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Systematic Error: Methodological and Sampling Errors01:15

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Assay Stability, the missing component of the Error Budget.

Mark Mackay1, Gabe Hegedus1, Tony Badrick1

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Quality control (QC) strategies must account for long-term assay stability, not just short-term performance. Including measured QC drift (SEdrift) in quality planning ensures reliable error detection and assay management.

Keywords:
Analytical Performance SpecificationAssay CapabilityAssay biasError detectionQC rulesSix sigma

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Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Quality Management Systems

Background:

  • Effective quality control (QC) is crucial for improving laboratory performance and minimizing patient risk.
  • Current QC strategies often rely on short-term performance metrics, potentially overlooking long-term assay stability.
  • The Six Sigma methodology and sigma metric are increasingly used to assess assay performance and select QC rules.

Purpose of the Study:

  • To introduce and evaluate the significance of measured QC drift (SEdrift) as a key component of assay stability.
  • To demonstrate how SEdrift addresses limitations in traditional standard error budgets based on short-term QC.
  • To propose a simplified method for determining target imprecision for QC algorithms by incorporating SEdrift.

Main Methods:

  • Analysis of assay performance data considering both short-term variability and long-term drift.
  • Modeling the impact of calibration, reagent lot changes, and other factors on assay bias over time.
  • Developing a framework for integrating SEdrift into quality planning and QC rule selection.

Main Results:

  • The standard error budget is often inadequate as it overlooks the long-term stability component (SEdrift).
  • SEdrift provides a quantifiable measure of assay stability over time.
  • Incorporating an allowance for SEdrift simplifies the determination of target imprecision for effective QC algorithms.

Conclusions:

  • Assay stability, measured by SEdrift, is a critical but often neglected dimension in QC planning.
  • Traditional QC error budgets require revision to include long-term stability.
  • A simplified approach to setting target imprecision (Allowable Performance Specification divided by 4, 5, or 6) can enhance QC algorithm effectiveness by accounting for SEdrift.