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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Coronavirus disease 2019, first reported in China in late 2019, has quickly spread across the world. The outbreak was declared a pandemic by the World Health Organization on March 11, 2020. Here, we describe our initial efforts at the University of Florida Health for processing of large numbers of tests, streamlining data collection, and reporting data for optimizing testing capabilities and superior clinical management. Specifically, we discuss clinical and pathology informatics workflows and informatics instruments which we designed to meet the unique challenges of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. We hope these results benefit institutions preparing to implement SARS-CoV-2 testing.

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