Improving the accuracy of chloride measurements through participation in regular external quality assessment programme.

BACKGROUND: A chloride test is an integral part of a basic metabolic panel that is essential for the assessment of a patient's acid-base and electrolyte status. While many methods are available commercially for the routine measurement of chloride, there is a need to address the accuracy and variability among the measurement results, especially with the prevalence of patients seeking treatment across different healthcare providers for alternative opinions. METHOD: A method based on sector field inductively coupled plasma isotope dilution mass spectrometry (SF-ICP-IDMS) was developed for the measurement of chloride in human serum. The SF-ICP-IDMS method was then used to assign the target values in the Health Sciences Authority (HSA) External Quality Assessment (EQA) Programme to evaluate the results of chloride test from participating clinical laboratories. RESULTS: The accuracy of the measurements was evaluated by comparing the results with the certified values of Electrolytes in Frozen Human Serum Certified Reference Materials (SRM 956c and SRM 956d) from the National Institute of Standards and Technology (NIST) at different chloride concentration levels. Over a five-year period from 2014-2018, the number of clinical laboratories which participated in the EQA Programme increased from 23 to 33. Comparison of robust means from the laboratories' results with our assigned target values revealed a reduction in relative deviation over time. The relationship between the deviation of each brand of clinical analysers and the chloride levels was established, where a larger deviation was uncovered at low chloride concentration. The SF-ICP-IDMS method was further demonstrated to be comparable with methods used by other metrology institutes in an international comparison organised by HSA under the auspice of the Consultative Committee for Amount of Substance - Metrology in Chemistry and Biology (CCQM). CONCLUSION: The use of metrologically traceable assigned target values enabled the study of method biasness from a small pool of dataset in each of the four brands of clinical analysers in HSA EQA Programme. This work underscores the need to improve the accuracy of chloride measurements by regular participation in an accuracy-based EQA Programme.

A Monte Carlo approach for estimating measurement uncertainty using standard spreadsheet software.

Despite the importance of stating the measurement uncertainty in chemical analysis, concepts are still not widely applied by the broader scientific community. The Guide to the expression of uncertainty in measurement approves the use of both the partial derivative approach and the Monte Carlo approach. There are two limitations to the partial derivative approach. Firstly, it involves the computation of first-order derivatives of each component of the output quantity. This requires some mathematical skills and can be tedious if the mathematical model is complex. Secondly, it is not able to predict the probability distribution of the output quantity accurately if the input quantities are not normally distributed. Knowledge of the probability distribution is essential to determine the coverage interval. The Monte Carlo approach performs random sampling from probability distributions of the input quantities; hence, there is no need to compute first-order derivatives. In addition, it gives the probability density function of the output quantity as the end result, from which the coverage interval can be determined. Here we demonstrate how the Monte Carlo approach can be easily implemented to estimate measurement uncertainty using a standard spreadsheet software program such as Microsoft Excel. It is our aim to provide the analytical community with a tool to estimate measurement uncertainty using software that is already widely available and that is so simple to apply that it can even be used by students with basic computer skills and minimal mathematical knowledge.