RL Solutions approached us with ways to improve healthcare through tackling the issues surrounding patient adherence. After some research, we realized one of the largest reasons as to why patients don't adhere to long-term care plans is due to the complicated medication taking process. We decided to solve this problem using software.

What it does

This program takes input information from healthcare providers, including doctors and pharmacists, regarding drug plans, and uploads them to a web application containing a patient profile. The patient can then access their profile on the web application, where all the information regarding their medication regimen is available, including dosage and frequency, as well as reminders to adhere to that regimen. The database can be updated by the healthcare professional whenever they desire through a shared registration code between them and their patient.

How we built it

We made use of Python and HTML in order to do the backend and frontend programming, respectively. With Python, we designed and laid out the algorithms which allowed the doctor to input and update the patient's drug plan. This involved mainly decision-making structures and function definitions. With HTML, we were able to design the patient profile and reminder/calendar system, this involved use of the W3 library of templates which helped tremendously with the aesthetic aspects of the webpage design without having to build everything up from scratch. However, we still had to take into account how to fit different templates together without causing an obvious clash in design.

Challenges we ran into

The main challenge was combining the front and backend into one program. This involved the use of flask, which none of our team had thorough knowledge of. Future prospects involve learning flask in order to embed the Python code into the HTML webpage.

Accomplishments that we're proud of

We are proud of our ability to refine and make the code more efficient. In previous projects we often made use of long, repetitive blocks of code. However, this time, through the use of more intermediate level coding techniques, such as function definition, we were able to condense the code into only the necessary elements.

What we learned

We learned that within time constraints, it is to our best benefit to use coding practices which we are familiar with. For example we tried using PHP, but soon abandoned it due to our inability to understand it.

What's next for Plan+

We plan to combine the front and backend programming as well as further develop the regimen as well as the SQL data frame. We also seek to add other lifestyle related regimens, such as diet and exercise routines, hoping to speak to health care professionals who

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