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Problem : No quality health service been given to low income and homeless people
Target Population : Uninsured adults, less salaried people who can't afford an insurance, Average salaried people who have a namesake insurance who will not be able to face a huge load on their head if at all anything bad happens health related, HOMELESS people who cant afford an insurance
SOLUTION : A Mobile application that leverages predictive analytics and recommendation systems to personalize health care solutions to people in need.
PLATFORM : Data from all the organizations in MedLink is gathered, cleaned, transformed and engineered to a single server. This master data is going to serve as the back end for our mobile application.
REACH : We use the past data to get more historical trends to select a time of the year people fall sick and based on the geographical data which shows what areas there is a lot of homeless population, we decide the time of the year and place in the city where awareness programs need to be conducted. Apart from that we also planning on conducting medical camps in the AREAS with high homeless population and set up kiosks at places where most of the homeless people dwell like Gas stations, Bus stops and Railway subways. Mobile Application prompts the user to enter the profile details while signing up. Once the preliminary details are entered, a check with database is been done to see if there is any existing medical records for the person. If yes, the details are been shown in the app once the user logins. Else a new record is added to the database. The app lets the user enter more medical details about themselves in 'My health' tab. The home page lets the user enter symptoms that he/she is facing. Once that is entered, the data science magic with predictive analytics kicks in. Based upon the lifestyle, Family history, personal health conditions and current symptoms being faced, we use data science algorithms to predict possible health condition with a probability score. Based on this result, a recommendation system algorithm works behind the screens to get the personalized MedLink Provider considering the financial stability of the person, nearby healthcare provider, services offered by each healthcare provider, the recommendation is given. Also the route directions are given. Since our target audience most of times might not have a car for commute, we give BUS and Train directions as well