Artificial Intelligence as a Decision Making Tool in Emergency Department

Time from ED registration to discharge from emergency department or admission to a hospital ward, focusing in addition on consultation cycle time.

Aim 1:LLM Diagnostic & Treatment Recommendation Appropriateness Appropriateness of LLM recommendations rated by senior clinicians (1=inappropriate, 5=appropriate) Timeframe:ED registration to discharge or inpatient admission, up to 24h Aim 2:Diagnostic Accuracy Rate- LLM-Assisted vs. Standard Care Clinical Decision-Making Proportion of correct diagnoses in LLM-assisted vs. standard care (%), matched to discharge diagnosis Timeframe:ED registration to final diagnosis, up to 24h Aim 3:Clinician-Rated Utility & Usability of LLM Outputs- SUS and Likert Scale Utility measured via SUS (0-100) and 5-point Likert rating, collected post-encounter with qualitative feedback Timeframe:End of each clinical encounter,up to 36 months Aim 4:LLM Retrospective Benchmark-Percent Agreement & Cohen's Kappa vs. Actual Clinical Outcomes Agreement between LLM recommendations and actual outcomes (diagnosis, disposition, LOS) in de-identified records Timeframe:Records up to 36 months prior to study initiation