NCT06065761

Improving Risk Stratification of Emergency Department Patients With Acute Heart Failure

Improving Risk Stratification of Emergency Department Patients With Acute Heart Failure: Building and Testing a Machine-learning Platform for Personalized, Accurate, Real-time Risk Prediction

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 17,459 (estimated)
• Sponsor: Kaiser Permanente · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The primary goal is to build and test a previously developed and validated risk model and clinical decision support tool embedded within the electronic health record to improve risk stratification of emergency department (ED) patients with acute heart failure (AHF).

Detailed description

The study team will build an electronic health record-embedded clinical decision support tool using a recently developed risk prediction model that curates patient-specific data in real-time, accurately estimates short-term patient risk, and presents tailored clinical recommendations. This will be a regional implementation study in which the tool is turned on at 21 emergency departments (ED) across Kaiser Permanente Northern California (KPNC). The study team will validate risk predictions and study key clinical outcomes as part of this trial.

Conditions

• Heart Failure

Interventions

Type	Name	Description
OTHER	Comprehensive ED heart failure management tool	The investigators plan a regional implementation of an electronic health record-based heart failure decision support tool across 21 EDs of Kaiser Permanente Northern California (KPNC).

Timeline

• Start date: 2024-10-01
• Primary completion: 2025-10-31
• Completion: 2025-12-31
• First posted: 2023-10-04
• Last updated: 2024-04-24

Locations

21 sites across 1 country: United States