Feasibility and acceptability testing of CommSense: A novel communication technology to enhance health equity in clinician-patient interactions

Virginia LeBaron; Tabor Flickinger; David Ling; Hansung Lee; James Edwards; Anant Tewari; Zhiyuan Wang; Laura E Barnes

doi:10.1177/20552076231184991

Feasibility and acceptability testing of CommSense: A novel communication technology to enhance health equity in clinician-patient interactions

Digit Health. 2023 Jul 11:9:20552076231184991. doi: 10.1177/20552076231184991. eCollection 2023 Jan-Dec.

Authors

Virginia LeBaron¹, Tabor Flickinger², David Ling², Hansung Lee², James Edwards¹, Anant Tewari², Zhiyuan Wang³, Laura E Barnes³

Affiliations

¹ University of Virginia School of Nursing, Charlottesville, VA.
² University of Virginia School of Medicine, Charlottesville, VA.
³ University of Virginia School of Engineering & Applied Science, Charlottesville, VA.

Abstract

Background: Quality patient-clinician communication is paramount to achieving safe and compassionate healthcare, but evaluating communication performance during real clinical encounters is challenging. Technology offers novel opportunities to provide clinicians with actionable feedback to enhance their communication skills.

Methods: This pilot study evaluated the acceptability and feasibility of CommSense, a novel natural language processing (NLP) application designed to record and extract key metrics of communication performance and provide real-time feedback to clinicians. Metrics of communication performance were established from a review of the literature and technical feasibility verified. CommSense was deployed on a wearable (smartwatch), and participants were recruited from an academic medical center to test the technology. Participants completed a survey about their experience; results were exported to SPSS (v.28.0) for descriptive analysis.

Results: Forty (n = 40) healthcare participants (nursing students, medical students, nurses, and physicians) pilot tested CommSense. Over 90% of participants "strongly agreed" or "agreed" that CommSense could improve compassionate communication (n = 38, 95%) and help healthcare organizations deliver high-quality care (n = 39, 97.5%). Most participants (n = 37, 92.5%) "strongly agreed" or "agreed" they would be willing to use CommSense in the future; 100% (n = 40) "strongly agreed" or "agreed" they were interested in seeing information analyzed by CommSense about their communication performance. Metrics of most interest were medical jargon, interruptions, and speech dominance.

Conclusion: Participants perceived significant benefits of CommSense to track and improve communication skills. Future work will deploy CommSense in the clinical setting with a more diverse group of participants, validate data fidelity, and explore optimal ways to share data analyzed by CommSense with end-users.

Keywords: Communication; digital health; natural language processing; palliative care; wearables.