CapsulePacker: Blister Pack Management Software

Datastax Astra Keyspace
Medication Table in Datastax Astra's cloud database

Inspiration

After volunteering at a pharmacy, I realized that many things could be made more efficient with the usage of computers.

Due to recent restrctive COVID-19 regulations, it is usually unsafe for people to visit commercial stores, including pharmacies. In addition, the majority of folks in need of medication are usually those in rather dire health situations. Therefore it would be even more hazardous for them to risk getting COVID-19.

My previous experiences working at a pharmacy has inspired me to create this software that helps manage blister packs.

Blister packs are daily bubble packages that give patients information on when to consume the medication. While this was originally intended to prevent medical non-adherence, I believe that it works perfectly in accordance with the increase in delivery requests that pharmacies have been receiving lately.

Managing blister packs is often very tedious, especially at smaller retail pharmacies. I usually had to flip through a huge binder that is several inches thick. It also proved to be a tremendous waste of paper.

Despite the work it takes to manage blister packs, they undoubtedly offer more convenience and act as a great fail-safe measure against medical non-compliance, especially for senior citizens who are sometimes forgetful.

Wouldn't it be great if we had a blister pack management software . . . ?

What it does

CapsulePacker is a software that I designed for small local retail pharmacists that can't justify spending thousands of $$$ on machines and software to increase their work efficiency.

It helps to handle the huge burden of delivery orders that COVID-19 put upon our neighbourhood pharmacists.

You can store the patient's data regarding a certain time period (usually 4-weeks) worth of medications in a database. From there, we have a cloud database containing all common medications including DIN numbers for verification purposes. Pharmacists can plan out the medication of blister packs depending on what time during the day the medicine should be administered.

This software, CapsulePacker, can definitely take care of the dull and mundane task of managing blister packs for delivery during COVID-19.

How I built it

I chose Python to be the foundation from which CapsulePacker is built upon.

One of the main concerns was development time. Since Python is such a high-level programming language with plenty of libraries for me to use, it was an obvious choice for me. Plus, I had the opportunity to use PySide2 as the GUI framework, which is one of the best GUI building frameworks for desktop applications.

As for the database, I went with DataStax Astra's cloud database. Previously, I only had experience using SQLite, which is a serverless database. Since hackathons are all about learning new technology, I decided to take a peek at what DataStax Astra had to offer.

In summary, CapsulePacker is just a simple program that communicates between the application and a cloud database to add/edit/display information about patients and store a large quantity of prescription medication information.

Challenges I ran into

A big challenge was storing the patient's prescription information into a database. I had planned this information to be stored into a list of dictionaries, but then I couldn't find a way to insert that into the databse. Due to time constraints and lack of sleep, I scrapped the idea of reading the documentation properly and jury-rigged a solution. In the end, I replaced the dictionary with a string that had a delimiter seperating each value.

Accomplishments that I'm proud of

I'm really proud that I managed to finish creating this program within the time limit of the hackathon. Honestly, I'm extremely happy with the results considering the fact that I'm a biochemistry major, who is working solo, and has picked up programming just a few months ago.

What I learned

I learned alot from the workshops about various different field within the scope of computer science. One particular area that caught my attention is machine learning. Since I'm mainly studying biology this year, I felt a sense of curiosity when listening to the panelists talk about creating neural networks with computers.

What's next for CapsulePacker

The next steps for this software is to design a better GUI. The current one is quite ugly.

Future plans:

Data analysis on whether or no certain types of medication works for treating certain medical conditions
Data analysis on how much stock of certain prescription drugs get used. Which drugs are prescribed at a higher frequency. How much quantity to order per month.
Online ordering system connected to pharmacists and family doctors.