Evidence-based approach to setting delta check rules

Corey Markus, Rui Zhen Tan, Tze Ping Loh

Research output: Contribution to journalReview articlepeer-review

3 Citations (Scopus)


Delta checks are a post-analytical verification tool that compare the difference in sequential laboratory results belonging to the same patient against a predefined limit. This unique quality tool highlights a potential error at the individual patient level. A difference in sequential laboratory results that exceeds the predefined limit is considered likely to contain an error that requires further investigation that can be time and resource intensive. This may cause a delay in the provision of the result to the healthcare provider or entail recollection of the patient sample. Delta checks have been used primarily to detect sample misidentification (sample mix-up, wrong blood in tube), and recent advancements in laboratory medicine, including the adoption of protocolized procedures, information technology and automation in the total testing process, have significantly reduced the prevalence of such errors. As such, delta check rules need to be selected carefully to balance the clinical risk of these errors and the need to maintain operational efficiency. Historically, delta check rules have been set by professional opinion based on reference change values (biological variation) or the published literature. Delta check rules implemented in this manner may not inform laboratory practitioners of their real-world performance. This review discusses several evidence-based approaches to the optimal setting of delta check rules that directly inform the laboratory practitioner of the error detection capabilities of the selected rules. Subsequent verification of workflow for the selected delta check rules is also discussed. This review is intended to provide practical assistance to laboratories in setting evidence-based delta check rules that best suits their local operational and clinical needs.

Original languageEnglish
Pages (from-to)49-59
Number of pages11
JournalCritical Reviews in Clinical Laboratory Sciences
Issue number1
Publication statusPublished - 2021
Externally publishedYes


  • analytical error
  • Auto-verification
  • delta check
  • laboratory error
  • post-analytical error
  • pre-analytical error
  • sample misidentification
  • sample mix-up
  • wrong blood in tube


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