Vanderbilt Electronic Health Record Voice Assistant Supports Clinicians

Abstract

Introduction: Electronic health records present navigation challenges due to time-consuming searches across segmented data. Voice assistants can improve clinical workflows by allowing natural language queries and contextually aware navigation of the electronic health record. Objective: To develop a voice-mediated electronic health record (EHR) assistant and interview providers to inform its future refinement. Methods: The Vanderbilt EHR Voice Assistant (VEVA) was developed as a responsive web application and designed to accept voice inputs and execute the appropriate EHR commands. Fourteen providers from Vanderbilt Medical Center were recruited to participate in interactions with VEVA and to share their experience with the technology. The purpose was to evaluate VEVA’s overall usability, gather qualitative feedback, and detail suggestions for enhancing its performance. Results: VEVA’s mean system usability scale score was 81 based on the fourteen providers’ evaluations, which was above the standard 50th percentile score of 68. For all five summaries evaluated (overview summary, A1C results, blood pressure, weight, and health maintenance), most providers offered a positive review of VEVA. Several providers suggested modifications to make the technology more useful in their practice, ranging from summarizing current medications to changing VEVA’s speech rate. Eight of the providers (64%) reported they would be willing to use VEVA in its current form. Conclusion: Our EHR voice assistant technology was deemed usable by most providers. With further improvements, voice assistant tools such as VEVA have the potential to improve workflows and serve as a useful adjunct tool in healthcare.

Designing the User Interface of a Nitroglycerin Dose Titration Decision Support System: User-Centered Design Study

“…24 This scale has garnered extensive use in assessing usability relating to health care applications. 26 27 28 OADRI is a validated instrument to measure the acceptability of clinical decision rules in the context of CDSS; therefore, it was selected for use in this study. 29 It is a 12-item instrument on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree).…”