Inspiration
Healthcare systems often report totals like funds received and patients treated, but they rarely show the connection between them. This lack of transparency makes it difficult to understand the real impact of funding. CareTrace was inspired by a simple question: can we track every rupee to the exact life it helps? The idea was to build a system where financial data directly connects to patient outcomes, making healthcare reporting more transparent, accountable, and aligned with SDG 3 (Good Health & Well-being).
What it does
CareTrace is a healthcare transparency dashboard that tracks funds, manages patient records, and links treatments directly to financial usage. It allows users to see how funds are received, where they are used, and how many patients benefit from them. The system maintains an audit trail, provides search functionality, and displays real-time analytics such as total funds, total usage, balance, and efficiency. At its core, it creates a clear flow from funds to usage to patient impact, making data meaningful and easy to understand.
How we built it
→Frontend: HTML, CSS, JavaScript →Backend: Python (Flask) →Database: SQLite →Example: from flask import Flask app = Flask(name) @app.route("/") def home(): return "HealTrace Running"
Challenges we ran into
One of the biggest challenges was debugging issues such as blank pages, missing variables, and session errors while working with Flask. Designing a proper data linkage system between patients and financial records was also complex, as it required maintaining consistency and avoiding duplication. Balancing frontend responsiveness with backend logic and ensuring the system remained simple yet meaningful was another key challenge throughout development.
Accomplishments that we're proud of
We built a system where people can clearly see how an NGO uses its funds to help real patients, making the entire process transparent and easy to understand. By allowing users to trace every rupee to actual impact, the platform creates accountability and openness. This not only shows how resources are used but also helps build trust between NGOs and the public, turning data into something meaningful and reliable rather than hidden or unclear.
What we learned
We learned that:
→Systems > features →Data relationships matter →Debugging is part of building
Example metric: →Utilization (%)=(Total Funds/Total Used)×100
→Inline version: Efficiency=Total Used/number of patients
What's next for CareTrace
The next step is to enhance CareTrace by adding role-based access for different users such as NGOs, hospitals, and administrators. We also plan to move to a cloud-based database for better scalability, implement real-time updates, and improve data visualization. Additional features like downloadable reports and full deployment for real-world usage will further strengthen the system and its impact.
Log in or sign up for Devpost to join the conversation.