Rural Taiwanese hospital cuts lab turnaround time 22% with AI auto-verification system

Clinical laboratories in resource-limited rural hospitals face inefficiencies from manual test result verification, which is time-consuming and prone to human error. The hospital needed a way to automate result validation to improve turnaround time (TAT) and reduce error rates without requiring large staffing resources.

An AI-driven Auto-Verification System (AVS) was implemented in two phases, integrating 287 rules in the initial phase. During the second validation phase, 107 rules (33%) were validated and six additional rule sets were introduced. The system automated test result validation using advanced software algorithms integrated with the hospital's Laboratory Information System (LIS).

The AVS achieved a 22% overall reduction in TAT (p=0.023), with urinalysis showing the highest improvement at 40.5%, followed by immunoassay (22.1%) and clinical biochemistry (20.4%). The auto-verification rate reached 67.5%, surpassing the 55–60% benchmark reported in prior studies. The system processed 19,903 patient reports and 158,544 test results over the study period.

• Rule-based AVS can be implemented in resource-limited settings and still outperform industry benchmarks for auto-verification rates.
• Different test types benefit unevenly — urinalysis gains the most from automation, making it a high-priority target.
• Phased implementation with iterative rule refinement is effective for validating and expanding AVS coverage.