Vanderbilt Electronic Health Record Voice Assistant Supports Clinicians

Yaa A. Kumah-Crystal; Christoph U. Lehmann; Dan Albert; Tim Coffman; Hala Alaw; Sydney Roth; Alexandra Manoni; Peter Shave; Kevin B. Johnson

doi:10.1055/a-2177-4420

Applied Clinical Informatics, Inhaltsverzeichnis

Appl Clin Inform 2024; 15(02): 199-203
DOI: 10.1055/a-2177-4420

Research Article

Vanderbilt Electronic Health Record Voice Assistant Supports Clinicians

Authors

Yaa A. Kumah-Crystal

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Christoph U. Lehmann

²Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, Texas, United States
Dan Albert

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Tim Coffman

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Hala Alaw

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Sydney Roth

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Alexandra Manoni

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Peter Shave

¹Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Kevin B. Johnson

³Department of Biomedical Informatics, University of Pennsylvania, Richards, Philadelphia, Pennsylvania, United States

Abstract

Background Electronic health records (EHRs) 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 EHR.

Objectives To develop a voice-mediated 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 14 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 health care.

Keywords

EHRs and systems - human–computer interaction - clinical decision support - natural language processing - clinical data management

Volltext

Referenzen

References
1 Lasko TA, Owens DA, Fabbri D, Wanderer JP, Genkins JZ, Novak LL. User-centered clinical display design issues for inpatient providers. Appl Clin Inform 2020; 11 (05) 700-709
2 Kumah-Crystal YA, Pirtle CJ, Whyte HM, Goode ES, Anders SH, Lehmann CU. Electronic health record interactions through voice: a review. Appl Clin Inform 2018; 9 (03) 541-552
3 Luengo-Polo J, Conde-Caballero D, Rivero-Jiménez B, Ballesteros-Yáñez I, Castillo-Sarmiento CA, Mariano-Juárez L. Rationale and methods of evaluation for ACHO, a new virtual assistant to improve therapeutic adherence in rural elderly populations: a user-driven living lab. Int J Environ Res Public Health 2021; 18 (15) 7904
4 Sezgin E, Noritz G, Lin S, Huang Y. Feasibility of a voice-enabled medical diary app (SpeakHealth) for caregivers of children with special health care needs and health care providers: mixed methods study. JMIR Form Res 2021; 5 (05) e25503
5 Jones VK, Hanus M, Yan C, Shade MY, Blaskewicz Boron J, Maschieri Bicudo R. Reducing loneliness among aging adults: the roles of personal voice assistants and anthropomorphic interactions. Front Public Health 2021; 9: 750736
6 Wilder JL, Nadar D, Gujral N. et al. Pediatrician attitudes toward digital voice assistant technology use in clinical practice. Appl Clin Inform 2019; 10 (02) 286-294
7 Frintner MP, Kaelber DC, Kirkendall ES, Lourie EM, Somberg CA, Lehmann CU. The effect of electronic health record burden on pediatricians' work-life balance and career satisfaction. Appl Clin Inform 2021; 12 (03) 697-707
8 Kissel AM, Maddox K, Francis JKR. et al. Effects of the electronic health record on job satisfaction of academic pediatric faculty. Int J Med Inform 2022; 168: 104881
9 Angular. Explore angular resources. Secondary explore angular resources n.d. Accessed August 30, 2023 https://angular.io/resources?category=development
10 Mandel JC, Kreda DA, Mandl KD, Kohane IS, Ramoni RB. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. J Am Med Inform Assoc 2016; 23 (05) 899-908
11 Fielding RT. Architectural styles and the design of network-based software architectures. 2000
12 Nuance Communications Inc. Medical speech recognition solutions. Secondary Medical speech recognition solutions n.d. Accessed August 30,2023 at https://www.nuance.com/healthcare/provider-solutions/speech-recognition.html
13 Corbisiero E, Costagliola G, Rosa MD, Fuccella V, Piscitelli A, Tabari P. Speech recognition in healthcare: a comparison of different speech recognition input interactions. International KES Conference on Innovation in Medicine and Healthcare, 2023: 142-52
14 Duda SN, Kennedy N, Conway D. et al. HL7 FHIR-based tools and initiatives to support clinical research: a scoping review. J Am Med Inform Assoc 2022; 29 (09) 1642-1653
15 Brooke J. SUS - a quick and dirty usability scale. Usability Evaluation in Industry, 1996: 4-7
16 Hoyt R, Yoshihashi A. Lessons learned from implementation of voice recognition for documentation in the military electronic health record system. Perspect Health Inf Manag 2010; 7 (Winter): 1e
17 Pirolli P, Card S. Information foraging. Psychol Rev 1999; 106 (04) 643

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