A system approach to the estimation of uncertainty in clinical laboratory measurement systems.

摘要

Uncertainties in clinical laboratory testing have a considerable impact on medical decision making leading to increased medical costs and a threat to patient safety. In an attempt to estimate the uncertainty propagation through a clinical laboratory system we have developed a Monte Carlo simulation model using a system based approach. The model identifies the individual uncertainties in a real world measurement system and discusses their combination and propagation through the system. It is found that sample pipetting uncertainty is the largest contributer to the overall uncertainty. Performance specifications for the clinical laboratory measurement system modeled in our work were collected from the manufacturer (Roche Diagnostics) and a typical medical user of these systems (Mayo clinic).