The Story

This project began as a research initiative titled "AI x Healthcare," exploring how artificial intelligence could solve critical healthcare challenges. My teammate, who originated the idea, highlighted a severe issue in Rwanda: hospital congestion.

The problem stems from an uneven distribution of medical workers, with most concentrated in urban areas. This forces patients from rural regions to travel to popular town hospitals, leading to overcrowding and long wait times, while rural facilities remain underutilized.

The Problem

Patients often flock to well-known hospitals regardless of the severity of their condition, causing massive bottlenecks. A patient might wait 6 hours just to see a doctor for a minor issue that could have been treated at home or at a less crowded local clinic.

The Solution: MedFlow

To address this, we conceptualized MedFlow, a system designed to streamline patient flow and reduce hospital workload.

How it works:

• Digital Triage: Users log in with their National ID and answer a series of diagnosis questions.
• AI Analysis: The system analyzes the symptoms to score the severity of the situation.
• Smart Recommendations:
  • Critical/Serious: The user is referred to the nearest appropriate hospital, and an appointment is automatically scheduled with their analysis attached.
  • Non-Critical: The app recommends home remedies, saving the patient a trip and reducing hospital load.

Implementation

The backend is designed to serve as a common interface for all hospitals, allowing for seamless integration. This ensures that patient data and appointments can be routed to the correct facility, balancing the load across the healthcare network.