ElderTree Via a Voice Activated Device for Managing Chronic Health Conditions (NHLBI)

University of Wisconsin (UW)

Status: Active, not recruiting

Conditions: Chronic Conditions, Multiple

Treatments: Behavioral: ET-Voice (Smart System); Behavioral: ET-Text (Laptop)

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT05240534

2020-0984

5R33HL151870 (U.S. NIH Grant/Contract)

A195000 (Other Identifier)

Protocol Version 3/2/2023 (Other Identifier)

1R61HL151870-01A1 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

Multiple chronic conditions (MCCs) are costly and pervasive among older adults. MCCs account for 90% of Medicare spending, and 65% of Medicare beneficiaries have 3 or more chronic conditions; 23% have 5 or more. MCCs are often addressed in primary care, where time pressures force a focus on medication and lab results rather than self-management skills. Patients often struggle with treatment adherence and the emotional and physical burdens of self-management and health tracking. Chronic conditions reduce quality of life (QOL) and increase loneliness, which exacerbate those conditions.

The primary purpose of this study is to investigate whether a voice-based platform is better for delivering an electronic health intervention to older adults than a text/typing-based platform. We have an evidence-based electronic health intervention (Elder Tree, ET) that has been shown to improve quality of life, physical and socio-emotional health outcomes for older adults with multiple chronic conditions when delivered via a text/typing-based system. The current project would test whether such patients would benefit even more if ET were delivered via a voice-based system (vs. the text-based system) because they would use it more consistently. ET is an existing intervention providing tools, motivation, and support on a computer platform to help older adults manage their health.

Enrollment: 502 patients

Sex: All

Ages: 60+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Be ≥60 years old;
• Have medical record diagnoses of at least 5 chronic conditions of which at least 3 must come from the following: hypertension, hyperlipidemia, obesity, prediabetes or diabetes, or depression;
• Be willing to share medical record data about healthcare use (30-day hospital readmissions and ER, urgent care, primary care, and specialty care visits);
• Allow researchers to share information with the patient's primary care provider

Exclusion criteria

• Require an interpreter
• Report no current psychotic disorder that would prevent participation
• Have no acute medical problem requiring immediate hospitalization
• Not report impairments preventing use of a computer or tablet (e.g. blind, deaf)

Trial design

Primary purpose: Supportive Care

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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502 participants in 2 patient groups, including a placebo group

Control group (ET-Text)

Placebo Comparator group

Description:

Participants will receive ElderTree on a laptop.

Treatment:

Behavioral: ET-Text (Laptop)

Experimental group (ET-Voice)

Experimental group

Description:

Participants will receive ElderTree on a smart system.

Treatment:

Behavioral: ET-Voice (Smart System)