Issues in assessing analytical performance specifications in healthcare systems assembling multiple laboratories and measuring systems

Abstract

Abstract Analytical performance specifications (APS) are usually compared to the intermediate reproducibility uncertainty of measuring a particular measurand using a single in vitro diagnostic medical device (IVD MD). Healthcare systems assembling multiple laboratories that include several IVD MDs and cater to patients suffering from long-term disease conditions mean that samples from a patient are analyzed using a few IVD MDs, sometimes from different manufacturers, but rarely all IVD MDs in the healthcare system. The reproducibility uncertainty for results of a measurand measured within a healthcare system and the components of this measurement uncertainty is useful in strategies to minimize bias and overall measurement uncertainty within the healthcare system. The root mean squares deviation (RMSD) calculated as the sample standard deviation (SD) and relative SD includes both imprecision and bias and is appropriate for expressing such uncertainties. Results from commutable stabilized internal and external control samples, from measuring split natural patient samples or using big-data techniques, are essential in monitoring bias and measurement uncertainties in healthcare systems. Variance component analysis (VCA) can be employed to quantify the relative contributions of the most influential factors causing measurement uncertainty. Such results represent invaluable information for minimizing measurement uncertainty in the interest of the healthcare systemʼs patients.