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A model to establish autoverification in the clinical laboratory
Deniz Ilhan Topcu1, Ozlem Gulbahar2
1Department of Biochemistry, Faculty of Medicine, Başkent University, Ankara, Turkey.
Clinical Biochemistry
|April 8, 2021
Summary
Developing a systematic model for autoverification (AV) rules improves laboratory efficiency. This model aids in establishing and evaluating AV systems, with manual review limits and delta checks being critical for high AV rates.
Area of Science:
- Clinical laboratory science
- Medical informatics
Background:
- Autoverification (AV) streamlines laboratory result validation using computer algorithms, reducing manual workload.
- Establishing and validating AV rules are complex and time-consuming processes.
Purpose of the Study:
- To develop a model for creating and evaluating autoverification rules.
- To assess the performance and validity of the proposed autoverification system.
Main Methods:
- A model was developed based on literature review and guidelines.
- Autoverification software (myODS) was created for rule generation and evaluation.
- Actual patient data and simulations were used, employing delta check algorithms (A and B) and review limits.
Main Results:
- Six hundred seventeen rules were generated using the model.
- Manual review limits significantly impact autoverification rates.
- Algorithm B, incorporating consecutive delta checks, demonstrated higher autoverification rates, particularly for inpatients.
Conclusions:
- Systematic rule formation is essential for successful autoverification.
- The proposed model facilitates the establishment and evaluation of AV systems in laboratories.
- Generated rules can serve as a foundation for various laboratory test groups.
