Establishing Evidence-Based Statistical Quality Control Practices.

Abstract:

OBJECTIVES:To establish an objective, scientific, evidence-based process for planning statistical quality control (SQC) procedures based on quality required for a test, precision and bias observed for a measurement procedure, probabilities of error detection and false rejection for different control rules and numbers of control measurements, and frequency of QC events (or run size) to minimize patient risk. METHODS:A Sigma-Metric Run Size Nomogram and Power Function Graphs have been used to guide the selection of control rules, numbers of control measurements, and frequency of QC events (or patient run size). RESULTS:A tabular summary is provided by a Sigma-Metric Run Size Matrix, with a graphical summary of Westgard Sigma Rules with Run Sizes. CONCLUSION:Medical laboratories can plan evidence-based SQC practices using simple tools that relate the Sigma-Metric of a testing process to the control rules, number of control measurements, and run size (or frequency of QC events).

journal_name

Am J Clin Pathol

authors

Westgard JO,Westgard SA

doi

10.1093/ajcp/aqy158

subject

Has Abstract

pub_date

2019-03-01 00:00:00

pages

364-370

issue

4

eissn

0002-9173

issn

1943-7722

pii

5231209

journal_volume

151

pub_type

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