Wait times are annoying for everybody and our group wanted to do something about it and come up with a unique way of doing so at the same time. Hospitals and Walk In clinics have wait times that can be over 2-3 hours. A system that would combat this would prove extremely effective as a it would help patients reduce their wait and help medical practitioners manage their clinics efficiently. Several clinics are open hours after their legal closing hours due to patient build up and wait times, our system will significantly reduce this and improve the overall efficiency of applying for a medical appointment.

What it does

With a simple picture of your health card, our OCS algorithm retrieves all your medical information after successfully matching the information on your card with the database containing all electronic medical records. Our IOS application has a user login system and a built in image scanner that will send all collected data to a database. The backend compares information and sets up an appointment with the clinic chosen and notifies the admin and the attending doctor of your entire medical history prior to the meeting, all from the tap of your health card.

How I built it

  • Front End: React Native and Expo
  • Database: Google Firebase/MongoDB
  • OCR: Tesseract
  • Location Services for Nearby Clinic Choices: Google Maps API

Challenges I ran into

Actually receiving and processing image data through expo and react native was extremely difficult. There was not too much documentation that helped with the actual application of this, instead the use of example programs helped design this system. Accessing multiple medical clinics near to you was fairly difficult as it required constant filtering of outlier clinics and pharmacies. The database was not easy to set up either as it needed to communicate with several API's to receive data and constantly update in real time. OCR was brand new to the entire team, however tesseract was fair simple to use and worked out well.

Accomplishments that I'm proud of

  • Got the OCR system with an integrated camera working
  • An amazing database that was designed with the intention of containing immense data points
  • A beautiful, simple and ideal front end design for consumer use
  • Dropdown selection integrated with google maps API to display only the patients nearest clinics
  • Tesseract OCR Image Analysis and IOS app implementation

What I learned

  • How important it is to divide the workload amongst a team. This ensured the project would get to a somewhat complete stage.
  • PATIENCE! Your code almost never works the first time and this was definitely the case with this project. The team took their time worked persistently and got everything to compile and build succssfully.

What's next for Pulse

  • App modifications on UI and adding new widgets or features
  • Potentially adding in a chatbot that uses machine learning to help treat patients waiting for longer periods of time or who are situated in very distant locations.
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