Error detection in anatomic pathology.
OBJECTIVE
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.


METHODS
(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.
Zarbo
Richard J
RJ
Department of Pathology and Laboratory Medicine, Henry Ford Health System, Detroit, MI 48202, USA.
Meier
Frederick A
FA
Raab
Stephen S
SS
D003951:Diagnostic Errors / Q000145:classification / Q000517:prevention & control / Q000706:statistics & numerical data; D006801:Humans; D008499:Medical Records; D010336:Pathology / Q000592:standards*; D039781:PubMed; D011785:Quality Assurance, Health Care / Q000379:methods*; D011786:Quality Control