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

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.

Keywords

clinical decision support - process management tools - specific types - clinical information systems - drug–drug interaction - alerting - system improvement - alert fatigue

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.

• References

• 1 Bates DW, Leape LL, Cullen DJ. , et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998; 280 (15) 1311-1316
• 2 Nanji KC, Seger DL, Slight SP. , et al. Medication-related clinical decision support alert overrides in inpatients. J Am Med Inform Assoc 2018; 25 (05) 476-481
• 3 Nanji KC, Slight SP, Seger DL. , et al. Overrides of medication-related clinical decision support alerts in outpatients. J Am Med Inform Assoc 2014; 21 (03) 487-491
• 4 Leapfrog Group. Castlight Health. Preventing medication errors in hospitals. 2016 . Available at: http://www.leapfroggroup.org/sites/default/files/Files/Leapfrog-Castlight%20Medication%20Safety%20Report.pdf . Accessed February 28, 2019
• 5 Payne TH, Hines LE, Chan RC. , et al. Recommendations to improve the usability of drug-drug interaction clinical decision support alerts. J Am Med Inform Assoc 2015; 22 (06) 1243-1250
• 6 Saiyed SM, Greco PJ, Fernandes G, Kaelber DC. Optimizing drug-dose alerts using commercial software throughout an integrated health care system. J Am Med Inform Assoc 2017; 24 (06) 1149-1154
• 7 McEvoy DS, Sittig DF, Hickman TT. , et al. Variation in high-priority drug-drug interaction alerts across institutions and electronic health records. J Am Med Inform Assoc 2017; 24 (02) 331-338
• 8 Scharnweber C, Lau BD, Mollenkopf N, Thiemann DR, Veltri MA, Lehmann CU. Evaluation of medication dose alerts in pediatric inpatients. Int J Med Inform 2013; 82 (08) 676-683
• 9 Wong A, Wright A, Seger DL, Amato MG, Fiskio JM, Bates D. Comparison of overridden medication-related clinical decision support in the intensive care unit between a commercial system and a legacy system. Appl Clin Inform 2017; 8 (03) 866-879
• 10 van der Sijs H, Aarts J, Vulto A, Berg M. Overriding of drug safety alerts in computerized physician order entry. J Am Med Inform Assoc 2006; 13 (02) 138-147
• 11 Rehr CA, Wong A, Seger DL, Bates DW. Determining inappropriate medication alerts from “inaccurate warning” overrides in the intensive care unit. Appl Clin Inform 2018; 9 (02) 268-274
• 12 Dexheimer JW, Kirkendall ES, Kouril M. , et al. The effects of medication alerts on prescriber response in a pediatric hospital. Appl Clin Inform 2017; 8 (02) 491-501
• 13 Sittig DF, Singh H. Electronic health records and national patient-safety goals. N Engl J Med 2012; 367 (19) 1854-1860
• 14 Lee J, Han H, Ock M, Lee SI, Lee S, Jo MW. Impact of a clinical decision support system for high-alert medications on the prevention of prescription errors. Int J Med Inform 2014; 83 (12) 929-940
• 15 Gregory ME, Russo E, Singh H. Electronic health record alert-related workload as a predictor of burnout in primary care providers. Appl Clin Inform 2017; 8 (03) 686-697
• 16 Osheroff JA, Teich JM, Middleton B, Steen EB, Wright A, Detmer DE. A roadmap for national action on clinical decision support. [published correction appears in J Am Med Inform Assoc. 2007 May-Jun;14(3):389]. J Am Med Inform Assoc 2007; 14 (02) 141-145