Health Condition 1: T07- Unspecified multiple injuries
Conditions
Interventions
Intervention1: Artificial Intelligence Powered Clinical Audit: The intervention involves the use of a Large Language Model to audit the clinical records of trauma patients. The artificial intelligence
Sponsors
MOSC MEDICAL COLLEGE
Eligibility
Inclusion criteria
Inclusion criteria: Patients presenting to the emergency medicine department with a history of trauma who underwent primary survey and management. The clinical records must contain completed initial documentation and triage notes from the emergency department visit.
Exclusion criteria
Exclusion criteria: Patients who were brought dead to the emergency department. Clinical records with grossly incomplete baseline data, missing primary triage notes, or illegible handwriting that entirely prevents human or digital transcription. Non trauma medical emergencies are also excluded from this study.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic accuracy of the artificial intelligence auditor in identifying missed clinical protocols, calculated using negative predictive value, positive predictive value, sensitivity, and specificity against a gold standard expert assessment.Timepoint: At baseline, Immediately upon the completion of the clinical audit for each individual patient record. | — |
Secondary
| Measure | Time frame |
|---|---|
| Difference in the time taken to complete the clinical audit of emergency trauma patient records between the artificial intelligence system & the manual human auditor.Timepoint: At baseline, immediately at the time of the clinical audit | — |
Countries
India
Contacts
Public ContactDR NISANTH MENON N
MALANKARA ORTHODOX SYRIAN CHURCH MEDICAL COLLEGE HOSPITAL
Outcome results
None listed