Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology

The social distancing requirements for COVID-19 coupled with the adverse health impacts of social isolation and decreased access to healthcare in rural areas places older adults with disabilities in a dire situation. The smart sensor system to be deployed and studied in this project aims to reduce disability for rural community-dwelling older adults and improve health-related quality of life, including depression and anxiety. An implementation guide will be developed to increase success of future scale-up evaluations.

Over 85% of Missouri is rural and individuals in these rural areas are older and have reduced access to regular healthcare as compared to individuals living in urban areas of Missouri. Those with disabilities, particularly older adults, are at higher risk for contracting COVID-19. There is a critical need to reduce disability and improve quality of life for community-dwelling older adults with disabilities for successful aging-in-place during the COVID-19 pandemic. We have developed, with our partner company Foresite Healthcare, a proven sensor-based technology solution for monitoring health-related behaviors in the home. In a multi-site randomized controlled trial, we demonstrated that the sensor system with nursing care coordination prevents declines in function for older adults living in assisted living facilities. The long-term goal of this research is to support independent living for older adults with disabilities for as long as possible. The purpose of this project is to deploy the sensor system in the homes of rural community-dwelling older adults with disabilities and evaluate the effect of the sensor system on reducing disability and improving health-related quality of life. Using a two-arm randomized controlled trial, the sensor system will be installed in the homes of 64 older adults. Participants randomized to Study Arm 1 will receive a multidisciplinary (nursing, occupational therapy, and social work) self-management intervention paired with the sensor system. This intervention is based on the 5As self-management approach and is a direct translation of the nursing care coordination in our prior research. Participants randomized to Study Arm 2 will have standard health education paired with the sensor system. An implementation guide for future use with different partner agencies will be developed using individual and setting level data collected from Aims 1, 2 and 3 using the RE-AIM framework. The project will be accomplished in three aims. In Aim 1, we evaluate the effect of a sensor system paired with a multidisciplinary self-management intervention as compared to the sensor system paired with standard health education care on disability and health-related quality of life after 1 year. In Aim 2, we will evaluate the effect of the sensor system on secondary health outcomes (depression, anxiety, occupational performance, and caregiver burden), rates of falls, and healthcare usage. In Aim 3, we will collect individual participant data for satisfaction and adoption and stakeholder data about organizational setting. Data from Aims 1, 2 and 3 will be analyzed using RE-AIM to produce implementation guidance contextualized by organizational setting. For older adults with disabilities living in rural areas, the sensor system has the potential to change the approach to healthcare and disability management.

Eligibility Criteria:
Inclusion Criteria:

* Over the age of 65, Live in a rural defined county, Have difficulty with at least 1 self-care task or 2 daily living tasks, Have internet access, Able to stand with or without assistance

Exclusion Criteria:

* Life expectancy less than one year, Severe cognitive impairment (mini mental state exam score \<17), Life in a facility that provides care services, Katz ADL Score of 6, Receiving in-home physical therapy, occupational therapy or nursing, Have been hospitalized more than three times in teh previous 12 months, Plan to change residences within the next year