Ross J. Scalese

Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review*

Review date: 1969 to 2003, 34 years. Background and context: Simulations are now in widespread use in medical education and medical personnel evaluation. Outcomes research on the use and effectiveness of simulation technology in medical education is scattered, inconsistent and varies widely in methodological rigor and substantive focus. Objectives: Review and synthesize existing evidence in educational science that addresses the question, ‘What are the features and uses of high-fidelity medical simulations that lead to most effective learning?’. Search strategy: The search covered five literature databases (ERIC, MEDLINE, PsycINFO, Web of Science and Timelit) and employed 91 single search terms and concepts and their Boolean combinations. Hand searching, Internet searches and attention to the ‘grey literature’ were also used. The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality. Inclusion and exclusion criteria: Four screening criteria were used to reduce the initial pool of 670 journal articles to a focused set of 109 studies: (a) elimination of review articles in favor of empirical studies; (b) use of a simulator as an educational assessment or intervention with learner outcomes measured quantitatively; (c) comparative research, either experimental or quasi-experimental; and (d) research that involves simulation as an educational intervention. Data extraction: Data were extracted systematically from the 109 eligible journal articles by independent coders. Each coder used a standardized data extraction protocol. Data synthesis: Qualitative data synthesis and tabular presentation of research methods and outcomes were used. Heterogeneity of research designs, educational interventions, outcome measures and timeframe precluded data synthesis using meta-analysis. Headline results: Coding accuracy for features of the journal articles is high. The extant quality of the published research is generally weak. The weight of the best available evidence suggests that high-fidelity medical simulations facilitate learning under the right conditions. These include the following: providing feedback—51 (47%) journal articles reported that educational feedback is the most important feature of simulation-based medical education; repetitive practice—43 (39%) journal articles identified repetitive practice as a key feature involving the use of high-fidelity simulations in medical education; curriculum integration—27 (25%) journal articles cited integration of simulation-based exercises into the standard medical school or postgraduate educational curriculum as an essential feature of their effective use; range of difficulty level—15 (14%) journal articles address the importance of the range of task difficulty level as an important variable in simulation-based medical education; multiple learning strategies—11 (10%) journal articles identified the adaptability of high-fidelity simulations to multiple learning strategies as an important factor in their educational effectiveness; capture clinical variation—11 (10%) journal articles cited simulators that capture a wide variety of clinical conditions as more useful than those with a narrow range; controlled environment—10 (9%) journal articles emphasized the importance of using high-fidelity simulations in a controlled environment where learners can make, detect and correct errors without adverse consequences; individualized learning—10 (9%) journal articles highlighted the importance of having reproducible, standardized educational experiences where learners are active participants, not passive bystanders; defined outcomes—seven (6%) journal articles cited the importance of having clearly stated goals with tangible outcome measures that will more likely lead to learners mastering skills; simulator validity—four (3%) journal articles provided evidence for the direct correlation of simulation validity with effective learning. Conclusions: While research in this field needs improvement in terms of rigor and quality, high-fidelity medical simulations are educationally effective and simulation-based education complements medical education in patient care settings.

A critical review of simulation-based medical education research: 2003-2009.

Objectives  This article reviews and critically evaluates historical and contemporary research on simulation‐based medical education (SBME). It also presents and discusses 12 features and best practices of SBME that teachers should know in order to use medical simulation technology to maximum educational benefit.

Simulation technology for skills training and competency assessment in medical education.

Medical education during the past decade has witnessed a significant increase in the use of simulation technology for teaching and assessment. Contributing factors include: changes in health care delivery and academic environments that limit patient availability as educational opportunities; worldwide attention focused on the problem of medical errors and the need to improve patient safety; and the paradigm shift to outcomes-based education with its requirements for assessment and demonstration of competence. The use of simulators addresses many of these issues: they can be readily available at any time and can reproduce a wide variety of clinical conditions on demand. In lieu of the customary (and arguably unethical) system, whereby novices carry out the practice required to master various techniques—including invasive procedures—on real patients, simulation-based education allows trainees to hone their skills in a risk-free environment. Evaluators can also use simulators for reliable assessments of competence in multiple domains. For those readers less familiar with medical simulators, this article aims to provide a brief overview of these educational innovations and their uses; for decision makers in medical education, we hope to broaden awareness of the significant potential of these new technologies for improving physician training and assessment, with a resultant positive impact on patient safety and health care outcomes.

Effect of practice on standardised learning outcomes in simulation-based medical education

Objectives  This report synthesises a subset of 31 journal articles on high‐fidelity simulation‐based medical education containing 32 research studies drawn from a larger qualitative review published previously. These studies were selected because they present adequate data to allow for quantitative synthesis. We hypothesised an association between hours of practice in simulation‐based medical education and standardised learning outcomes measured as weighted effect sizes.

Simulation in Health Care Education

During the past 15 years there has been widespread adoption of simulation in health care education as a method to train and assess learners. Multiple factors have contributed to this movement, including reduced patient availability, limited faculty teaching time, technological advances in diagnosis and treatment that require a new skills set, greater attention to patient safety with the need to reduce medical errors, and a focus on outcomes-based education. In this discussion, simulation refers broadly to any device or set of conditions that attempts to present the patient authentically. While simulation offers many advantages over traditional methods of teaching, there are several challenges that must be addressed to ensure its effective use. This article presents the range of available simulation technologies, explores the challenges that health care educators face when using this method, provides an example of a successful program that has integrated simulation into the culture of learning at its institution, and discusses an approach to maximizing the effectiveness of simulation as a means to learning and practicing skills in a safe, interactive environment.

Best evidence on high-fidelity simulation: What clinical teachers need to know

S ince the 1980s, medical education has witnessed a significant increase in the use of simulation technology for teaching and assessment. What had previously been thought of as just a hobby for technically savvy clinical educators has now been fully integrated into the culture of clinical training. This is true not only for undergraduate medical education, but also for postgraduate training and continuing professional development. Hundreds of medical schools worldwide have already developed, or are in the process of developing, clinical skills/ The most thorough search possible of peer-reviewed publications BEME review

Assessing cardiac physical examination skills using simulation technology and real patients: A comparison study

Objective  High‐stakes assessments of doctors’ physical examination skills often employ standardised patients (SPs) who lack physical abnormalities. Simulation technology provides additional opportunities to assess these skills by mimicking physical abnormalities. The current study examined the relationship between internists’ cardiac physical examination competence as assessed with simulation technology compared with that assessed with real patients (RPs).

What is evidence? Reflections on the AMEE symposium, Vienna, August 2011

In this article, we present a summary of the discussion from the symposium on ‘what is evidence’, which took place at the AMEE conference in 2011. A panel of five academics and clinicians, plus the chair, considered the nature of evidence, in particular in relation to the ‘evidence’ in the best evidence medical education reviews. Evidence has multiple meanings depending on context and use, and this reflects the complex and often chaotic world in which we work and research.

Assessing the relationship between cardiac physical examination technique and accurate bedside diagnosis during an objective structured clinical examination (OSCE)

Background Many standardized patient (SP) encounters employ SPs without physical findings and, thus, assess physical examination technique. The relationship between technique, accurate bedside diagnosis, and global competence in physical examination remains unclear. Method Twenty-eight internists undertook a cardiac physical examination objective structured clinical examination, using three modalities: real cardiac patients (RP), “normal” SPs combined with related cardiac audio–video simulations, and a cardiology patient simulator (CPS). Two examiners assessed physical examination technique and global bedside competence. Accuracy of cardiac diagnosis was scored separately. Results The correlation coefficients between participants’ physical examination technique and diagnostic accuracy were 0.39 for RP (P < .05), 0.29 for SP, and 0.30 for CPS. Patient modality impacted the relative weighting of technique and diagnostic accuracy in the determination of global competence. Conclusions Assessments of physical examination competence should evaluate both technique and diagnostic accuracy. Patient modality affects the relative contributions of each outcome towards a global rating.

Revisiting ‘A critical review of simulation-based medical education research: 2003–2009’

Editor’s note: As part of our 50th volume celebrations, Medical Education is looking back at its most impactful articles, as defined by citation count. The most cited articles from each 5-year interval were identified and the original authors of one of them (or other knowledgeable scholars if the original authors could not be found) were asked to comment on the state of the field at the time of the publication, the impact of the article, and what we have learned since then. The article illustrated in Figure 1 was one of the most cited articles in our journal in the 2007–2011 period. To see the other top-cited articles from Volumes 1–50 please view the interactive PDF by visiting www.mededuc.com.