Applying to Track 2 - Reducing Inefficiencies in Health Care

Subtrack 1- Streamline redundant processes for patients at the pharmacy and/or clinic

Inspiration

In busy retail pharmacies, pharmacists are busy answering question from patients and doctors phone calls and filling prescriptions. Many times, people want to talk to the pharmacists to see if they need to take an OTC for their sickness. Sometimes they know they want to take a medication for headache, but there are many OTC for headache, and they are unsure which one to take. However, due to long wait time, patients decide to pick for themselves, which might not be the best medication or best safety decision because some symptoms require urgent medical attention.

What it does

Our app Ephicient allows patient to fill out a form regarding their patient information and issues/symptoms. This way, when they come in for a consultation for an OTC recommendation. Pharmacist can be more efficient in providing help. It is more efficient because pharmacist has some information already to help the patient, so the pharmacist doesn't have to spend time gathering basic information like age, gender, pregnancy, current medications, etc.

How we built it

The frontend of the application was built with ReactJS. The backend API was built with flask.

Challenges we ran into

Managing the queues of the requests were difficult. The idea was that different pharmacists from different location will help with the request orders.

Accomplishments that we're proud of

We were able to build a full stack application (front end and back end) where patients can fill out their information/issues and pops up in the queue for pharmacist to evaluate.

What we learned

Ideas change very fast. We have to be flexible to add, update and delete features.

What's next for Ephicient

If we had more time, we would have the decisions for every request without contact information go into a pooled database for federated learning for healthcare that can potentially be fed as training data for machine learning models.

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