Abstract
There appears to be a growing debate with regard to the use of “Westgard style” total error and “GUM style” uncertainty in measurement. Some may argue that the two approaches are irreconcilable. The recent appearance of an article “Quality goals at the crossroads: growing, going, or gone” on the well-regarded Westgard Internet site requires some comment. In particular, a number of assertions which relate to ISO 15189 and uncertainty in measurement appear misleading. An alternate view of the key issues raised by Westergard may serve to guide and enlighten others who may accept such statements at face value.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Declaration of conflicting interests: The authors declared no potential conflicts of interest with respect to the authorship and/or publication of this article.
References
1. Panteghini M, Sandberg S. Total error vs. measurement uncertainty: the match continues. Clin Chem Lab Med 2016;54:195–6.10.1515/cclm-2015-1036Search in Google Scholar PubMed
2. Westgard JO. Useful measures and models for analytical quality management in medical laboratories. Clin Chem Lab Med 2016;54:223–33.10.1515/cclm-2015-0710Search in Google Scholar PubMed
3. Westgard S. Quality requirements and standards – quality goals at the crossroads: growing, going or gone? Available at: http://www.westgard.com/gone-goals-gone.htm. Accessed: March 2016.Search in Google Scholar
4. International Organization for Standardization. ISO 15189:2012, Medical laboratories – Requirements for quality and competence. Available at: http://www.iso.org/iso/catalogue_detail?csnumber=56115. Accessed: March 2016.Search in Google Scholar
5. Bureau International des Pois et Mesures. JCGM 200:2012, International vocabulary of metrology – basic and general concepts and associated terms (VIM). Available at: http://www.bipm.org/en/publications/guides/vim.html. Accessed: March 2016.Search in Google Scholar
6. Bureau International des Pois et Mesures. JCGM 100:2008, Evaluation of measurement data – guide to the expression of uncertainty in measurement (GUM). Available at: http://www.bipm.org/en/publications/guides/gum.html. Accessed: March 2016.Search in Google Scholar
7. Tate JR, Johnson R, Barth JH, Panteghini M. Harmonization of laboratory testing – A global activity. Clin Chim Acta 2014;432:1–3.10.1016/j.cca.2014.02.006Search in Google Scholar PubMed
8. Koerbin G, Sikaris KA, Jones GR, Ryan J, Reed M, Tate J, et al. Evidence-based approach to harmonized reference intervals. Clin Chim Acta 2014;432:99–107.10.1016/j.cca.2013.10.021Search in Google Scholar PubMed
9. Tate JR, Sikaris KA, Jones GR, Yen T, Koerbin G, Ryan J, et al. Harmonising adult and paediatric reference intervals in Australia and New Zealand: An evidence-based approach for establishing a first panel of chemistry analytes. Clin Biochem Rev 2014;35:213–35.Search in Google Scholar
10. Koerbin G, Tate J, Ryan J, Jones GR, Sikaris KA, Kanowski D, et al. Bias assessment of general chemistry analytes using commutable samples. Clin Biochem Rev 2014;35:203–11.Search in Google Scholar
11. Fraser CG. Quality specifications. In: Fraser CG, editor. Biological variation: from principles to practice. Washington, DC: AACC Press, 2001:29–66.Search in Google Scholar
12. Linnet KL, Boyd JC. Selection and analytical evaluation of methods – with statistical techniques. In: Burtis CA, Ashwood ER, Burns DE, editors. Tietz, Fundamentals of Clinical Chemistry. St Louis, MO: Saunders Elsevier, 2008:201–28.Search in Google Scholar
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