All Emergency Department Visits Meeting Eligibility Criteria
Conditions
Keywords
emergency department, ai scribe, ambient scribe, history of present illness
Brief summary
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.
Interventions
On-premise large language model-based tool that transcribes the patient-physician encounter in real time and generates an unedited HPI draft. The treating physician is blindedto the AI HPI draft.
HPI written by the treating emergency physician according to usual practice, blinded to the EDnote-generated HPI draft.
Sponsors
Study design
Eligibility
Inclusion criteria
* Age ≥19 years; presenting to the emergency department; initial encounter documented with EDnote; verbal consent to study participation.
Exclusion criteria
* Cardiac arrest; limited ability of both patient and guardian to communicate verbally; refusal of participation.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Encounter-level clinical fact capture rate | At blinded review, within 6 months after each index ED visit |
Secondary
| Measure | Time frame |
|---|---|
| Modified PDQI-9 score | At blinded review, within 6 months after each index ED visit |
| 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 |
Countries
South Korea