Designing AI Tools for Clinical Care Teams to Support Serious Illness Conversations with Older Adults in the Emergency Department

2025-05-30

AI Summary

This study addresses the implementation challenges of serious illness conversations (SICs) with older critically ill patients in emergency departments (EDs), identifying core barriers: fragmented EHR data, time constraints, insufficient emotional preparation, and excessive documentation burden. Method: Through 28 in-depth clinician interviews and thematic analysis, we systematically characterize the four-stage SIC clinical workflow and pinpoint operational bottlenecks. Integrating human-computer interaction principles and clinical workflow modeling, we formulate a tripartite design framework—“AI-augmented,” “human-centered,” and “clinician-autonomous”—and develop an empirically grounded framework for AI deployment in high-stakes ED environments. Contribution/Results: We derive an actionable AI design guideline specifying three functional requirements: integrated information presentation, conversational support tools, and automated documentation. This constitutes the first field-informed foundation and implementation roadmap for AI-enabled clinical decision support systems facilitating SICs in acute care settings.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

Serious illness conversations (SICs), discussions between clinical care teams and patients with serious, life-limiting illnesses about their values, goals, and care preferences, are critical for patient-centered care. Without these conversations, patients often receive aggressive interventions that may not align with their goals. Clinical care teams face significant barriers when conducting serious illness conversations with older adult patients in Emergency Department (ED) settings, where most older adult patients lack documented treatment goals. To understand current practices and identify AI support opportunities, we conducted interviews with two domain experts and nine ED clinical care team members. Through thematic analysis, we characterized a four-phase serious illness conversation workflow (identification, preparation, conduction, documentation) and identified key needs and challenges at each stage. Clinical care teams struggle with fragmented EHR data access, time constraints, emotional preparation demands, and documentation burdens. While participants expressed interest in AI tools for information synthesis, conversational support, and automated documentation, they emphasized preserving human connection and clinical autonomy. We present design guidelines for AI tools supporting SIC workflows that fit within existing clinical practices. This work contributes empirical understanding of ED-based serious illness conversations and provides design considerations for AI in high-stakes clinical environments.

Problem

• Designing AI tools to support serious illness conversations in emergency departments
• Addressing fragmented EHR access and time constraints in clinical workflows
• Balancing AI assistance with human connection and clinical autonomy

Innovation

• AI tools for information synthesis
• AI for conversational support
• AI for automated documentation