The Impact of an Ehealth System in Older Adults

Rachel Kornfield1, Roberta Johnson2, Fiona McTavish2, Marie-Louise Mares2, Dhavan Shah2, David Gustafson1, Jane Mahoney2, John Lee, Rajan Veerimani2

  • 1University of Wisconsin, Madison
  • 2University of Wisconsin-Madison
Also at:
11:45 - 12:15 | Thursday 27 October 2016 | Main Auditorium

Details

Category

Research Abstracts (Poster)

Sessions

08:30 - 19:30 | Wed 26 Oct | Auditorium Foyer | WePOS

Poster Session

11:45 - 12:15 | Thu 27 Oct | Main Auditorium | IS-2

Ignite Session 2

Abstract

Background: By 2030, the number of Americans over age 65 will be 71 million, and half will have metabolic syndrome; 44% of those (15 million) will be depressed. Annual medical costs of those with metabolic syndrome will exceed $200 billion; metabolic syndrome has also been shown to increase readmission rates by 30-45%. Avoidable readmissions "are a strong indicator of a fragmented health care system that often leaves discharged patients confused . . . and unable to follow instructions and get the necessary follow-up care." Those with depression tend to have reduced self-care and greater adverse health behaviors (e.g., smoking; sedentary lifestyle), as well as more somatic symptoms. The negative impact of depression on health service use exceeds 40%. Finding effective methods of treating these older adults has urgency for patients and the healthcare system. Purpose is to determine whether older adults improve their long-term quality of life by having access to an electronic information and support system. Methods: In an Agency for Healthcare Policy and Research grant, 396 older adults (age 65+) from urban, suburban and rural counties in Wisconsin were randomly assigned to either treatment as usual or to a home based computer system designed to reduce loneliness and improve quality of life. In designing the intervention, over 300 older adults were interviewed to identify their challenges and assets using Community Based Participatory Research. Developers interacted frequently with over 80 elders to obtain guidance on and reaction to tailored interface design, content, and operation. The resulting system (called Elder Tree) contains the following features: long duration, assertive outreach, monitoring, prompts, action planning, reinterpretation of symptoms, and access to peer and family support. These services are designed to improve relatedness, competence and intrinsic motivation. The randomized trial selected subjects who, in the previous 6 months, had an event placing them at risk of admission to long-term care. Approximately 900 older adults (65+) were approached; 396 (67% female) volunteered to join study (17 have since died); 192 had 3 or more chronic conditions and 109 had a combination of metabolic syndrome and depression (the focus of this presentation). The analysis employs surveys submitted at pretest and 12 months. Patients were evaluated on changes in quality of life, mood, support, symptom distress, primary care visits and other health service use (e.g. hospital admissions). Hypotheses were generated prior to data collection beginning. Results: Significant effects were found in four of 6 outcomes examined. Quality of life improved with Elder Tree [1.94 (SD=5.5); p

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