Literature DB >> 17145620

Measuring errors in surgical pathology in real-life practice: defining what does and does not matter.

Andrew A Renshaw1, Edwin W Gould.   

Abstract

This review summarizes our experience using blinded review as a method to measure quality in surgical pathology. It details the specifics about how the review is performed, the weaknesses in the method, and then summarizes our results so far. These results suggest that error rates correlate with the individual pathologist, the type of specimen, the type of diagnosis, subspecialization, and the number of pathologists who review a case. Errors do not correlate with workload. This method is relatively unbiased and effective at identifying significant errors in real life clinical practice. The drawback to this method is the amount of work involved. Blinded review, performed so that errors can be corrected in a timely manner, and eventually integrated into an interlaboratory review process, represents a realistic and fair method to provide quantitative quality assurance information.

Mesh:

Year:  2007        PMID: 17145620     DOI: 10.1309/5KF89P63F4F6EUHB

Source DB:  PubMed          Journal:  Am J Clin Pathol        ISSN: 0002-9173            Impact factor:   2.493


  9 in total

1.  Second opinion in breast pathology: policy, practice and perception.

Authors:  Berta M Geller; Heidi D Nelson; Patricia A Carney; Donald L Weaver; Tracy Onega; Kimberly H Allison; Paul D Frederick; Anna N A Tosteson; Joann G Elmore
Journal:  J Clin Pathol       Date:  2014-07-22       Impact factor: 3.411

Review 2.  Multiparametric and semiquantitative scoring systems for the evaluation of mouse model histopathology--a systematic review.

Authors:  Robert Klopfleisch
Journal:  BMC Vet Res       Date:  2013-06-21       Impact factor: 2.741

3.  Validation of diagnostic accuracy using digital slides in routine histopathology.

Authors:  László Fónyad; Tibor Krenács; Péter Nagy; Attila Zalatnai; Judit Csomor; Zoltán Sápi; Judit Pápay; Júlia Schönléber; Csaba Diczházi; Béla Molnár
Journal:  Diagn Pathol       Date:  2012-03-31       Impact factor: 2.644

4.  Robust extraction of quantitative structural information from high-variance histological images of livers from necropsied Soay sheep.

Authors:  Q Caudron; R Garnier; J G Pilkington; K A Watt; C Hansen; B T Grenfell; T Aboellail; A L Graham
Journal:  R Soc Open Sci       Date:  2017-07-19       Impact factor: 2.963

5.  Computational Algorithms that Effectively Reduce Report Defects in Surgical Pathology.

Authors:  Jay J Ye; Michael R Tan
Journal:  J Pathol Inform       Date:  2019-07-01

6.  A loss-based patch label denoising method for improving whole-slide image analysis using a convolutional neural network.

Authors:  Murtaza Ashraf; Willmer Rafell Quiñones Robles; Mujin Kim; Young Sin Ko; Mun Yong Yi
Journal:  Sci Rep       Date:  2022-01-26       Impact factor: 4.379

7.  Spinal giant cell-rich osteosarcoma-diagnostic dilemma and treatment strategy: A case report.

Authors:  Chen-Sheng Tseng; Chia-En Wong; Chi-Chen Huang; Hao-Hsiang Hsu; Jung-Shun Lee; Po-Hsuan Lee
Journal:  World J Clin Cases       Date:  2022-07-26       Impact factor: 1.534

8.  Diagnostic testing managed by hematopathology specialty and other laboratories: costs and patient diagnostic outcomes.

Authors:  Nicole M Engel-Nitz; Benjamin Eckert; Rui Song; Priyanka Koka; Erin M Hulbert; Jeffrey McPheeters; April Teitelbaum
Journal:  BMC Clin Pathol       Date:  2014-04-27

Review 9.  Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges.

Authors:  Maxwell A Konnaris; Matthew Brendel; Mark Alan Fontana; Miguel Otero; Lionel B Ivashkiv; Fei Wang; Richard D Bell
Journal:  Arthritis Res Ther       Date:  2022-03-11       Impact factor: 5.156

  9 in total

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