Building the future of medical management with cutting-edge technology
- π― Problem Statement
- π‘ Solution Overview
- ποΈ System Architecture
- π API Routes & Endpoints
- π± Technology Stack
- π Project Structure
- π Real-time Features & Notification
- π Impact & Analytics
India's healthcare system faces critical challenges that directly impact patient lives:
- 1.6 million Indians died in 2016 due to poor quality care and management (The Lancet)
- 75% of cancer deaths at AIIMS Delhi are attributed to long waiting times
- 10,000+ OPD patients daily at AIIMS with many turned away
| Issue | Impact | Consequence |
|---|---|---|
| Excessive Queuing | 3-8 hours wait time | Patient mortality, delayed treatment |
| Disease Spread | Crowded waiting areas | TB, COVID-19, Influenza transmission |
| Staff Overload | Unmanaged crowds | Reduced care quality |
| Manual Processes | Paper-based systems | Appointment conflicts, confusion |
- Mumbai Hospital Staff Dies After 3-Hour Wait
- Man Dies Waiting for Ultrasound at Noida Hospital
- COVID Patient Dies Outside Thane Hospital Waiting for ICU
- Patient Dies After 3-Hour Queue Wait in Kolkata
β
Real-time appointment dashboard
β
Smart patient flow management
β
Automated arrival notifications
β
Queue status updates
β
One-click patient communication
β
Online appointment booking
β
Real-time queue tracking (like Uber/Ola)
β
SMS & push notifications
β
Estimated wait times
β
Just-in-time arrival alerts
β
Reduced exposure to crowds
β
Centralized patient management
β
Digital workflow automation
β
Real-time analytics
β
Staff coordination tools
β
Resource optimization
graph TB
%% Frontend Clients with Icons
A["π₯ Patient Web Portal"] --> B["π API Gateway"]
C["π¨ββοΈ Doctor Dashboard"] --> B
D["π¨βπΌ Hospital Admin Panel"] --> B
E["π©βπ» Assistant Dashboard"] --> B
%% Core Services
B --> F["π Authentication Service"]
B --> G["π
Appointment Service"]
B --> H["β±οΈ Real-time Queue Service"]
B --> I["π Notification Service"]
B --> J["π₯ User Management Service"]
%% Database Layer
F --> K["ποΈ MongoDB Atlas"]
G --> K
J --> K
%% Firebase Real-time Layer
H --> L["π₯ Firebase Realtime DB"]
L --> M["π Live Queue Updates"]
L --> N["π Patient Status Tracking"]
%% Notification Channels
I --> O["π± Firebase FCM"]
I --> P["π± SMS Gateway"]
I --> Q["π§ Email Service"]
%% Analytics & Intelligence
R["π Analytics Engine"] --> K
R --> S["π Hospital Dashboard"]
R --> T["π Performance Reports"]
%% External Integrations
U["π³ Payment Gateway"] --> B
V["ποΈ Government Health API"] --> B
%% Enhanced Styling with Icons and Colors
classDef frontend fill:#4f46e5,stroke:#312e81,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef service fill:#059669,stroke:#064e3b,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef database fill:#dc2626,stroke:#7f1d1d,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef firebase fill:#f59e0b,stroke:#92400e,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef notification fill:#8b5cf6,stroke:#581c87,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef analytics fill:#06b6d4,stroke:#0e7490,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef gateway fill:#ec4899,stroke:#9d174d,stroke-width:3px,color:#fff,stroke-dasharray: 0
classDef external fill:#64748b,stroke:#334155,stroke-width:3px,color:#fff,stroke-dasharray: 0
%% Apply classes to nodes
class A,C,D,E frontend
class F,G,H,I,J service
class K database
class L,M,N firebase
class O,P,Q notification
class R,S,T analytics
class B gateway
class U,V external
| Event Type | Trigger | Recipients | Message Template |
|---|---|---|---|
| Doctor Arrival | Assistant check-in | Waiting patients | "π©Ί Dr. {name} has arrived. Your estimated wait: {time} mins" |
| You're Next | Queue management | Next patient | "π You're next! Please proceed to Room {number}" |
| Appointment Reminder | 30 mins before | Patient | "β° Reminder: Appointment with Dr. {name} at {time}" |
| Queue Update | Real-time | All waiting | "π Queue Update: {position} people ahead of you" |
| Delay Notification | Doctor/Staff | Affected patients | "β³ Delay Alert: Dr. {name} is running {mins} minutes late" |
| Report Ready | Lab upload | Patient | "π Your test results are ready for download" |
| Prescription | Doctor | Patient | "π New prescription available from Dr. {name}" |
| Metric | Current State | Target Improvement |
|---|---|---|
| Average Wait Time | 3-8 hours | 15-30 minutes |
| Patient Satisfaction | 40% | 85%+ |
| Doctor Efficiency | 60% | 90%+ |
| Disease Transmission Risk | High | 70% reduction |
| Administrative Cost | 100% | 40% reduction |
| No-show Rate | 30% | 10% |
π₯ Building a Healthier Tomorrow, One Queue at a Time π₯
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