Appl Clin Inform 2019; 10(05): 777-782
DOI: 10.1055/s-0039-1697596
Case Report
Georg Thieme Verlag KG Stuttgart · New York

Differences, Opportunities, and Strategies in Drug Alert Optimization—Experiences of Two Different Integrated Health Care Systems

Salim M. Saiyed
1  Division of Health Sciences Informatics, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States
2  CaroMont Health, Gastonia, North Carolina, United States
,
Katherine R. Davis
3  Department of Family Medicine, The MetroHealth System, Case Western Reserve University, Cleveland, Ohio, United States
4  The Center for Clinical Informatics Research and Education, The MetroHealth System, Case Western Reserve University, Cleveland, Ohio, United States
,
David C. Kaelber
4  The Center for Clinical Informatics Research and Education, The MetroHealth System, Case Western Reserve University, Cleveland, Ohio, United States
5  Department of Internal Medicine, The MetroHealth System, Case Western Reserve University, Cleveland, Ohio, United States
6  Department of Pediatrics, The MetroHealth System, Case Western Reserve University, Cleveland, Ohio, United States
7  Department of Population and Quantitative Health Sciences, The MetroHealth System, Case Western Reserve University, Cleveland, Ohio, United States
› Author Affiliations
Funding None.
Further Information

Publication History

21 March 2019

05 August 2019

Publication Date:
16 October 2019 (online)

Abstract

Background Concerns about the number of automated medication alerts issued within the electronic health record (EHR), and the subsequent potential for alarm fatigue, led us to examine strategies and methods to optimize the configuration of our drug alerts.

Objectives This article reports on comprehensive drug alerting rates and develops strategies across two different health care systems to reduce the number of drug alerts.

Methods Standardized reports compared drug alert rates between the two systems, among 13 categories of drug alerts. Both health care systems made modifications to the out-of-box alerts available from their EHR and drug information vendors, focusing on system-wide approaches, when relevant, while performing more drug-specific changes when necessary.

Results Drug alerting rates even after initial optimization were 38 alerts and 51 alerts per 100 drug orders, respectively. Eight principles were identified and developed to reflect the themes in the implementation and optimization of drug alerting.

Conclusion A team-based, systematic approach to optimizing drug-alerting strategies can reduce the number of drug alerts, but alert rates still remain high. In addition to strategic principles, additional tactical guidelines and recommendations need to be developed to enhance out-of-the-box clinical decision support for drug alerts.

Authors' Contributions

All authors made substantial contributions to the manuscript. S.S. and K.D. served as the lead authors, conducting data analysis and leading manuscript preparation and writing. D.K. provided substantial guidance, feedback, and edits during the research and edit process. All authors have approved this work.


Protection of Human and Animal subjects

No human subjects were involved in the project.