A-186 Performance Evaluation of Selected Biochemical Tests Using Sigma Metrics and the Quality Goal Index

Background Quality reporting is a critical global concern, necessitating the implementation and evaluation of quality indicators to ensure reliable outcomes. While developed countries have established benchmarks through national policies and significantly minimized errors, developing nations like Nepal remain in the early stages of adopting such practices. Sigma metrics approach provide a robust framework for performance evaluation, while the Quality Goal Index (QGI) aids in identifying causes of low sigma values. The integration of Westgard rules with Sigma metrics enables tailored quality control strategies, ensuring compliance with stringent standards and reducing errors effectively. This study aimed to analyze the performance of a selected biochemical tests using Sigma metrics and the Quality Goal Index. Methods A cross-sectional study was conducted in the Clinical Biochemistry Laboratory of Dhulikhel Hospital-Kathmandu University Hospital, Nepal, from April to June 2024. Twenty routine biochemical tests were analyzed using the Vitros 5600 analyzer. Sigma metrics and Quality Goal Index (QGI) were derived from internal and external quality control data. Method Decision Charts were employed for visual performance evaluation. Statistical analysis was conducted using MS Excel and STATA to calculate and interpret the results. Results Tests with high Sigma Metrics, such as Triacylglycerol and Alkaline phosphatase (ALP), exhibited excellent performance, indicating optimal accuracy and precision. Conversely, tests with low Sigma Metrics, including Alanine transaminase (ALT) and albumin, showed unacceptable performance, with QGI analysis identifying significant inaccuracies and imprecision. Conclusion This study emphasizes the application of Sigma metrics and the Quality Goal Index (QGI) to evaluate test performance and the implementation of Westgard rules to enhance Quality Control (QC) strategies. It recommends refining QC protocols, conducting long-term performance monitoring, and assessing performance across analyzers to drive continuous quality improvement.