Building an allergy reconciliation module to eliminate allergy discrepancies in electronic health records.

IF 4.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Suzanne V Blackley, Ying-Chih Lo, Sheril Varghese, Frank Y Chang, Oliver D James, Diane L Seger, Kimberly G Blumenthal, Foster R Goss, Li Zhou
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引用次数: 0

Abstract

Objective: Accurate, complete allergy histories are critical for decision-making and medication prescription. However, allergy information is often spread across the electronic health record (EHR); thus, allergy lists are often inaccurate or incomplete. Discrepant allergy information can lead to suboptimal or unsafe clinical care and contribute to alert fatigue. We developed an allergy reconciliation module within Mass General Brigham (MGB)'s EHR to support accurate and intuitive reconciliation of discrepancies in the allergy list, thereby enhancing patient safety.

Materials and methods: We combined data-driven methods and knowledge from domain experts to develop 5 mechanisms to compare allergy information across the EHR and designed a user interface to display discrepancies and suggested reconciliation actions, with links to relevant data sources. Qualitative and quantitative analyses were conducted to assess the module's performance and measure user acceptance.

Results: We implemented and tested the proposed allergy reconciliation mechanisms and module. A comprehensive integration workflow was developed for the module, which was piloted among 111 primary care physicians at MGB. F1 scores of the reconciliation mechanisms range from 0.86 to 1.0. Qualitative analysis showed majority positive feedback from pilot users.

Discussion: Our allergy reconciliation module achieved high performance, and physicians who used it largely accepted its recommendations. However, 56% of the pilot group ultimately did not use the module. User engagement and education are likely needed to increase adoption.

Conclusion: We built a module to automatically identify discrepancies within patients' allergy records and remind providers to reconcile and update the allergy list. Its high accuracy shows promise for enhancing patient safety and utility of drug allergy alerts.

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来源期刊
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association 医学-计算机:跨学科应用
CiteScore
14.50
自引率
7.80%
发文量
230
审稿时长
3-8 weeks
期刊介绍: JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
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