Improving the efficiency of quality control in clinical laboratory with an integrated PBRTQC system based on patient risk.

Objectives: Recent advances in information technology have renewed interest in patient-based real-time quality control (PBRTQC) as an alternative to internal quality control (IQC). However, since regulations mandate IQC, PBRTQC can only be implemented as a separate system. The additional labor required for PBRTQC may hinder widespread adoption. Therefore, a more efficient system that integrates IQC with PBRTQC is needed for laboratories to implement the methods effectively.

Methods: A QC system that integrates IQC with PBRTQC is proposed. The maximum average number of patients with unacceptable analytical errors (MaxANP_TE) was introduced as a critical metric to benchmark the efficiency of the integrated PBRTQC system against the IQC-only system using a modified Parvin patient risk model. With the historical data of serum sodium (Na), chloride (Cl), alanine aminotransferase (ALT), and creatinine (CREA) from Zhongshan Hospital, Fudan University, in 2019, the integrated system incorporating the simple PBRTQC model and the more advanced regression-adjusted real-time quality control (RARTQC) were compared with the IQC-only system.

Results: In most cases, the integrated system incorporating RARTQC models outperformed the IQC-only system, particularly for ALT, where QC events were reduced by up to 45 %. Based on these findings, we proposed strategies for laboratories to design the integrated system.

Conclusions: The study demonstrated the improvement of efficiency of the integrated PBRTQC system over the IQC-only system. These insights can help laboratories make informed decisions on adopting PBRTQC models and provide as evidence for revising regulation on IQC.