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Am J Health Syst Pharm. 2019 Apr 8;76(8):530-536. doi: 10.1093/ajhp/zxz012.

A systematic approach to optimize electronic health record medication alerts in a health system.

Author information

1
Department of Pharmacy Services, Houston Methodist Hospital, Houston, TX.
2
University of Houston College of Pharmacy, Houston, TX.
3
Department of Pharmacy Practice and Translational Research, University of Houston College of Pharmacy, Houston, TX.

Abstract

PURPOSE:

The effectiveness of a systematic, streamlined approach to optimize drug-drug interaction alerts in an electronic health record for a health system was studied.

METHODS:

An 81-week quasi-experimental study was conducted to evaluate interventions made to medication-related clinical decision-support (CDS) alerts. Medication-related CDS alerts were systematically reduced using a multi disciplinary healthcare committee. The primary endpoint was weekly overall, modification, and acknowledgement rates of medication alerts after drug-drug interaction reclassification. Secondary endpoints included sub analysis of types of medication alerts (drug-drug interaction and duplicate therapy alerts) and alert use by providers (pharmacist and prescribers). Data was analyzed using interrupted time series regression analysis.

RESULTS:

After implementation of the new alert system, total number of weekly inpatient alerts decreased from 68,900 (66,300-70,900) and 50,300 (48,600-53,600) in the postintervention period (p < 0.001). The perentage of alerts acknowledged weekly increased from 11.8% (IQR, 11.4-12.1%) in the preintervention period to 13.7% (IQR, 13.3-14.0%) in the postintervention period (p < 0.001). The percentage of alerts that were modified also increased from 5.0% (IQR, 4.9-5.3%) in the preintervention period to 7.3% (IQR, 7.0-7.6%) in the postintervention period (p < 0.001). Both increases were primarily seen with pharmacists versus other healthcare professionals (p < 0.001).

CONCLUSION:

A committee-led systematic approach to optimizing drug-drug interactions facilitated a significant decrease in the overall number of alerts and an increase in both medication alert acknowledgement and modification rates.

KEYWORDS:

adverse events; automation; clinical pharmacy; pharmacovigilance

PMID:
31361861
DOI:
10.1093/ajhp/zxz012

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