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Implementation of the Autovalidation Algorithm for Clinical Chemistry Testing in the Laboratory Information System
Vladimira Rimac1, Ivana Lapic2, Kresimir Kules3
1Department of Transfusion Medicine and Transplantation Biology, University Hospital Center Zagreb, Zagreb, Croatia.
Laboratory Medicine
|February 13, 2018
Summary
An autovalidation algorithm for laboratory information systems (LIS) was developed and validated. This system successfully autovalidated 78.3% of samples, reducing manual reviews in routine laboratory work.
Area of Science:
- Clinical Chemistry
- Laboratory Medicine
- Health Informatics
Background:
- Autovalidation requires well-defined criteria for data review.
- Manual validation of laboratory results is time-consuming and resource-intensive.
Purpose of the Study:
- To establish rules for autovalidation within a laboratory information system (LIS).
- To validate the autovalidation algorithm before its routine implementation.
Main Methods:
- Implemented an autovalidation algorithm for all routine serum biochemistry tests.
- Algorithm criteria included analytical measurement ranges (AMR), delta checks, critical values, serum indices, and analyzer flags.
Main Results:
- 9805 samples were analyzed; 78.3% were autovalidated.
- 54.9% of non-validated samples failed AMR criteria; critical values were the least common reason (1.8%).
- 38 samples required manual validation due to unmet criteria.
Conclusions:
- The autovalidation algorithm implementation necessitated LIS redesign.
- This model significantly reduced manually validated results and serves as a template for other labs.
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