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Analytical goal-setting for monitoring patients when two analytical methods are used

P H Petersen1, C G Fraser, J O Westgard

  • 1Department of Clinical Chemistry, Odense University Hospital, Denmark.

Clinical Chemistry
|November 1, 1992
PubMed

Insights

Analytical errors in medical testing can impact patient care. This study presents a model to set allowable analytical imprecision and bias limits for serial testing methods, ensuring reliable patient monitoring.

Area of Science:

  • Clinical chemistry
  • Analytical toxicology
  • Medical diagnostics

Background:

  • Serial patient results often use multiple methods, requiring result transferability across time and location.
  • Analytical errors (imprecision and bias) must be defined to ensure optimal patient care.
  • Existing guidelines propose limits for analytical error based on biological variation.

Purpose of the Study:

  • To develop a general model for relating analytical imprecisions of two methods and their bias to biological variation.
  • To quantitatively determine goals for method imprecisions and allowable bias differences in clinical monitoring.

Main Methods:

  • Utilized Harris's proposal relating desirable imprecision to within-subject biological variation.
  • Developed a general formula incorporating analytical imprecisions and bias between two methods.
  • Applied the derived formula to clinical monitoring scenarios with defined probability of change triggering clinical action.

Main Results:

  • Established a quantitative relationship between analytical imprecisions, bias, and biological variation.
  • Provided a framework for setting specific goals for method imprecision and bias in clinical monitoring.
  • Demonstrated the application of the general model in clinical practice.

Conclusions:

  • The developed model allows for quantitative determination of analytical performance goals for serial testing methods.
  • Setting appropriate imprecision and bias limits is crucial for reliable patient monitoring and clinical decision-making.
  • This approach facilitates the selection and validation of methods for longitudinal patient health assessment.

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