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[Collaborative clinical simulation to train medical students].

Sergio Guinez-Molinos1, Patricio Maragaño Lizama1, Carmen Gomar-Sancho2

  • 1Escuela de Medicina, Universidad de Talca, Talca, Chile.

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|August 28, 2018
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This study introduces a combined model of Computer Supported Collaborative Learning (CSCL) and Clinical Simulation (CS) to enhance medical students' clinical competence and patient safety. The model is feasible and has been implemented in medical schools in Chile and Spain.

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Area of Science:

  • Health Sciences Education
  • Medical Training
  • Collaborative Learning

Background:

  • Collaborative learning is crucial for developing clinical problem-solving skills in medical education.
  • Effective cooperation, coordination, and communication are vital for patient safety.
  • Computer Supported Collaborative Learning (CSCL) and Clinical Simulation (CS) are established educational methods.

Purpose of the Study:

  • To describe a novel educational model combining CSCL and CS for medical students.
  • To integrate personalized attention, infrastructure, materials, teaching techniques, and assessment within the combined model.
  • To present the application of this model in medical schools.

Main Methods:

  • The study describes the application of a combined CSCL and CS model.
  • This model has been integrated into the curriculum at Universidad de Talca Medical School since 2015.
  • The model was also applied to students at Universidad de Barcelona Faculty of Medicine in 2016-2017.

Main Results:

  • The collaborative clinical simulation model has been part of the medical training agenda in Chile since 2015.
  • The model was successfully applied to medical students in Spain during 2016 and 2017.
  • Implementation of this combined method is feasible using standard resources.

Conclusions:

  • The combined CSCL and CS model offers a structured approach to teaching clinical competences.
  • The model's feasibility has been demonstrated in international medical education settings.
  • Further evaluation is needed to determine the model's definitive efficacy in improving student outcomes.