Establishing and Evaluating Autoverification Rules with Intelligent Guidelines for Arterial Blood Gas Analysis in a Clinical Laboratory

Author:

Wu Jie1,Pan Meichen1,Ouyang Huizhen1,Yang Zhili1,Zhang Qiaoxin1,Cai Yingmu1

Affiliation:

1. Department of Clinical Laboratory, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China

Abstract

Arterial blood gas (ABG) analysis is important for acutely ill patients and should be performed by qualified laboratorians. The existing manual verifications are tedious, time-consuming, and prone to send wrong reports. Autoverification uses computer-based rules to verify clinical laboratory test results without manual review. To date, no data are available on the use of autoverification for ABG analysis. All autoverification rules were established according to AUTO10-A. Additionally, the rules were established using retrospective patient data, and then validated by actual clinical samples in a “live” environment before go-live. The average autoverification passing rate was 75.5%. The turnaround time (TAT) was reduced by 33.3% (27 min vs 18 min). Moreover, the error rate fell to 0.05% after implementation. Statistical analysis resulted in a kappa statistic of 0.92 ( p < 0.01), indicating close agreement between autoverification and senior technician verification, and the chi-square value was 22.4 ( p < 0.01), indicating that the autoverification error rate was lower than the manual verification error rate. Results showed that implementing autoverification rules with intelligent guidelines for ABG analysis of patients with critical illnesses could decrease the number of samples requiring manual verification, reduce TAT, and eliminate errors, allowing laboratorians to concentrate more time on abnormal samples, patient care, and collaboration with physicians.

Publisher

Elsevier BV

Subject

Medical Laboratory Technology,Computer Science Applications

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