Abstract: A method of detecting impending analytical failure in a networked diagnostic clinical analyzer is based upon detecting whether the operation of a particular analyzer is statistically distinguishable based on one or more thresholds. A failure occurs when one or more components or modules of the analyzer fails. A method to detect such an impending failure is disclosed. Baseline data on a pre-selected set of analyzer variables for a population of diagnostic clinical analyzers is used to generate an impending failure threshold. Subsequently, operational data comprising the same pre-selected set of analyzer variables allows generation of a time series of operational statistics. If the operational statistic exceeds the impeding failure threshold in a prescribed manner, an impending analytical failure is predicted. Such detection of impending analytical failures facilitates intelligent scheduling of service for the analyzer in question to maintain high assay throughput and accuracy.

Abstract: A method of detecting impending analytical failure in a networked diagnostic clinical analyzer is based upon detecting whether the operation of a particular analyzer is statistically distinguishable based on one or more thresholds. A failure occurs when one or more components or modules of the analyzer fails. A method to detect such an impending failure is disclosed. Baseline data on a pre-selected set of analyzer variables for a population of diagnostic clinical analyzers is used to generate an impending failure threshold. Subsequently, operational data comprising the same pre-selected set of analyzer variables allows generation of a time series of operational statistics. If the operational statistic exceeds the impeding failure threshold in a prescribed manner, an impending analytical failure is predicted. Such detection of impending analytical failures facilitates intelligent scheduling of service for the analyzer in question to maintain high assay throughput and accuracy.