The Effects of Medication Alerts on Prescriber Response in a Pediatric Hospital

Appl Clin Inform. 2017 May 10;8(2):491-501. doi: 10.4338/ACI-2016-10-RA-0168.

Abstract

Objective: More than 70% of hospitals in the United States have electronic health records (EHRs). Clinical decision support (CDS) presents clinicians with electronic alerts during the course of patient care; however, alert fatigue can influence a provider's response to any EHR alert. The primary goal was to evaluate the effects of alert burden on user response to the alerts.

Methods: We performed a retrospective study of medication alerts over a 24-month period (1/2013-12/2014) in a large pediatric academic medical center. The institutional review board approved this study. The primary outcome measure was alert salience, a measure of whether or not the prescriber took any corrective action on the order that generated an alert. We estimated the ideal number of alerts to maximize salience. Salience rates were examined for providers at each training level, by day of week, and time of day through logistic regressions.

Results: While salience never exceeded 38%, 49 alerts/day were associated with maximal salience in our dataset. The time of day an order was placed was associated with alert salience (maximal salience 2am). The day of the week was also associated with alert salience (maximal salience on Wednesday). Provider role did not have an impact on salience.

Conclusion: Alert burden plays a role in influencing provider response to medication alerts. An increased number of alerts a provider saw during a one-day period did not directly lead to decreased response to alerts. Given the multiple factors influencing the response to alerts, efforts focused solely on burden are not likely to be effective.

Keywords: Medical informatics; alert fatigue; alerting; clinical decision support; electronic health records and systems; inpatient (inpatient CPOE).

MeSH terms

  • Child
  • Drug Prescriptions*
  • Electronic Health Records
  • Hospitals, Pediatric*
  • Humans
  • Medical Order Entry Systems*
  • Outcome Assessment, Health Care