The Quality Improvement Program for Missouri's Long - Term Care Facilities (QIPMO) is committed to Missouri's Elderly.
The "Aging-in-place" model allows older adults to receive health care in their preferred place of living, eliminating the need for a more restricted living space, such as a nursing home.
TigerPlace is a specially designed elder housing project initiated by the MU Sinclair School of Nursing, working to provide elders a better quality of life.
AgingMO is a centralized online home for the University of Missouri’s Aging in Place (AIP) program and its related projects. Our unique AIP model allows older adults to receive health care in their preferred place of living. As their care needs increase, residents contract for more care in the same setting, eliminating the need for a move to a more restrictive living environment such as a nursing home. This project, which began in 1996, is a multidisciplinary project including MU’s School of Nursing, College of Electrical and Computer Engineering, School of Social Work, Department of Physical Therapy, Department of Management and Informatics, Biostatistics Group, and Department of Family and Community Medicine, along with outside consultants. We have developed this website to assist you by allowing complete and easy access to the many distinctive aspects of our groundbreaking research.
America’s 75 million aging adults soon will face decisions about where and how to live as they age. Current options for long-term care, including nursing homes and assisted-living facilities, are costly and require seniors to move from place to place. University of Missouri researchers have found that a new strategy for long-term care called Aging in Place (AIP) is less expensive and provides better health outcomes. The AIP model provides services and care to meet residents’ increasing needs to avoid relocation to higher levels of care. AIP includes continuous care management, a combination of personalized health services with nursing care coordination. Click here for an AIP overview.
Consider the current reality for Mrs Florence Jones, a woman of advanced age and mild dementia in a long-term care facility, who insists everyone call her "Flossie":On May 1, Karen, the nurse aide taking care of Flossie, needs to assist Flossie to the restroom more than usual. Since her urine does not have an odor, the nurse aide attributes this increased urination to the iced tea served at lunch today. Karen remarks to Jane, the LPN (licensed practical nurse), that the iced tea at lunch sure got Flossie going today, and Jane documents normal toileting for Flossie...
Rantz, M., Alexander, G., Galambos, C., Vogelsmeier, A., Popejoy, L., Flesner, M., Lueckenotte, A., Crecelius, C., & Zwygart-Stauffacher, M. (2013). Initiative to test a multidisciplinary model with advanced practice nurses to reduce avoidable hospitalizations among nursing facility residents. Journal of Nursing Care Quality, 29(1), 1-8.
This paper describes the evolution of an early illness warning system used by an interdisciplinary team composed of clinicians and engineers in an independent living facility. The early illness warning system consists of algorithms which analyze resident activity patterns obtained from sensors embedded in residents' apartments. The engineers designed an automated reasoning system to generate clinically relevant alerts which are sent to clinicians when significant changes occur in the sensor data, for example declining activity levels. During January 2010 through July 2010, clinicians and engineers conducted weekly iterative review cycles of the early illness warning system to discuss concerns about the functionality of the warning system, to recommend solutions for the concerns, and to evaluate the implementation of the solutions. A total of 45 concerns were reviewed during this period. Iterative reviews resulted in greater efficiencies and satisfaction for clinician users who were monitoring elder activity patterns.
Alexander G.L., Rantz M.J., Skubic M., Koopman R., Phillips L., Guevara R.D., & Miller S. (2011). Evolution of an early illness warning system to monitor frail elders in independent living. Journal of Healthcare Engineering, 2(2), 259-286.
In this paper, we propose a Pulse-Doppler radar system for in-home gait assessment of older adults. A methodology has been developed to extract gait parameters including walking speed and step time using Doppler radar. The gait parameters have been validated with a Vicon motion capture system in the lab with 13 participants and 158 test runs. The study revealed that for an optimal step recognition and walking speed estimation, a dual radar set up with one radar placed at foot level and the other at torso level is necessary. An excellent absolute agreement with intra-class correlation coefficients of 0.97 was found for step time estimation with the foot level radar. For walking speed, although both radars show excellent consistency they all have a system offset compared to the ground truth due to walking direction with respect to the radar beam. The torso level radar has a better performance (9% offset on average) in the speed estimation compared to the foot level radar (13-18% offset). Quantitative analysis has been performed to compute the angles causing the systematic error. The results demonstrate the capability of the system to be used as a daily gait assessment tool in home environments, useful for fall risk assessment and other health care applications. The system is now tested in an unstructured home environment.
Wang, F., Skubic, M., Rantz, M., Yardibi, T., & Cuddihy, P.E. (2014). Quantitative gait measurement with pulse-Doppler radar for passive in-home gait assessment. IEEE Transactions on Biomedical Engineering, 61(9), 2434-2443.