Voice-Based Platform for Chronic Health Management

Overseen By Klaren Pe-Romashko, MS

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of Wisconsin, Madison

Disqualifiers: Psychotic disorder, Acute medical problem, Impairments, others

Compensation: Varies

Number of Visits: 6

Duration: 12 months

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine whether a voice-based platform can help older adults manage multiple chronic conditions more effectively than a text-based system. The electronic health tool, called Elder Tree, supports health management by providing tools, motivation, and support. Participants will use this tool on either a laptop (text-based) or a smart system (voice-based) to assess which method more effectively improves their quality of life. The trial is ideal for individuals aged 60 and over with at least five chronic conditions, such as high blood pressure, high cholesterol, diabetes, or depression. As an unphased trial, this study offers a unique opportunity to contribute to innovative research that could enhance health management for older adults.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It seems focused on testing a voice-based health management platform, so it's likely you can continue your usual medications.

What prior data suggests that this voice-based platform is safe for older adults?

Research has shown that the Elder Tree platform, used in this trial, helps older adults manage their health more effectively. It enhances quality of life and improves both physical and emotional health for those with multiple chronic conditions when used on a computer.

Although specific safety data for the new voice-based version of Elder Tree is not yet available, the text-based version has been used safely and effectively. Therefore, similar results are expected with the voice-based version. Importantly, this trial does not test a new drug or medical device, which often carry more safety concerns. Instead, it explores whether a voice-based system can make it easier for older adults to use the platform regularly, suggesting a lower risk of negative effects. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores how a voice-based platform, ElderTree, can help manage chronic health conditions. Unlike traditional methods that often require in-person visits or text-based apps, this approach uses a smart system to deliver care through voice interaction. This means it could offer a more accessible and user-friendly way for patients to manage their health, especially for those who may find technology challenging. By comparing this to a text-based system, researchers hope to find out if voice interaction can improve engagement and outcomes for people with chronic conditions.

What evidence suggests that this voice-based platform is effective for managing multiple chronic conditions?

Research has shown that the Elder Tree (ET) program can improve the quality of life and health for older adults with multiple long-term health issues. Studies have found that ET provides tools, motivation, and social support, aiding individuals in adhering to treatment plans and managing their health more effectively. In this trial, participants in the experimental group will receive ET on a smart system using voice-activated platforms. Early results suggest this approach might enhance its usefulness by making it easier and more engaging to use. Overall, evidence supports ET as a promising method to enhance the well-being of older adults with multiple health conditions. ^{1 2 3 6 7}

Who Is on the Research Team?

David H Gustafson, PhD

Principal Investigator

University of Wisconsin, Madison

Are You a Good Fit for This Trial?

This trial is for people aged 60 or older who have at least five chronic health conditions, with hypertension, high cholesterol, obesity, prediabetes/diabetes, or depression being among them. Participants must be willing to share their medical records and allow communication with their primary care provider.

Inclusion Criteria

I am 60 years old or older.

Allow researchers to share information with the patient's primary care provider

Be willing to share medical record data about healthcare use (30-day hospital readmissions and ER, urgent care, primary care, and specialty care visits)

Exclusion Criteria

Report no current psychotic disorder that would prevent participation

Not report impairments preventing use of a computer or tablet (e.g. blind, deaf)

I do not need to be in the hospital right now for a sudden illness.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive the ElderTree intervention via either a voice-based or text-based platform to manage chronic health conditions

12 months

Regular use of the platform is encouraged

Follow-up

Participants are monitored for changes in function, disability, and other health outcomes

6 months

Assessments at 6, 12, and 18 months

What Are the Treatments Tested in This Trial?

Interventions

• Elder Tree

Trial Overview The study compares two ways of delivering a health management program called Elder Tree (ET) to seniors with multiple chronic illnesses: one using voice commands through a smart system (ET-Voice), and the other via text on a laptop (ET-Text).

How Is the Trial Designed?

Group I: Experimental group (ET-Voice) Experimental Treatment 1 Intervention

Participants will receive ElderTree on a smart system.

Group II: Control group (ET-Text) Placebo Group 1 Intervention

Participants will receive ElderTree on a laptop.

Who Is Running the Clinical Trial?

University of Wisconsin, Madison

Lead Sponsor

Trials

1,249

Recruited

3,255,000+

National Heart, Lung, and Blood Institute (NHLBI)

Collaborator

Trials

3,987

Recruited

47,860,000+

Published Research Related to This Trial

In a study reviewing 1289 charts of older adults with cardiovascular diagnoses, 50% had triggers indicating potential adverse drug events (ADEs), with 232 of these triggers confirmed as ADEs, highlighting the prevalence of medication-related issues in this population.

Only nine out of 39 triggers were highly predictive of ADEs, accounting for 94.4% of the detected events, suggesting that a more streamlined trigger tool could be developed to improve the identification of ADEs in primary care settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Experience with a trigger tool for identifying adverse drug events among older adults in ambulatory primary care. Singh, R., McLean-Plunckett, EA., Kee, R., et al.[2022]

The FDA's ASTER pilot study demonstrated that electronic health record (EHR)-triggered adverse event reports can provide valuable postmarketing safety information, particularly for known adverse drug events (ADEs).

However, the quality of the reports varied, with many lacking critical details such as informative descriptions and relevant laboratory data, highlighting the need for improved data quality to enhance the utility of EHR-triggered ADE reporting.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Quality assessment of spontaneous triggered adverse event reports received by the Food and Drug Administration. Brajovic, S., Piazza-Hepp, T., Swartz, L., et al.[2012]

A significant 86% of the 111 diabetes patients experienced at least one adverse event (AE) or potential adverse event (PotAE) over a 9-month period, highlighting the prevalence of safety issues in chronic disease management.

The majority of AEs (63%) were related to medication management, and 77% of events involved patient actions, indicating that enhancing patient self-management and communication with healthcare providers is crucial for preventing these events.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

What happens between visits? Adverse and potential adverse events among a low-income, urban, ambulatory population with diabetes. Sarkar, U., Handley, MA., Gupta, R., et al.[2021]

A review of 26 studies on conversational agents (CAs) in healthcare for chronic conditions shows that users generally find these tools helpful, satisfying, and easy to use, indicating promising acceptance for self-management.

Despite positive user feedback, there is a significant gap in reliable evidence regarding the efficacy of AI-enabled CAs due to insufficient reporting on their technical implementation, which limits the ability to compare their effectiveness.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions. Bin Sawad, A., Narayan, B., Alnefaie, A., et al.[2022]

The study analyzed 16,453 lines of dialog from 424 patients with inflammatory bowel diseases (IBD) to explore the feasibility of using natural language processing (NLP) for categorizing patient communications, demonstrating that NLP can effectively categorize patient data into relevant categories such as symptoms, medications, and appointments.

The categorization algorithm showed a high agreement with independent physician evaluations, with 95% of cases having minor or no differences, indicating that NLP can reliably assist in developing chatbots for chronic disease management, potentially improving patient monitoring and education.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study. Zand, A., Sharma, A., Stokes, Z., et al.[2020]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC7935655/

A Web-Based eHealth Intervention to Improve the Quality ... 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.

2. digital.ahrq.gov digital.ahrq.gov/ahrq-funded-projects/using-smart-devices-implement-evidence-based-ehealth-system-older-adults

Using Smart Devices to Implement an Evidence-based ... The evidence-based electronic health intervention Elder Tree (ET) is a laptop application that provides coping tools, motivation, and social support to help ...

3. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC9121223/

Using Smart Displays to Implement an eHealth System for ... The aim of this study is to assess whether participants using an evidence-based intervention (ElderTree) on a smart display will experience decreased pain ...

4. withpower.com withpower.com/trial/phase-disease-3-2022-610df

Voice-Based Platform for Chronic Health Management 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 ...

5. withpower.com withpower.com/trial/phase-chronic-pain-6-2021-82b3b

ElderTree Smart System for Older Adults · Info for Participants This trial is testing if voice-activated smart devices can help older adults with multiple chronic conditions use a health management app more often.

6. mdpi.com mdpi.com/2227-7080/13/2/48

Challenges and Ethical Considerations in Implementing ... The “ElderTree” interactive eHealth platform aims to enhance the quality of life, social connections and independence of the elderly. ElderTree was developed ...

7. dl.acm.org dl.acm.org/doi/10.1145/3706598.3713839

Voice Assistants for Health Self-Management: Designing ... We co-designed an LLM-powered voice assistant with older adults that uses doctors' after-visit summary (AVS) to provide debriefs and facilitates ...