Learning sciences principles that can inform the construction of new approaches to diagnostic training

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The author suggests that the ill-defined nature of human diseases is a little appreciated, nonetheless important contributor to persistent and high levels of diagnostic error. Furthermore, medical education's continued use of traditional, non-evidence based approaches to diagnostic training represents a systematic flaw likely perpetuating sub-optimal diagnostic performance in patients suffering from ill-defined diseases. This manuscript briefly describes how Learning Sciences findings elucidating how humans reason in the face of the uncertainty and complexity posed by ill-defined diseases might serve as guiding principles in the formulation of first steps towards a codified, 21st century approach to training and assessing the diagnostic capabilities of future health care providers.

Original languageEnglish
Pages (from-to)125-129
Number of pages5
JournalDiagnosis (Berlin, Germany)
Volume1
Issue number1
DOIs
StatePublished - 1 Jan 2014

Keywords

  • Diagnostic errors
  • Diagnostic training
  • Learning sciences

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