AI to Create Accessible & Reliable Patient Education Materials

Summary

This study investigates the use of Generative AI (GAI) to support primary care practices in delivering accurate, accessible patient education. With the rise of health misinformation, increasingly complex patient needs, and a strained healthcare workforce, primary care must find new ways to communicate trusted health information effectively. Leveraging the Canadian Primary Care Information Network (CPIN), this study will generate patient education messages on key health topics using both GAI and human content experts.

Diverse review panels of patients and providers will assess the messages on quality of information, adaptability, and relevance and usefulness, with special attention to socioeconomic factors that may impact message accessibility. CPIN will recruit a diverse sample of participants to evaluate both GAI- and human-generated messages. Review panels will provide structured feedback via surveys, aiming to identify differences in content quality and effectiveness.

The study's goal is to determine whether GAI can produce high-quality health information that meets primary care standards. Results will reveal how GAI tools can support primary care in reducing misinformation and administrative burdens, fostering patient-provider relationships, and improving health equity. Findings will inform best practices for integrating GAI in primary care to ensure accessible, timely patient education across Canada.

Conditions

• Primary Care Patients

Interventions

OTHER

Health promotional messages generated by Artificial Intelligence

Short (850 characters) and long (1 page) messages will be generated by a Generative Artificial Intelligence (ChatGPT 4.0) on different health-related topics

OTHER

Health promotional messages generated by humans

Short (850 characters) and long (1 page) messages will be generated by a primary care and/or public health human expert on different health-related topics

Sponsors & Collaborators

• Cheo Research Institute

  collaborator OTHER

• Eastern Ontario Health Unit

  collaborator UNKNOWN

• Hopital Montfort

  lead OTHER

Principal Investigators

• Sharon Johnston, MD, LLM · Institut du Savoir Montfort

• William Hogg, MD, MSc · Institut du Savoir Montfort

Study Design

Allocation

RANDOMIZED

Purpose

HEALTH_SERVICES_RESEARCH

Masking

DOUBLE

Model

CROSSOVER

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2025-01-16

Primary Completion

2026-04-30

Completion

2026-09-30

Countries

• Canada

Study Locations