MediCure
From Queue to Care, Faster.
The problem MediCure solves
The Problem It Solves
Hospitals across India face:
-
Long OPD queues → Patients wait for hours without knowing their turn.
-
Unclear bed availability → No real-time info about ICU, general, or private rooms.
-
Slow admission process → Manual paperwork and lack of transparency.
-
Poor emergency coordination → No centralized system for hospital transfers or load balancing.
These challenges lead to patient frustration, delayed treatment, and even risk to lives in critical cases.
What People Can Use It For
Patients:
-
Get digital OPD tokens with live queue status.
-
Know bed availability in real-time.
-
Upload documents & complete admission online.
-
Receive SMS/notifications when their turn is near.
Hospitals:
-
Admin dashboards to track bed occupancy & patient flow.
-
Doctors’ dashboard to see upcoming patients and manage workload.
-
Reduced manual effort & better utilization of staff.
City Health Systems:
-
A centralized view of hospitals for referrals & emergencies.
-
Smarter ambulance routing during critical cases.
-
Data-driven planning for healthcare infrastructure.
How It Makes Tasks Easier & Safer
-
Cuts down waiting times for patients.
-
Makes admissions transparent and faster.
-
Improves emergency handling with priority logic.
-
Ensures better hospital coordination during crises.
-
Provides data security & compliance with NDHM standards.
Challenges we ran into
Challenges I Ran Into
1. Real-Time Updates
Problem: Displaying OPD queues and bed availability in real-time was challenging. We faced delays while syncing Firebase sockets and APIs.
Solution: We implemented a hybrid approach using WebSockets and Firebase Realtime Database, ensuring instant updates for both notifications and dashboards.
2. Data Privacy & Security
Problem: Handling sensitive patient data required robust authentication and access control.
Solution: We adopted JWT-based authentication with strict role-based access (Patient, Doctor, Admin) to keep the data secure and compliant.
3. Integration with Existing Hospital Systems
Problem: Every hospital uses different legacy systems, which made data exchange difficult.
Solution: We designed standardized REST APIs and kept our architecture flexible to align with FHIR (Fast Healthcare Interoperability Resources) standards in the future.
4. Scalability Testing
Problem: The initial prototype worked for a single hospital, but performance dropped when simulating city-wide scaling.
Solution: We optimized database queries, added indexing, and conducted load testing to make the system more scalable and reliable.
Technologies used