What is Measurement of Uncertainty?
Measurement Uncertainty (MU) relates to the margin of doubt that exists for the result of any measurement, as well as how significant the doubt is. For example, a piece of string may measure 20 cm plus or minus 1 cm, at the 95% confidence level. As a result, this could be written: 20 cm ±1 cm, with a confidence of 95%. Therefore, we are 95% sure that the piece of string is between 19 cm and 21 cm long.
Standards such as ISO 15189 require that the laboratory must determine uncertainty for each test. However, they have not specified how this should be done.
How do we calculate Measurement Uncertainty using QC data?
Employing your QC data to calculate uncertainty makes several assumptions; your test system is under control, the patient samples are treated in the same manner as your controls and gross outliers have been removed. If you choose to use your QC data to calculate this you should ensure that you use a commutable control with a matrix similar to that of a patient sample, with analytes present at clinically relevant levels
To calculate MU, labs must look at the intra-assay precision and inter-assay precision of their test.
Intra-assay precision: Sometimes known as ‘within run’ precision, is where 20 or more replicates of the same sample are run at the same time, under the same conditions (calculated from a single experiment). Intra-assay precision helps to assess systematic uncertainties
Inter-assay precision: Sometimes known as ‘between run’ precision, is where 20 or more replicates are run at different times – e.g. 1 replicate every day for 20 days (can be calculated from routine IQC data). Inter-assay precision can help identify random uncertainties within the test system.
*The Australian Association of Clinical Biochemists (AACB) recommends that at least 6 months’ worth of QC data are used when calculating the inter-assay precision1.
Once the data is collected, you must calculate the standard error of the mean (SEM) of the intra-assay precision (A) and the SD of the inter-assay precision (B) in order to measure the uncertainty (u). Once A and B have been calculated, they need to be squared, added together and the square root of the sum found:
As uncertainty is calculated as SD and 1SD is equal to 68% confidence on a standard Gaussian curve, we can conclude that if we multiply using a coverage factor of 2, we can attain 2SD confidence of 95%. This is known as the Expanded Uncertainty (U):
What is the Advantage of Measurement Uncertainty for a lab?
Labs need to carry out MU as it is a requirement of ISO 15189. It states: “The laboratory shall determine measurement uncertainty for each measurement procedure, in the examination phases used to report measured quantity values on patients’ samples. The laboratory shall define the performance requirements for the measurement uncertainty of each measurement procedure and regularly review estimates of measurement uncertainty”.
MU also helps determine whether the difference between two results is negligible due to uncertainty or significant due to a genuine change in condition of the patient; giving labs a greater confidence in reported results.
How can Randox help?
Our new Acusera 24.7 Live Online software provides automatic calculation of MU, saving valuable time and helping labs meet ISO 15189 requirements with ease.
Contact email@example.com to find out how your lab can benefit from Acusera 24.7 Live Online
According to the NHS Litigation Authority; in 2015 within the UK alone, £193,680,744.30 was spent on ‘wrong diagnosis’ or ‘failed/delayed diagnosis’ causing huge financial strain and impact on labs.
With approximately 75% of clinical decisions and diagnosis based on laboratory test results. The only way to guarantee a high degree of accuracy is to implement a good Quality Control plan. The importance of this is recognised globally, several bodies exist internationally including ISO (International organisation for standardisation) who have developed a set of guidelines and quality systems to ensure the reliability of laboratory test results.
So what can you do to improve accuracy and reliability?
Choose a third party QC
ISO 151589:2012 Section 126.96.36.199 states that “the use of third party control materials should be considered, either instead of, or in addition to, any control materials supplied by the reagent or instrument manufacturer”.
First Party Controls are those manufactured by the instrument/reagent manufacturer. These controls are optimised specifically for use with the manufacturers test system and therefore will mask a multitude of weaknesses. First Party Controls tend to result in perceived accuracy and a biased assessment of performance.
Third Party Controls on the other hand are designed to be completely independent and are not optimised for use with a specific test or system. Leading manufacturers of third party controls will assign target values based on data collected from thousands of independent laboratories, ensuring the availability of statistically robust multi-method, multi-analyser data. Therefore laboratories using Third Party Controls can be assured of unbiased error detection across multiple platforms.
Randox Acusera is a world leading manufacturer of true third party controls providing a cost effective, high quality solution for any laboratory-regardless of size or budget.
Look out for QC samples with clinically relevant concentrations
ISO 15189:2012 states that ‘The laboratory should choose concentrations of control materials wherever possible, especially at or near clinical decision values, which ensure the validity of decisions made’.
It is important to assess the full clinical range of an assay i.e. the range between the lowest and highest results which can be reliably reported. In order to make sure a laboratory instrument is performing accurately across the full clinical range and in particular at the medical decision level, QC materials that cover low, normal and elevated concentrations should be used.
Due to the superior manufacturing process used by Randox, QC target values consistently cover the MDL of tests. By ensuring the controls in use cover clinical decision levels laboratories can be confident of the reliability and accuracy of the patient results they release.
Opt for a commutable control material
A good QC material has many essential properties but above all, controls must perform consistently and reflect the performance of patient samples – if a control meets these requirements then we can say it is commutable. Having a commutable control would aid in the prevention of incorrect patient results because they replicate the performance of a patient sample and react to the test system in a similar manner. Use of a commutable control will also reduce costly shifts in QC target values when reagent batch is changed.
At Randox we take quality seriously, that’s why all QC products are manufactured to the highest possible standard, delivering controls of unrivalled quality. Designed to be commutable, the Acusera range will ensure accurate and reliable instrument performance while simultaneously helping laboratories to meet ISO 15189:2012 requirements. A good QC process will include the use of Third Party Controls, Clinically Relevant Concentrations and controls which can be described as commutable. By employing Quality Control’s that encompass these traits, a laboratory professional can be certain that they have taken the necessary steps to decrease incorrect results and therefore potential misdiagnosis.