Related Experiment Video
Updated: Aug 15, 2026
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Error detection in anatomic pathology
Richard J Zarbo1, Frederick A Meier, Stephen S Raab
1Department of Pathology and Laboratory Medicine, Henry Ford Health System, Detroit, MI 48202, USA.
Objectives:
To define the magnitude of error occurring in anatomic pathology, to propose a scheme to classify such errors so their influence on clinical outcomes can be evaluated, and to identify quality assurance procedures able to reduce the frequency of errors.
Design:
(a) Peer-reviewed literature search via PubMed for studies from single institutions and multi-institutional College of American Pathologists Q-Probes studies of anatomic pathology error detection and prevention practices; (b) structured evaluation of defects in surgical pathology reports uncovered in the Department of Pathology and Laboratory Medicine of the Henry Ford Health System in 2001-2003, using a newly validated error taxonomy scheme; and (c) comparative review of anatomic pathology quality assurance procedures proposed to reduce error.
Results:
Marked differences in both definitions of error and pathology practice make comparison of error detection and prevention procedures among publications from individual institutions impossible. Q-Probes studies further suggest that observer redundancy reduces diagnostic variation and interpretive error, which ranges from 1.2 to 50 errors per 1000 cases; however, it is unclear which forms of such redundancy are the most efficient in uncovering diagnostic error. The proposed error taxonomy tested has shown a very good interobserver agreement of 91.4% (kappa = 0.8780; 95% confidence limit, 0.8416-0.9144), when applied to amended reports, and suggests a distribution of errors among identification, specimen, interpretation, and reporting variables.
Conclusions:
Presently, there are no standardized tools for defining error in anatomic pathology, so it cannot be reliably measured nor can its clinical impact be assessed. The authors propose a standardized error classification that would permit measurement of error frequencies, clinical impact of errors, and the effect of error reduction and prevention efforts. In particular, the value of double-reading, case conferences, and consultations (the traditional triad of error control in anatomic pathology) awaits objective assessment.
