A Web-Based eHealth Intervention to Improve the Quality of Life of Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial (Preprint)

Abstract

BACKGROUND Multiple chronic conditions (MCCs) are common and expensive among older adults. Of Medicare beneficiaries, two-thirds have multiple conditions (eg, diabetes, osteoarthritis) and account for more than 90% of Medicare spending. At the same time, patients with MCCs experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on lab results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving the lives of patients with MCCs. OBJECTIVE To assess effects of ElderTree, an eHealth intervention for older adults with MCCs, on quality of life and related measures. METHODS In this unblinded study, 346 adults age 65+ with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, BMI 30+) were recruited from primary care clinics and randomized 1:1 to one of two conditions: (1) usual care plus laptop computer, Internet service, and ElderTree, or (2) a control consisting of usual care plus laptop and Internet but no ElderTree. Patients with ElderTree have access for 12 months and will be followed for an additional 6 months after the intervention ends, for a total of 18 months. Primary outcomes are the differences between the two groups on measures of quality of life, psychological well-being, and loneliness. Secondary outcomes are between-groups differences on lab scores, number and severity of falls, symptom distress, medication adherence, and crisis and long-term healthcare use. We will also examine mediators and moderators of the effects of ElderTree. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; lab data are collected from electronic health records; healthcare use and chronic conditions are collected from both health records and patient surveys; and ElderTree use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. RESULTS Recruitment ran from January 2018 through December 2019; a total of 346 participants were recruited. The intervention period will end June 2021. CONCLUSIONS With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ElderTree may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. CLINICALTRIAL ClinicalTrials.gov NCT03387735