Transforming Complex Questionnaires into Clear Patient Summaries — How Dr. Tambasco Uses Empathia AI in Environmental Medicine
Environmental Health Clinic at Women’s College hospital
Huntsville, ON, Canada
Doctor
Dr. Domenica Tambasco
Specialty
Family Medicine
Empathia can’t replace my judgment — but it can do the busy work that slows me down.
The challenge
Before Empathia
- Manual Questionnaire Processing: Intake questionnaires had to be scanned into Epic and couldn’t be easily summarized or searched.
- Fragmented EMR Templates: Subjective sections, investigations, and plans had to be entered manually despite some pre-populated fields (like medications/allergies).
- Time-Consuming Documentation: Functional assessments required repetitive copy-pasting from scanned documents.
“Once a form is scanned into Epic, we can’t manipulate or download it — it just becomes static. Even though Epic has templates, we still end up typing half the note manually.”
Dr. Tambasco practices in a clinic specializing in environmental and exposure-related medicine, where each patient completes detailed work and environmental history questionnaires. These forms are crucial for diagnosis but time-consuming to review, summarize, and enter into Epic EMR.
“Our questionnaires are long — patients fill them out before referral, and it’s hard to turn that into a concise summary.”
The clinic director was also exploring ways to streamline documentation processes across the team, looking for practical tools that could summarize patient data, generate structured notes, and integrate with Epic.
Manual Questionnaire Processing: Intake questionnaires had to be scanned into Epic and couldn’t be easily summarized or searched.
Fragmented EMR Templates: Subjective sections, investigations, and plans had to be entered manually despite some pre-populated fields (like medications/allergies).
Time-Consuming Documentation: Functional assessments required repetitive copy-pasting from scanned documents.
“Once a form is scanned into Epic, we can’t manipulate or download it — it just becomes static. Even though Epic has templates, we still end up typing half the note manually.”
How Empathia AI Fits Into the Workflow
The Discovery
Dr. Tambasco connected with Empathia to setup and explore how AI could support documentation automation.
Implementation & Workflow Adaptation
With Empathia, they could generate structured intake summaries directly from patient questionnaires and support custom template creation tailored to environmental medicine workflows.
They explored:
How Empathia can read patient responses and generate sectioned summaries for review and editing.
Template customization for intake histories, exposure summaries, and consultation letters.
Building a new HPI template specific to chemical sensitivities, using targeted questions designed by Dr. Tambasco.
Understanding that AI suggestions for treatments are clinician-reviewed — Empathia generates notes and differentials but leaves management decisions to the provider.
Create templates matching Epic’s consultation layout, so summaries could be easily copied into existing EMR sections without breaking structure.
The Transformation
After Empathia
Key Improvements
Through Empathia AI, Dr. Tambasco’s clinic took the first step toward integrating AI-assisted documentation into an Epic-based workflow. By focusing on questionnaire summarization, template customization, and streamlined note generation, Empathia has helped reduce documentation load while preserving clinical accuracy.
The result: less time spent on repetitive entry, clearer intake summaries, and more time for clinical reasoning.
Empathia helped Dr. Tambasco simplify how patient intake information was turned into usable clinical summaries, reducing manual work while maintaining accuracy. The AI-generated summaries allowed for faster chart preparation, freeing up more time for patient analysis and interpretation rather than data entry. The optimized template is shared across the team to ensure efficiency and consistency.
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Key Features Used
Intake Summary
Auto-generates patient history from intake forms
Templates
Customizable templates for common visit types
AI Differential Diagnosis
Suggests possible diagnoses based on encounter data, with linked evidence and cited resources
