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Demystifying EQA statistics and reports
Reports act as an important feedback tool in External Quality Assessment (EQA). Their main role is to score laboratories for their performance in an EQA round. The most common scores that apply to quantitative data are Q- and Z-scores. To calculate these scores, EQA providers need to have an assigne...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Croatian Society of Medical Biochemistry and Laboratory Medicine
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382862/ https://www.ncbi.nlm.nih.gov/pubmed/28392725 http://dx.doi.org/10.11613/BM.2017.006 |
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author | Coucke, Wim Soumali, Mohamed Rida |
author_facet | Coucke, Wim Soumali, Mohamed Rida |
author_sort | Coucke, Wim |
collection | PubMed |
description | Reports act as an important feedback tool in External Quality Assessment (EQA). Their main role is to score laboratories for their performance in an EQA round. The most common scores that apply to quantitative data are Q- and Z-scores. To calculate these scores, EQA providers need to have an assigned value and standard deviation for the sample. Both assigned values and standard deviations can be derived chemically or statistically. When derived statistically, different anomalies against the normal distribution of the data have to be handled. Various procedures for evaluating laboratories are able to handle these anomalies. Formal tests and graphical representation techniques are discussed and suggestions are given to help choosing between the different evaluations techniques. In order to obtain reliable estimates for calculating performance scores, a satisfactory number of data is needed. There is no general agreement about the minimal number that is needed. A solution for very small numbers is proposed by changing the limits of evaluation.
Apart from analyte- and sample-specific laboratory evaluation, supplementary information can be obtained by combining results for different analytes and samples. Various techniques are overviewed. It is shown that combining results leads to supplementary information, not only for quantitative, but also for qualitative and semi-quantitative analytes. |
format | Online Article Text |
id | pubmed-5382862 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Croatian Society of Medical Biochemistry and Laboratory Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-53828622017-04-07 Demystifying EQA statistics and reports Coucke, Wim Soumali, Mohamed Rida Biochem Med (Zagreb) Review Reports act as an important feedback tool in External Quality Assessment (EQA). Their main role is to score laboratories for their performance in an EQA round. The most common scores that apply to quantitative data are Q- and Z-scores. To calculate these scores, EQA providers need to have an assigned value and standard deviation for the sample. Both assigned values and standard deviations can be derived chemically or statistically. When derived statistically, different anomalies against the normal distribution of the data have to be handled. Various procedures for evaluating laboratories are able to handle these anomalies. Formal tests and graphical representation techniques are discussed and suggestions are given to help choosing between the different evaluations techniques. In order to obtain reliable estimates for calculating performance scores, a satisfactory number of data is needed. There is no general agreement about the minimal number that is needed. A solution for very small numbers is proposed by changing the limits of evaluation.
Apart from analyte- and sample-specific laboratory evaluation, supplementary information can be obtained by combining results for different analytes and samples. Various techniques are overviewed. It is shown that combining results leads to supplementary information, not only for quantitative, but also for qualitative and semi-quantitative analytes. Croatian Society of Medical Biochemistry and Laboratory Medicine 2017-02-15 2017-02-15 /pmc/articles/PMC5382862/ /pubmed/28392725 http://dx.doi.org/10.11613/BM.2017.006 Text en |
spellingShingle | Review Coucke, Wim Soumali, Mohamed Rida Demystifying EQA statistics and reports |
title | Demystifying EQA statistics and reports |
title_full | Demystifying EQA statistics and reports |
title_fullStr | Demystifying EQA statistics and reports |
title_full_unstemmed | Demystifying EQA statistics and reports |
title_short | Demystifying EQA statistics and reports |
title_sort | demystifying eqa statistics and reports |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382862/ https://www.ncbi.nlm.nih.gov/pubmed/28392725 http://dx.doi.org/10.11613/BM.2017.006 |
work_keys_str_mv | AT couckewim demystifyingeqastatisticsandreports AT soumalimohamedrida demystifyingeqastatisticsandreports |