Real-time Patient Sample Quality Control (PBRTQC): Overview and recommendations

The concept of patient-based quality control (PBRTQC) has been discussed and applied in hematology laboratories for many years, but its implementation in clinical chemistry remains limited. This is because this form of quality control (QC) requires individual optimization for each patient group and often for each analyte. Nevertheless, the obvious advantages of PBRTQC against the backdrop of realizing the limitations of traditional QC have necessitated the development of guidelines for its implementation in the laboratory. This review discusses the key components of the PBRTQC system (calculation algorithm, block size, truncation limits, control limits) and their relationship to specific analytes. It also discusses the need to optimize PBRTQC using patient data from a particular laboratory, thereby enabling timely detection of systematic errors and minimizing the false positive rate.

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Publication Details

Journal
Laboratory Service
Published
2025-04-08
DOI
https://doi.org/10.17116/labs20251401150
Primary Topic
Clinical Laboratory Practices and Quality Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Real-time Patient Sample Quality Control (PBRTQC): Overview and recommendations

Jian‐Ping Luo, Alex Katayev, T. Badrik, A. Bitenbeck et al.
Laboratory Service
Clinical Laboratory Practices and Quality Control
article

Real-time Patient Sample Quality Control (PBRTQC): Overview and recommendations

Jian‐Ping Luo, Alex Katayev, T. Badrik, A. Bitenbeck, M.A. Chervinsky, H.H. Wang Rossum
article en

Abstract

The concept of patient-based quality control (PBRTQC) has been discussed and applied in hematology laboratories for many years, but its implementation in clinical chemistry remains limited. This is because this form of quality control (QC) requires individual optimization for each patient group and often for each analyte. Nevertheless, the obvious advantages of PBRTQC against the backdrop of realizing the limitations of traditional QC have necessitated the development of guidelines for its implementation in the laboratory. This review discusses the key components of the PBRTQC system (calculation algorithm, block size, truncation limits, control limits) and their relationship to specific analytes. It also discusses the need to optimize PBRTQC using patient data from a particular laboratory, thereby enabling timely detection of systematic errors and minimizing the false positive rate.

Laboratory ServiceVol. 14(1)
Dartmouth College (US), Dartmouth–Hitchcock Medical Center (US), Royal College of Pathologists of Australasia (AU), München Klinik (DE), National University Hospital (SG)
Openalex Percentile: Top 91%
Clinical Laboratory Practices and Quality Control
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