Literature DB >> 16196511

Error detection in anatomic pathology.

Richard J Zarbo1, Frederick A Meier, Stephen S Raab.   

Abstract

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.

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Mesh:

Year:  2005        PMID: 16196511     DOI: 10.5858/2005-129-1237-EDIAP

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  11 in total

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2.  Multicenter Assessment of Gram Stain Error Rates.

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Journal:  J Clin Microbiol       Date:  2016-02-17       Impact factor: 5.948

Review 3.  What is quality in surgical pathology?

Authors:  R E Nakhleh
Journal:  J Clin Pathol       Date:  2006-07       Impact factor: 3.411

Review 4.  Laboratory results that should be ignored.

Authors:  Dirk M Elston
Journal:  MedGenMed       Date:  2006-10-11

5.  How trustworthy is a diagnosis in head and neck surgical pathology? A consideration of diagnostic discrepancies (errors).

Authors:  Julia A Woolgar; Alfio Ferlito; Kenneth O Devaney; Alessandra Rinaldo; Leon Barnes
Journal:  Eur Arch Otorhinolaryngol       Date:  2011-02-22       Impact factor: 2.503

6.  A Six-Sigma approach for comparing diagnostic errors in healthcare-where does laboratory medicine stand?

Authors:  Giuseppe Lippi; Mario Plebani
Journal:  Ann Transl Med       Date:  2018-05

7.  Quality Measures in Pre-Analytical Phase of Tissue Processing: Understanding Its Value in Histopathology.

Authors:  Shalinee Rao; Suresh Masilamani; Sandhya Sundaram; Prathiba Duvuru; Rajendiran Swaminathan
Journal:  J Clin Diagn Res       Date:  2016-01-01

8.  Analysis of errors in histology by root cause analysis: a pilot study.

Authors:  P Morelli; E Porazzi; M Ruspini; U Restelli; G Banfi
Journal:  J Prev Med Hyg       Date:  2013-06

Review 9.  Confusion-specimen mix-up in dermatopathology and measures to prevent and detect it.

Authors:  Wolfgang Weyers
Journal:  Dermatol Pract Concept       Date:  2014-01-31

10.  Clinical audit of repeat fine needle aspiration in a general cytopathology service.

Authors:  Rachna Goyal; Pankaj Kumar Garg; Arati Bhatia; Vinod Kumar Arora; Navjeevan Singh
Journal:  J Cytol       Date:  2014-01       Impact factor: 1.000

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