- Journal of Gerontological Nursing
- April 2012 - Volume 38 · Issue 4: 18-23
Our team has developed a technological innovation that detects changes in health status that indicate impending acute illness or exacerbation of chronic illness before usual assessment methods or self-reports of illness. We successfully used this information in a 1-year prospective study to alert health care providers so they could readily assess the situation and initiate early treatment to improve functional independence. Intervention participants showed significant improvements (as compared with the control group) for the Short Physical Performance Battery gait speed score at Quarter 3 (p = 0.03), hand grip-left at Quarter 2 (p = 0.02), hand grip-right at Quarter 4 (p = 0.05), and the GAITRite functional ambulation profile score at Quarter 2 (p = 0.05). Technological methods such as these could be widely adopted in older adult housing, long-term care settings, and in private homes where older adults wish to remain independent for as long as possible.
Dr. Rantz is Curator’s Professor, Sinclair School of Nursing and Curtis W. and Ann H. Long Department of Family and Community Medicine, and Helen E. Nahm Chair and University Hospital Professor of Nursing, Dr. Skubic is Professor, and Mr. Guevara is a master’s student, Electrical and Computer Engineering, Dr. Koopman is Associate Professor, Curtis W. and Ann H. Long Department of Family and Community Medicine, Dr. Alexander and Dr. Aud are Associate Professors, and Dr. Phillips is Assistant Professor, Sinclair School of Nursing, Ms. Musterman is Care Coordinator and Nursing Manager, and Ms. Back is Social Worker, Tiger-Place, Sinclair School of Nursing, Dr. Galambos is Professor, School of Social Work, and Mr. Miller is Research Associate, University of Missouri, Columbia, Missouri.
The authors have disclosed no potential conflicts of interest, financial or otherwise. This article is based on results of research funded by the National Institute of Nursing Research (NINR) grant 1R21NR011197-02 (PI: Rantz, 2009–2012), Technology to Automatically Detect Early Signs of Illness in Senior Housing. The results and conclusions are the responsibility of the researchers and not the opinion of the NINR. The authors gratefully acknowledge the residents and staff of TigerPlace who graciously participate in their technology development research and the students and faculty of the Eldertech Research Team at the University of Missouri.
Address correspondence to Marilyn J. Rantz, PhD, RN, FAAN, Curator’s Professor, S406 Sinclair School of Nursing, University of Missouri, Columbia, MO 65211; e-mail: email@example.com.
Posted: March 14, 2012