Measurement uncertainty in laboratory reports: A tool for improving the interpretation of test results (original) (raw)
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Uncertainty of Measurement in Laboratory Medicine
Journal of Medical Biochemistry, 2018
An adequate assessment of the measurement uncertainty in a laboratory medicine is one of the most important factors for a reliable interpretation of the results. A large number of standards and guidelines indicate the need for a proper assessment of the uncertainty of measurement re sults in routine laboratory practice. The available docu ments ge nerally recommend participation in the proficiency schemes/ external quality control, as well as the internal quality control, in order to primarily verify the quality performance of the method. Although all documents meet the re quirements of the International Standard, ISO 15189, the standard itself does not clearly define the method by which the measurement results need to be assessed and there is no harmonization in practice regarding to this. Also, the uncertainty of measurement results is the data relating to the measured result itself, but all factors that influence the interpretation of the measured value, which is ultimately used for diagnosis and monitoring of the patient's treat ment, should be taken into account. So in laboratory medicine, an appropriate assessment of the uncertainty of the measurement results should have the ultimate goal of reducing diagnostic uncertainty. However, good profes sional laboratory practice and understanding analytical aspects of the test for each individual laboratory is ne ces sary to adequately define the uncertainty of measurement results for specific laboratory tests, which helps to imple ment good clinical practice. Also, setting diagnoses in medicine is a decision with a certain degree of uncertainty, rather than statistically and mathematically calculated conclusion.
Scandinavian Journal of Clinical and Laboratory Investigation, 2019
Laboratory tests are an integral part of clinical decision making. Therefore, measurement uncertainty comes into prominence in the context of the accuracy of the laboratory result. This study aims to investigate measurement uncertainty of 14 immunoassay analytes, to compare them with different quality goals and to utilize them in the result interpretation. Measurement uncertainties of 14 immunoassay analytes were estimated by using internal and external quality control data by using Nordtest approach. Expanded uncertainties (U) were compared with allowable total error (TEa%), permissible relative deviation in the external quality assessment (PRD EQA %) and permissible expanded uncertainty for external quality assessment (pU EQAS %). Uncertainties were incorporated into the calculation of reference change values (RCV) and uncertainty adjusted reference intervals. RCVs of 14 analytes were calculated by three different methods reported by Harris, Clinical Laboratory Standards Institute (CLSI), and National Pathology Accreditation Advisory Council (NPAAC). Measurement uncertainties of TSH, estradiol, LH, progesterone, prolactin, and vitamin B12 were within defined allowable limits. U one-sided FT3 and U one-sided ferritin exceeded defined TEa% but U FT3 and U ferritin were found below the limits of pU EQAS %. Measurement uncertainties of FT4, cortisol, DHEAS, FSH, testosterone, and folate did not meet the specification limits. Recently defined permissible expanded uncertainty promises new targets to compare estimated measurement uncertainty. Measurement uncertainty should be applied to the laboratory result interpretation within the scope of RCV and reference interval to obviate misdiagnosis. Furthermore, we suggest that laboratories should inform clinicians about the tests with high uncertainties to assist them making the right clinical diagnosis.
Clinical Chemistry and Laboratory Medicine (CCLM), 2015
Background: International organizations require from medical laboratories a quantitative statement of the uncertainty in measurement (UM) to help interpret patient results. The French accreditation body (COFRAC) recommends an approach (SH GTA 14 IQC/EQA method) using both internal quality control (IQC) and external quality assessment (EQA) data. The aim of this work was to validate an alternative way to quantify UM using only EQA results without any need for IQC data. This simple and practical method, which has already been described as the long-term evaluation of the UM (LTUM), is based on linear regression between data obtained by participants in EQA schemes and target values. We used it for 43 routine analytes covering biochemistry, immunoassay, and hemostasis fields. Methods: Data from 50 laboratories participating in Pro-BioQual (PBQ) EQA schemes over 25 months were used to obtain estimates of the median and 90th percentile LTUM and to compare them to the usual analytical goals. Then, the two UM estimation methods were compared using data from 20 laboratories participating in both IQC and EQA schemes. Results: Median LTUMs ranged from 2.9% (sodium) to 16.3% (bicarbonates) for biochemistry analytes, from 12.6% (prothrombin time) to 18.4% (factor V) for hemostasis analytes when using the mean of all participants, and were around 10% for immunoassays when using the peergroup mean. Median LTUMs were, in most cases, slightly lower than those obtained with the SH GTA 14 method, whatever the concentration level. Conclusions : LTUM is a simple and convenient method that gives UM estimates that are reliable and comparable to those of recommended methods. Therefore, proficiency testing (PT) organizers are allowed to provide participants with an additional UM estimate using only EQA data and which could be updated at the end of each survey.
The uncertainty concept and its implications for laboratory medicine
Laboratory measurement performance needs to be estimated in a uniform and standardized manner to allow comparison of results and become scientifically valid. A much-used measure is the variation of repeated measurements and the agreement of the result with a reference or true value. There are thus principally two types of variation of results of measurements, systematic and random. Information on both types needs to be attached to the result of the measurement; that information shall be informative and understood by the end-users. Provided some rules are observed that can be achieved by relying on the concept of uncertainty. Systematic variations result in changes in the agreement between the obtained value and the true value, i.e. the trueness of the result. If the bias, the statistic used to measure trueness, can be assessed, the results can be compensated for the deviation. Bias is however difficult to assess and particularly so in biological systems since the true value is rarely known. Bias can then be expressed as the deviation from a reference value obtained by reference methods. The random variation, precision, is the closeness of the average of the results of a large number of replicate measurements. The statistic that is used to describe precision numerically is imprecision. The over-* Definitions of a selection of metrological terms used in the document are given in the Appendix.
2017
OBJECTIVE To estimate relative expanded uncertainty measurement of routine clinical chemistry analytes for international organisation for standardisation 15189 accreditation. METHODS This cross-sectional study was conducted at Dow International Medical College, Karachi, from September 2013 to May 2014. During the process of international organisation for standardisation 15189 accreditation, measurement uncertainty was estimated for 13 clinical chemistry analytes using top-down approach. Relative combined uncertainty of each analyte was calculated by combining uncertainties of imprecision, bias and calibrators. Results of estimated imprecision, bias and expanded uncertainties were observed for allowable imprecision, bias and total analytical error for the respective analyte.. RESULTS Uncertainties of imprecision were found within acceptable limits for all analytes except total protein (2.4% vs. 1.3%). Uncertainties of bias of all analytes were found within allowable limits. Relative ...
The use of error and uncertainty methods in the medical laboratory
Clinical Chemistry and Laboratory Medicine (CCLM), 2017
Error methods – compared with uncertainty methods – offer simpler, more intuitive and practical procedures for calculating measurement uncertainty and conducting quality assurance in laboratory medicine. However, uncertainty methods are preferred in other fields of science as reflected by the guide to the expression of uncertainty in measurement. When laboratory results are used for supporting medical diagnoses, the total uncertainty consists only partially of analytical variation. Biological variation, pre- and postanalytical variation all need to be included. Furthermore, all components of the measuring procedure need to be taken into account. Performance specifications for diagnostic tests should include the diagnostic uncertainty of the entire testing process. Uncertainty methods may be particularly useful for this purpose but have yet to show their strength in laboratory medicine. The purpose of this paper is to elucidate the pros and cons of error and uncertainty methods as gr...
Scandinavian Journal of Clinical & Laboratory Investigation, 2012
Healthcare laboratories are increasingly joining into larger laboratory organizations encompassing several physical laboratories. This caters for important new opportunities for re-defining the concept of a 'laboratory' to encompass all laboratories and measurement methods measuring the same measurand for a population of patients. in order to make measurement results, comparable bias should be minimized or eliminated and measurement uncertainty properly evaluated for all methods used for a particular patient population. The measurement as well as diagnostic uncertainty can be evaluated from internal and external quality control results using guM principles. in this paper the uncertainty evaluations are described in detail using only two main components, within-laboratory reproducibility and uncertainty of the bias component according to a nordtest guideline. The evaluation is exemplified for the determination of creatinine in serum for a conglomerate of laboratories both expressed in absolute units (mmol/l) and relative (%). an expanded measurement uncertainty of 12 mmol/l associated with concentrations of creatinine below 120 mmol/l and of 10% associated with concentrations above 120 mmol/l was estimated. The diagnostic uncertainty encompasses both measurement uncertainty and biological variation, and can be estimated for a single value and for a difference. This diagnostic uncertainty for the difference for two samples from the same patient was determined to be 14 mmol/l associated with concentrations of creatinine below 100 mmol/l and 14 % associated with concentrations above 100 mmol/l.
COURSE NOTES A model for calculating measurement uncertainty in medical laboratories
Revista Român de Medicin de …, 2010
Introduction: All medical laboratories that require recognition for competency assessment have to estimate the uncertainty of measurement of assay test results "where relevant and possible" (ISO 15189:2007 Medical laboratories-Particular requirements for quality and competence). The repeated quantitative examination of an analyte with the same method will offer more or less different results. This is happening because the outcome of an assay depends not only upon the analyte itself, but also upon few error factors that could yield doubts about the obtained result. The mathematical, quantitative expression of this doubt is known as uncertainty of measurement (UM). Methods: It is the responsibility of each medical laboratory to identify all error sources that can be quantified and converted in standard deviations that could be used to estimate the type A or B of uncertainty. In the case of Romanian medical laboratories, the European Accreditation (EA) accepted as reference documents for UM estimation the Guide to the Expression of Uncertainty in Measurement (GUM) and Romanian Standard SR ENV 13005. Discussion and conclusion: In this paper, authors present and discuss the modalities of UM estimation in two different situations: when the used reference materials (calibrators) are or are not traceable to certified reference materials (CRM). Complete and informative UM reporting can only lead to better decisions in healthcare.