Literature DB >> 16196510

An insurer's perspective on error and loss in pathology.

David B Troxel1.   

Abstract

OBJECTIVES: To identify errors in surgical pathology practice that lead to malpractice claims, and to define the frequency and severity of pathology malpractice claims and discuss the implications.
DESIGN: Three hundred seventy-eight pathology malpractice claims reported to The Doctors Company of Napa, Calif, between 1998 and 2003, were reviewed. Nuisance claims and autopsy claims were excluded; the 335 remaining claims were analyzed.
RESULTS: Pathology claim frequency is low. Pathology claim severity is high, especially for claims involving a misdiagnosis of melanoma or a false-negative Papanicolaou test. Fifty-seven percent of claims involved the following 5 categories: breast specimens, melanoma, Papanicolaou smears, gynecologic specimens, and operational error. Sixty-three percent of claims involved failure to diagnose cancer, resulting in delay in diagnosis or inappropriate treatment.
CONCLUSION: A false-negative diagnosis of melanoma is the single most common reason for filing a malpractice claim against a pathologist. Nearly one third of misdiagnoses involve melanoma misdiagnosed as Spitz nevus, "dysplastic" nevus, spindle cell squamous carcinoma, atypical fibroxanthoma, and dermatofibroma.

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Mesh:

Year:  2005        PMID: 16196510     DOI: 10.5858/2005-129-1234-AIPOEA

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


  3 in total

1.  Malpractice and Patient Safety Concerns.

Authors:  Lisa M Reisch; Martiniano J Flores; Andrea C Radick; Hannah L Shucard; Kathleen F Kerr; Michael W Piepkorn; Raymond L Barnhill; David E Elder; Stevan R Knezevich; Joann G Elmore
Journal:  Am J Clin Pathol       Date:  2020-10-13       Impact factor: 2.493

2.  How concerns and experiences with medical malpractice affect dermatopathologists' perceptions of their diagnostic practices when interpreting cutaneous melanocytic lesions.

Authors:  Patricia A Carney; Paul D Frederick; Lisa M Reisch; Stevan Knezevich; Michael W Piepkorn; Raymond L Barnhill; David E Elder; Berta M Geller; Linda Titus; Martin A Weinstock; Heidi D Nelson; Joann G Elmore
Journal:  J Am Acad Dermatol       Date:  2015-11-11       Impact factor: 11.527

3.  Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders.

Authors:  Dariusz Kucharski; Pawel Kleczek; Joanna Jaworek-Korjakowska; Grzegorz Dyduch; Marek Gorgon
Journal:  Sensors (Basel)       Date:  2020-03-11       Impact factor: 3.576

  3 in total

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