A spreadsheet tool for designing statistical quality control programs based on patient risk parameters

Abstract

Quality control (QC) in the laboratory aims to reduce the risk of harm to a patient due to erroneous results, as highlighted by the Clinical Laboratory Standards Institute (CLSI) guidance for Statistical Quality Control (SQC) (C24-Ed4). To effectively reduce patient risk, a convenient spreadsheet tool was developed to assist laboratories in SQC design based on patient risk parameters. In accordance with Parvin's patient risk model and the mathematical formula for calculating the expected number of unreliable final patient results [E(Nuf)], the function is edited using Excel software, and the maximum E(Nuf) [MaxE(Nuf)] value and other risk parameters based on the current QC strategy are calculated to assess the risk of the QC strategy. A convenient spreadsheet tool is proposed in this study. After the quality requirements, performance parameters, practical run size, QC rules and the number of QC results of test items are input, the laboratory is enabled to quickly obtain MaxE(Nuf) value, maximum run size and other data based on the strategy. The QC strategy conforming to the risk requirements can be developed by changing the QC rules or the quantity of run size. Moreover, the Power Function Graph of the QC strategy and two risk diagrams are presented simultaneously. Convenient spreadsheet tools can be adopted by laboratories to assess the risks of QC strategies and design appropriate risk-based SQC strategies to reduce patient risk to acceptable levels.