Literature DB >> 31361861

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

Sunny B Bhakta1,2, A Carmine Colavecchia1,2, Linda Haines1, Divya Varkey3, Kevin W Garey3.   

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. © American Society of Health-System Pharmacists 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  adverse events; automation; clinical pharmacy; pharmacovigilance

Year:  2019        PMID: 31361861     DOI: 10.1093/ajhp/zxz012

Source DB:  PubMed          Journal:  Am J Health Syst Pharm        ISSN: 1079-2082            Impact factor:   2.637


  4 in total

1.  Optimizing clinical decision support alerts in electronic medical records: a systematic review of reported strategies adopted by hospitals.

Authors:  Bethany A Van Dort; Wu Yi Zheng; Vivek Sundar; Melissa T Baysari
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

Review 2.  Reducing medication errors for adults in hospital settings.

Authors:  Agustín Ciapponi; Simon E Fernandez Nievas; Mariana Seijo; María Belén Rodríguez; Valeria Vietto; Herney A García-Perdomo; Sacha Virgilio; Ana V Fajreldines; Josep Tost; Christopher J Rose; Ezequiel Garcia-Elorrio
Journal:  Cochrane Database Syst Rev       Date:  2021-11-25

3.  Pharmacists' perceptions of a machine learning model for the identification of atypical medication orders.

Authors:  Sophie-Camille Hogue; Flora Chen; Geneviève Brassard; Denis Lebel; Jean-François Bussières; Audrey Durand; Maxime Thibault
Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

4.  Assessment of Physician's Knowledge of Potential Drug-Drug Interactions: An Online Survey in China.

Authors:  Jing Yuan; Chunying Shen; Chengnan Wang; Gang Shen; Bing Han
Journal:  Front Med (Lausanne)       Date:  2021-03-01
  4 in total

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