Improvement of the post-analytical phase by means of an algorithm based autoverification

Abstract

Abstract Objectives Autoverification (AV) is releasing laboratory results using predefined rules. AV standardizes the verification of laboratory results, improves turnaround time (TAT), detects errors in the total test process, and enables effective use of laboratory staff. In this study, we aimed to evaluate the outcomes of implementing the AV in a tertiary hospital. Methods The study was performed in Gazi University Health Research and Application Hospital, Core Biochemistry Laboratory, between August 2017 and October 2019. Step by step, AV algorithms were designed and implemented via middleware for 29 clinical biochemistry tests. A comprehensive validation was performed before the AV system was run. Initially, AV system was tested with datasets and simulated patients (dry testing). Next, samples that may violate AV rules were tested anonymously with no-named trial barcodes (wet testing). Finally, validation of the system was performed with real patients, while the AV was running in the background but not active (i.e., while the manual verification was still going on). After all these steps were successful, the system was started. Results In the daytime, AV rates were ≥75 % for 23 of 29 tests. In night-shift, AV rates were ≥70 % for 16 of 25 tests. Report-based performance was found 26 % for daytime. TAT in the daytime decreased after AV implementation. Conclusions Although this is the first time we have implemented the AV, a significant percentage of the tests have been verified. However, approaches that will increase the percentage of report-based verification will enhance the efficiency of autoverification.