Improvement in Pharmacy Student Responses to Medication-Related Problems with and without Clinical Decision Support Alerts
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Le résumé fourni par la source
OBJECTIVE: To assess pharmacy student responses to medication problems with and without clinical decision support (CDS) alerts during simulated order verification. METHODS: Three classes of students completed an order verification simulation. The simulation randomized students to a different series of 10 orders with varying CDS alert frequency. Two of the orders contained medication-related problems. The appropriateness of the students' interventions and responses to the CDS alerts were evaluated. In the following semester for 2 classes, 2 similar simulations were completed. All 3 simulations contained 1 problem with and 1 without an alert. RESULTS: During the first simulation, 384 students reviewed an order with a problem and an alert. Students exposed to prior inappropriate alerts within the simulation had less appropriate responses (66% vs 75%). Of 321 students who viewed a second order with a problem, those reviewing an order lacking an alert recommended an appropriate change less often (45% vs 87%). Among 351 students completing the second simulation, those who participated in the first simulation appropriately responded to the alert for a problem more often than those who only received a didactic debrief (95% vs 87%). Among those completing all 3 simulations, appropriate responses increased between simulations for problems with (n = 238, 72-95-93%) and without alerts (n = 49, 53-71-90%). CONCLUSIONS: Some pharmacy students displayed baseline alert fatigue and overreliance on CDS alerts for medication problem detection during order verification simulations. Exposure to the simulations improved CDS alert response appropriateness and detection of problems.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Improvement in Pharmacy Student Responses to Medication-Related Problems with and without Clinical Decision Support Alerts
- Date Crossref
- 01/05/2023
- Éditeur
- Elsevier BV
- Type
- journal-article
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