Due to the rapidly evolving COVID-19 crisis, it is becoming increasingly evident that there is a lack of a centralized system that allows for fast and efficient communication between local hospitals and patients, resulting in an uncoordinated relief effort. Some hospitals are receiving a disproportionate amount of patients while other hospitals may have additional resources to spare. As a result, certain hospitals have much longer wait times when anticipating patients compared to others. Keeping this issue in mind, we aimed to create a web app which allows patients access to the information as to which nearby hospital/clinic will be able to provide timely aid.
What it does
This web app serves one primary purpose. For the public, it displays the wait times of nearby hospitals, clinics, and other medical facilities. It also lists the capacity of hospitals to take patients (i.e. hospitals registering low capacities will have fewer patients choosing to go to that hospital over another one). You simply type your address into the search bar on the homepage, and then you see the wait and drive time for hospitals in your area. On the admin side, it is possible to add hospitals and input data on their wait times and remaining capacities. This project presents a scalable proof of concept in which hospitals can add their information such that it is viewable by the public. With the integration of google maps and a more scalable database, alongside full hospital reporting, we hope to grow this project into something field-deployable with full functionality.
How we built it
Like many projects, our project started out as an idea. We noted many people who would normally go to the hospital for illness or injury became more reluctant to do so. This was often because they were unsure of how long the wait would be and would not want to risk virus infection should they come into contact with a COVID patient. Thus, we decided to build a website with one goal in mind: to tell patients how long their anticipated wait would be so they can get care as fast as possible.
To build it, first we gained a foundational knowledge of both Python and Django through a variety of tutorials. After gaining some experience we began building using our understanding of Python and Django. We used tutorials to figure out how to configure a short term database and set it up for use. We relied a lot on what Django had already made available as part of their framework so we wouldn’t have to ‘reinvent the wheel’ each time we went through our code and scaled up from what we had rapidly. To create our proof of concept, we modelled what a user may see once they put an address into the search bar.
Challenges we ran into
The biggest challenge our team ran into was the learning curve. We are a team composed primarily of beginners with little to no prior programming experience. Navigating Python and learning Django from scratch was tough, but as a team, we rose to the challenge to create a product we can say that we are proud of and with development can help others.
Accomplishments that we are proud of
Correlating to the challenges we faced as a team, overcoming the steep learning curve was our biggest challenge. However, within a relatively short time span, we were successful in attaining the skills necessary to develop this project. As a result, we were able to convert our idea into a working web application which has the potential to help coordinate the relief effort.
What we learned
The team learned a lot from this project. For most of us, we had very limited knowledge on the usage of Python and Django, and its application for real-word projects. Due to the very short time span to complete this project, we had to learn to communicate efficiently with all the team members: this includes distributing work modules for each member in an equal manner, as well as assigning tasks based on individual skill sets. For example, one of the team members was more experienced with the Django framework than others, so they took the lead on software development.
Initially, we learned to install Django inside of a virtual environment and then learned how to connect that framework with the text editor that was utilized. After that, following tutorials and official documentation for both Python and Django, we created a basic web page operating on a localhost server. Following that, we were required to learn how to add certain features which we wanted to incorporate including: a search bar, a sign-in/sign up button, and the creation of model hospital data. Throughout the creation of this project, we learned through tutorials on various websites and through video, often facing difficulties during a specific task. This provided us with the greatest takeaway, which was problem-solving.
What's next for Hospital Resource Coordination and Patient Insight Project
First, we hope to integrate google maps API to give accurate drive times. Secondly, we also hope to give each hospital a main admin login which is able to give doctors and registrars the power to edit data in real-time for patients to view. Lastly, we aim to replace our current sqlite database with a more scalable database for utilization.
Our plan is also to create a medium for hospitals to communicate what resources are in shortage with each other. This would help to clarify which hospitals have excess capacity that can be taken advantage of. This would also be extrapolated to key resources like ventilators or negative pressure rooms. However, this data would not be made accessible to the public. Next, our objective is to integrate our resources with common hospital database formats. We strive to make the website as easy to use and be as convenient as possible for health workers in the field. By making it easy to sync a hospital database data into our resource, it becomes much easier to update information.
Try It out
django, python, sqlite