Artificial Intelligence as a Decision Making Tool in Emergency Department

Conditions: Clinical Decision-making, Medical Reporting, Emergency Department Visit, Information Systems, Electronic Health Records, Artificial Intelligence in Medicine

Sex: All

Ages: 0 Years – 120 Years

Healthy volunteers: No

Enrollment: 100000

Sponsor: Rambam Health Care Campus

Location: Rambam healthcare campus Haifa

Summary

This study will evaluate the performance of a large language model (LLM)-based clinical decision support system in the emergency department at Rambam Health Care Campus. The system analyzes structured patient data from the electronic health record and generates diagnostic and treatment recommendations for physicians. The study will assess the system's ability to support diagnostic reasoning, its impact on diagnostic accuracy when used by physicians, and its perceived clinical usefulness. In addition, a retrospective analysis of de-identified patient records will be conducted to compare LLM-generated recommendations with actual clinical outcomes, including diagnosis, disposition decisions, and length of stay. The study will also examine the performance of the system in a multilingual clinical environment where both Hebrew and English are used in medical documentation and communication.

Eligibility Criteria

Inclusion Criteria: Patients aged 0 to 120 years presented to the emergency department Exclusion Criteria: None

Interested in this study? View the official listing for contact and enrollment details.

View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT06902675). StuddyBuddy aggregates publicly available trial information.