engleski

Evaluation of rules in autovalidation algorithm

Introduction: Autovalidation is a part of the laboratory information system whereby laboratory results are released without manual human intervention through defined rules and algorithms. Autovalidation rules may include: analytical measurement range, interference indices (hemolysis, icterus, lipemia), critical values or delta checks. Rules must be set for laboratory testing and patient population for which autovalidation will be applied. The aims of the study were to examine the credibility of the rules in the algorithm for autovalidation and determine the percentage of samples that were autovalidated in comparison to the total number of samples included in validation, as well as rules that stop autovalidation. Materials and Methods: The validation results included 9805 samples of biochemical tests analyzed in the Department of Laboratory Diagnostics, University Hospital Centre Zagreb from May to July 2014. Validation was performed in such a way that, before starting the system of autovalidation, the results were reviewed by a medical biochemist who recorded samples that should meet the rules set in the algorithm. Statistical analysis was made using the software MedCalc (version 9.3.2.0). Results: 78.3% (7677) of the samples included in validation were autovalidated. The highest percentage of samples (54.9%) was not autovalidated due to set rules for analytical measurement ranges, while the lowest percentage of non-validated samples was recorded in the rules for interference indices for icterus (0.6%). The correspondence of autovalidation and the person who carried it out was 99.5%, i.e. the mismatch is observed only in 0.5% of samples (38). An analysis of Χ2-test data showed no statistically significant difference (P=0.523) in the number of samples that were autovalidated (7677) in relation to those validated by medical biochemist (7639). Conclusion: The analysis of results showed that set rules in the algorithm are credible, and that system autovalidation can be implemented in routine laboratory use.

autovalidation algorithm, laboratory information system, serum biochemistry tests

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