How a Simple Dashboard Can Transform TMS Therapy Management

OlhaStfn — Fri, 15 Aug 2025 13:24:10 +0000

(by Olha Tishchenko, Independent HealthTech Developer at Freeway Psychiatry)

All patient information shown here is entirely synthetic and created for demonstration purposes only. No real patient data is used.

Why TMS Management Needs a Rethink

Transcranial Magnetic Stimulation (TMS) therapy is life-changing for many patients — especially for those who haven’t responded to traditional medications.
But here’s the problem: managing TMS at scale is messy.

Multiple treatment courses per patient
Tracking attendance and gaps
Writing clinical notes
Keeping everything HIPAA-compliant

Most clinics still rely on spreadsheets, manual logs, or generic EHR modules. These aren’t built for TMS workflows — and that means more admin work, more room for mistakes, and fewer chances to spot patterns early.

The Idea: A Single Dashboard for Everything

I wanted a single screen where a clinician could instantly see:

How many treatment courses are active or completed
Which patients are missing too many sessions
Attendance trends over time
A breakdown of session types (New, Follow-Up, Service)

So I built the TMS Session Tracker — a streamlined dashboard designed with privacy in mind.

How It Works Today

The current version runs on synthetic demo data for public sharing, but the production version is fully HIPAA-compliant.
Key features include:

Summary statistics: Total courses, active vs. completed, extended courses (>70 sessions)
Patient course overview: Session counts, first/last dates, average and maximum gaps, current status
Session type distribution: Easy-to-read charts for quick insights
Trend visualization: Attendance and demand over time

AI Is the Next Step

While the current tracker is already useful, I designed it to integrate AI in the future:

Predictive scheduling — flagging patients likely to miss sessions
Automated clinical notes — SOAP format with ICD-10 and SNOMED codes
Outcome analytics — suggesting treatment adjustments based on aggregated trends

Why Privacy Came First

From the very start, I knew this project had to put privacy first. Here’s how I made sure of that:

Only fake patients here – every demo uses 100% synthetic data.

Real data stays safe – encrypted storage and secure production setup.

No peeking without permission – role-based access so only authorized staff can see or edit.

Two worlds, no mixing – real and demo environments are totally separate.

Real-World Impact

Even without AI, early pilot testing showed:

30–40% less admin time thanks to automated tracking
Better adherence monitoring and earlier interventions
Easier scheduling during high-demand periods (like holidays)

What’s Next

The architecture isn’t limited to TMS — it can work for neurofeedback or other mental health therapies. My goal is to create a multi-modal mental health management dashboard that helps clinicians spend less time on admin and more time with patients.

DEV Community: OlhaStfn