Artificial Intelligence applications in Advance Care Planning

Abstract This scoping review examines artificial intelligence (AI) applications in advance care planning (ACP), synthesizing evidence from databases like PubMed, Web of Science, and Scopus (2019-2024), ten articles, using PRISMA guidelines. The review focused on AI tools for ACP documentation, decision-making, and workflow optimization, excluding studies lacking clinical validation or patient-centered outcomes. Findings reveal promising AI applications in ACP: predictive models, like Stanford’s EHR-based mortality predictor, improved high-risk patient identification, triggering earlier ACP discussions. Natural Language Processing reduced ACP documentation review time significantly. AI-powered chatbots increased ACP literacy among older adults by 40%, addressing health disparities. Challenges like algorithmic bias from non-diverse datasets exacerbates inequities in ACP access persist. Clinician resistance stems from unclear liability frameworks and poor EHR interoperability. Only 25% of tools address caregiver burden or surrogate decision-maker needs. Research gaps include limited evidence on AI-driven e-planning tools’ cost-effectiveness, lack of standardized metrics for evaluating AI’s impact on patient autonomy and understudied ethical risks of over-reliance on AI for sensitive end-of-life conversations. Future directions focus on equity-driven design, the integration of e-planning into electronic medical records, and the assessment of AI’s capacity to alleviate caregiver burden and enhance preparedness of surrogate decision-makers. This research emphasizes the necessity to transform ACP from a documentation-oriented process to a communication-centered continuum, utilizing AI to democratize access and tackle systemic inequalities. It highlights the potential of AI to transform ACP, while emphasizing the importance of ethical implementation and patient-centered outcomes.