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Related Experiment Video

Updated: May 12, 2026

Remote Neuronal Activation Coupled with Automated Blood Sampling to Induce and Measure Circulating Luteinizing Hormone in Mice

Remote Neuronal Activation Coupled with Automated Blood Sampling to Induce and Measure Circulating Luteinizing Hormone in Mice

Published on: August 25, 2023

Computerized bar code-based blood identification systems and near-miss transfusion episodes and transfusion errors.

Gregory A Nuttall¹, John P Abenstein, James R Stubbs

¹Department of Anesthesiology, Mayo Clinic, Rochester, MN 55905, USA. gnuttall@mayo.edu

Mayo Clinic Proceedings

|April 2, 2013

Summary

A computerized bar code system for blood transfusions did not reduce errors but significantly increased the detection of near-miss events. This highlights improved safety monitoring in transfusion practices.

Related Experiment Videos

Last Updated: May 12, 2026

Remote Neuronal Activation Coupled with Automated Blood Sampling to Induce and Measure Circulating Luteinizing Hormone in Mice

Remote Neuronal Activation Coupled with Automated Blood Sampling to Induce and Measure Circulating Luteinizing Hormone in Mice

Published on: August 25, 2023

Area of Science:

Medical Informatics
Patient Safety
Transfusion Medicine

Background:

Transfusion errors pose significant risks to patient safety.
Accurate identification of blood products and patients is critical to prevent adverse events.
Existing manual identification processes are prone to human error.

Purpose of the Study:

To evaluate the impact of a computerized bar code-based blood identification system on transfusion errors.
To assess changes in the incidence of transfusion errors and near-miss events before and after system implementation.

Main Methods:

Retrospective analysis of transfusion error data from January 2002 to December 2005 (pre-implementation).
Retrospective analysis of transfusion error data from January 2007 to December 2010 (post-implementation).
Comparison of misidentification and near-miss transfusion episode rates between the two periods.

Main Results:

Before implementation (2002-2005), there were 6 misidentification errors (1.5 per 100,000 U) and 1 near-miss event (0.3 per 100,000 U).
After implementation (2007-2010), there was 1 misidentification error (0.3 per 100,000 U) and 34 near-miss events (11.2 per 100,000 U).
The implementation of the bar code system was associated with a statistically significant increase in reported near-miss transfusion errors (P<.001).

Conclusions:

A computerized bar code system did not significantly reduce transfusion misidentification errors.
The system led to a substantial increase in the detection and reporting of near-miss transfusion events.
This suggests enhanced vigilance and improved safety monitoring within the transfusion process.