In response to the demand for health care reform,1–3 the need for health professional education restructuring has become urgent. New educational models are being urged in prelicensure programs to leverage educational technologies that can steepen the learning curve and improve competency levels of new practitioners.4 With the increasing recognition, adoption, and promotion of simulation-based education (SBE) and interest in interprofessional education (IPE), SBE is increasingly being used for IPE. There seem to be parallel efforts to create programs that use simulation-enhanced IPE (Sim-IPE).5 Rather than building on existing work, seeking to fill needed knowledge gaps or replicating for establishing reliability, we suspect that programs are duplicating efforts because of a lack of awareness of what others have done or are exploring.6 We see a need to compile extant information about sim-IPE to avoid duplication of effort and identify types of research needed to explain how sim-IPE might be used to improve population health.7
In addition to possible duplication of effort, the Sim-IPE research literature seems to lack rigorous approaches.8–10 Factors that induce positive or negative outcomes in Sim-IPE are undefined. Thus, limited evidence exists to demonstrate the effect of Sim-IPE on practice or patient outcomes.9 The rapid growth in Sim-IPE activities in the face of limited evidence calls for reviewing and building on existing knowledge.8–17 We reviewed the literature on Sim-IPE activities in prelicensure students to learn what evidence exists to recommend their use, guide practice in how best to use Sim-IPE, and identify areas in need of research.
The purposes of this review were to (1) understand what evidence exists to support Sim-IPE, (2) provide a compilation of information from this review so that health profession educators can best use simulation for interprofessional education (IPE), and (3) identify and suggest focus areas where educators and researchers can contribute findings to fill knowledge gaps in the field as identified in this review. To achieve our purposes, we analyzed research studies of the use of SBE for IPE for prelicensure students to answer the following questions:
- ▪ Where are studies being conducted, and what are the professions of the authors of the publications (i.e., demographics of the studies)?
- ▪ What subjects were studied, and what was their academic level (i.e., sample or learner demographics)?
- ▪ What theories and frameworks were used in the Sim-IPE curricula?
- ▪ What research methods were used?
- ▪ What simulation modalities were used in Sim-IPE (e.g., one modality or blended modalities)?
- ▪ What measurements were used? Were the measures reliable and valid? What Kirkpatrick learning level was addressed?
- ▪ What characteristics have been found to influence positive and negative outcomes in IPE?
- ▪ What are the common challenges that researchers and reviewers (i.e., readers) encounter?
In addressing these questions, we try to clarify some of the more complex factors in implementing Sim-IPE to assist educators and researchers to better understand their simulation teaching and research practices.
Interprofessional education occurs when “students from 2 or more professions learn about, from, and with each other to enable effective collaboration and improve health.”18 Formal IPE is developed as an educational event or program that aims to achieve interprofessional learning by bringing learners from different professions together and fostering collaboration in practice.19 The intent for formal IPE is for learning to be applied in the practice setting through interprofessional practice and ultimately enhance the quality of patient care.
Simulation is “a technique that uses a situation or created environment to allow persons to experience a representation of a real event for the purpose of practice, learning, evaluation, testing, or to gain understanding of systems or human actions. Simulation is the application of a simulator to training and/or assessment.”20 A simulator is “any object or representation used during training or assessment that behaves or operates like a given system and responds to the user’s actions.”6
We applied standard literature review procedures21 for reading abstracts, scrutinizing full papers, and abstracting data. In partnership with a licensed academic librarian, we obtained 7578 hits resulting from a search of 9 major literature databases (see Appendix A) using the earliest date available in each database ranging from the 1800 to Dec 2014. We used 33 single simulation, interprofessional, and health profession search terms and multiple Boolean combinations (see Appendix A). Twenty-four other potential abstracts were found by hand search.
Of the initial 7602 articles found for IPE and SBE, inclusion and exclusion criteria were narrowed to include the following:
- an educational intervention that involved prelicensure learners from at least 2 professions,
- focus on formal prelicensure (e.g., nursing, medical, physician assistant, pharmacy, respiratory therapy students) educational initiatives (may have involved practicing providers with a minimum of prelicensure learners from 2 professions),
- an experiential* (see below) SBE activity that involved direct experience,
- an interprofessional intervention** (see below),
- measured and reportable results (Fig. 1), and
- written in English.
*For this review, learning considered “experiential” included all of the following elements:
- opportunities for students to engage physically, socially, and emotionally,
- reflection or critical analysis,
- facilitated opportunities for students to take initiative and make decisions, and
- a learning experience reflecting a real situation or environment that is interactive with learner actions.22
Forms of simulation that were experiential include the following: participants using interactive, mannequin-based simulation; standardized patients; embedded-simulation persons (ESPs); virtual avatar platform; or role play with preactivity training and task trainers. Our definition of experiential excluded solely didactic settings, case-based didactic, reading, and/or discussion, or passive video review.
**An interprofessional intervention occurs when members of more than 1 health or social care profession learn interactively together for the explicit purpose of improving interprofessional collaboration in prelicensure learners. Interactive learning requires active learner participation within the group and active exchange between learners from different professions (modified from Reeves11). Because measurements of IPE (by definition: learning about, from, and with each other) were not apparent in each article (e.g., how much one learner learned about or from another), the authors used “interprofessional intervention” as an inclusion measure for the purpose of this literature review.
Two authors individually reviewed each abstract and filtered publications via consensus according to the specific inclusion criteria below. Owing to poorly written abstracts, some papers were not included if inclusion criteria seemed unlikely from the title and existing abstract, whereas a cursory full review of some papers occurred if inclusion criteria seemed likely. Because the literature generally lacked adequate methodological strength, strength of findings, and similarity in research questions, variables, populations, or measures, a meta-analysis was not appropriate. Development of a literature database was initiated using a synthesis of literature review management items23,24 (see Appendix A).
The filtering resulted in 54 articles. A comprehensive table of review for the 54 research studies is available as supplementary digital content and can be accessed via Figure 2. Articles that met the inclusion criteria (see Table 1 and Table, Supplemental Digital Content 1, http://links.lww.com/SIH/A281, which provides detailed information around the criteria) were logged (see Appendix A).
RESULTS AND DISCUSSION
Information gathered from the compilation regarding demographics and methods, theories, modalities, and characteristics reported by the 54 research studies is outlined in Table 2. Additionally, when exploring challenges found in the studies, common themes emerged from the data and are described in the discussion.
In this synthesis of the literature, we have identified some key aspects of the state of knowledge of Sim-IPE. In this discussion, we describe many areas that need further evidence to determine when and how simulation should be optimally used for IPE.
Demographics of Activities
There has been a substantial increase in the number of publications regarding Sim-IPE over the past decade, with most studies published over the past 5 years. Trends in publications indicate levels of activity, awareness, needs, development, and growth of the field. The increasing publications reflect increasing awareness of simulation as an effective educational method and the increasing awareness of IPE as necessary for safe patient care. The trend also suggests increasing adoption of Sim-IPE, suggesting the need for faculty development.
When determining the state of a science, demographic data are essential to identify needs and habits in the field, providing parameters that suggest areas of focus for researchers and reveal biases in recommendations. Half of the studies reviewed here occurred in the United States, likely posing a bias in our recommendations toward US culture and Western medicine. Low-resource simulation activities have provided creative and powerful methods that could be used in other settings.89 There is a need for research and publications from other cultures and developing countries.
Community-based collaboration is the collaboration between primary care or home settings and health systems in the community. Community-based collaboration is a critical area in need of IPE given primary care provider shortages.90,91 The global need for effective, less costly health system redesign requires coordination and aligned planning in health systems activities (including strategies, funding, and policies) with health education.9,92,93 There were only 2 studies using simulation for community-based IPE.94,95 The use of SBE with interprofessional community learners is both encouraging and in need of further study.96
Of the studies reviewed, 43% (n=23) did not report faculty composition or author credentials. Author credentials indicate experience and knowledge, whereas affiliations indicate target students. Like all experiential learning, Sim-IPE requires a great deal of preliminary planning97 owing to its highly complex and interactive nature of SBE. None of the studies reported on what was the involvement of a faculty or student of each participating profession during the development of the course. To achieve simulations appropriate for each learner, a member for each involved learner profession should be involved in the planning to promote equal and realistic learning opportunities for all involved learners.19 Faculty composition in the development, implementation, and research of simulated IPE may influence the outcomes of the activities.
Scheduling issues often pose challenges in matching learner levels, since learners from different professions at similar levels of learning often are not available at the same time. Interprofessional education program educators and coordinators often accept a variety of learner levels to have various professions involved in the activity. A few studies had prelicensure learners (i.e., students) and postlicensure learners (e.g., practicing providers), which may have influenced the learning for the prelicensure learners. The numbers of each professional group were often not reported (41%  studies). Uneven numbers may influence learning for each group. The effects of different learner compositions need further study.
The sample sizes were generally small, with a range of 8 to 312 participants (median, 88 participants). Findings in studies with large sample sizes increase the generalizability of the reported results.21 Because Sim-IPE is faced with many complex confounding variables (further detailed below), different levels of study, large sample sizes, multisite studies, as well as funding to support these studies are needed.
Volunteer Versus Mandatory
The impact of mandatory activities on learning outcomes has been studied in higher education.98–101 Haggarty and Dalcin101 describe the benefits in collaborative systems between patients, students, and communities from volunteer student-run clinics. Ryan and Deci99 describe the effectiveness of volunteer learning, as well as the variable effectiveness of mandatory activities. The participants in 50% (n=27) of the studies attended the education voluntarily (vs mandatory attendance for at least 1 profession or for all). The impact of learner motivations (i.e., intrinsic or extrinsic) in participation is in need of further study.
Theories and Frameworks
Studies that used a theory or framework (50%; n=27) detailed rigorous approaches to the research in comparison to studies that did not use a framework. Because assessment instruments for these frameworks are still being developed and refined, critique of the effects of frameworks on outcomes is not addressed at this time and is suggested for future study. Particular relationships in these models or specific team skill tools (e.g., TeamSTEPPS) were not comparatively studied. Whereas these findings suggest a need to increase the use of a theoretical or conceptual framework, the authors note that there is a slight increase annually in studies that used a framework suggesting increasing awareness and use.
We initially included the assessment of each study’s outcomes using the Grades of Recommendation, Assessment, Development and Evaluation tool.102 All studies were found to have weak recommendations because they were either not randomized trials or randomized with serious methodological limitations (e.g., lack of blinding, high loss to follow-up) or had indirectness in population, intervention, or outcome. Whereas the studies lacked the rigor needed to achieve strong recommendations by Grades of Recommendation, Assessment, Development and Evaluation standards, standardizing Sim-IPE is highly complex with many confounding variables that are simulation-specific or IPE-specific. Because of the many simulation-specific confounding variables (e.g., modality, setup, acting, learner comfort, learner participation, realism) and IPE-specific confounding variables (e.g., learners, participation, sample sizes, hierarchy),9 the rigor in research methodology requires a level of programmatic rigor, as well as multiple approaches or perspectives (i.e., mixed research methods).
Quantitative and Qualitative Methods
Most studies in this review used a mixed methods design with both quantitative and qualitative data. Because of the complexity of compounding variables in Sim-IPE, a mixed-methods approach provides more inclusive data.9 Using mixed methods requires additional rigor in both the qualitative and quantitative methods used. Continued use of mixed methods approaches will provide more aggregated knowledge.
Blended Teaching Modalities
Most studies included a blend of teaching (e.g., lecture or online coupled with simulation) with 26% combining simulation methods (e.g., case-based online discussion with mannequin simulation). Salas et al. found that simulation significantly increased team learning and the significance increased by blending simulation with an additional teaching modality (e.g. didactic, online, or team-based activity).103 The levels of blending, as well as the types of modalities blended with simulation, should be further studied.
Observing Versus Active Participation
In health care simulation, frequently, there are observing and active participants. This occurs for 2 reasons: (1) simulation emulates a typical hospital event, where there are usually only a few providers at the bedside74 and (2) simulation programs have limited resources66 that requires larger groups than realistically are actively involved in the case. Few studies detailed observing or active participation. Alinier et al. (2014) found a perceived potential benefit of being an observing participant. Simulations often have observing participants who are included in the postsimulation debriefing with opportunity for active engagement in the discussion. The relative contribution of observation and active participation to learning in Sim-IPE needs further exploration.
Length of Activity
Many studies reported the length of the course activity. Because blended teaching modalities were used in most studies, it is difficult to discern how much time was dedicated to each activity, specifically the length of each simulation and debriefing. Whereas many studies used more than one simulation, learner exposure to each simulation was unclear. To understand how duration of a simulation or other modality affects learning is yet another area for further study.
The training and standardization of simulation technology were generally not reported, leaving unknown how these might influence the facilitation learning.
Embedded Simulated Person)
Many studies reported the use of an ESP or simulated health care providers or family (also referred to in programs as “confederates” or “actors”). Only a few studies specified the role of the persons in the cases (e.g., a standardized patient, simulated family, or simulated provider). Training and standardization of these embedded persons may influence the facilitation (or lack of facilitation) of a simulation.6
Debriefing has been identified in SBE literature to be the heart of learning in simulation.104,105 Some studies reported anecdotal evidence of learners and educators finding value in the discussions during the simulation. Most studies did not specify the use of debriefing or the type of debriefing methodology used.6,106 Learning how to talk with other professions is a key skill in collaborative practice and is often learned serendipitously during the debriefing of a simulation. The simulation serves as a common experience for discussion and is arguably the most relevant skill learned from Sim-IPE toward interprofessional practice.107 Because debriefing is, perhaps, the heart of Sim-IPE, the role of debriefing in Sim-IPE warrants future study.
There was a lack of rigor and low effect levels (i.e., Kirkpatrick levels 1-3) in evaluation. Many studies seemed to have a mismatch in measurement instruments as paired with the reported purposes of the study and activity (e.g. intent is program evaluation but measurement instrument focused on role perception). The lack of psychometric testing is identified broadly from literature reviews within SBE and IPE separately8–13,17,108–110 and is substantiated in this literature review.
As identified in prior SBE and IPE literature reviews,8–13,17,108–110 Kirkpatrick levels remain in the learner reaction, attitudes and perception, and acquisition of knowledge and skill levels. Global health organizations are calling for SBE and IPE studies that demonstrate behavioral change, organizational practice, patient outcomes, as well as system outcomes.9,18 A common theme in the literature and considered for future directions is the need to study patient outcomes; however, no studies in this review reported patient outcome-based research. Owing to changing health care systems and patient needs, researchers and educators need to shift their focus to higher levels of outcomes to inform the development of new health care models.
Business groups have since added a fifth level to the Kirkpatrick levels of studies: Return on investment and systematic impact. This fifth level embraces any effect on the field toward health care improvement, particularly the return on investment in that training.88 Sim-IPE studies evaluating these levels are needed to inform health system and health education design and redesign.
Reliability and Validity
Reliability refers to the measures and whether they are repeatable and consistent with similar results. Validity addresses whether or not the instruments actually measure what it was intended to measure. Some studies reported the use of measurement instruments that have been widely published with tested reliability and validity. However, most studies did not address reliability and validity. Studies frequently reported the use of investigator-developed measures with no evidence of reliability and validity. The lack of reliability and validity contributes to the weakness in recommendations discovered.
Characteristics that Influence Outcome
A synthesis of the teaching methods used in Sim-IPE suggested two main classification structures when examining simulation facilitation methods: simulation-based interprofessional education (SimBIE) and interprofessional simulations (IPsim).107 This SimBIE versus IPsim classification centers on the objectives used to structure the simulation.
SimBIE or IPsim
A distinction that has been made in IPE literature is IPE and multiprofessional education (MPE). Inteprofessional education describes those occasions when students from 2 or more professions learn about, from, and with each other to enable effective collaboration and improve health.18 Multiprofessional education is when members (or students) of 2 or more professions learn alongside one another: in other words, parallel rather than interactive learning.19 There is evidence in IPE literature that learning is better achieved through IPE versus MPE.12
This distinction can also be made in simulation-based education and appears in 2 forms, which we refer to as, “SimBIE” and “IPsim.” These methods depend on the objectives specified for the simulation. SimBIE refers to a simulation that was structured according to IPE objectives, where 2 or more professionals learn with, from, and about each other to improve collaboration and the quality of care. IPsim corresponds with MPE and involves learners from 2 or more professions learning alongside one another in the simulation. In IPsim, the simulation is structured around a patient’s condition or situation that requires coordination and demonstration of skills specific to the individual professions. In this study, 76% of simulations used IPsim. By nature, debriefing as a separate modality fosters SimBIE. We identified that 66% of IPSim studies were coupled with debriefing and therefore provided a hybrid approach of IPsim to SimBIE.
Exploring potential characteristics or isolated factors that influence positive or negative interprofessional learning outcomes has proven difficult. Although this review of published literature finds positive and negative outcomes (Table 2) through anecdotal evidence or data from untested or psychometrically tested instruments, a report of outcomes is not adequate when variables that can influence those outcomes are not fully disclosed or reported. In several studies, potential confounding variables were not reported or controlled in the analysis. In addition to faculty composition, other potential confounders included faculty perceptions and enthusiasm, faculty development, simulation facilitation, debriefing methods, instrument development, and simulation bias or IPE bias from previous exposure. From the findings of this review, a checklist of reporting points is suggested in Table 3. We offer this checklist as a preliminary guide, since a dedicated and rigorous process is needed to determine reporting standards.
Overcoming Challenges Found in Studies
The challenges reported during implementation of the Sim-IPE reflects common challenges found in both simulation and in IPE in general. Each practice alone (i.e., SBE or IPE) is complex. This compound complexity of combining the challenges of both practices points toward studying the solutions for the challenges found in each field. Since most educators are more versed in either SBE or IPE over the other, with the intent to assist all educators, we list in Table 4 many of these challenges identified in the literature and found in each field, as well as offer solutions to overcome each as suggested in the studies reviewed, in supporting literature, and from our experience.
SUMMARY AND CONCLUSION
What Evidence Exists to Support Sim-IPE?
Positive outcomes were reported by all investigators with regard to participant satisfaction, and the studies generally reported enthusiastic verbal or written feedback from participants. This suggests that Sim-IPE positively affects interprofessional learning, and the collective findings in this review recommend its use for prelicensure health profession education. Despite positive reports, a synthesis of these studies showed low rigor in research design (e.g., lack of standardized interventions, lack of adequate evaluation, small samples, and lack of valid and reliable measures). The studies examined had varied weaknesses and lacked uniformity, thus preventing comparisons or meta-analysis. No studies in this review reported patient outcome–based research. There is, therefore, little credible evidence that Sim-IPE is useful for improving patient outcomes.
How Can Health Profession Educators Best Use Simulation for IPE?
We review 54 studies in this article, providing a comprehensive table of information (see Table, Supplemental Digital Content 1, http://links.lww.com/SIH/A281, which provides detailed information on each article) and a summarized table of results (Table 2). We discuss many considerations for educators when using simulation for IPE, highlighting common challenges found in the studies and offering solutions to overcome those challenges (Table 4). Thoughtful use of simulation around the considerations discussed can guide educators toward the development and implementation of effective Sim-IPE.
How Do We Fill Knowledge Gaps?
Many studies sought to provide evidence around the use of simulation. The problem that ensues is that the science has not yet identified confounding variables. The lack of rigor in controlling for confounding variables leaves us with limited knowledge about what are the major influences on IPE outcomes. The lack of detail about simulation scenarios (i.e., the protocol or intervention) does not allow for replication of the study. In addition, despite many efforts, each study is laced with the presence of unknown confounding variables, affecting the credibility of each finding and future study to determine confounding variables.
Despite the lack of strong evidence, the use of Sim-IPE is rapidly increasing. With a global call to improve patients’ safety, care, and costs through better communication and teamwork, many institutions have invested financial and human resources to develop effective health care education using simulation for IPE. Rather than seeking to provide evidence to promote the use of Sim-IPE, the need now exists at the level of: what are the most important variables that can impact learning? This heightens the importance to rigorously design research (e.g., randomized controlled trials) that studies characteristics that influence Sim-IPE outcomes but with attention to documenting these variables. From our findings in this review, we suggest a checklist of potentially valuable reporting items (Table 3) so that future literature reviews may study these variables and determine priorities for the field.
Reviews of the research literature often result in evidence-based recommendations for research, development, methods, and measures. However, for this still immature and complex Sim-IPE field, the science is lacking. We suggest that Sim-IPE researchers design their studies with consideration for generalizability and transferability of their study findings. Research designs that will identify characteristics that influence positive and negative outcomes will help establish new frameworks for the use of Sim-IPE. Once potential characteristics are identified, more detailed frameworks for reporting or supplemental mechanisms (e.g., online video addendums) can be developed that would allow further evidence to study these characteristics.
The authors thank the support of Drs Jeffrey Cooper, Patricia Jones, and Mark Haviland, as well as our colleagues at the Center for Medical Simulation for their editorial consultation; Dr Herrmann and LLU School of Nursing for their methodological consultation; Martha Stones for search strategies; and the Interprofessional Education and Health care Simulation Collaborative for accepting and building on the work presented here.
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Appendix A: LITERATURE SEARCH TERMS
Major literature databases searched: CINAHL, PubMed, MEDLINE, EBSCO Academic Search Premier, Social Sciences Citation Index, PsychINFO, JSTOR, Cochrane Collaborative Review, Google Scholar
Search terms: (* indicates any following character string) “health*” and “simulat*, standardized, experiential, case-based, or virtual” and “interprofession*, educ*, team*, collaborat*, profession*, communicat*, staff development, physician, medic* + nurs*, or TeamSTEPPS” and multiple Boolean combinations.
Using Microsoft Office Access (Microsoft, Inc, Redmond, WA), database fields for each article were logged.
Literature Database Fields