Choreo-ED

by X by 2

Contact Information

info@choreo-ed.com; marketing@xby2.com

Release Stage

Production

Release Date

2025-05-15

Version

1.2

Regulatory Approval

N/A

Global Availability

USA

Summary

Choreo-ED is an Artificial Intelligence / Machine Learning (AI/ML) powered tool designed to predict the likelihood of hospital admission or discharge early during an emergency department (ED) encounter. The system analyzes real-time Electronic Health Record (EHR) data and generates an admission or discharge probability score with high precision to support operational decision-making, such as bed allocation and care coordination, with the goal of improving throughput. The tool is not intended for diagnostic use or to replace clinical judgment.

Uses and Directions

Intended Use

The system continuously evaluates patient data during an ED encounter and generates an admission likelihood score (ADTA - Anticipated Decision to Admit) and discharge likelihood score (AEDD - Anticipated ED Discharge). When predefined thresholds (90% for admission and 95% for discharge) are met, alerts are displayed within the EHR to support early operational decisions.

Primary Users

Emergency physicians, Throughput coordinators, Bed managers, Hospitalists

How to Use

Model continuously updates its predictions based on new data available from EHR in real-time. Generates alerts within the EHR based on predefined thresholds. Staff incorporates insights into patient flow decisions.

Target Population

All patients who arrive at the emergency department

Cautioned Out-of-Scope Settings

Not intended for clinical decision-making. Not a replacement for clinician judgment.

EHR Compatibility

Compatible EHRs:

Epic
Cerner / Oracle Health
athenahealth
Allscripts / Altera
Meditech