Literature DB >> 16482988

A 2-year study of Gram stain competency assessment in 40 clinical laboratories.

Nancy Goodyear1, Sara Kim, Mary Reeves, Michael L Astion.   

Abstract

We used a computer-based competency assessment tool for Gram stain interpretation to assess the performance of 278 laboratory staff from 40 laboratories on 40 multiple-choice questions. We report test reliability, mean scores, median, item difficulty, discrimination, and analysis of the highest- and lowest-scoring questions. The questions were reliable (KR-20 coefficient, 0.80). Overall mean score was 88% (range, 63%-98%). When categorized by cell type, the means were host cells, 93%; other cells (eg, yeast), 92%; gram-positive, 90%; and gram-negative, 88%. When categorized by type of interpretation, the means were other (eg, underdecolorization), 92%; identify by structure (eg, bacterial morphologic features), 91%; and identify by name (eg, genus and species), 87%. Of the 6 highest-scoring questions (mean scores, > or = 99%) 5 were identify by structure and 1 was identify by name. Of the 6 lowest-scoring questions (mean scores, < 75%) 5 were gram-negative and 1 was host cells. By type of interpretation, 2 were identify by structure and 4 were identify by name. Computer-based Gram stain competency assessment examinations are reliable. Our analysis helps laboratories identify areas for continuing education in Gram stain interpretation and will direct future revisions of the tests.

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Year:  2006        PMID: 16482988

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


  3 in total

1.  Multicenter Assessment of Gram Stain Error Rates.

Authors:  Linoj P Samuel; Joan-Miquel Balada-Llasat; Amanda Harrington; Robert Cavagnolo
Journal:  J Clin Microbiol       Date:  2016-02-17       Impact factor: 5.948

2.  Competency assessment of microbiology medical laboratory technologists in Ontario, Canada.

Authors:  Marc Desjardins; Christine Ann Fleming
Journal:  J Clin Microbiol       Date:  2014-06-04       Impact factor: 5.948

3.  Performances of automated digital imaging of Gram-stained slides with on-screen reading against manual microscopy.

Authors:  Adrien Fischer; Nouria Azam; Lara Rasga; Valérie Barras; Manuela Tangomo; Gesuele Renzi; Nicolas Vuilleumier; Jacques Schrenzel; Abdessalam Cherkaoui
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2021-05-08       Impact factor: 3.267

  3 in total

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