Dynamic reaction picklist for improving allergy reaction documentation: A usability study. (February 2023)

• Record Type: Journal Article
• Authors: Wang, Liqin; Park, Heekyong; Vallamkonda, Sachin; Seger, Diane L.; Blackley, Suzanne V.; Garabedian, Pamela M.; Goss, Foster; Blumenthal, Kimberly G.; Bates, David W.; Murphy, Shawn; Zhou, Li
• Is Part Of: International journal of medical informatics. Volume 170(2023)
• Publication Date: 2023-02
• Subjects: Drug hypersensitivity -- Drug-related side effects and adverse reactions -- Electronic health record -- Documentation -- User interface evaluation -- Usability; EHR Electronic Health Record -- CDS Clinical Decision Support -- TFIDF Term Frequency Inverse Document Frequency -- MGB Mass General Brigham -- UI User Interface; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2022.104939
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: Dynamic reaction picklists significantly reduced the number of free-text entries. Dynamic reaction picklists could reduce the time for allergy documentation by 15%. Clinicians preferred dynamic reaction picklist over static picklist. Abstract: Objective: To assess novel dynamic reaction picklists for improving allergy reaction documentation compared to a static reaction picklist. Materials and methods: We developed three web-based user interfaces (UIs) mimicking the Mass General Brigham's EHR allergy module: the first and second UIs (i.e., UI-1D, UI-2D) implemented two dynamic reaction picklists with different ranking algorithms and the third UI (UI-3S) implemented a static reaction picklist like the one used in the current EHR. We recruited 18 clinicians to perform allergy entry for 10 test cases each via UI-1D and UI-3S, and another 18 clinicians via UI-2D and UI-3S. Primary measures were the number of free-text entries and time to complete the allergy entry. Clinicians were also interviewed using 30 questions before and after the data entry. Results and discussions: Among 36 clinicians, less than half were satisfied with the current EHR reaction picklists, due to their incomprehensiveness, inefficiency, and lack of intuitiveness. The clinicians used significantly fewer free-text entries when using UI-1D or UI-2D compared to UI-3S ( p < 0.05). The clinicians used on average 51 s (15 %) less time via UI-1D and 50 s (16 %) less time via UI-2D in completing the allergy entries versus UI-3S, and there was not a statistically significant difference in documentation time for either group between the dynamic and static UIs. Overall, 15–17 (83–94 %) clinicians rated UI-1D and 13–15 (72–83 %) clinicians rated UI-2D as efficient, easy to use, and useful, while less than half rated the same for UI-3S. Most clinicians reported that the dynamic reaction picklists always or often suggested appropriate reactions (n = 30, 83 %) and would decrease the free-text entries (n = 26, 72 %); nearly all preferred the dynamic picklist over the static picklist (n = 32, 89 %). Conclusion: We found that dynamic reaction picklists significantly reduced the number of free-text entries and could reduce the time for allergy documentation by 15%. Clinicians preferred the dynamic reaction picklist over the static picklist.