M

MediFast

A full-stack web application to provide complete healthcare assistance to people

M

MediFast

A full-stack web application to provide complete healthcare assistance to people

The problem MediFast solves

HealthCare is one of the most important services among all sectors but what if I tell you-
According to the latest statistics, approximately 40% of the people are unaware of good hospitals and medical facilities available even in their own locality.
Severe accidents and delay of treatment because of waiting for ambulances cause approximately 2 lakh death alone in India every year.
The current situation caused by COVID has given rise to a few precautions like- going out only when very much needed and avoiding public gatherings, maintaining social-distancing and much more.
It is definitely obvious that having a like-minded community of people to interact and discuss among themselves would help improve people perspective about medical conditions and ultimately would contribute to awareness and mutual help.

All the statistics have been referred from different surveys and studies conducted by reliable sources like Outlook, MIT, Indian Express and others.

What's the solution then, well-
What if we could build an application that would give people all the needed information regarding hospitals, their specializations, their contacts, allowing them to search and filter based on areas, kind of treatment and much more with a single click.
What if we could use machine learning and data analysis to early diagnose early symptoms that a person is having beforehand
What if we could build an integrated system of ambulance services and hospitals available just at a single tap on a mobile screen.
What if we could bring hospitals at the doorstep hosted on the web for application forms and appointments by the doctor.
What if we could build and support a like-minded community of people willing to help each other in need and also spread the word of medic awareness among themselves.

Future prospects of the project could be integrating machine learning models with the web to diagnose early symptoms and predict diseases. We would love to work further on it

Challenges we ran into

There were quite a few challenges I ran into but I enjoyed every bit of the learning -

The first challenge was working in a team of only 2. I have worked in teams of 4-5 to build projects earlier but this time I decided to do at least one with less help so that we get to do more ourselves. Limited time span and a lot of research required posed another challenge but we learnt to work under pressure.

Selection of tech-stack to work was also a dilemma. Initially, we thought to build it using MERN-stack but because of the heavy boilerplate involved, we decided to do it in the normal way.

Another challenge was finding dummy APIs to fetch data be it the hospital's data or the google maps API but with a bit of googling, we found it.

Perhaps, the most difficult yet interesting challenge was handling a lot of schemas in MongoDB while interacting with a single server. This was finally resolved by using schemas under schemas like using the ambulance data as a child and bound to the hospital data.

Bugs were always there but with a little bit of attention and dry-run, we were able to figure them out.

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