| Literature DB >> 29539984 |
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.Entities:
Keywords: diagnostic errors; diagnostic training; learning sciences
Year: 2014 PMID: 29539984 DOI: 10.1515/dx-2013-0013
Source DB: PubMed Journal: Diagnosis (Berl) ISSN: 2194-802X