Analytical Error Definition
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StandardsQuality of Laboratory TestingStatisticsSix SigmaToolsTrendsGuest EssayRisk ManagementQC ApplicationsQC DesignBasic QC PracticesMethod ValidationSix SigmaSigma Metric AnalysisQuality StandardsLessonsBasic QC PracticesBasic Planning for QualityBasic Method ValidationZ-Stats / Basic StatisticsQuality ManagementAdvanced Quality Management / Six Sigma"Westgard Rules"Patient Safety ConceptsHigh ReliabilityISOCLIA & QualityQuality RequirementsCLIA Final RuleDownloadsStoreResourcesAbout UsFeedback Form HomeEssaysGuest EssayPre-, Post- analytical errors in the clinical laboratory ppt & Analytical Errors Guest Essay Pre-, Post- & Analytical Errors Written by analytical phase of laboratory testing David Plaut, Sten Westgard, and James O. Westgard. Which improvements should be made first? Unfortunately, we seem to be arguing pre and post analytical errors that some errors are more important (i.e. worse) than others. But rather than make a Chicken-or-Egg choice, David Plaut, Dr. Westgard, and Sten Westgard urge an analysis of these types of errors. http://www.medscape.com/viewarticle/758467_4 The answer to the question of which improvements come first need not be "pre" or "post" or "analytical" - it should be "all three at once." Whose errors are more "obvious?" A Half-Baked Analogy Which errors are worse? Which improvements come first? A final thought Making sense of conflicting priorities in the laboratory We've often heard the opinion that the Quality Control of laboratory testing https://www.westgard.com/guest20.htm isn't the biggest problem we're facing. Sometime people quote a statistic that 40% of the errors in the laboratory are pre-analytical, 40% are post-analytical, and "only" 20% are analytical. There are more "P-errors" than "A-errors", therefore, many laboratories believe they should put a higher priority on pre- and post-analytical errors than on analytical errors. First of all, you may find it depressing when we admit we've got problems everywhere and we only argue over which problems are worse, which problems will be fixed next, and which problems will be ignored for the time being. Ignoring problems is not a good thing. We should be incensed that we've got so many errors in so many different areas of laboratory testing and patient care. The source of this commonly accepted knowledge about laboratory errors is an abstract, not a peer-reviewed paper [see the complete abstract in an earlier discussion on this website]. It seems that people want to believe that analytical errors aren't as frequent as the pre-analytical and post-analytical errors. This belief is part of today's quality compliance mentality that assumes analytical quality is okay if laboratories follow CLIA rules and regulations. Laboratories
error, the test results obtained with the device, are compared with the reference values. The errors are estimated for all pairs of results according to: Error = (Device Test Result) - http://labdataanalysis.com/medical_devices/performance5.html (Reference Value) (1) The total analytical error is defined as http://www.mlo-online.com/pre-analytical-errors-their-impact-and-how-to-minimize-them.php the range that contains a certain proportion (e.g., 95%) of the errors. A quick and non-parametric way to estimate the total analytical error is to sort the errors calculated in equation (1), assign ranks and calculate percentiles. If the distribution of the errors is shown to be normal, the total analytical error can analytical error be estimated using the mean error, the standard deviation of the errors and the appropriate t value from the t-distributions associated with the number of differences and the specified proportion of the distribution of errors. If the total analytical error appears to be larger than anticipated, it is recommended that you examine a histogram of the errors for potential discrepancies and/or plot the errors (on the post analytical errors y-axis) versus the reference values (x-axis) and inspect the plot for trends. The errors computed in equation (1) above may increase as the analyte level (the reference value) increases. In this case, it may be more appropriate to use relative errors instead of absolute errors at high analyte levels. The total analytical error may also be estimated at different ranges of reference values. Three clinically relevant ranges (low, medium and high) are typically used. It is important to note that if the total analytical error is specified for 95% of the errors, the remaining 5% of the errors must not be so large as to cause harmful treatment to patients. The proportion of the errors that are large enough to cause a harmful outcome must be evaluated with respect to the size of patient sample used in estimating the total analytical error. Total analytical error can be very useful in deciding which device is suitable for a certain application. Consider, for example, a case of tight glycemic control where a patient's blood glucose is to be kept in the range 80 mg/dL to 110 mg/dL. If the patient is treated such that the blood glucose lev
Pre-analytical errors: their impact and how to minimize them By: Nitin Kaushik By: Sol Green May 18, 2014 0 13513 The clinical laboratory plays an increasingly important role in the patient-centered approach to the delivery of healthcare services. Physicians rely on accurate laboratory test results for proper disease diagnosis and for guiding therapy; it is estimated that more than 70% of clinical decisions are based on information derived from laboratory test results.1 The process of blood testing, also known as the “Total Testing Process,” begins and ends with the patient. It includes the entire process from ordering the test to interpretation of the test results by the clinician. The Total Testing Process can be subdivided into three stages: Pre-analytical: test request, patient and specimen identification, specimen collection, transport, accessioning and processing Analytical: specimen testing Post-analytical: reporting test results, interpretation, follow up, storage, retesting if needed. Additionally, the term “pre-pre-analytical phase” has been used for the initial part of the pre-analytical phase, focused on test selection and identification of test needed, and the term “post-post-analytical phase” has been used for the interpretation of results by the clinician.2 The numbers don’t lie: it’s a significant problem Clinical laboratory errors directly lead to increased healthcare costs and decreased patient satisfaction. A laboratory error is defined as any defect that occurs during the entire testing process, from ordering tests to reporting results, that in any way influences the quality of laboratory services.3 Any error during the laboratory testing process can affect patient care, including delay in reporting, unnecessary redraws, misdiagnosis, and improper treatment. Sometimes, these errors may even be fatal (e.g., acute hemolytic reaction after incompatible blood transfusion