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 language | English |
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Pages (from-to) | 125-129 |
Number of pages | 5 |
Journal | Diagnosis (Berlin, Germany) |
Volume | 1 |
Issue number | 1 |
DOIs | |
State | Published - 1 Jan 2014 |
Keywords
- Diagnostic errors
- Diagnostic training
- Learning sciences