Diagnostic errors in patients dying in hospital: radiology's contribution

J Med Imaging Radiat Oncol. 2009 Apr;53(2):188-93. doi: 10.1111/j.1754-9485.2009.02065.x.


We propose a comprehensive taxonomy of diagnostic errors in radiology that incorporates requests, image acquisition, radiological reports and evidence of communication to the treating team, and is retrospectively applicable to a given set of radiological episodes using pre-existing standard hospital databases. The taxonomy applies four binary tests to each diagnostic error using widely available hospital records, such as radiological requests, images in Picture Archiving and Communication System, radiological reports and hospital patient records. The taxonomy classifies errors into seven mutually exclusive patterns: no relevant imaging, consistent error (technical non-demonstration), consistent error (human error), ignored correct dissenting radiology result, de novo radiology error (technical non-demonstration), de novo radiology error (human error), and ignored correct confirmatory radiology result. The taxonomy was validated against a set of 250 diagnostic errors identified from an audit of clinical and radiological diagnoses with autopsy as the reference standard. All errors were successfully classified by the taxonomy, and the point of initiation of the error assigned. Of a total of 250 diagnostic errors, 138 (55%) had no relevant imaging performed. Ninety percent of all errors (226) were due to human error only, whether at the stage of clinical suspicion, the radiologist's diagnosis, or afterwards. Of the 112 imaged errors, only 12 (11%) were initiated at diagnostic imaging. The taxonomy of diagnostic error we present is comprehensive, allows retrospective audit of error with commonly available data, and provides clinically useful identification of the point of error initiation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Australia / epidemiology
  • Cause of Death*
  • Diagnostic Errors / classification*
  • Diagnostic Errors / statistics & numerical data*
  • Diagnostic Imaging / statistics & numerical data*
  • Mortality*
  • Radiology / statistics & numerical data*
  • Risk Management / statistics & numerical data*