Clinical Research Directory

Evaluating the Preferences and Tradeoffs of AI-based Electronic Consultations for Older Adults in Primary Care

Electronic consultations, or e-consults, let a primary care doctor request medical advice from a specialist without requiring the patient to attend a separate visit. Artificial intelligence (AI) systems may be able to provide this type of advice, potentially making e-consults faster and less costly. However, whether AI-based e-consults are acceptable may depend on how patients and clinicians weigh factors such as who provides the advice, how quickly it is received, its cost, and its quality. The purpose of this study is to examine how older adult patients and primary care clinicians weigh these factors when comparing e-consults produced by a human specialist with those produced by an AI system. In the study, participants will complete a one-time survey in which they compare sets of two hypothetical e-consults. Each e-consult will include a different combination of features, such as whether the advice comes from a human or AI, the expected wait time, the cost, and the quality of the advice. This study will estimate how much patients and clinicians value each feature in an e-consult. The findings will inform the potential future AI e-consults, so they better reflect patient and clinician preferences.

AI to Create Accessible & Reliable Patient Education Materials

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.