External quality assessment in the absence of proficiency testing: A split-sample testing program experience

Area of Science:

• Laboratory Medicine
• Analytical Chemistry
• Quality Management Systems

Background:

• Proficiency testing (PT) is essential for ensuring the reliability of laboratory results and adherence to standards like ISO 15189:2012.
• Formal PT may not be available for all analytes, necessitating alternative methods for quality assurance.
• The Clinical and Laboratory Standards Institute (CLSI) QMS24 guideline provides a framework for alternative testing strategies.

Purpose of the Study:

• To evaluate a split-sample testing program as an alternative to formal PT for heparan sulfate measurement.
• To assess the comparability of results between two independent laboratories using this alternative method.
• To provide evidence for accreditation audits by demonstrating adherence to quality standards.

Main Methods:

• A split-sample testing program was conducted based on CLSI QMS24 recommendations.
• Two laboratories measured heparan sulfate concentrations in five samples using ultra-performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS).
• Data analysis for interlaboratory comparability followed Appendix E of the CLSI QMS24 guideline.

Main Results:

• Mean interlaboratory differences were within the maximum allowable differences calculated using the QMS24 guideline.
• Results indicated comparable heparan sulfate measurements between the two participating laboratories across the tested concentrations.
• The split-sample approach provided objective evidence of test result quality.

Conclusions:

• The CLSI QMS24-based split-sample testing program serves as a viable alternative to formal PT for analytes lacking official PT schemes.
• This method allows laboratories to objectively assess comparability and meet accreditation requirements.
• Laboratory specialists should critically evaluate the suitability of calculated maximum allowable differences for specific applications, especially with small sample sizes.