| Overall Rating | Gold - expired |
|---|---|
| Overall Score | 69.30 |
| Liaison | Srinivasan Raghavan |
| Submission Date | Feb. 16, 2018 |
| Executive Letter | Download |
University of Missouri
IN-26: Innovation C
| Status | Score | Responsible Party |
|---|---|---|
|
1.00 / 1.00 |
Srinivasan
Raghavan Sustainability Manager Sustainability Office |
Name or title of the innovative policy, practice, program, or outcome:
A brief description of the innovative policy, practice, program, or outcome that outlines how credit criteria are met and any positive measurable outcomes associated with the innovation:
For more than 10 years, two University of Missouri researchers have researched and developed technology to help people age in place safely and independently. The research started at TigerPlace, an independent housing facility in Columbia, which was developed by the University of Missouri in collaboration with Americare Systems Inc. Now, the researchers are taking their technology into aging adults’ own homes through Sinclair@Home, a service through Sinclair Home Care of the MU Sinclair School of Nursing.
Which of the following impact areas does the innovation most closely relate to? (select up to three):
Public Engagement
Wellbeing & Work
A letter of affirmation from an individual with relevant expertise or a press release or publication featuring the innovation :
The website URL where information about the programs or initiatives is available:
Additional documentation to support the submission:
Data source(s) and notes about the submission:
This study investigated and refined health alerts produced by environmentally-embedded in-home sensor networks designed to detect early signs of health change and functional decline in older adults, the keys to successful intervention. When the sensor network detects these changes the system automatically sends appropriate alerts to the caregivers to allow early intervention. By helping older adults remain healthier, active, and in control of their chronic illnesses with early detection of changes in health status and early intervention by health care providers, millions can remain independent as they age, avoiding or reducing debilitating and costly hospital stays and, for many, avoiding or delaying the move to a nursing home. This is a great contribution to the health and quality of life, both of which are sustainability essentials, of an increasing aging population.
During the data collection phase of this project there were 241 older adult participants (128 with sensors and health alerts as the intervention, 113 controls receiving normal care only) living in 14 assisted living and senior housing communities throughout mid-Missouri, collecting many terabytes of data describing resting pulse and breathing rates, bed restlessness, in-home gait speed, fall risk, actual falls, and typical daily activity patterns. The system analyzes the collected data using advanced algorithms to detect signs of health change and functional decline and automatically sends alerts to the facility care staff when appropriate to enhance their ability to provide proactive care.
https://www.eldertech.missouri.edu/projects/intelligent-sensor-system-for-early-illness-alerts-in-senior-housing/
This study investigated and refined health alerts produced by environmentally-embedded in-home sensor networks designed to detect early signs of health change and functional decline in older adults, the keys to successful intervention. When the sensor network detects these changes the system automatically sends appropriate alerts to the caregivers to allow early intervention. By helping older adults remain healthier, active, and in control of their chronic illnesses with early detection of changes in health status and early intervention by health care providers, millions can remain independent as they age, avoiding or reducing debilitating and costly hospital stays and, for many, avoiding or delaying the move to a nursing home. This is a great contribution to the health and quality of life, both of which are sustainability essentials, of an increasing aging population.
During the data collection phase of this project there were 241 older adult participants (128 with sensors and health alerts as the intervention, 113 controls receiving normal care only) living in 14 assisted living and senior housing communities throughout mid-Missouri, collecting many terabytes of data describing resting pulse and breathing rates, bed restlessness, in-home gait speed, fall risk, actual falls, and typical daily activity patterns. The system analyzes the collected data using advanced algorithms to detect signs of health change and functional decline and automatically sends alerts to the facility care staff when appropriate to enhance their ability to provide proactive care.
https://www.eldertech.missouri.edu/projects/intelligent-sensor-system-for-early-illness-alerts-in-senior-housing/
The information presented here is self-reported. While AASHE staff review portions of all STARS reports and institutions are welcome to seek additional forms of review, the data in STARS reports are not verified by AASHE. If you believe any of this information is erroneous or inconsistent with credit criteria, please review the process for inquiring about the information reported by an institution or simply email your inquiry to stars@aashe.org.