Implementation and application of moving average as continuous analytical quality control instrument demonstrated for 24 routine chemistry assays

2017 ◽  
Vol 55 (8) ◽  
pp. 1142-1151 ◽  
Author(s):  
Huub H. van Rossum ◽  
Hans Kemperman

Abstract Background: General application of a moving average (MA) as continuous analytical quality control (QC) for routine chemistry assays has failed due to lack of a simple method that allows optimization of MAs. A new method was applied to optimize the MA for routine chemistry and was evaluated in daily practice as continuous analytical QC instrument. Methods: MA procedures were optimized using an MA bias detection simulation procedure. Optimization was graphically supported by bias detection curves. Next, all optimal MA procedures that contributed to the quality assurance were run for 100 consecutive days and MA alarms generated during working hours were investigated. Results: Optimized MA procedures were applied for 24 chemistry assays. During this evaluation, 303,871 MA values and 76 MA alarms were generated. Of all alarms, 54 (71%) were generated during office hours. Of these, 41 were further investigated and were caused by ion selective electrode (ISE) failure (1), calibration failure not detected by QC due to improper QC settings (1), possible bias (significant difference with the other analyzer) (10), non-human materials analyzed (2), extreme result(s) of a single patient (2), pre-analytical error (1), no cause identified (20), and no conclusion possible (4). Conclusions: MA was implemented in daily practice as a continuous QC instrument for 24 routine chemistry assays. In our setup when an MA alarm required follow-up, a manageable number of MA alarms was generated that resulted in valuable MA alarms. For the management of MA alarms, several applications/requirements in the MA management software will simplify the use of MA procedures.

Author(s):  
Huub H. van Rossum ◽  
Hans Kemperman

AbstractBackground:To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA.Methods:MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin.Results:Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection.Conclusions:Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.


1986 ◽  
Vol 18 (4-5) ◽  
pp. 35-41 ◽  
Author(s):  
M. J. Gardner ◽  
D T. E. Hunt ◽  
G. Topping

It is widely recognised that, unless special steps are taken, analytical results from a group of laboratories engaged in a monitoring programme are likely to be of poor comparability. This in turn can prejudice the conclusions drawn from the results of monitoring. On the basis of previous studies, the problem is known to be particularly acute for measurements of trace metals in saline waters. Recognising the difficulty, the Marine Pollution Monitoring Management Group (MPMMG) and the Water Research centre (WRc) have organised a programme of Analytical Quality Control (AQC). This has the objective of ensuring that analytical results for filterable cadmium and mercury in saline waters, obtained by water industry and other relevant laboratories, are of adequate accuracy and comparability for their intended uses. WRc is to coordinate a series of tests, some involving distributions of standards and samples, which the participating laboratories undertake; this series of tests, the background to the approach and some of the results obtained to date are described here.


2015 ◽  
Vol 30 (6) ◽  
pp. 302-309 ◽  
Author(s):  
F. Marques-Garcia ◽  
M.F. Garcia-Codesal ◽  
M.R. Caro-Narros ◽  
T. Contreras-SanFeliciano

Talanta ◽  
2021 ◽  
Vol 228 ◽  
pp. 122137
Author(s):  
Alaa A. Makki ◽  
Suha Elderderi ◽  
Victor Massot ◽  
Renaud Respaud ◽  
Hugh.J. Byrne ◽  
...  

2001 ◽  
Vol 84 (6) ◽  
pp. 1786-1792 ◽  
Author(s):  
Philippe Quevauviller

Abstract Reference materials represent an invaluable tool for analytical quality control. Certified Reference Materials (CRMs) are used for the validation of methods, whereas various types of (uncertified) Reference Materials (RMs) are used for routine quality control (establishment of control charts) and interlaboratory testing (e.g., proficiency testing). This paper provides background information on the production and use of environmental RMs and describes recent CRMs produced by the BCR (European Commission) for quality assurance in environmental analysis.


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