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Process capability and stability of analytical systems assessed from proficiency testing data

R W Jenny1

  • 1New York State Department of Health, Wadsworth Center for Laboratories and Research, Albany 12201-0509.

Clinical Chemistry
|May 1, 1994
PubMed
Summary
This summary is machine-generated.

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Proficiency testing (PT) programs enhance laboratory quality control. Statistical process control (SPC) applied to PT data identifies analytical errors and suggests performance improvements for better patient care.

Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Quality Management

Background:

  • Proficiency testing (PT) is crucial for maintaining reliable laboratory analytical methods.
  • Integrating PT with healthcare professional expectations can drive continuous quality improvement.
  • Statistical process control (SPC) and capability analysis are established industrial tools for process monitoring.

Purpose of the Study:

  • To conceptualize the application of SPC and capability analysis to laboratory PT data.
  • To evaluate laboratory performance in the context of peer performance and regulatory specifications.
  • To identify opportunities for improving laboratory analytical performance.

Main Methods:

  • Treating a set of five PT results (theophylline) as a process sample.

Related Experiment Videos

  • Applying SPC, including mean (X-bar) and s-charts, to analyze PT data from multiple laboratories.
  • Utilizing capability analysis with clinical specification limits.

    • Main Results:

    • Control charts effectively identified significant analytical errors relative to peer performance and specifications.
    • Capability index (Cp) values indicated room for improvement in the analytical systems evaluated.
    • The study demonstrated the utility of SPC for monitoring laboratory performance in PT programs.

    Conclusions:

    • SPC and capability analysis are valuable tools for assessing and improving laboratory performance in PT programs.
    • The findings highlight specific areas where analytical systems can be enhanced to meet clinical demands.
    • Implementing these analytical methods can lead to more reliable patient care outcomes.