Recent advances in technology allow for the possibility of more dynamic assessment and monitoring of older individuals across a variety of key environments: rehabilitation, long term care, home, and assisted living. Within the past year, intelligent easy-to-use electronic devices have been brought to market that are able to collect and transmit various types of biodata-patient position, time in motion, and even responses to questionnaires delivered remotely. These devices can also be paired with in-facility and in-home ambient activity and location sensors to monitor patient movement and activity continuously over time and provide real-time feedback about changes in patient status over time. This technology comes at a very critical time when our aging population will result in large numbers of geriatric patients placing increasing demand on our healthcare system (in both acute care and post-acute care settings). Projections indicate that in the near future our supply of trained medical personnel will not be sufficient to meet the patient demand of our growing population. In preparation for this project, our group has already designed and validated platform that includes: a SmartWatch, ambient location and activity sensors, a smarthphone, and an specialized application and analytic engine for functional and performance measurement designed for pre-frail and frail individuals.. This platform allows for the detection and classification of patient motion and position with an accuracy of over 85%.This project proposal seeks to expands and clinical validate our current technology to establish a more comprehensive remote sensing system called the Safety and Independence Tracking System. Participating subjects will be monitored in several post-acute care settings of interest: acute rehabilitation, long-term care or nursing facility, and at home. Participation will commence at time of hospital discharge and will last 21 days in rehabilitation and 3 months in long-term care or at home. Our current validated and tested tools allow for continuous, passive collection of important information characterizing patient position, physical function, indoor location, and specific activities of interest (includin validated measures like ADLs, IADLs and Get up and Go) without requiring time in today's busy clinical settings. This project will apply our novel healthcare monitoring system in a large population of elderly patients through various phases of post-acute care: rehabilitation, long-term care, assisted living and the home. The data collected by our intelligent system can in turn be used to generate novel, personalized predictive models and algorithms. We can apply these models to encourage safety by detecting evolving fall risk, track independence by monitoring validated activities over time, and decrease healthcare utilization by predicting risk for hospitalization and allowing for early intervention by providers and caregivers.

Public Health Relevance

As our population ages, the number of elderly patients will likely exceed the providers and resources available. To deal with this problem, physicians will need novel and efficient ways to monitor and manage patients without using the limited supply of clinic time or emergency department space. This project will follow patients through many post-acute settings, collecting continuous activity and position data with analytics that can detec change within each patient over time-allowing for early detection of decline and intervention to prevent harm and promote safety and independence.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Research Project (R01)
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Special Emphasis Panel (ZHS1-HSR-X (01))
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Bartman, Barbara
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University of California Los Angeles
Internal Medicine/Medicine
Schools of Medicine
Los Angeles
United States
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