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

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.