Medical care remains one of the most expensive and elusive markets for patients despite the prevalence of information online. Prices for the same treatment can vary by 200% per hospital. Yet only 20% of Americans compare these prices before heading to a hospital.
With AHA, patients are one click away from taking control of their health.
What we did
Challenges we ran into
- Finding, cleaning and preprocessing available public data (data wrangling);
- Extracting data corresponding to 220 hospitals in the California;
- Sorting output in ascending order according to price.
What we learned
- Debugging pandas dataframe issues;
- Handling different files in Python;
- Started learning Flask Microframework and tools needed for full-stack development.
What's next for AHA:
- Adding insurance as a variable to which the final displayed price will be adjusted: result out-of-pocket prices;
- Displaying the price ranges in the form of an interactive histogram;
- Adding more data to increase the market from Bay Area to California and other states in the U.S.