Automatic analysis of summary statements in virtual patients - a pilot study evaluating a machine learning approach.

Journal: BMC medical education
Published Date:

Abstract

BACKGROUND: The ability to compose a concise summary statement about a patient is a good indicator for the clinical reasoning abilities of healthcare students. To assess such summary statements manually a rubric based on five categories - use of semantic qualifiers, narrowing, transformation, accuracy, and global rating has been published. Our aim was to explore whether computer-based methods can be applied to automatically assess summary statements composed by learners in virtual patient scenarios based on the available rubric in real-time to serve as a basis for immediate feedback to learners.

Authors

  • Inga Hege
    Medical Education Sciences, University of Augsburg, Augsburg, Germany. inga.hege@med.uni-augsburg.de.
  • Isabel Kiesewetter
    Department of Anaesthesiology, Klinikum der Ludwig-Maximilians-Universität München, Munich, Germany.
  • Martin Adler
    Instruct gGmbH, Kapuzinerstr.5, 80337, Munich, Germany.