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Practical guidelines for applying statistical process control to blood component production
Author(s) -
Beckman N.,
Nightingale M. J.,
Pamphilon D.
Publication year - 2009
Publication title -
transfusion medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.471
H-Index - 59
eISSN - 1365-3148
pISSN - 0958-7578
DOI - 10.1111/j.1365-3148.2009.00942.x
Subject(s) - statistical process control , blood component , component (thermodynamics) , computer science , sampling (signal processing) , reliability engineering , process (computing) , sample size determination , data mining , medicine , statistics , engineering , intensive care medicine , mathematics , physics , filter (signal processing) , computer vision , thermodynamics , operating system
summary. Legislation, guidelines and recommendations for blood components related to statistical process control (SPC) and the selection of a quality monitoring (QM) sampling regimen are subject to misinterpretation and lack practical guidance on implementation. The aim of this article is: to review and interpret applicable European legislation and guidelines and to develop an SPC strategy that meets these requirements; and to provide practical guidance on the selection and application of appropriate techniques and the interpretation of resultant blood component QM data. A methodology is presented which utilizes: an algorithm to select an appropriate quality‐monitoring strategy for the blood component parameter under consideration; a range of straightforward, validated SPC techniques for variable data and an assessment of process capability (Cpk) and blood component parameter ‘criticality’ to determine the sampling regimen. The methodology was applied to routine National Health Service Blood and Transplant (NHSBT) blood component data for 2005–2006. Cpk values ranged from 0.22 to >3 and their predicted non‐conformance rates were close to those observed (23 to <0.001%). Required sample size ranged from 0.01 to 10%. Chosen techniques identified significant deviation from ‘as validated’ performance within an appropriate time‐scale. Thus the methodology was straightforward to apply and prompted the choice of a clinically and operationally appropriate sampling regimen and analysis for each blood component parameter. This evidence‐based, targeted use of SPC for blood component monitoring provides an essential focus on processes with a low capability in achieving their specifications.