Article
The performance of delta check methods.
Clinical Chemistry (Impact Factor: 7.15). 01/1980; 25(12):20347.
Source: PubMed

Article: Intraindividual reference values.
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ABSTRACT: When a biological quantity examination exhibits a high degree of individuality, developing a strategy for interpreting these values in an individual context can be a useful alternative. Timeseries analysis is the appropriate statistical framework to build a model for explanation of the behaviour of laboratory information and to forecast future values. The key concepts in this approach are autocorrelation and withinperson variance. Unfortunately, the powerful tools provided by timeseries analysis require many observations, a requisite difficult to meet in every day practice. However, introducing some restrictions in the autocorrelation parameter of the most reliable model, the first order autocorrelation model, and using the average withinperson variance from a selected population, it is possible to build predictive reference intervals for an individual, based on only few observations. The most common case is the minimum time series: when there are just two observations. The statistical significance of the change from a previous observation is a problem that arises from both quality control (delta checks) and the interpretative diagnostic fields (reference change limit). Applying the same restrictive criteria, it is possible to develop specific limits for a difference between consecutive observations based on a withinperson variance selected from the distribution of variances found in a sample of similar individuals.Clinical Chemistry and Laboratory Medicine 02/2004; 42(7):76577. · 3.01 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: Quality control plays a vital role helping to ensure the reliability of laboratory test results. The application of statistical quality control has been a component of laboratory medicine for approximately 50 years. Many of the control rules based on the early applications of statistical quality control have remained essentially unchanged since their initial introduction. Optimization of quality control rules can vary depending on the application for which a test is to be used. This review explores the various applications of laboratory quality control procedures and their role in identifying laboratory error. The ubiquitous use of computers in today's laboratories has enabled the development of more sophisticated means of assessing laboratory quality. The use of the Six Sigma technique and its adoption by the laboratory community is one example. Other examples include the use of patientderived quality control procedures as a means of assessing laboratory performance. Early examples of these types of applications include use of Bull's algorithm, anion gap measurements, and delta checking. More recent applications include the correlation of laboratory test results, the average of normals procedure, and the Bhattacharya method.Clinical Chemistry and Laboratory Medicine 06/2003; 41(5):61727. · 3.01 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: Autoverification is a process of using computerbased rules to verify clinical laboratory test results without manual intervention. To date, there is little published data on the use of autoverification over the course of years in a clinical laboratory. We describe the evolution and application of autoverification in an academic medical center clinical chemistry core laboratory.Journal of pathology informatics. 01/2014; 5:13.
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