A prescription written by a physician vs it's meaning in natural language
An overview of the RxEasy web application
Features of the RxEasy web application for physicians and mobile-optimized application for patients
RxEasy web application interface (dashboard)
RxEasy web application interface (text shortcut interface)
RxEasy mobile-optimized web application interface
A huge issue in healthcare nowadays is the weakened relationship between patients and physicians due to the lack of communication technologies and overload on the system; this was our focus for this hack
Prescriptions written by doctors for retrieving medication is often not intuitive to decode for the average person as they often contain shorthand abbreviations derived from Latin. While they are mainly written an interpreted by pharmacists who receive the prescriptions, this extra step in the workflow raises areas susceptible to error. We decided to work on a solution which aims to increase the transparency for patients receiving prescriptions to strengthen patient-doctor relationships, while boosting productivity in physicians' workflows.
What it does
RxEasy is a web application to help doctors manage and communicate their patients’ prescriptions. It uses keyboard shortcuts for doctors to generate natural language prescriptions using the shorthand they are already used to. The dashboard view allows them to manage their productivity at a glance. A mobile view is also available for patients to see their prescription information in a centralized location.
How we built it
We used the Hypercare API and Python web scraping for the key features of the app. The Hypercare API was used to create a stronger, more clearer connection between doctor and patient. Web scraping was used to help streamline prescription writing for the doctor’s side.
The prototypes for the mobile and desktop app representing the patient’s interface and doctor’s interface, respectively, was built using Figma.
Challenges we ran into
One of the preliminary challenges we faced was putting our idea into a set of use cases to make a viable product. We knew what we wanted to do and how to do it, but finding the right users and stakeholders in the context of this application was a new experience for us.
Prior to this hackathon, we never used Hypercare’s API, making it relatively unfamiliar to work with, especially with its GraphQL configurations. Additionally, despite past experience with Postman, this hackathon brought a few new challenges particularly with authentication and admin access when testing with the Postman app. Additionally, VueJS was a new technology for majority of our team mates.
Accomplishments that we're proud of
We’re particularly proud of the prototype and its design complete with its animations. This took quite a while and is an app we see actually being used by our audience base.
Additionally, the text replacement as brought about by the web scraping tools was a great accomplishment with little to no overhead. This helped our program run more efficiently and bring about new use cases for our audience.
What we learned
We learned how to use VueJS and its uses within both the backend and front end of applications. To add on, our unfamiliarity with Hypercare’s API encouraged us to learn more about authorization and admin access when dealing with APIs and how to navigate them.
What's next for RxEasy
NLP would be incredibly useful with reading prescriptions for users as these are not typically written in language that is easy to decipher from the get-go. Additionally, the application can be further enhanced by integrating AI to detect when a series of logged systems may indicate an adverse reaction to a drug, notifying the patient and doctor.
One thing we would like to include in a later version of this application is a built in messaging system between doctor and patient, fully compliant with PHIPAA and PIPEDA policies. This would further aid in reducing the communication gap between the two parties.