A multi-test planning model for risk based statistical quality control strategies.
Frequency of QC
Multi-rule QC
Multi-stage QC
Multi-test analyzer
QC rules
QC schedule
Risk based SQC strategy
Run size
Statistical Quality Control
Journal
Clinica chimica acta; international journal of clinical chemistry
ISSN: 1873-3492
Titre abrégé: Clin Chim Acta
Pays: Netherlands
ID NLM: 1302422
Informations de publication
Date de publication:
Dec 2021
Dec 2021
Historique:
received:
14
09
2021
revised:
22
09
2021
accepted:
23
09
2021
pubmed:
1
10
2021
medline:
15
12
2021
entrez:
30
9
2021
Statut:
ppublish
Résumé
Efforts to improve QC for multi-test analytic systems should focus on risk-based bracketed SQC strategies, as recommended in the CLSI C24-Ed4 guidance for QC practices. The objective is to limit patient risk by controlling the expected number of erroneous patient test results that would be reported over the period an error condition goes undetected. A planning model is described to provide a structured process for considering critical variables for the development of SQC strategies for continuous production multi-test analytic systems. The model aligns with the principles of the CLSI C24-Ed4 "roadmap" and calculation of QC frequency, or run size, based on Parvin's patient risk model. Calculations are performed using an electronic spreadsheet to facilitate application of the planning model. Three examples of published validation data are examined to demonstrate the application of the planning model for multi-test chemistry and enzyme analyzers. The ability to assess "what if" conditions is key to identifying the changes and improvements that are necessary to simplify the overall system to a manageable number of SQC procedures. The planning of risk based SQC strategies should align operational requirements for workload and reporting intervals with QC frequency in terms of the run size or the number of patient samples between QC events. Computer tools that support the calculation of run sizes greatly facilitate the planning process and make it practical for medical laboratories to quickly assess the effects of critical variables.
Sections du résumé
BACKGROUND
BACKGROUND
Efforts to improve QC for multi-test analytic systems should focus on risk-based bracketed SQC strategies, as recommended in the CLSI C24-Ed4 guidance for QC practices. The objective is to limit patient risk by controlling the expected number of erroneous patient test results that would be reported over the period an error condition goes undetected.
METHODS
METHODS
A planning model is described to provide a structured process for considering critical variables for the development of SQC strategies for continuous production multi-test analytic systems. The model aligns with the principles of the CLSI C24-Ed4 "roadmap" and calculation of QC frequency, or run size, based on Parvin's patient risk model. Calculations are performed using an electronic spreadsheet to facilitate application of the planning model.
RESULTS
RESULTS
Three examples of published validation data are examined to demonstrate the application of the planning model for multi-test chemistry and enzyme analyzers. The ability to assess "what if" conditions is key to identifying the changes and improvements that are necessary to simplify the overall system to a manageable number of SQC procedures.
CONCLUSIONS
CONCLUSIONS
The planning of risk based SQC strategies should align operational requirements for workload and reporting intervals with QC frequency in terms of the run size or the number of patient samples between QC events. Computer tools that support the calculation of run sizes greatly facilitate the planning process and make it practical for medical laboratories to quickly assess the effects of critical variables.
Identifiants
pubmed: 34592308
pii: S0009-8981(21)00340-5
doi: 10.1016/j.cca.2021.09.020
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
216-223Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.