Auditing quality control procedures in a chemical pathology laboratory--a multiple regression analysis.

Area of Science:

• Clinical laboratory science
• Medical diagnostics
• Quality management in healthcare

Background:

• Automated laboratory analyzers are crucial for diagnostic testing.
• Monitoring test rejection rates and external quality assessment (EQA) performance is vital for laboratory quality.
• Factors influencing laboratory performance require investigation to optimize efficiency and accuracy.

Purpose of the Study:

• To analyze factors affecting monthly test rejection rates and EQA performance indices for two automated analyzers.
• To identify associations between laboratory workload, manpower, staff training, instrument servicing, and quality metrics.
• To determine the impact of calibration, method, and internal quality control (IQC) changes on laboratory performance.

Main Methods:

• Retrospective analysis of monthly data for test rejection rates and EQA performance.
• Utilized multiple linear regression and stepwise multiple linear regression.
• Examined associations with workload, manpower, staff training, instrument factors, seasonality, and QC parameters.

Main Results:

• Test rejection rates varied significantly between instruments, being highest on the analyzer with the widest test variety and lowest volume.
• On this instrument, rejection rates correlated with new staff introduction and manpower levels, showing an upward trend over time.
• EQA performance showed minor trends, was unrelated to rejection rates, but associated with new staff and laboratory workload.

Conclusions:

• Introduction of new staff and reduced laboratory manpower may significantly increase test rejection rates.
• Appropriate quality control protocols maintain result quality but may not eliminate all variations.
• Clinical laboratories should employ statistical approaches to identify factors impacting quality and costs, validating QC effectiveness.