Article,
Society for Simulation in Healthcare Guidelines for Simulation Training
Affiliations
- [1] Indiana Univ Sch Med, Dept Surg, 545 Emerson Hall,EH 130, Indianapolis, IN 46202 USA [NORA names: United States; America, North; OECD];
- [2] Indiana Univ Sch Med, Dept Surg, 545 Emerson Hall,EH 130, Indianapolis, IN 46202 USA [NORA names: United States; America, North; OECD];
- [3] Mayo Clin, Dept Internal Med, Rochester, MN USA [NORA names: United States; America, North; OECD];
- [4] Emory Univ, Dept Surg, Atlanta, GA USA [NORA names: United States; America, North; OECD];
- [5] Univ Louisville, Dept Surg, Louisville, KY 40292 USA [NORA names: United States; America, North; OECD];
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Abstract
BackgroundSimulation has become a staple in the training of healthcare professionals with accumulating evidence on its effectiveness. However, guidelines for optimal methods of simulation training do not currently exist.Systematic reviews of the literature on 16 identified key questions were conducted and expert panel consensus recommendations determined using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology.These evidence-based guidelines from the Society for Simulation in Healthcare intend to support healthcare professionals in decisions on the most effective methods for simulation training in healthcareTwenty recommendations on 16 questions were determined using GRADE. Four expert recommendations were also provided.The first evidence-based guidelines for simulation training are provided to guide instructors and learners on the most effective use of simulation in healthcare.Simulation is being used for the training of healthcare workers in many settings and to address a variety of clinical issues. Available evidence suggests that performance improvements as a result of simulation training result in improvements in the clinical care of patients. However, current practices vary widely in simulation training, and there are no existing guidelines based on systematic synthesis of best available evidence to guide practices. In this manuscript, we present the first evidence-based guidelines relevant to simulation training that were developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology.BackgroundSimulation has become a staple in the training of healthcare professionals with accumulating evidence on its effectiveness. However, guidelines for optimal methods of simulation training do not currently exist.Systematic reviews of the literature on 16 identified key questions were conducted and expert panel consensus recommendations determined using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology.These evidence-based guidelines from the Society for Simulation in Healthcare intend to support healthcare professionals in decisions on the most effective methods for simulation training in healthcareTwenty recommendations on 16 questions were determined using GRADE. Four expert recommendations were also provided.The first evidence-based guidelines for simulation training are provided to guide instructors and learners on the most effective use of simulation in healthcare.Simulation is being used for the training of healthcare workers in many settings and to address a variety of clinical issues. Available evidence suggests that performance improvements as a result of simulation training result in improvements in the clinical care of patients. However, current practices vary widely in simulation training, and there are no existing guidelines based on systematic synthesis of best available evidence to guide practices. In this manuscript, we present the first evidence-based guidelines relevant to simulation training that were developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology.BackgroundSimulation has become a staple in the training of healthcare professionals with accumulating evidence on its effectiveness. However, guidelines for optimal methods of simulation training do not currently exist.