JMIR Publications

ABSTRACT

Background:

Artificial intelligence-enabled patient decision aids (AI-PDAs) hold promise for supporting older adults with chronic diseases in accessing personalized health information, clarifying preferences, and engaging in shared decision-making. Achieving equity in their design requires attention to the complex healthcare and digital contexts in which these tools are used. While the Digital Health Equity Framework (DHEF) provides a conceptual foundation, practical strategies for its application remain limited.

Objective:

To identify equity-related determinants and generate actionable design strategies for applying the DHEF to AI-PDAs for older adults.

Methods:

Semi-structured interviews were conducted with older adults living with hypertension and/or diabetes, healthcare providers, and medical students to explore equity determinants relevant to AI-PDAs. In parallel, a review of reviews synthesized existing evidence on approaches to addressing these determinants. Findings were integrated through interdisciplinary consultations involving experts from medicine, public health, social services, and computer science to generate actionable recommendations.

Results:

A total of 15 older adults, 8 healthcare providers, and 10 medical students were interviewed. Evidence from 13 reviews, combined with stakeholder insights, informed a set of practical recommendations addressing equity determinants across individual, interpersonal, community, societal, and cross-level domains.

Conclusions:

This study operationalizes the DHEF by translating its principles into an evidence-based roadmap for equitable AI-PDA design. The findings offer practical guidance for researchers, clinicians, and policymakers to promote digital health equity and support inclusive, age-friendly decision-making tools.