Managing multiple prescription medications can be daunting, particularly for the elderly community or individuals with complex medication regimens. With more than 80 percent of older patients relying on at least one prescription medication daily and over 50 percent juggling five or more medications or supplements, an efficient and reliable tracking system becomes evident. Failing to take medications correctly or in the wrong amounts can have hazardous consequences.

At our core, we are driven by a deep commitment to our community's well-being, so we took on the challenge of addressing the medication management issue among the elderly population. We recognized the significant impact medication-related challenges can have on the health and quality of life of individuals in our community.

By creating a solution specifically designed for our community, we aim to empower individuals with the tools to manage their medications and improve their overall health outcomes effectively. Our goal is to provide a user-friendly and feature-rich platform that addresses the unique needs and challenges faced by seniors and those with complex medication regimens.

What it does

Our comprehensive design revolves around three key components to ensure a seamless and user-friendly medication management experience.

Website - It is an interactive platform for users to engage with our system. Users can conveniently communicate with the chatbot via WhatsApp, allowing for easy access and familiar communication channels. The chatbot provides personalized medication reminders, allowing users to receive timely notifications and stay on track with their medication schedules. This feature ensures that users never miss a dose and promotes medication adherence.

Detecting text -users can quickly and securely upload their prescription documents. The website interface is intuitive, making it easy for users to navigate and submit their prescriptions. Once uploaded, our system utilizes Google's Vision API to detect and extract the text from the prescription documents. This text is processed and stored in our SQLite database, ensuring accurate and organized medication information.

WhatsApp chatbot - Based on the extracted information, such as medication names, dosages, and schedules, the chatbot sends reminders to users at the appropriate times. This proactive approach ensures that users are constantly informed about their medication regimen and minimizes the risk of missed doses or incorrect administration.

How we built it

We used HTML, CSS, JavaScript, and Bootstrap for the front end. We utilized Flask for the backend and the chatbot, SQLite for CRUD, Auth0 for authentication, Google's Vision API for detecting text, and Twilio to build the Bot.

Note: We could not use WhatsApp buttons since it is only available for business numbers, but we will indeed implement that feature when the idea is implemented at a large scale.

Challenges we ran into

  • I wanted to create a project with real societal influence and wanted to deliver a genuine product, even if it was a bit bare bones
  • CSS and website design

To get a head start, I had to scour the internet for information, and things weren't easy because I couldn't add the Vision API. I had trouble saving and sending the prescription image to the Vision API.

Accomplishments that we're proud of

I am pleased to Combine a user-friendly interface with the capabilities of Google's Vision API, making our solution accessible and beneficial to a wide range of users. Individuals can easily manage their medications with confidence and peace of mind whether they are technologically inclined or not.

Furthermore, integrating Google's Vision API into our solution was a significant milestone. Although it was my first time utilizing this API, I thoroughly researched and familiarized myself with its capabilities. This enabled us to leverage the power of optical character recognition (OCR) and accurately extract handwritten text from prescription documents. Incorporating Google's Vision API enhances the precision and reliability of our system, ensuring the extracted information is captured correctly.

What we learned

I learned a lot during the weekend. I found out —

  • Flask can construct web apps that are quick, scalable, and easy to use.
  • How using Flask helps us to build backends faster.
  • Frontend development and design
  • Using google cloud
  • Uploading and retrieving images from the database Finally, I learned a lot from HackLah throughout the weekend.

What's next for MedEase

Future ambitions for MedEase include developing a more personalized approach to data analysis. By leveraging NLP techniques, we aim to extract valuable insights from the data collected, enabling us to offer tailored recommendations and guidance to individual users. This personalized approach will consider medical history, allergies, and specific medication requirements, providing users with customized reminders and suggestions to optimize their medication routines.

Additionally, we plan to implement image recognition capabilities to allow users to retrieve information about their medications directly from images. By leveraging image recognition technology, users can capture a picture of their prescription or its packaging. MedEase will analyze it to provide relevant details such as dosage instructions, side effects, and potential drug interactions. This feature will empower users with quick and convenient access to critical information, ensuring they comprehensively understand their medications.

Share this project: