Inspiration

An Ambulance Diversion is a tactic used by Hospitals to prevent overcrowding of hospitals. If hospitals don’t have enough doctors or too many patients, they are allowed to turn away ambulance patients in critical care. Ambulance Diversions have turned away mothers and young children to hospitals much farther away, and when time is of the essence, lives can potentially be lost. That is why, in order to improve the quality of life for emergency patients by providing swift care, I decided to make Life Support.

What it does

Life Support allows paramedics to plug in information about the patient, such as type of accident, and filter searches to the best hospital choice which is not only nearby, but has the right specialists, enough supply, and acceptable amount of occupancy so that ambulance patients won’t be sent to another hospital after arriving. This drastically cuts the time for emergency trips in these situations and can save many lives. Hospitals would hypothetically plug in the data in the dataset for this information which my website filters for the best choice.

How we built it

I created a mock dataset filled with example hospitals of varying supply, specialists, occupancy, and more in order to show how the website works. The website is built with HTML, CSS, and Javascript, and the data for the database and filtering system is in python. I used the editor Atom for the user interface aspect and python for the backend of the code.

Challenges we ran into

Some challenges I ran into include combining the Javascript and Python elements in order to connect the database with the website. I attempted to connect the two using third-party apps, but I never completed the task. However, in the future, I will completely integrate the system. Moreover, another challenge was accessing the dataset in the cvs file through code.

Accomplishments that we're proud of

Fortunately, I ultimately succeeded in accessing the cvs file in the python code, which I am proud of. Moreover, I am happy that I did all the code by myself, as I usually work in groups. My independent work shows how much I have grown as a coder. Another coding accomplishment I am proud of is the user interface, as I often work on the backend of the code.

What we learned

I learned how to code with excel and accessing two datasets, and also how to create a user interface that is more than just a title and a paragraph. I also learned that I should use more compatible languages in the future to code with, as python and javascript don't really work together and I wasn't able to fully connect the two.

What's next for Life Support

In the future, I would like to add real hospitals into the dataset and connect with hospital staff who could update the information. Moreover, to make the dataset more realistic, I would add more categories for specialists and supplies such as oxygen tanks or blood bags. Also, an important thing to take into account is other possible emergency situations that need specific solutions, which would also be added to Life Support in the future. Finally, in the future, Life Support will have a fully integrated platform between the user interface and data sets.

Share this project:

Updates