Laboratory quality control: Using patient data to assess analytical performance

Research output: Contribution to journalReview articlepeer-review

48 Scopus citations


Quality control plays a vital role helping to ensure the reliability of laboratory test results. The application of statistical quality control has been a component of laboratory medicine for approximately 50 years. Many of the control rules based on the early applications of statistical quality control have remained essentially unchanged since their initial introduction. Optimization of quality control rules can vary depending on the application for which a test is to be used. This review explores the various applications of laboratory quality control procedures and their role in identifying laboratory error. The ubiquitous use of computers in today's laboratories has enabled the development of more sophisticated means of assessing laboratory quality. The use of the Six Sigma technique and its adoption by the laboratory community is one example. Other examples include the use of patient-derived quality control procedures as a means of assessing laboratory performance. Early examples of these types of applications include use of Bull's algorithm, anion gap measurements, and delta checking. More recent applications include the correlation of laboratory test results, the average of normals procedure, and the Bhattacharya method.

Original languageEnglish (US)
Pages (from-to)617-627
Number of pages11
JournalClinical Chemistry and Laboratory Medicine
Issue number5
StatePublished - Jun 27 2003


  • Anion gap
  • Average of normals
  • Delta check
  • Laboratory error
  • Quality control
  • Six Sigma

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Biochemistry, medical


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