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New research · Home health

Will patients actuallyengage with AI voice agents?

Real-world research reveals what happens when AI voice agents reach patients, listen to their concerns, and surface information care teams can act on.

20,000+

AI-supported calls

5 agencies

Across 5 US states

Mar–Oct 2026

Study period

Industry research · Authored by Lindsay Doak · Supported by CareBestie

The report will be delivered to your email.

Industry research / 2026

How Agentic AI Voice Agents Are Transforming Home Health Patient Engagement and Outcomes

Patient acceptance, operational implementation, and outcome improvement

Evidence at a glance

Patients aren't just answering.

They're engaging.

Early implementation findings challenge common assumptions about patient receptiveness to conversational AI.

87.3%

of patients called were successfully reached

<2%

of connected patients encountered strong resistance

1 in 3

connected conversations surfaced an actionable alert

30%

of reached patients proactively called back

About the research

Research grounded inreal patient conversations.

The report examines patient engagement, actionable alerts, and operational workflows across participating home health organizations.

These observational findings describe patient engagement and operational experience. They do not establish causal improvements in clinical outcomes.

Research & authorship

Lindsay Doak

Author

Healthcare industry research and strategy leader with 15 years of experience spanning healthcare education, business intelligence, patient satisfaction, and national research initiatives.

Research supported by CareBestie.

Inside the report

Three findings that matter

for home health leaders.

Finding 01

Patients are more receptive to AI than many agencies expect.

High reach, limited strong resistance, and proactive callbacks challenge assumptions about older adults' willingness to engage in conversations with AI voice agents.

Finding 02

Conversations uncover actionable patient needs.

Patients raised medication concerns, falls, changes in condition, hospitalizations, scheduling issues, and patient experience problems—information that can support earlier review and intervention.

Finding 03

Turning patient insights into action is the next challenge.

The research examines how agencies review alerts, coordinate follow-up, address operational issues, and integrate patient-reported information into everyday care delivery.

Patient acceptance

Finding 01

Patients are more receptive to AI than many agencies expect.

High reach, limited strong resistance, and proactive callbacks challenge assumptions about older adults' willingness to engage in conversations with AI voice agents.

Actionable insights

Finding 02

Conversations uncover actionable patient needs.

Patients raised medication concerns, falls, changes in condition, hospitalizations, scheduling issues, and patient experience problems—information that can support earlier review and intervention.

Operational response

Finding 03

Turning patient insights into action is the next challenge.

The research examines how agencies review alerts, coordinate follow-up, address operational issues, and integrate patient-reported information into everyday care delivery.

Get the full report

Go beyond

the headline findings.

Explore patient acceptance, engagement patterns, actionable alerts, and implementation lessons from real-world home health organizations.

Download the Report

INDUSTRY EVENTS

Where CareBestie shows up.

Michael connects to the tools your care team already uses, and stays inside the clinical boundaries, oversights, and privacy standards your agency requires.

View all events →

Speaking at the National Alliance for Care at Home Annual Conference

Oct 29, 2026 · Washington, DC