Difference between revisions of "Informatics Interchange - Alert Fatigue"

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== Comments ==
 
== Comments ==
 
The authors were successful in determining the type of alerts, which ones were most commonly ignored, how many alerts of each specific types, the number of occurrences of the alerts, and also many other stats. However, in the paper, the authors only recommend ways to reduce the number of alerts and how to make the alerts more effective. Other studies suggest that use of [[Evaluation of Medication Alerts in Electronic Health Records for Compliance with Human Factors Principles|human factors design principles]] may improve receptiveness to alerts. It would have been really nice if the authors were able to actually implement these recommendations to their study and then follow up after a period of time to determine if their recommendations were successful.
 
The authors were successful in determining the type of alerts, which ones were most commonly ignored, how many alerts of each specific types, the number of occurrences of the alerts, and also many other stats. However, in the paper, the authors only recommend ways to reduce the number of alerts and how to make the alerts more effective. Other studies suggest that use of [[Evaluation of Medication Alerts in Electronic Health Records for Compliance with Human Factors Principles|human factors design principles]] may improve receptiveness to alerts. It would have been really nice if the authors were able to actually implement these recommendations to their study and then follow up after a period of time to determine if their recommendations were successful.
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==Related Article Review ==
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[[A Framework for Evaluating the Appropriateness of Clinical Decision Support Alerts and Responses]]
  
 
== References ==
 
== References ==

Revision as of 04:56, 25 February 2015

This is a review of Jared J. Cash's (2009) article, Alert Fatigue published on the American Journal of Health-System Pharmacy. [1]

Summary

Clinical Decision Support (CDS) enhance the clinicians' workflow and decision making. The authors discuss Alert Fatigue, which is one of the unintended consequences of a CDS. Alert Fatigue, as the name implies, is when the end user begins to ignore the numerous pop ups and notification from the system. A lot of times, physicians ignores or overrides the alerts because they are relying on their own judgment or because the alert does not necessarily apply to the situation. Alert fatigue is the most common complaint about CPOE systems and alerts are overridden 49-96% of the time. [1]


Study

The authors tried to determine the following information:

  • How many alerts occurred per week, per day, per shift, per patient, per pharmacist?
  • The most common type of alerts
  • The most common triggers
  • Most common reasons why alerts are overridden
    • Ex: The system will automatically send an alert when two sedatives are ordered, in reality, the operating room uses two or even three sedatives at the same time.
  • If the override reasons were mandatory


Results

From the data they gathered, the authors were able to determine a few ways to reduce the frequency of the alerts.

  • Change the sensitivity of alerts
    • Firing alerts only when the severity is high
  • Customizing alerts based on practices
    • In a trauma setting, the medication used may require higher dosage while the dosing in an ambulatory setting may not need such high dosage.
  • Keeping the patient’s allergies up to date
  • Allowing more options on the alerts such as alternative dosing


Comments

The authors were successful in determining the type of alerts, which ones were most commonly ignored, how many alerts of each specific types, the number of occurrences of the alerts, and also many other stats. However, in the paper, the authors only recommend ways to reduce the number of alerts and how to make the alerts more effective. Other studies suggest that use of human factors design principles may improve receptiveness to alerts. It would have been really nice if the authors were able to actually implement these recommendations to their study and then follow up after a period of time to determine if their recommendations were successful.

Related Article Review

A Framework for Evaluating the Appropriateness of Clinical Decision Support Alerts and Responses

References

  1. 1.0 1.1 Cash, J. J., (2009). Alert Fatigue. http://www.ajhp.org/content/66/23/2098?hw-tma-check=true