PreCare: Designing AI Assistants for Advance Care Planning (ACP) to Enhance Personal Value Exploration, Patient Knowledge, and Decisional Confidence

TL;DR

PreCare is an AI-assisted website designed to improve personal value exploration, knowledge, and decision confidence in advance care planning, addressing limitations of online ACP through personalized guidance and professional collaboration.

Contribution

This paper introduces PreCare, an innovative AI-driven platform that enhances online ACP by integrating personalized assistants based on clinical insights.

Findings

PreCare achieved an excellent SUS usability rating.

Participants preferred PreCare's AI assistants by 92%.

PreCare significantly improved value exploration, knowledge, and decisional confidence.

Abstract

Advance Care Planning (ACP) allows individuals to specify their preferred end-of-life life-sustaining treatments before they become incapacitated by injury or terminal illness (e.g., coma, cancer, dementia). While online ACP offers high accessibility, it lacks key benefits of clinical consultations, including personalized value exploration, immediate clarification of decision consequences. To bridge this gap, we conducted two formative studies: 1) shadowed and interviewed 3 ACP teams consisting of physicians, nurses, and social workers (18 patients total), and 2) interviewed 14 users of ACP websites. Building on these insights, we designed PreCare in collaboration with 6 ACP professionals. PreCare is a website with 3 AI-driven assistants designed to guide users through exploring personal values, gaining ACP knowledge, and supporting informed decision-making. A usability study (n=12) showed that PreCare achieved a System Usability Scale (SUS) rating of excellent. A comparative evaluation (n=12) showed that PreCare's AI assistants significantly improved exploration of personal values, knowledge, and decisional confidence, and was preferred by 92% of participants.