Gustafson David H, Mares Marie-Louise, Johnston Darcie C, Mahoney Jane E, Brown Randall T, Landucci Gina, Pe-Romashko Klaren, Cody Olivia J, Gustafson David H, Shah Dhavan V
Center for Health Enhancement Systems Studies, University of Wisconsin-Madison, Madison, WI, United States.
Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, United States.
JMIR Res Protoc. 2021 Feb 19;10(2):e25175. doi: 10.2196/25175.
Multiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also 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 laboratory 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 these patients' lives.
This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures.
In this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET 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.
Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021.
With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET 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.
ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/25175.
多种慢性病(MCCs)在老年人中很常见,且管理成本高昂。三分之二的医疗保险受益人患有多种疾病(如糖尿病和骨关节炎),占医疗保险支出的90%以上。与没有多种慢性病的患者相比,患有多种慢性病的患者生活质量更低,医疗和精神状况更差。在通常治疗多种慢性病的初级保健机构中,由于时间限制,护理往往侧重于实验室检查结果和药物管理,而非生活质量。电子健康系统已被证明能改善多种结果,或许能够填补这一空白,补充初级保健并改善这些患者的生活。
本研究旨在评估针对患有多种慢性病的老年人的电子健康干预措施ElderTree(ET)对生活质量及相关指标的影响。
在这项非盲研究中,从初级保健诊所招募了346名65岁及以上、患有5种目标高危慢性病(高血压、高脂血症、糖尿病、骨关节炎和体重指数≥30kg/m²)中至少3种疾病的成年人,并按1:1的比例随机分为2组:常规护理(UC)加笔记本电脑、互联网服务和ET,或由UC加笔记本电脑和互联网但无ET组成的对照组。使用ET的患者可使用12个月,并将再随访6个月,共计18个月。本研究的主要结局是两组在生活质量、心理健康和孤独感测量方面的差异。次要结局是两组在实验室检查得分、跌倒、症状困扰、药物依从性以及危机和长期医疗保健使用方面的差异。我们还将研究ET效果的中介因素和调节因素。在基线以及第6、12和18个月,患者完成书面调查问卷,其中包括为具有相似人群的良好心理测量特性而选择的经过验证的量表;从电子健康记录中收集实验室数据;从健康记录和患者调查中收集医疗保健使用情况和慢性病信息;并在系统日志中持续收集ET使用数据。我们将使用一般线性模型和线性混合模型来评估随时间变化的主要和次要结局,将治疗条件作为组间因素。对于非连续或与其他结局不相关的结局,将进行单独分析。
招募工作于2018年1月至2019年12月进行,共招募了346名参与者。干预期将于2021年6月结束。
通过自我管理和激励策略、健康跟踪、教育工具以及同伴社区和支持,ET可能有助于改善应对持续、复杂的多种慢性病患者的结局。此外,它可能减轻初级保健系统的一些压力,具有潜在的成本影响。
ClinicalTrials.gov NCT03387735;https://www.clinicaltrials.gov/ct2/show/NCT03387735。
国际注册报告识别码(IRRID):DERR1-10.2196/25175。