Prospective Evaluation of Artificial Intelligence-generated History of Present Illness Drafts in the Emergency Department
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Encounter-level clinical fact capture rate
研究概览
简要总结
This single-center prospective observational study evaluates whether an on-premise, large language model-based tool (EDnote) that generates a draft history of present illness (HPI) from real-time transcription of the patient-physician encounter produces documentation of higher quality than conventional physician-written HPI in the emergency department. The treating physician writes the conventional HPI blinded to the AI draft. Unedited AI-generated HPI drafts and conventional HPI are compared through blinded review by independent emergency physicians.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 19 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥19 years; presenting to the emergency department; initial encounter documented with EDnote; verbal consent to study participation.
排除标准
- •Cardiac arrest; limited ability of both patient and guardian to communicate verbally; refusal of participation.
研究组 & 干预措施
ED patients with EDnote-assisted initial encounter
Adult emergency department patients whose initial encounter was recorded by EDnote. While the treating physician conducts usual care and writes the conventional HPI, EDnote generates an AI HPI draft in the background; the physician remains blinded to the draft. Both HPIs are evaluated by independent raters blinded to document source.
干预措施: EDnote HPI (AI-generated HPI draft) (Other)
ED patients with EDnote-assisted initial encounter
Adult emergency department patients whose initial encounter was recorded by EDnote. While the treating physician conducts usual care and writes the conventional HPI, EDnote generates an AI HPI draft in the background; the physician remains blinded to the draft. Both HPIs are evaluated by independent raters blinded to document source.
干预措施: Conventional physician HPI (Other)
结局指标
主要结局
Encounter-level clinical fact capture rate
时间窗: At blinded review, within 6 months after each index ED visit
次要结局
- AI HPI draft generation time(At index ED visit)
- Rater identification of document authorship (AI vs. physician-written)(At blinded review, within 6 months after each index ED visit)
- Modified PDQI-9 score(At blinded review, within 6 months after each index ED visit)
研究者
LEE STEPHEN GYUNG WON
Clinical assistant professor
Yonsei University