How It Works
Emergency department overcrowding impacts throughput and patient satisfaction, increases wait times and compromises community access to care. A product of collaboration with physicians, hospitalists and technologists, Choreo-ED tackles ED crowding head-on, helping care teams better coordinate each step in the patient flow.
Choreo-ED works as a non-disruptive addition to your care team. A suite of deep learning patient disposition models focused on transitions in a patient’s care journey, Choreo-ED integrates directly with your EHR system using historical data as well as real-time patient encounter data like, labs, vitals, and orders in real time. As new data comes in, Choreo-ED anticipates patient disposition decisions and notifies care teams to initiate next steps in the patient flow, improving throughput efficiency.
Secure and scalable.
SOC2 and HIPAA compliant, our model was built following AI best practices and security measures to ensure your patient data remains protected.
Partner Hospital Analysis
At a mid-size suburban hospital, Choreo-ED helped:
ED boarding
ED per month.
Improving lead time creates a more efficient patient flow.
The Anticipated Decision to Admit model (ADTA) notifies of a Decision to Admit up to 2.5 hours in advance, helping initiate key steps in patient flow sooner, while our Anticipated Emergency Department Discharge (AEDD) model targets clear discharges, prompting care teams to better coordinate with patients and families and get them home sooner.
Explore a real-world patient scenario with with Choreo-ED’s Encounter Navigator
