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 networked clinical diagnostic analyzer is disclosed with support for monitoring by a remote back office. The disclosed analyzer includes a module to detect in real-time events of interest while allowing the back office to modify the definitions of the events. The module may be networked using virtual private networking into the back office network, which is usually different from the network at the site of the clinical diagnostic analyzer's deployment. The real-time alerts allow both a quick response to actual or expected error conditions and the downloading of logged data that is likely of most interest and relevance.

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 networked clinical diagnostic analyzer is disclosed with support for monitoring by a remote back office. The disclosed analyzer includes a module to detect in real-time events of interest while allowing the back office to modify the definitions of the events. The module may be networked using virtual private networking into the back office network, which is usually different from the network at the site of the clinical diagnostic analyzer's deployment. The real-time alerts allow both a quick response to actual or expected error conditions and the downloading of logged data that is likely of most interest and relevance.