We thought the drive-thru for MacDonalds was long, until we saw the line for Covid-19 Testing. That got us thinking, if the demand for healthcare services was so high, how are we able to meet this demand if new, more viral coronavirus strains emerge and what would happen to those that cannot afford it? Our project seeks to answer this question.
What it does
In-depth analysis with data scraped and called from US Census Data, World Bank, and CDC Data.
How we built it
The team primarily used Python for data analysis and data scraping
Challenges we ran into
Data was unstructured and sparse. We overcame this by scraping data from websites that generally is not available to download directly into a csv as well as comb for multiple sources of data to corroborate our findings and analysis.
Accomplishments that we're proud of
Answered many questions and were excited to be able to create a project that can have a meaningful impact to push for telemedicine to be more widely adopted.
What we learned
Data is sparse, but with enough focus and openness to analyze a myriad of data sources, we were able to produce meaningful insights.
What's next for Future of Healthcare: Telemedicine
We hope to continue this project and publish it to a blog post (i.e medium.com/datascience websites) to raise awareness for healthcare coverage differences and telemedicine's role to play as a possible solution.