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Accuracy-based equivalence evaluation using reference data for the clinical application of patient-based quality

Xueling Shang1, Tingting Wang2, Minglong Zhang3

  • 1Department of Laboratory Medicine, Beijing Chao-yang Hospital, Capital Medical University, Beijing, PR China.

Clinica Chimica Acta; International Journal of Clinical Chemistry
|July 11, 2025
PubMed
Summary

Digital metrology and algorithm traceability standardize patient-based real-time quality control (PBRTQC) evaluation. This approach ensures accuracy-based equivalence for PBRTQC models, aiding clinical selection and deployment.

Keywords:
Algorithm traceabilityDigit-measuring instrumentDigital metrologyPatient-based real-time quality controlPerformance evaluationReference data

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Area of Science:

  • Clinical laboratory science
  • Metrology
  • Biomedical engineering

Background:

  • Patient-based real-time quality control (PBRTQC) monitors analytical performance using patient test results.
  • Current PBRTQC models require independent validation for accuracy-based equivalence before clinical use.
  • Standardized evaluation methods are needed for PBRTQC model selection and accreditation compliance.

Purpose of the Study:

  • To introduce digital metrology and algorithm traceability for standardized PBRTQC evaluation.
  • To enable accuracy-based equivalence assessment of different PBRTQC models/software.
  • To provide evidence for selecting and deploying PBRTQC models in clinical settings.

Main Methods:

  • Established a reference dataset as a digital measuring instrument (DMI) for metrological traceability.
  • Developed the DMI using digital twin technology with standardized data and measurement uncertainty (MU).
  • Evaluated five PBRTQC models using the DMI, focusing on red blood cell (RBC) count data.

Main Results:

  • Constructed a hierarchical traceability chain from PBRTQC models to the DMI and original instrument data.
  • The DMI incorporated both in-control and out-of-control states for QC scenarios.
  • Calculated algorithm evaluation values (Y) for five PBRTQC models, ranging from 0.638986 to 0.798970, with MU of (4.1-4.3) × 10-5.

Conclusions:

  • Reference data as DMI and algorithm traceability offer accuracy-based equivalence evaluation for PBRTQC models.
  • This methodology supports laboratory users in selecting and implementing PBRTQC solutions.
  • Standardized evaluation enhances confidence in PBRTQC model performance for clinical applications.