Implementation and validation of an intelligent auto-verification system in a coagulation testing automatic line

Area of Science:

• Clinical Laboratory Science
• Automation and Robotics in Healthcare
• Diagnostic Testing

Background:

• High-throughput laboratories face challenges in maintaining efficiency and standardization.
• Coagulation testing is critical for patient diagnosis and management.
• Manual processes in laboratory testing can lead to errors and delays.

Purpose of the Study:

• To evaluate the implementation and optimization of a fully automated coagulation testing system.
• To assess the impact of dual-coagulation-autoline and auto-verification protocols on laboratory operations.
• To enhance operational efficiency, standardization, and clinical utility in a high-volume setting.

Main Methods:

• Deployment of a dual-coagulation-autoline system with four automated analyzers per line.
• Pre-implementation quality assessments of centrifuge performance, sampling, robotic arm effects, and sample stability.
• Optimization and validation of auto-verification rules using 18,373 samples, measuring pass rate, sensitivity, specificity, and turnaround time (TAT).

Main Results:

• The automated system reduced outpatient and inpatient TAT by 16.78% and 33.06%, respectively.
• Optimized auto-verification achieved a 62.48% pass rate with 100% sensitivity and 93.50% specificity, eliminating false negatives.
• Further TAT reductions of 8.29% (outpatient) and 16.21% (inpatient) were observed post-auto-verification implementation.

Conclusions:

• Integration of dual-autoline and auto-verification significantly improved TAT and reduced errors in high-volume coagulation testing.
• Personalized system optimization, including dynamic testing allocation, enhanced clinical efficiency.
• The validated auto-verification framework demonstrated generalizability for large-scale laboratories, offering valuable experience for others.