January 1, 2018
Wang, V., Wang, B. (2018). Culturally Adaptive Digital Avatars for Psychosocial and Self-Management Support of High Risk Elders. Poster presented at Aging in America 2018.
Victor Wang, MS (Robotics)
Brittany Wang, MA (Gerontology)
care.coach has developed a technology-enabled care platform that con-nects a diverse, global team of health advocates with older adults in Ameri-ca via a continuously present, digital avatar. The health advocates provide real-time conversational responses in a social, compassionate way, helping to build rapport and relationships, while software algorithms programmed with clinical and care-related best practices guide the avatar to coach and support the older adults in their multiple chronic condition self-management and other risk-mitigating, wellness-promoting protocols. This system has been shown to work well with diverse patient populations, and has been clinically validated to reduce falls among hospitalized elders by up to 85%, mitigate delirium, and reduce loneliness and depression.
EXAMPLE: RESULTS WITH CULTURALLY DIVERSE HOSPITALIZED ELDERS
Methods: A pilot clinical study (Wexler, Drury, Pollak, 2017) was conducted by Pace University at Jamaica Hospital Medical Center with 95 elderly, eth-nically diverse inpatients. Research assistants (nursing students) coordinat-ed with hospital nursing staff to identify older patients who they felt would be suitable due to high subjective falls/delirium risk. Patients were assigned to intervention/control based on the unit they were on. Interven-tion patients received a care.coach avatar for their entire length of stay, on average checking in (starting an audio/video stream, visually waking up the avatar) 71.3 times per day per patient, engaging each patient for 61 minutes per day (including the use of 11.5 images or audio files), and com-pleting 6.5 protocol-driven tasks per patient per day (designed to mitigate falls and delirium). Control patients received daily nursing student visits.
Patient Characteristics: Across all study patients, mean age was 76.9 years, with 68.3% female, 24.4% white (53.7% African American, 12.2% Asian or Pacific Islander, 7.3% Hispanic), and 39% spoke English as a second language. Typical length of stay was 3-6 days.
Results: The intervention unit which deployed care.coach avatars at the bedside of high-risk patients for 3 months showed a fall rate of only 0.9 falls per 1000-patient days, representing an 85% reduction in rate of falls compared to the control unit with a similar patient population during the same time period. Fall rate reduction was 70% compared to historical, pre-intervention data from the intervention unit. Intervention patients also showed a significant reduction in delirium (CAM) and loneliness (UCLA-LS).
Conclusions: Through psychosocial support and engagement, eliciting care needs, and behavioral coaching, the care.coach avatar can improve care outcomes in culturally diverse, high-risk older adult populations.
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