# Balancing Efficiency and Empathy: Healthcare Providers' Perspectives on AI-Supported Workflows for Serious Illness Conversations in the Emergency Department

arXiv: https://arxiv.org/abs/2506.00241 · HTML: https://mlsanity.com/paper/2506.00241/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 113 references that are in the map.
- First posted on arXiv 30 May 2025.

## Builds on (most cited first, 7 of 7)

- [Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens](https://mlsanity.com/paper/2102.00593/) (2021)
- [Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis](https://mlsanity.com/paper/2309.12368/) (2023)
- [Improving Palliative Care with Deep Learning](https://mlsanity.com/paper/1711.06402/) (2017)
- [Customizing Emotional Support: How Do Individuals Construct and Interact With LLM-Powered Chatbots](https://mlsanity.com/paper/2504.12943/) (2025)
- [The Future of Learning in the Age of Generative AI: Automated Question Generation and Assessment with Large Language Models](https://mlsanity.com/paper/2410.09576/) (2024)
- [CommSense: A Wearable Sensing Computational Framework for Evaluating Patient-Clinician Interactions](https://mlsanity.com/paper/2407.08143/) (2024)
- [Envisioning Possibilities and Challenges of AI for Personalized Cancer Care](https://mlsanity.com/paper/2408.10108/) (2024)

## Abstract (arXiv)

Serious Illness Conversations (SICs), discussions about values and care preferences for patients with life-threatening illness, rarely occur in Emergency Departments (EDs), despite evidence that early conversations improve care alignment and reduce unnecessary interventions. We interviewed 11 ED providers to identify challenges in SICs and opportunities for technology support, with a focus on AI. Our analysis revealed a four-stage SIC workflow (identification, preparation, conduction, documentation) and barriers at each stage, including fragmented patient information, limited time and space, lack of conversational guidance, and burdensome documentation. Providers expressed interest in AI systems for synthesizing information, supporting real-time conversations, and automating documentation, but emphasized concerns about preserving human connection and clinical autonomy. This tension highlights the need for technologies that enhance efficiency without undermining the interpersonal nature of SICs. We propose design guidelines for ambient and peripheral AI systems to support providers while preserving the essential humanity of these conversations.