Sign Up Page (Mobile number is used to send sms notification via twilio
Animation after login/signup
Nurse have to select a patient on an insulin drip
Enter the blood sugar level of that particular time
Gives the insulin titration of respective blood glucose readings
Gives the hourly reminder to Nurse to check the blood sugar level
Nurses often encounter a problem — insulin titration (or adjusting the flow of the IV fluid) is a complicated and manual procedure that takes many hours and may span multiple nurses. This pain point provided the inspiration for SugarGuardian.
What it does
A mobile app that simplifies the complexity of the insulin titration procedure, minimizing the risk of making dangerous and entirely preventable mistakes.
How we built it
We used React Native for the frontend. We used the FastAPI web framework and Python for the backend, then deployed the API service to Google Cloud's serverless Cloud Run service. We used MongoDB to store the nurse and patient data.
Challenges we ran into
One challenge we ran into was integration of all the parts of the application. In addition, many of our team members had relative inexperience with React Native so had to go through a learning curve.
Accomplishments that we're proud of
We are proud of building a usable that adds actual value in the healthcare industry. Personally, most of the projects I have worked on may be personal interest or be far-fetched and not that feasible for people to actually use. But this application solves a real problem, making nurses' lives easier and potentially saving lives by automating the complicated, laborious calculations that come with old school tables and flowcharts.
What we learned
We learned about the impact that technology can have on the health and safety of people.
What's next for SugarGuardians
Our plans for the future include adding further automation and IoT to automatically adjust the rate of titration in the IV after the PoC (point of care) finger prick. The nurse need not even have to input the BG (blood glucose) measurement in the app, further reducing the already reduced risk of human error.