Older Adults' Perceptions of and Preferences for a Fall Risk Assessment System: Exploring Stages of Acceptance Model.

Aging in place is a preferred and cost-effective living option for older adults. Research indicates that technology can assist with this goal. Information on consumer preferences will help in technology development to assist older adults to age in place. The study aim was to explore the perceptions and preferences of older adults and their family members about a fall risk assessment system. Using a qualitative approach, this study examined the perceptions, attitudes, and preferences of 13 older adults and five family members about their experience living with the fall risk assessment system during five points in time. Themes emerged in relation to preferences and expectations about the technology and how it fits into daily routines. We were able to capture changes that occurred over time for older adult participants. Results indicated that there was acceptance of the technology as participants adapted to it. Two themes were present across the five points in time-safety and usefulness. Five stages of acceptance emerged from the data from preinstallation to 2 years postinstallation. Identified themes, stages of acceptance, and design and development considerations are discussed.

Enhanced registered nurse care coordination with sensor technology: Impact on length of stay and cost in aging in place housing.

BACKGROUND: When planning the Aging in Place Initiative at TigerPlace, it was envisioned that advances in technology research had the potential to enable early intervention in health changes that could assist in proactive management of health for older adults and potentially reduce costs. PURPOSE: The purpose of this study was to compare length of stay (LOS) of residents living with environmentally embedded sensor systems since the development and implementation of automated health alerts at TigerPlace to LOS of those who are not living with sensor systems. Estimate potential savings of living with sensor systems. METHODS: LOS for residents living with and without sensors was measured over a span of 4.8 years since the implementation of sensor-generated health alerts. The group living with sensors (n = 52) had an average LOS of 1,557 days (4.3 years); the comparison group without sensors (n = 81) was 936 days (2.6 years); p = .0006. Groups were comparable based on admission age, gender, number of chronic illnesses, SF12 physical health, SF12 mental health, Geriatric Depression Scale (GDS), activities of daily living, independent activities of daily living, and mini-mental status examination scores. Both groups, all residents living at TigerPlace since the implementation of health alerts, receive registered nurse (RN) care coordination as the standard of care. DISCUSSION: Results indicate that residents living with sensors were able to reside at TigerPlace 1.7 years longer than residents living without sensors, suggesting that proactive use of health alerts facilitates successful aging in place. Health alerts, generated by automated algorithms interpreting environmentally embedded sensor data, may enable care coordinators to assess and intervene on health status changes earlier than is possible in the absence of sensor-generated alerts. Comparison of LOS without sensors TigerPlace (2.6 years) with the national median in residential senior housing (1.8 years) may be attributable to the RN care coordination model at TigerPlace. Cost estimates comparing cost of living at TigerPlace with the sensor technology vs. nursing home reveal potential saving of about $30,000 per person. Potential cost savings to Medicaid funded nursing home (assuming the technology and care coordination were reimbursed) are estimated to be about $87,000 per person. CONCLUSIONS: Early alerts for potential health problems appear to enhance the current RN care coordination care delivery model at TigerPlace, increasing LOS for those living with sensors to nearly twice that of those who did not. Sensor technology with care coordination has cost saving potential for consumers and Medicaid.

Automated In-Home Fall Risk Assessment and Detection Sensor System for Elders.

PURPOSE OF THE STUDY: Falls are a major problem for the elderly people leading to injury, disability, and even death. An unobtrusive, in-home sensor system that continuously monitors older adults for fall risk and detects falls could revolutionize fall prevention and care. DESIGN AND METHODS: A fall risk and detection system was developed and installed in the apartments of 19 older adults at a senior living facility. The system includes pulse-Doppler radar, a Microsoft Kinect, and 2 web cameras. To collect data for comparison with sensor data and for algorithm development, stunt actors performed falls in participants' apartments each month for 2 years and participants completed fall risk assessments (FRAs) using clinically valid, standardized instruments. The FRAs were scored by clinicians and recorded by the sensing modalities. Participants' gait parameters were measured as they walked on a GAITRite mat. These data were used as ground truth, objective data to use in algorithm development and to compare with radar and Kinect generated variables. RESULTS: All FRAs are highly correlated (p < .01) with the Kinect gait velocity and Kinect stride length. Radar velocity is correlated (p < .05) to all the FRAs and highly correlated (p < .01) to most. Real-time alerts of actual falls are being sent to clinicians providing faster responses to urgent situations. IMPLICATIONS: The in-home FRA and detection system has the potential to help older adults remain independent, maintain functional ability, and live at home longer.

In-home fall risk assessment and detection sensor system.

Falls are a major problem in older adults. A continuous, unobtrusive, environmentally mounted (i.e., embedded into the environment and not worn by the individual), in-home monitoring system that automatically detects when falls have occurred or when the risk of falling is increasing could alert health care providers and family members to intervene to improve physical function or manage illnesses that may precipitate falls. Researchers at the University of Missouri Center for Eldercare and Rehabilitation Technology are testing such sensor systems for fall risk assessment (FRA) and detection in older adults' apartments in a senior living community. Initial results comparing ground truth (validated measures) of FRA data and GAITRite System parameters with data captured from Microsoft(®) Kinect and pulse-Doppler radar are reported.

Evaluation of aging in place model with home care services and registered nurse care coordination in senior housing.

A state-sponsored evaluation of aging in place (AIP) as an alternative to assisted living and nursing home has been underway in Missouri. Cost, physical, and mental health assessment data reveal the cost-effectiveness and positive health measures of AIP. Findings of the first four years of the AIP evaluation of two long-term care settings in Missouri with registered nurse care coordination are compared with national data for traditional long-term care. The combined care and housing cost for any resident who received care services beyond base services of AIP and who qualified for nursing home care has never approached or exceeded the cost of nursing home care at either location. Both mental health and physical health measures indicate the health restoration and independence effectiveness of the AIP model for long-term care.

Improving nurse care coordination with technology.

Technology offers potential solutions to the pending crisis of healthcare for older adults, while healthcare workers are in short supply. Technology can enable remote monitoring of individuals and early detection of potential problems, so that early interventions can help older adults remain as healthy and independent as possible. Research is under way with passive monitoring technology in senior housing that is finding patterns in the data that can enhance nurse care coordination through early illness detection. With early detection, interventions can be more effective and reduce hospitalization and other healthcare expenses. Case studies are presented, and implications are discussed.

Developing a comprehensive electronic health record to enhance nursing care coordination, use of technology, and research.

As in acute care, use of health information technology in long-term care holds promise for increased efficiency, better accuracy, reduced costs, and improved outcomes. A comprehensive electronic health record (EHR), which encompasses all health care measures that clinicians want to use-both standard health care assessments and those acquired through emerging technology-is the key to improved, efficient clinical decision making. New technologies using sensors to passively monitor older adults at home are being developed and are commercially available. However, integrating the clinical information systems with passive monitoring data so that clinical decision making is enhanced and patient records are complete is challenging. Researchers at the University of Missouri (MU) are developing a comprehensive EHR to: (a) enhance nursing care coordination at TigerPlace, independent senior housing that helps residents age in place; (b) integrate clinical data and data from new technology; and (c) advance technology and clinical research.