Accepted for/Published in: JMIR Research Protocols
Date Submitted: Mar 14, 2022
Open Peer Review Period: Mar 14, 2022 - Mar 21, 2022
Date Accepted: Mar 30, 2022
(closed for review but you can still tweet)
Exploring the use of wearable sensors and natural language processing technology to improve patient-clinician communication: Protocol for a feasibility study
ABSTRACT
Background:
Effective communication is the bedrock of quality healthcare, but it continues to be a major problem for patients, family caregivers, healthcare providers, and organizations. While progress has been made related to communication skills training for healthcare providers, clinical practice and research gaps persist, particularly related to how to best monitor, measure, and evaluate the implementation of communication skills in the actual clinical setting and provide timely feedback about communication effectiveness and quality.
Objective:
With this multi-phase, 1-year feasibility study, our interdisciplinary team aims to develop and pilot test a novel sensing system and associated natural language processing algorithms (CommSense) that can: 1) be deployed on mobile devices, such as smart watches; 2) reliably capture patient-provider interactions in a clinical setting; and 3) process these communications to extract key markers of communication effectiveness/quality. The long-term goal of this research is to deploy CommSense in a variety of healthcare contexts to provide real-time feedback to end-users to improve communication and patient health outcomes.
Methods:
During Phase I (Aim 1) we will identify feasible metrics of communication to extract from conversations using CommSense. To achieve this, clinical investigators will conduct a thorough review of the recent healthcare communication and palliative care literature to develop an evidence-based ‘ideal and optimal’ list of communication metrics. This list will be discussed collaboratively within the study team and consensus reached about the included items. In Phase II (Aim 2) we will develop the CommSense software by sharing the ‘ideal and optimal’ list of communication metrics with engineering investigators to gauge technical feasibility. CommSense will build upon prior work using an existing Android smartwatch platform (SWear) to collect multi-modal, sensor signals on smartwatches and will include sensing modules that can collect: (1) physiological metrics via embedded sensors to measure markers of stress (e.g., heart rate variability); (2) gesture data via embedded accelerometer and gyroscope sensors; and (3) voice and ultimately textual features via the embedded microphone. In Phase III (Aim 3), we will pilot test the ability of CommSense to accurately extract identified communication metrics using simulated clinical scenarios with nurse and physician participants.
Results:
Development of the CommSense platform began in November 2021, with participant recruitment expected to begin Summer 2022. We anticipate preliminary results will be available in Fall 2022.
Conclusions:
CommSense is poised to make a valuable contribution to communication science, ubiquitous computing technologies, and natural language processing. We are particularly eager to explore the ability of CommSense to support effective virtual/remote healthcare interactions, and to reduce disparities related to patient-clinician communication in the context of serious illness. Clinical Trial: n/a
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Copyright
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