Modeling uncertainty due to instrument drift in clinical laboratories

Clinical laboratory tests play a vital role in the medical decision making process, including diagnosis, prognostic assessment and drug dosage prescription. Drift or degradation in the performance of the analytic instrument over time can have a significant effect on the uncertainty of the clinical laboratory measurement test result. In this paper, we model the drift in the analytic instrumentation used to perform the laboratory tests, and estimate its effect on the uncertainty of the measurement result. This is accomplished developing a physics-based mathematical model of the serum albumin laboratory test that describes the measurement result as a function of various sources of uncertainty operating within the serum albumin measurement process. The Monte Carlo method is used to estimate the uncertainty associated with this model. Drift in the instrument is modeled as affecting both the mean (inaccuracy) and the standard deviation (imprecision) of each source of uncertainty. Further, recalibrating the instrument is postulated as a method to nullify the effect of instrument drift on inaccuracy of the measurement result, and the model is used to estimate the average time interval between successive calibrations such that the drift does not exceed clinically significant total error limits and prevents misdiagnosis.