Abstract: Methods, apparatuses, and systems are disclosed for analyzing quality control (QC) strategies that are applied to testing processes an analyte in order to meet an acceptable level of probability of patient harm that could result from incorrect test results. The measure of patient harm takes into account severity of patient harm, as well as its occurrence. Methods include calculating, based on the parameters of the QC strategies and the test apparatus, an expected number of incorrect final results E(Nuf) due to a test system failure. The value of E(Nuf) can be used as part of a calculation of a predicted level of probability patient harm. The ratio of the acceptable level of probability of patient harm to the predicted level of probability patient harm can determine the adequacy of the QC strategies.

Abstract: Methods, apparatuses, and systems are disclosed for analyzing quality control (QC) strategies that are applied to testing processes an analyte in order to meet an acceptable level of probability of patient harm that could result from incorrect test results. The measure of patient harm takes into account severity of patient harm, as well as its occurrence. Methods include calculating, based on the parameters of the QC strategies and the test apparatus, an expected number of incorrect final results E(Nuf) due to a test system failure. The value of E(Nuf) can be used as part of a calculation of a predicted level of probability patient harm. The ratio of the acceptable level of probability of patient harm to the predicted level of probability patient harm can determine the adequacy of the QC strategies.

Abstract: Methods, apparatuses, and systems are disclosed for analyzing quality control (QC) strategies that are applied to testing processes an analyte in order to meet an acceptable level of probability of patient harm that could result from incorrect test results. The measure of patient harm takes into account severity of patient harm, as well as its occurrence. Methods include calculating, based on the parameters of the QC strategies and the test apparatus, an expected number of incorrect final results E(Nuf) due to a test system failure. The value of E(Nuf) can be used as part of a calculation of a predicted level of probability patient harm. The ratio of the acceptable level of probability of patient harm to the predicted level of probability patient harm can determine the adequacy of the QC strategies.

Abstract: Methods, apparatuses, and systems are disclosed for analyzing quality control (QC) strategies that are applied to testing processes an analyte in order to meet an acceptable level of probability of patient harm that could result from incorrect test results. The measure of patient harm takes into account severity of patient harm, as well as its occurrence. Methods include calculating, based on the parameters of the QC strategies and the test apparatus, an expected number of incorrect final results E(Nuf) due to a test system failure. The value of E(Nuf) can be used as part of a calculation of a predicted level of probability patient harm. The ratio of the acceptable level of probability of patient harm to the predicted level of probability patient harm can determine the adequacy of the QC strategies.

Abstract: A method of establishing statistically valid assay means and ranges for quality control materials, used to qualify medical testing machines, utilizes tests on a new lot of quality control material to establish an assay mean, and uses data from a database of historical test results to establish an assay range. The system may estimate the variability of test results from prior lot data, and then compute the limits of the assay range such that a new test on a new lot of the quality control material will be expected to fall within the range with a specified probability. Because historical data is used to estimate the test variability, the number of new tests required to specify a statistically valid mean and range may be dramatically reduced, as compared with establishing the mean and range based only on tests of the new lot of material.

Abstract: A method of establishing statistically valid assay means and ranges for quality control materials, used to qualify medical testing machines, utilizes tests on a new lot of quality control material to establish an assay mean, and uses data from a database of historical test results to establish an assay range. The system may estimate the variability of test results from prior lot data, and then compute the limits of the assay range such that a new test on a new lot of the quality control material will be expected to fall within the range with a specified probability. Because historical data is used to estimate the test variability, the number of new tests required to specify a statistically valid mean and range may be dramatically reduced, as compared with establishing the mean and range based only on tests of the new lot of material.