team training (HTT), there was a need to update previous systematic reviews examining the underlying structure driving team training initiatives. METHODS This investigation was guided by 10 research questions. A literature search identified 197 empirical samples detailing the evaluation of team training programs within the health care context; 1,764 measures of HTT effectiveness were identified within these samples. Trained coders extracted information related to study design and training development, implementation, and evaluation to calculate percentages detailing the prevalence of certain training features. RESULTS HTT was rarely informed by a training needs analysis (k = 47, 23.9%) and most commonly addressed communication strategies (k = 167, 84.8%). HTT programs that incorporated practice (k = 163, 82.7%) often employed high-fidelity patient simulators (k = 38, 25.2%) and provided participants with feedback opportunities (k = 107, 65.6%). Participants were typically practicing clinicians (k = 154, 78.2%) with a lower prevalence of health care students (k = 35, 17.8). Evaluations primarily relied on repeated measures designs (k = 123, 62.4%) and self-reported data (k = 1,257, 71.3%). Additional trends were identified and are discussed. CONCLUSIONS Many trends in HTT practice and evaluation were identified. The results of this review suggested that, in the literature, HTT programs are more frequently following recommendations for training design and implementation (for example, providing feedback) in comparison to findings from previous reviews. However, there were still many areas in which improvement could be achieved to improve patient care.

Utilizing telemedicine in the trauma intensive care unit: does it impact teamwork?

BACKGROUND The aim of this study was to examine the impact of a telemedical robot on trauma intensive care unit (TICU) clinician teamwork (i.e., team attitudes, behaviors, and cognitions) during patient rounds. MATERIALS AND METHODS Thirty-two healthcare providers who conduct rounds volunteered to take surveys assessing teamwork attitudes and cognitions at three time periods: (1) the onset of the study, (2) the end of the 30-day control period, and (3) the end of the 30-day experimental period, which immediately followed the control period. Rounds were recorded throughout the 30-day control period and 30-day experimental period to observe provider behaviors. For the initial 30 days, there was no access to telemedicine. For the final 30 days, the rounding healthcare providers had access to the RP-7 robot (Intouch Health Inc., Santa Barbara, CA), a telemedical tool that can facilitate patient rounds conducted away from bedside. RESULTS Using a one-tailed, one-way repeated-measures analysis of variance (ANOVA) to compare trust at Times 1, 2, and 3, there was no significant effect on trust: F(2, 14)=1.20, p=0.16. When a one-tailed, one-way repeated-measures ANOVA to compare transactive memory systems (TMS) at Times 1, 2, and 3 was conducted, there was no significant effect on TMS: F(2, 15)=1.33, p=0.15. We conducted a one-tailed, one-way repeated-measures ANOVA to compare team psychological safety at Times 1, 2, and 3, and there was no significant effect on team psychological safety: F(2,15)=1.53, p=0.12. There was a significant difference in communication between rounds with and without telemedicine [t(25)=-1.76, p<0.05], such that there was more task-based communication during telerounds. Telemedicine increased task-based communication and did not negatively impact team trust, psychological safety, or TMS during rounds. CONCLUSIONS Telemedicine may offer advantages for some teamwork competencies without sacrificing the efficacy of others and may be adopted by intact rounding teams without hindering teamwork.

Bringing the Science of Team Training to School-Based Teams.

Teams are ubiquitous in schools in the 21st Century; yet training for effective teaming within these settings has lagged behind. The authors of this article developed 5 modules, grounded in the science of team training and adapted from an evidence-based curriculum used in medical settings called TeamSTEPPS®, to prepare instructional and administrative personnel for teamwork and to enhance their teamwork skills. The resulting 5 modules, available for download on the American Psychological Association website, are collectively called Teach Teamwork and include: Introduction to Teams and Teamwork, Communication, Mutual Support, Situation Monitoring, and Leadership. In this article, the modules and supplemental materials are described, along with recommendations for implementation.

Evaluation of a Distance Learning Curriculum for Interprofessional Quality Improvement Leaders

As health care systems move toward value-based care, training future leaders in quality improvement (QI) is essential. Web-based training allows for broad dissemination of QI knowledge to geographically distributed learners. The authors conducted a longitudinal evaluation of a structured, synchronous web-based, advanced QI curriculum that facilitated engagement and real-time feedback. Learners (n = 54) were satisfied (overall satisfaction; M = 3.31/4.00), and there were improvements in cognitive (immediate QI knowledge tests; P = .02), affective (self-efficacy of QI skills; P < .001), and skill-based learning (Quality Improvement Knowledge Application Tool; P < .001). There was significant improvement in affective transfer (interprofessional attitudes on the job; p < .01) but no significant change on cognitive (distal QI knowledge test; P = .91), or skill-based transfer (self-reported interprofessional collaboration job skills; P = .23). The findings suggest that this model can be effective to train geographically distributed future QI leaders.

Chapter 13 Disaster and Response in Emergency Medical Services: Team Training to the Rescue

Resilience has always been a critical property of all human (and most other “live”) systems, but its more recent use in the safety literature has brought an old term to a new understanding. As such, this newer usage has the potential to be more insightful and, thus, more useful when trying to understand accident causation. Prior to the relatively new concepts of the new view of human error and how organizations and people are resilient to failure, investigators relied on a blame-and-train-type 204mentality. That is, actors at the sharp end, being the last ones involved, are blamed for the event and are retrained, so they will perform better next time. However, more frequently, the actors at the sharp end are either fired and/or prosecuted, which further represents a strictly old view mentality.

Teammate Familiarity, Teamwork, and Risk of Workplace Injury in Emergency Medical Services Teams

Introduction: Increased teammate familiarity in emergency medical services (EMS) promotes development of positive teamwork and protects against workplace injury. Methods: Measures were collected using archival shift records, workplace injury data, and cross‐sectional surveys from a nationally representative sample of 14 EMS agencies employing paramedics, prehospital nurses, and other EMS clinicians. One thousand EMS clinicians were selected at random to complete a teamwork survey for each of their recent partnerships and tested the hypothesized role of teamwork as a mediator in the relationship between teammate familiarity and injury with the PROCESS macro. Results: We received 2566 completed surveys from 333 clinicians, of which 297 were retained. Mean participation was 40.5% (standard deviation [SD] = 20.5%) across EMS agencies. Survey respondents were primarily white (93.8%), male (67.3%), and ranged between 21‐62 years of age (M = 37.4, SD = 9.7). Seventeen percent were prehospital nurses. Respondents worked a mean of 3 shifts with recent teammates in the 8 weeks preceding the survey (M = 3.06, SD = 4.4). We examined data at the team level, which suggest positive views of teamwork (M = 5.92, SD = 0.69). Our hypothesis that increased teammate familiarity protects against adverse safety outcomes through development of positive teamwork was not supported. Teamwork factor Partner Adaptability and Backup Behavior is a likely mediator (odds ratio = 1.03, P = .05). When dyad familiarity is high and there are high levels of backup behavior, the likelihood of injury is increased. Discussion: The relationship between teammate familiarity and outcomes is complex. Teammate adaptation and backup behavior is a likely mediator of this relationship in EMS teams with greater familiarity.

Decision Making on the Labor and Delivery Unit: An Investigation of Influencing Factors:

Objective The aim of this study was to describe the relationship between negative affect (NA), decision-making style, time stress, and decision quality in health care. Background Health care providers must often make swift, high-stakes decisions. Influencing factors of the decision-making process in this context have been understudied. Method Within a sample of labor and delivery nurses, physicians, and allied personnel, we used self-report measures to examine the impact of trait factors, including NA, decision-making style, and perceived time stress, on decision quality in a situational judgment test (Study 1). In Study 2, we observed the influence of state NA, state decision-making style, state time stress, and their relationship with decision quality on real clinical decisions. Results In Study 1, we found that trait NA significantly predicted avoidant decision-making style. Furthermore, those who were higher on trait time stress and trait avoidant decision-making style exhibited poorer decisions. In Study 2, we observed associations between state NA with state avoidant and analytical decision-making styles. We also observed that these decision-making styles, when considered in tandem with time stress, were influential in predicting clinical decision quality. Conclusion NA predicts some decision-making styles, and decision-making style can affect decision quality under time stress. This is particularly true for state factors. Application Individual differences, such as affect and decision-making style, should be considered during selection. Training to reduce time stress perceptions should be provided.