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Cited by 3,966Simulation-Based Education in HealthcareSurgical Simulation and TrainingInnovations in Medical Education

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

Barry Issenberg, S., Mcgaghie, William C., Petrusa, Emil R., Lee Gordon, David, Scalese, Ross J.·2005·Medical Teacher
DOI 10.1080/01421590500046924
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Abstract

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 The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality.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.

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  • Significant challenges remain in ensuring alignment with varying curricula, gathering longitudinal evidence of student growth, and developing flexible implementation models that accommodate diverse learning objectives and timelines.

    “While technological advancements offer promising solutions through digital platforms, high-fidelity simulations, and streamlined feedback mechanisms, significant challenges remain in ensuring alignment with varying curricula, gathering longitudinal evidence of student growth, and developing flexible implementation models that can accommodate diverse learning objectives and timelines [12,13].”

    From Formative assessment and feedback in medical education: A practical guide: AMEE Guide No. 189 (2026) · cites this paper as [13]

  • Simulation facilitates learning when used in appropriate conditions that include providing feedback, repetition, curriculum integration, individualized learning and controlled environment.

    “However, it has been accepted that simulation facilitates learning when it is used in the appropriate conditions that include providing feedback, repetition, curriculum integration, individualized learning and controlled environment [28].”

    From The virtual patient as a learning tool: a mixed quantitative qualitative study (2018) · cites this paper as [28]

  • Instructional strategies, whether technology-based or not, must include some solid principles from pedagogical theory that were incorporated to the virtual patient course and some of what Issenberg et al. described as key for simulation-based learning.

    “This suggests that instructional strategies, whether technology-based or not, must include some solid principles from pedagogical theory that were incorporated to the VP course and some of what Issenberg et al. described as key for simulation-based learning [28].”

    From The virtual patient as a learning tool: a mixed quantitative qualitative study (2018) · cites this paper as [28]

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Authors
Barry Issenberg, S., Mcgaghie, W. C., Petrusa, E. R., Lee Gordon, D., & Scalese, R. J.
Affiliations
  • Northwestern University (US)
  • Duke Medical Center (US)
  • University of Miami (US)
ORCID
Venue
Medical Teacher
Publisher
Informa UK Limited
Published
2005-01
Volume
27
Issue
1
Pages
10-28
ISSN
  • 0142-159X (ISSN-L)
  • 1466-187X
DOI
10.1080/01421590500046924
OpenAlex
W2162661914
Cited by
3,966
References
203
Citations by year
2026: 311 · 2025: 239 · 2024: 194 · 2023: 177 · 2022: 198 · 2021: 245 · 2020: 224 · 2019: 233 · 2018: 191 · 2017: 178 · 2016: 227 · 2015: 252 · 2014: 199 · 2013: 233 · 2012: 190
FWCI
9.61
Type
journal article
Language
en
Open access
closed
Locations
  • Medical Teacher (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Simulation-Based Education in Healthcare
  • Health Sciences › Medicine › Surgery › Surgical Simulation and Training
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
Keywords
high-fidelity simulation, simulation-based medical education, medical education, instructional feedback, repeated practice, curriculum integration, task difficulty, student outcomes, research quality, graduate medical education, student motivation, learner confidence, student self-efficacy, student self-assessment, student self-regulation, learner autonomy
MeSH terms
Clinical Competence, Education, Medical, Humans, Research Design, Software, Patient Simulation, Total Quality Management, Medical Errors

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