VitalHealth

Patient view: live vitals, medications due and Vital alerts for the whole unit, sorted by severity.
Check a new medication against the patient's meds, conditions and labs. Every action is saved in the activity log.
Unit view for the charge nurse: every bed colored by risk, with the next time-critical task for each patient.
Admit a patient with conditions and allergies. Vital starts checking every medication against them right away.

Inspiration

We have a personal connection to a healthcare worker, who voiced their concern about the difficulty of comparing the affects medication over time across a portfolio of multiple patients with different conditions.

What it does

Vital Health is a medicinal database analyst and patient monitoring system. Medical staff are able to examine the patient's drug necessities and determine based off the type of projected symptoms how they would effect the patient's health status. Patient's vitals and BPI are tracked as live from the EKG Machine, a simulator. Logs and time are tracked as well from when the patient was given their last dose of medication and the following time they would need it again.

How we built it

The main purpose was to create a FastAPI server and WebSocket live feed to simulate vitals, new drug orders/doses, and bedside monitors. A variety of coding languages were used, including Python for the backend routing systems, as wells as React & TypeScript for building the UI and Frontend.

Challenges we ran into

Deploying and completing the backend of the system's program and understanding the database needs of nurses and doctors upon completing assessment of patients. Other challenges include putting confidential information into the database's program without jeopardizing the patients' private information.

Accomplishments that we're proud of

We are proud of creating an efficient system for medical professionals to evaluate the effects of drugs based on differing symptoms and health complications. We were also able to accomplish and finish the project in effective manner based on a well-organized team structure, even as we came along obstacles.

What we learned

We learned how to create a functional system for medical professionals to screen medical options for their patients without the possibility of jeopardizing their health.

What's next for VitalHealth

In the future we could implement a private AI function to simulate the effect of drugs on patient's diseases & symptoms to create possible cures.

Built With

Submitted to

ShellHacks 2026

Created by

I contributed to the project by working on the backend system program that helps show results and medical information about specific drugs and patients information.

abdul razaq olawale
I contributed to the planning process in finding necessary functions medical professionals would look for and need, as well as what features would make the medicinal mapping process easier to examine along with real time effects. During the post-coding portion, I worked through some possible issues and inefficiencies, lastly contributing to the submission and demo.

jnatalus2024
Sadjell Mamon
Wiwi Victoria