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Building consensus for the future of paediatric simulation: a novel ‘KJ Reverse-Merlin’ methodology
  1. Elizabeth A Hunt1,
  2. Jordan Duval-Arnould1,
  3. Nnenna O Chime1,2,
  4. Marc Auerbach3,
  5. David Kessler4,
  6. Jonathan P Duff5,
  7. Nicole Shilkofski1,6,
  8. Marissa Brett-Fleegler7,
  9. Vinay Nadkarni8,
  10. Adam Cheng9
  11. for the International Network for Simulation-based Pediatric Innovation, Research and Education (INSPIRE) Investigators
    1. 1Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
    2. 2Albert Einstein College of Medicine and Children's Hospital at Montefiore, Bronx, New York, USA
    3. 3Yale University School of Medicine, New Haven, Connecticut, USA
    4. 4Columbia University College of Physicians and Surgeons, New York, New York, USA
    5. 5University of Alberta, Edmonton, Alberta, USA
    6. 6Perdana University Graduate School of Medicine
    7. 7Boston Children's Hospital, Boston, Massachusetts, USA
    8. 8Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
    9. 9Alberta Children's Hospital, Calgary, Alberta, Canada
    1. Correspondence to Dr Nnenna O Chime, Department of Pediatrics, Children's Hospital at Montefiore, 111 East 210th Street, Rosenthal 4, Bronx, NY 10467, USA; nnenna_chime{at}yahoo.com

    Abstract

    Objectives This project aims to identify guiding strategic principles to optimise simulation-based educational impact on learning, patient safety and child health.

    Methods Study participants included 39 simulation experts who used a novel ‘KJ Reverse-Merlin’ consensus process in the systematic identification of barriers to success in simulation, grouped them in themes and subsequently identified solutions for each theme.

    Results 193 unique factors were identified and clustered into 6 affinity groups. 6 key consensus strategies were identified: (1) allocate limited resources by engaging health systems partners to define education and research priorities; (2) conduct and publish rigorous translational and cost-effectiveness research; (3) foster collaborative multidisciplinary research and education networks; (4) design simulation solutions with systems integration and sustainability in mind; (5) leverage partnerships with industry for simulation, medical and educational technology; (6) advocate to engage the education community, research funding agencies and regulatory bodies.

    Conclusions Simulation can be used as a research, quality improvement and or educational tool aimed at improving the quality of care provided to children. However, without organisation, strategy, prioritisation and collaboration, the simulation community runs the risk of wasting resources, duplicating and misdirecting the efforts.

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