![]() The goal in laboratory medicine is to minimize the measurement error so that it does not adversely affect the clinical decision-making process. Some have suggested that trueness should be used to refer to the agreement of the measurement to the true value and accuracy to encompass both trueness and precision.Īccuracy and precision are related to a concept called measurement error: every measurement is associated with a degree of error or uncertainty. These metrics are complementary and a good clinical test needs to be both accurate and precise. Precision measures reliability and reproducibility. Accuracy (or rather trueness) is a measure of the proximity of the test results to the true value. A precise test will produce similar results when the test is repeated multiple times. Ī test is technically accurate if it produces valid information. The most important metrics that a test must possess to be used in clinical laboratory are technical accuracy and precision. The modern clinical laboratory uses a plethora of instruments to quantify and measure different analytes and reports results that are used by clinicians. These measurements are a central part of modern clinical management they are used by clinicians to diagnose disease states, to guide treatment course and to determine prognosis. The role of clinical laboratory is to measure and test patient samples. An alternative is use of statistical methods that analyze actual patient values either as an “Average of Normals” or a “Moving Patient Averages.” Fundamental questions should be decided before a quality control method is used: how are weights assigned to the results? Is preference given to more recent samples or to the older samples? How sensitive should the model be? In this chapter, we will expand the fundamental notion of systematic error and explain why it is difficult to identify and measure and current statistical methods that are used to detect systematic error or bias. A common approach to identify systematic error is to use control samples with a method comparison approach. One of the types of error is systematic error, also called bias, because these errors errors are reproducible and skew the results consistently in the same direction. This measurement error refers to the difference between the true value of the measured sample and the measured value. Measurements in laboratory medicine have a degree of uncertainty this uncertainty is often called “error” and refers to imprecisions and inaccuracies in measurement. ![]()
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