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Importance of the choice of assumptions and models in the estimation of analytical quality specifications
Authors:Per Hyltoft Petersen
Institution:(1) Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense-C, Denmark e-mail: per.hyltoft.Petersen@ouh.fyns-amt.dk, DK;(2) NOKLUS Norwegian centre for external quality assurance of primary care laboratories, Division of General Practice, University of Bergen, Norway, NO
Abstract:The validity of any model depends on its ability to imagine the situation or problem to which it is applied. Further, the assumptions made in relation to the model are determining for the actual outcome. Within the field of clinical biochemistry a lot of models for analytical quality specifications, based on a variety of concepts and ’clinical settings’, have been proposed. A hierarchical structure for application of these approaches and models has been agreed on at several occasions in 1999. In this hierarchy, the highest rank is given to evaluation of analytical quality specifications based on ’clinical settings’/’clinical outcome’ models, followed by specifications based on biological variation and on ’clinicians opinions’. This contribution, deals with the problems of combining random and systematic errors and the implications of application of different models to a variety of clinical settings. Received: 1 June, 2002 Accepted: 17 July 2002 Presented at the European Conference on Quality in the Spotlight in Medical Laboratories, 7–9 October 2001, Antwerp, Belgium
Keywords:  Analytical bias  Bi-modal distributions  Ordinal scale  Point-of-care-testing (POCT)  Random error  Ratio scale  Systematic errors  Uni-modal distributions
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