Difference between revisions of "Drug interaction alert override rates in the Meaningful Use era"

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[[Category: Alerts]]

Revision as of 01:30, 23 November 2015

This is a review of the article written by Bryant, Fletcher, and Payne (2010) : Creating Drug Interaction Alert Override Rates in the Meaningful Use era. [1]


Introduction

Alert fatigue has been a serious issue in healthcare. Interruptive drug interaction alerts may reduce adverse drug events, but they have been bypassed by healthcare workers. Override rates have been very high, and despite the convenience of commercial EHR systems, there has not been a proper investigation on the acceptance of these alerts

Methods

The purpose of the study was to measure the override rates of impatient medication alerts within a commercial clinical decision support system. The study also measures the override rates between drug-drug interaction, and drug-allergy interaction alerts. The response to the alerts was retrospectively analyzed.

Results

Over four days into the study there were 18,354 medication orders. In those orders 2,455 alerts were seen, and 2,280 over those alerts were overridden. The override rate of the drug-drug alert override rate was 95.1%, and the drug-allergy alerts were 90.9%. Overall, a majority of the alerts that were seen were overridden every time they appeared.

Conclusion

The alerts provide a good way to prevent healthcare workers from making mistakes in the healthcare field. But the constant and repetitive appearance of these alerts led these healthcare workers to what it’s called alert fatigue. Alert fatigue involves being exposed to a large number of alerts and becoming desensitized to them. The physicians in this study have been constantly exposed to these alerts and are bypassing them. However, in doing so they can cause important information overlooked and serious consequences can occur to either the patient or the physician. There are ways to prevent alarm fatigue from becoming a frequent problem, but alarm fatigue can only be reduced, not eliminated.


References

  1. Lee, E. K., Mejia, A. F., Senior, T., & Jose, J. (2010). Improving Patient Safety through Medical Alert Management: An Automated Decision Tool to Reduce Alert Fatigue. AMIA Annual Symposium Proceedings, 2010, 417–421. http://www.ncbi.nlm.nih.gov/pubmed/25298818