X-Legion-Coders – DrComm – Health

Project is made under Scaler HackX hackathon

Problem Statement

Improve medical and emergency communication

  • So the Doctor reaches anytime anywhere!
  • We face issues that we are not able to reach the doctor many times due to lack of infrastructure
  • Either the doctor is not available or the patient is not able to reach the doctor on time.

Tech Stacks

ℹ️ Project information

  • Our Theme : Health
  1. Project Name: DrComm

  2. Short Project Description: Communication Network between Patient & Doctor

  3. Team Name: X-Legion-Coders

  4. Team Members: Ayush Kejariwal, Rohan Verma, Avinaba Ray, Siddhant Jaiswal

  5. Demo Link: https://drive.google.com/file/d/1usTHHo4_Kh95TyHYEVryaB_fiyx6jKXV/view?usp=drivesdk

  6. Presentation Link: https://docs.google.com/presentation/d/1oIgvbbBP5Tden4r1teJWyYXwoMtWif0U/edit?usp=sharing&ouid=100124382136325516910&rtpof=true&sd=true

? Our Pitch

Our application is the one stop solution for all the needs
We have a dedicated team of doctors who are available to cater to the patients’ needs on demand
The patient app will show the status of doctors and their location
Are they available for a home visit or a clinic visit
The doctors will have the option to choose their preferred time slot and can do offline when they need some time for their family.

? Any other specific thing you want to highlight?

  • This idea is completely feasible as of now because the technology stack used is cross platform allowing reach for a larger number of audience

  • The backend can be scaled up infinitely to match the scale of audience required to carter using the industry standard technologies like Kubernetes. The same is true for the no-sql database mongodb that can be scaled horizontally using concepts of sharding.

  • Some of our Future Aspects

    • Add patient profiling for easy assessment of patient by the doctors.
    • Add an SOS feature to notification panel for quick emergency response from nearby doctors.
    • Add sensor profiling to auto detect accidents and auto emergency response.


View Github