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NCT Number: NCT07804407

Prospective Evaluation of AI Generated History of Present Illness Drafts in the Emergency Department

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.

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Key information

Conditions

All Emergency Department Visits Meeting Eligibility Criteria Disease Attributes Emergencies Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

19 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Yonsei University Severance Hospital

Seoul, Seoul City, 03722, South Korea

Location status: Recruiting

Location contact

Stephen GW LEE

CONTACT

[email protected]

82-2-2228-2678

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

EDnote HPI (AI-generated HPI draft)

Other

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.

Conventional physician HPI

Other

HPI written by the treating emergency physician according to usual practice, blinded to the EDnote-generated HPI draft.

Primary outcomes

  1. Encounter-level clinical fact capture rate

    Time frame: At blinded review, within 6 months after each index ED visit

Secondary outcomes

  1. Modified PDQI-9 score

    Time frame: At blinded review, within 6 months after each index ED visit

  2. AI HPI draft generation time

    Time frame: At index ED visit

  3. Rater identification of document authorship (AI vs. physician-written)

    Time frame: At blinded review, within 6 months after each index ED visit

Study contacts

Contact information is provided by the study sponsor or research team.

Stephen GW LEE

CONTACT

[email protected]

82-2-2228-2678

Sponsors and collaborators

Lead sponsor

Yonsei University

Other

Registry information

Official study title

Prospective Evaluation of Artificial Intelligence-generated History of Present Illness Drafts in the Emergency Department

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Sep 4, 2026
Registry last updated
Sep 4, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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