Aledade EHR Overlay (for ML App, Staging) logo

Aledade EHR Overlay (for ML App, Staging)

Paid

Real-time EHR integration with machine learning diagnosis support

HealthcareContact
Type
Saas
Company
Aledade EHR Overlay

About Aledade EHR Overlay (for ML App, Staging)

The Aledade EHR Overlay is a tool that integrates with existing Electronic Health Record (EHR) workflows to help practices review potential diagnoses and take action. Changes made within the Overlay are reflected in real-time within the Aledade App and the EHR. It uses machine learning to identify fields within the EHR to display relevant patient information. It is a beta version and surfaces potential diagnoses, but the practice remains responsible for accurate code selection and documentation.

How to Use

The Overlay integrates directly into your existing EHR system. When viewing a patient's record, the Overlay will display potential diagnoses based on machine learning analysis. You can then review these suggestions and take appropriate action, with changes reflected in both the Aledade App and your EHR.

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Key Features

  • Real-time integration with existing EHR workflows
  • Machine learning-driven diagnosis suggestions
  • Synchronization with Aledade App
  • Identification of relevant EHR fields

Use Cases

  • Reviewing potential diagnoses within the EHR system
  • Taking action on diagnosis suggestions directly within the EHR
  • Improving coding accuracy and documentation

FAQ

Is the Aledade EHR Overlay a production version? APIMart 99.9% SLA. Your AI, Always On.

Key Features

Real-time integration with existing EHR workflows
Machine learning-driven diagnosis suggestions
Synchronization with Aledade App
Identification of relevant EHR fields

Pros & Cons

Pros
  • Supports accurate code selection and documentation
  • Leverages ML to surface relevant patient information
  • Real-time bidirectional sync with EHR and Aledade App
Cons
  • Currently in beta, may have limitations or bugs
  • Practice remains fully responsible for final coding decisions

Best For

Reviewing potential diagnoses within the EHR systemTaking action on diagnosis suggestions directly within the EHRImproving coding accuracy and documentation

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