Bertil Magnusson

Uncertainty of standard addition experiments: a novel approach to include the uncertainty associated with the standard in the model equation

A new model equation for determining the measurement result in standard addition experiments was derived and successfully applied to the quantitative determination of rhodium in automotive catalysts. Existing equations for standard addition experiments with gravimetric preparation were changed in order to integrate the novel idea of including the uncertainty associated with the standard into the model equation. Using this novel equation combined with the ordinary least squares algorithm for the regression line also yielded a new formula for the associated measurement uncertainty. This uncertainty accounts for the first time for the uncertainty associated with the standard. The derivation for the model equation and the resulting associated measurement uncertainty is shown for gravimetric standard addition experiments both with and without an internal standard.

Methodology in internal quality control of chemical analysis

Internal quality control (IQC) is an essential feature of routine analysis, serving to ensure that the uncertainty of results found during the validation of a procedure is maintained over long periods of time. The primary method of IQC is to analyse a surrogate material alongside the test materials in every run of analysis and thus address run-to-run precision (a subset of VIM3-defined ‘intermediate conditions’). This ‘control material’ must be as similar as practicable in composition to the routine test materials, although there are always some differences. Results from the control material (control values) are plotted on a control chart, and out-of-control results have to be investigated and problems rectified. Considerable care is needed in obtaining correct values of the parameters for determining statistical control limits, and these can be adequately estimated only during routine use of the analytical procedure. In contrast, target control limits have to be set on a fitness-for-purpose basis and are necessarily wider that statistical control limits. An additional type of internal quality control can be executed by the analysis of duplicate test portions of some of the actual test samples. This provides a realistic dispersion, but addresses only repeatability precision. A further complication of duplication is that the precision of results typically varies with concentration of the analyte.

Use of characteristic functions derived from proficiency testing data to evaluate measurement uncertainties

Interlaboratory comparisons show that reproducibility standard deviations are dependent on the concentration of the analyte. Many attempts have been made to model this. In this paper, ‘characteristic’ functions are used for modelling the concentration dependence of the reproducibility standard deviations based on data from proficiency tests for water analysis. The characteristics of the resulting functions can be used for the estimation of measurement uncertainties at different concentration levels. These functions are especially useful to determine the concentration levels below which absolute uncertainties tend to be constant and above which the relative uncertainties are more constant. By comparing the characteristic functions of different analytical procedures for the determination of the same analyte, the performance of these procedures under routine application can be compared. Finally, these functions may be used to get an indication on the average quality of analytical result in a specific field to be used by regulators in order to formulate requirements in the legislation that are in accordance with current measurement quality.

Routine internal- and external-quality control data in clinical laboratories for estimating measurement and diagnostic uncertainty using GUM principles

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 (μmol/L) and relative (%). An expanded measurement uncertainty of 12 μmol/L associated with concentrations of creatinine below 120 μmol/L and of 10% associated with concentrations above 120 μmol/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 μmol/L associated with concentrations of creatinine below 100 μmol/L and 14 % associated with concentrations above 100 μmol/L.

Method validation in analytical sciences: discussions on current practice and future challenges

Eurachem held a workshop on method validation in analytical sciences in Gent, Belgium, on 9–10 May 2016. A summary of the working group discussions is provided here. The discussions covered a range of issues concerned with current practice and future challenges in method validation, i.e. setting requirements for a method to be validated; planning validation studies; validation of qualitative and semi-quantitative methods; validation of multi-parameter methods; determination of trueness/bias; assessment of working range; validation in microbiology; and method validation under flexible scope of accreditation. Delegates (129) from 24 different countries and from different backgrounds, e.g. from both public and private laboratories, laboratory associations, accreditation bodies and universities, attended the working groups, thus providing opportunities to collect a variety of views and experiences as well as to identify potential gaps in current guidance and regulations. While the practicalities of assessing method performance characteristics are generally well understood, the issue of setting requirements for those characteristics beforehand is less straightforward. Although a number of documents addressing the principles of method validation are available, guidance on dealing with more complex and ‘non-ideal’ situations, as well as examples of good practice, would be welcomed and greater harmonisation of approaches was deemed necessary. There remains a need for guidance on both the concepts that apply to ‘qualitative’ or ‘nominal’ test methods and on the practical implementation of validation studies in such cases.

Full method validation in clinical chemistry

Clinical chemistry is subject to the same principles and standards used in all branches of metrology in chemistry for validation of measurement methods. The use of measuring systems in clinical chemistry is, however, of exceptionally high volume, diverse and involves many laboratories and systems. Samples for measuring the same measurand from a certain patient are likely to encounter several measuring systems over time in the process of diagnosis and treatment of his/her diseases. Several challenges regarding method validation across several laboratories are therefore evident, but rarely addressed in current standards and accreditation practices. The purpose of this is paper to address some of these challenges, making a case that appropriate conventional method validation performed by the manufacturers fulfils only a part of the investigation needed to show that they are fit for purpose in different healthcare circumstances. Method validation across several laboratories using verified commercially available measuring systems can only be performed by the laboratories—users themselves in their own circumstances, and need to be emphasised more by the laboratories themselves and accreditation authorities alike.

Allowable bias when monitoring reference change values

Two articles in the current issue of The Scandinavian Journal of Clinical & Laboratory Investigation deal with the reference change measured by two different measurement systems and the maximal allowable bias between two systems. Here follows a general comment on this important issue. In 1983, Harris and Yasaka [1] pioneered in suggesting the concept of ‘reference change values’ (rCv) being ‘the value that must be exceeded before a change in consecutive test results is statistically significant at a predetermined probability’ [2]. The concept of reference change [3] also known by the name critical difference provides a theoretical and practical framework for evaluation of whether a change in concentration of a measurand requires medical attention.

Survey analysis and chemical characterization of solid inhomogeneous samples using a general homogenization procedure including acid digestion, drying, grinding and briquetting together with X-ray fluorescence

A survey analysis and chemical characterization methodology for inhomogeneous solid waste samples of relatively large samples (typically up to 100g) using X-ray fluorescence following a general homogenization procedure is presented. By using a combination of acid digestion and grinding various materials can be homogenized e.g. pure metals, alloys, salts, ores, plastics, organics. In the homogenization step, solid material is fully or partly digested in a mixture of nitric acid and hydrochloric acid in an open vessel. The resulting mixture is then dried, grinded, and finally pressed to a wax briquette. The briquette is analyzed using wave-length dispersive X-ray fluorescence with fundamental parameters evaluation. The recovery of 55 elements were tested by preparing samples with known compositions using different alloys, pure metals or elements, oxides, salts and solutions of dissolved compounds. It was found that the methodology was applicable to 49 elements including Na, Mg, Al, Si, P, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Y, Zr, Nb, Mo, Ru, Rh, Pd, Ag, Cd, In, Sn, Sb, Te, Cs, Ba, La, Ce, Ta, W, Re, Ir, Pt, Au, Tl, Pb, Bi, and Th, that all had recoveries >0.8. 6 elements were lost by volatilization, including Br, I, Os, and Hg that were completely lost, and S and Ge that were partly lost. Since all lanthanides are chemically similar to La and Ce, all actinides are chemically similar to Th, and Hf is chemically similar to Zr, it is likely that the method is applicable to 77 elements. By using an internal standard such as strontium, added as strontium nitrate, samples containing relatively high concentrations of elements not measured by XRF (hydrogen to fluorine), e.g. samples containing plastics, can be analyzed.

Measurement Quality in Water Analysis

Measurement quality is about fulfilling analytical requirements, which should be based on the intended use of the results. In the water sector in Europe the requirements are set in European Union (EU) directives for groundwater, freshwater, and coastal sea water (Water Framework Directive (WFD)), and in a separate directive for drinking water. The requirements in the WFD are set on limit of quantification single and measurement uncertainty, and in the drinking water directive on detection capability (limit of detection) and precision and trueness.

Metrology in Chemistry and Traceability of Analytical Measurement Results

This gives an overview of metrology in analytical chemistry as well as describing the role of measurement traceability. The traceability part of the presentation is based on the CITAC position paper on measurement traceability (Traceability in Chemical Measurement, Accred. Qual. Assur. (2000) 5:388-389)