A Trial of AI-Powered Text Message Outreach on Well-Child Visit Completion

Summary

The goal of this clinical trial is to evaluate whether conversational AI-powered text message outreach with appointment scheduling assistance improves well-child visit completion rates in Medicaid-enrolled children aged 0-21 years compared with automated text messages alone or traditional passive outreach. The main questions it aims to answer are: Does automated SMS outreach improve well-child visit completion rates compared to traditional passive outreach? Does conversational AI-powered scheduling assistance lead to higher completion rates than automated SMS alone?

Researchers will compare three groups: Control Group: Participants receive traditional passive outreach (mailed reminders). Automated SMS Group: Participants receive standardized automated text message reminders. Automated SMS + Conversational AI Scheduling Assistance Group: Participants receive automated text messages plus AI-powered appointment scheduling assistance that contacts primary care providers directly to book appointments on behalf of families.

Participants will: Be randomized into one of three study groups at the household level. Receive outreach from June 9-July 14, 2025. Have well-child visit completion ascertained through administrative claims through December 31, 2025.

This study tests whether concrete scheduling support - rather than reminders alone - drives preventive care utilization in pediatric Medicaid populations.

Conditions

• Well Child Visit
• Gaps in Care

Interventions

BEHAVIORAL

Automated SMS

Participants received standardized automated text message reminders at predetermined intervals (initial contact, 2-week follow-up, 4-week follow-up). Messages provided general information about visit importance and instructions to call providers to schedule. Messages did not include interactive scheduling or conversational capabilities.

BEHAVIORAL

Automated SMS + Conversational AI Scheduling Assistance

Participants received automated text message reminders with response options. When families expressed interest, structured follow-up texts collected appointment preferences. An AI-powered telephone scheduling system (GPT-4o, OpenAI) then contacted the child's primary care provider directly to book appointments on behalf of families. The system disclosed its automated nature at call initiation and escalated to human staff when clinic policies were incompatible with automated scheduling or technical failures occurred.

OTHER

Traditional Passive Outreach

Participants received standard health plan outreach consisting of periodic mailed reminders. Families retained access to all standard appointment scheduling methods including telephone calls to provider offices.

Sponsors & Collaborators

• Waymark

  lead INDUSTRY

Study Design

Allocation

RANDOMIZED

Purpose

PREVENTION

Masking

DOUBLE

Model

PARALLEL

Eligibility

Min Age

0 Years

Max Age

21 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2025-06-01

Primary Completion

2025-12-31

Completion

2026-03-17

Countries

• United States

Study Locations