Automating Clinical Consultation Summaries Inside the EMR

Project Overview

A healthcare provider partnered with Cubet to reduce the growing burden of clinical documentation using AI and natural language processing. The goal was to automate consultation summaries directly within the EMR without requiring doctors to change how they worked. The solution, Whizz, enables doctors to generate accurate, structured notes from patient conversations—saving time, improving consistency, and reducing fatigue.
 

Industry

Healthcare
 

Challenges Addressed

• Excessive time spent by clinicians on manual documentation
• Inconsistent consultation notes across departments
• Delays in completing EMR entries
• Rising clinician fatigue due to administrative overload
• Lack of intelligent automation in existing EMR workflows
• The need for data privacy, clinician trust, and compliance within regulated environments

Collaboration in Action

Cubet integrated Whizz directly into the healthcare provider’s EMR system. Whizz listens to clinician–patient conversations during consultations (with patient consent), transcribes the dialogue, and uses clinical NLP to extract relevant information. Clinicians remain in control by reviewing and approving the final notes before they are submitted to the EMR, ensuring accuracy and ownership without disruption to existing workflows.
 

Technologies Deployed

• AI-powered speech recognition trained for healthcare
• Natural language processing tailored for clinical context
• Embedded EMR application layer integration
• Human-in-the-loop validation workflow
• Role-based access control and audit logging
• Modular and scalable architecture
• On-premise processing within the healthcare network

Innovative Features

• Real-time voice capture during clinical consultations
• Automatic transcription and structuring of clinical data
• Entity mapping (symptoms, diagnoses, meds) into predefined EMR templates
• Built-in clinician review, editing, and approval
• Full alignment with HIPAA and regional data protection policies
• No patient data leaves the client-controlled environment

Value Delivered

For Clinicians:

• Reduced time spent on documentation
• Lower post-visit fatigue
• Faster and more consistent EMR updates

For Operations:

• Structured and standardized clinical records
• Noticeable drop in documentation delays
• Improved data quality for analytics and reporting

For Leadership:

• High adoption due to minimal disruption
• Operational efficiency without added headcount
• Scalable architecture for future healthcare automation

User Feedback

Doctors welcomed the solution because it fit their workflow and respected their role. Automation supported rather than replaced them, preserving trust and clinical judgment. The human-in-the-loop model gave clinicians full control, making the transition smooth and the adoption high.

Conclusion

By automating consultation summaries, Cubet enabled the healthcare provider to streamline documentation without compromising quality or compliance. The success of Whizz laid the groundwork for broader AI adoption, including discharge summaries, follow-ups, and longitudinal records—marking a practical, trusted starting point for real-world AI in healthcare.