Unit-5.1-Quality-Assurance-and-Figures-of-Merit

Quality Assurance Overview

  • Definition: Quality Assurance (QA) is a program that ensures the production of defensible data with known precision and accuracy in laboratory operations.

  • Purpose:

    • Real-time monitoring of chemical analyses in labs.

    • Control of systematic and random errors.

  • Key Assumptions: When under statistical control, results are bias-free and have defined confidence intervals.

  • Documentation: Defined in a QA manual containing policies, written procedures, work instructions, and records.

Key Components of Quality Assurance Program

1. Quality Control (QC)

  • Encompasses activities ensuring analyses are statistically controlled.

  • Includes directives for laboratory operations (e.g., Good Laboratory Practices).

2. Quality Assessment (Method Validation)

  • Ensures QC measurements meet required standards and helps determine data quality.

    • Internal Methods: Immediate feedback on statistical control.

    • External Methods: Certification and accreditation requirements.

Quality Control Elements

  1. Initial Demonstration of Capability (IDC)

    • Analysts must prove method proficiency before analyzing samples.

    • Includes checks like reagent blanks and laboratory-fortified blanks.

  2. Ongoing Demonstration of Capability (ODC)

    • Ensures laboratory control while samples are analyzed.

    • Comparison to calibration standards reinforces accuracy.

  3. Method Detection Level (MDL)

    • MDL determined via standard deviation of sample measurements; calculated as MDL = 3.14s.

    • Verification is routine to ensure detection limits are maintained.

  4. Laboratory-Fortified Blanks (LFB) and Laboratory-Fortified Matrix (LFM)

    • LFB: Blank sample with known concentrations to assess recovery in blanks.

    • LFM: Sample with known concentration added to evaluate matrix effect.

  5. Reagent Blanks

    • Evaluates contribution from reagents to measurement uncertainty.

    • Must be included with sample sets to check for contamination.

QC Calculations and Acceptance Criteria

  • Perform regular evaluations to ensure deviations don’t occur.

  • Employ statistical methods (mean, standard deviation) to establish acceptable limits.

Corrective Actions in QC

  • Quick response is essential when QC data are outside accepted limits.

  • Actions include checking for errors, repeating analyses, and verifying calibration standards.

Quality Assessment Methods

  • Internal Methods: Analyzing duplicates, blanks, and standard samples.

  • External Methods: Proficiency testing, ring tests, and clients' tests to ensure compliance and accuracy.