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Inspiration

Vaccination schedules are complex, and most people don’t know which vaccines they’re eligible for, when boosters are due, or how risk factors affect eligibility. Clinics often rely on manual checks, outdated records, and reactive reminders, which leads to missed immunizations.

We were inspired to build Keep Me Alive to make vaccine eligibility transparent, explainable, and proactive. We wanted to reduce confusion, prevent missed vaccines, and create a system that actually empowers patients instead of overwhelming them.

What it does

Keep Me Alive is a smart vaccine eligibility and reminder system that:

Determines vaccine eligibility based on age, medical history, vaccination records, and risk factors

Classifies vaccines as Eligible, Due Soon, Overdue, Completed, or Not Eligible

Explains why a vaccine is recommended using a transparent rule engine

Generates calendar-ready reminders

Provides a clinic-facing dashboard showing overdue patients and upcoming immunizations

It turns a confusing vaccine schedule into a clear, actionable plan.

How we built it

We divided the system into modular components:

Rule Engine

We built a custom rule-based eligibility engine that:

Takes a patient profile (DOB, chronic conditions, risk tags, dose history)

Evaluates eligibility against structured vaccine rules

Returns status, next dose number, due date, and explanation reasons

Outputs a consistent object structure for frontend display

Frontend

Built a responsive dashboard with a timeline view

Created a detailed vaccine explanation panel

Added calendar file generation for reminders

AI Assistant

We integrated an AI chatbot that:

Injects patient context + rule engine results

Answers vaccine-related questions

References the same rule logic used in eligibility

Includes medical safety disclaimers

We implemented:

Overdue counts

Upcoming vaccine metrics

Risk tag filtering

Outreach-style patient views

The system works end-to-end: profile → rule engine → results → timeline → reminders → clinic insights.

Challenges we ran into

Designing a rule engine that was flexible yet hackathon-realistic

Handling edge cases like incomplete dose histories

Ensuring explanations were clear and human-readable

Structuring data so the same rule engine supports both patient and clinic views

Balancing AI integration with medical safety guardrails

We had to carefully design the data model early to avoid rebuilding core logic later.

Accomplishments that we're proud of

Building a fully explainable eligibility engine from scratch

Creating a clean, intuitive immunization timeline

Supporting multiple family members under one account

Connecting eligibility results directly to actionable steps (calendar + clinic locator)

Designing a system that serves both patients and clinics

Delivering an end-to-end working prototype within hackathon constraints

Most importantly, we didn’t just build a UI, we built logic that can scale.

What we learned

Healthcare logic requires clarity and explainability

Rule engines must be structured, not hardcoded

User trust depends on transparency (“Why am I eligible?”)

Family-based healthcare systems need modular data design

AI in healthcare must always be contextual and safety-aware

We also learned how important it is to balance technical ambition with demo reliability.

What's next for Keep Me Alive

Integrate real provincial immunization schedules

Connect with real clinic datasets

Add secure authentication and encrypted health data storage

Implement automated SMS/email reminders

Expand into multilingual support

Add predictive analytics for outreach prioritization

Pilot with community clinics

Our vision is to turn Keep Me Alive into a proactive immunization platform that reduces missed vaccines at both the individual and community level.

Built With

• css
• firebase
• html
• javascript
• react
• tailwind