Impact of an electronic health record alert on inappropriate prescribing of high-risk medications to patients with concurrent "do not give" orders.
Am J Health Syst Pharm
; 79(14): 1198-1204, 2022 07 08.
Article
in English
| MEDLINE | ID: covidwho-1764495
ABSTRACT
PURPOSE:
To evaluate the effectiveness of clinical decision support (CDS) alerts tied to high-risk medications at a Michigan health system by determining the true prescriber action rate in response to select "do not give" (DNG) alerts.METHODS:
A retrospective review of prescriber actions in response to CDS alerts was conducted to evaluate the effectiveness of alerts designed to prevent prescribing of high-risk medications to patients with concurrent DNG orders. The primary endpoint was the overall action rate, determined by totaling orders cancelled within the alert display and orders modified shortly after an alert. The overall action rate was hypothesized to significantly exceed the action rate estimated on the basis of alert overrides alone. Following the initial review, changes were made to the alert format and preset documentation choices ("acknowledgement comments"), and it was hypothesized that these changes would increase the overall action rate. A repeat analysis was conducted to evaluate the impact of these changes.RESULTS:
Across a total of 506 CDS alerts over 14 months, 78% resulted in prescribers modifying orders to comply with alert recommendations. Prescribers cancelled orders in response to only 26% of alerts, often overriding alerts prior to modifying orders. Documentation of rationale or approval for overrides was inconsistent, and while requiring acknowledgement comments facilitated documentation of prescriber rationale, it did not consistently improve overall action rates.CONCLUSION:
These findings demonstrate that override rates alone are not good markers for the true effectiveness of CDS alerts and support the need for frequent evaluation of alerts at the institutional level. CDS alerts remain a valuable tool to prevent inappropriate prescribing of high-risk medications and for promoting patient safety.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Decision Support Systems, Clinical
/
Medical Order Entry Systems
/
Electronic Prescribing
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Am J Health Syst Pharm
Journal subject:
Pharmacy
/
Hospitals
Year:
2022
Document Type:
Article
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