title: Detection and classification of diagnostic discrepancies (errors) in surgical pathology.
abstract: Detecting and classifying error in a surgical pathology (SP) practice is an important part of a comprehensive quality assurance program. There are a number of mechanisms to detect error, including secondary review, examination of amended reports, correlation studies (cytology-histology and frozen-final diagnosis correlation). These different detection methods are reviewed in this paper. Additionally, the most common methods for error classification are also reviewed, along with the benefits and limitations of each. Although there is presently no gold standard for detecting or classifying errors in SP, based on this review of the literature, it is clearly good practice to consistently apply a standard method. Most importantly, these data should be incorporated into quality assurance and quality improvement activities, such that departments strive to reduce errors, and to help improve overall quality in SP.
authors: Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
authors: Jennifer E
authors: JE
authors: Roy
authors: Jennifer L
authors: JL
authors: Hunt
mesh_terms: D003951:Diagnostic Errors / Q000145:classification* / Q000517:prevention & control; D006801:Humans; D007753:Laboratories / Q000592:standards; D008499:Medical Records; D010340:Pathology, Surgical / Q000592:standards*; D011785:Quality Assurance, Health Care; D058996:Quality Improvement