Humans (Call Dispatchers + Physicians) vs AI in Emergency Medical Dispatch, One-to-one Impact Analysis
HARMONIA is a prospective cohort study with continuous enrollment, evaluating the performance of a GPT model compared to Medical Regulation Assistants (ARM) and dispatch physicians at the SAS-Centre 15 of Lille University Hospital. The study uses 60 simulated call scenarios, managed by ARM–physician pairs and simultaneously analyzed by AI. The goal is to determine whether AI can match or exceed human performance in telephone triage using the ARM triage scale.
Prospective cohort with continuous enrollment, double-blind and intra-protocol randomization
60 simulated scenarios
13 dispatch physicians
10 volunteer ARMs
January - March 2026
(3-month enrollment)
SAS-Centre 15
Lille University Hospital
Primary: Compare GPT algorithm performance with actual ARM triage at the SAS-Centre 15 of CHU Lille against the gold-standard ARM triage scale.
Secondary:
Each scenario is managed by an ARM–physician pair, formed interchangeably from a volunteer pool. Matching follows a double-blind scheme with intra-protocol randomization. Each volunteer is exposed to all simulated cases, ensuring a complete crossover evaluation.
The gold standard is composite: strict application of the ARM triage scale to call data and expert opinion (panel of 3 blinded physicians).
MAE, RMSE, weighted Kappa, exact agreement and ±1 class, AUC-ROC
F1 micro/macro, Spearman correlation, multiclass Brier score
Bland-Altman plots, confusion matrices, reliability diagrams
R® (v4.2.2+)
α = 5% threshold, Bonferroni correction
The study does not modify patient care in any way. It relies exclusively on simulated data (anonymized by default, AES-256 encrypted). AI models do not store or archive audio recordings. Signed consent from participating ARMs and physicians. Analysis conducted on the secured CHU Lille platform (SNDS security framework).
Protocol writing, scientific council validation, DPO declaration
Start of enrollment
End of enrollment
End of data extraction
Analysis and results validation
Final report
Peer-reviewed journal publication