Joseph’s Grandma often goes to the hospital every two months. There is often a long process and lots of confusion to understand the status of her health in between the visits. He witnessed first-hand the inefficiency of the current communication between the Healthcare facility and patient and was motivated to change it.

What it does

Ai texting service for patients to easily access customized and immediate health information, resources and referrals, and providers to automate the follow-up and scheduling process to lower the patient-provider barrier. We allow for individuals to text our number if they have symptoms or are generally not feeling well. The individuals will then interact with our Ai bot to answer a series of questions to better gauge their level of health status. The individuals will have the option to be connected to doctors who accept medicaid or a local healthcare facilities and the option to have an overview report. We send a check-in message later to the patient.

How we built it

We used Python and Flask to build a text based application. Functionalities of texting is developed with Twilio and our backend database is configured with AWS Lambda.

Challenges we ran into

One of the biggest challenges we came across was not being able to find an api that provides data for the information of local doctors. We solved this by building our own web scraper to obtain this information.

Accomplishments that we're proud of

We are proud of ourselves for how much we have accomplished despite the short time frame and the limited knowledge we have about the healthcare system.

What we learned

Going into the Hackathon, we had little understanding of how the healthcare system currently operates. We extensively researched and reached out to a couple of our mentors at the Hackathon who are currently working to solve similar issues in the healthcare system. Thanks to Colby Takeda, Justin Puckett, and Hui Cheng, we learned more about the health system barriers, important medical terms, and the day-to-day processes. In addition, we learned how to better focus and market our product and build a business strategy in a 3-minute pitch.

What's next for Carey

In our next steps for Carey, we aim to develop our product to integrate features such as the option of photo symptom identification, and to officially standardize our data to fit the healthcare standards. Further, we hope to pilot our product with smaller clinics and with demographics who may find it harder to access health care at the current status quo.

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