Using Machine Learning-Based Multianalyte Delta Checks to Detect Wrong Blood in Tube Errors.
Journal:
American journal of clinical pathology
Published Date:
Oct 24, 2018
Abstract
OBJECTIVES: An unfortunate reality of laboratory medicine is that blood specimens collected from one patient occasionally get mislabeled with identifiers from a different patient, resulting in so-called "wrong blood in tube" (WBIT) errors and potential patient harm. Here, we sought to develop a machine learning-based, multianalyte delta check algorithm to detect WBIT errors and mitigate patient harm.