Structured override reasons for drug-drug interaction alerts in electronic health records

Author:

Wright Adam1234,McEvoy Dustin S4,Aaron Skye1,McCoy Allison B5,Amato Mary G16,Kim Hyun7ORCID,Ai Angela8,Cimino James J9,Desai Bimal R10,El-Kareh Robert11,Galanter William12,Longhurst Christopher A11ORCID,Malhotra Sameer13,Radecki Ryan P14,Samal Lipika12,Schreiber Richard15,Shelov Eric10,Sirajuddin Anwar Mohammad16,Sittig Dean F17

Affiliation:

1. Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts, USA

2. Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA

3. Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA

4. Partners eCare, Partners HealthCare, Boston, Massachusetts, USA

5. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA

6. Department of Pharmacy Practice, Massachusetts College of Pharmacy and Health Sciences University, Boston, Massachusetts, USA

7. Clinical Pharmacogenomics Service, Boston Children’s Hospital, Boston, Massachusetts, USA

8. University of Wisconsin School of Medicine and Public Health, University of Wisconsin Madison, Madison, Wisconsin, USA

9. Informatics Institute and Department of Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA

10. Division of General Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA

11. Department of Medicine, UC San Diego Health, University of California, San Diego, San Diego, California, USA

12. Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA

13. Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, New York, USA

14. Department of Emergency Medicine, Northwest Permanente, Portland, Oregon, USA

15. Physician Informatics and Department of Internal Medicine, Geisinger Holy Spirit, Camp Hill, Pennsylvania, USA

16. Department of Medical Informatics, Memorial Hermann Health System, Houston, Texas, USA

17. School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA

Abstract

Abstract Objective The study sought to determine availability and use of structured override reasons for drug-drug interaction (DDI) alerts in electronic health records. Materials and Methods We collected data on DDI alerts and override reasons from 10 clinical sites across the United States using a variety of electronic health records. We used a multistage iterative card sort method to categorize the override reasons from all sites and identified best practices. Results Our methodology established 177 unique override reasons across the 10 sites. The number of coded override reasons at each site ranged from 3 to 100. Many sites offered override reasons not relevant to DDIs. Twelve categories of override reasons were identified. Three categories accounted for 78% of all overrides: “will monitor or take precautions,” “not clinically significant,” and “benefit outweighs risk.” Discussion We found wide variability in override reasons between sites and many opportunities to improve alerts. Some override reasons were irrelevant to DDIs. Many override reasons attested to a future action (eg, decreasing a dose or ordering monitoring tests), which requires an additional step after the alert is overridden, unless the alert is made actionable. Some override reasons deferred to another party, although override reasons often are not visible to other users. Many override reasons stated that the alert was inaccurate, suggesting that specificity of alerts could be improved. Conclusions Organizations should improve the options available to providers who choose to override DDI alerts. DDI alerting systems should be actionable and alerts should be tailored to the patient and drug pairs.

Funder

National Library of Medicine

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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