Inspiration
Congestive Heart Failure (CHF) affects millions globally, leading to frequent hospital readmissions that are often preventable. We were inspired to create a solution that empowers patients and healthcare providers to detect early warning signs of CHF deterioration. By leveraging technology, we aim to reduce hospital readmissions, lower healthcare costs, and improve the quality of life for patients.
What It Does
Our CHF Preventative Monitoring and Early Intervention System is a digital platform that monitors key health indicators of CHF patients. Patients regularly input data such as heart rate, weight, blood pressure, and symptoms through a user-friendly survey system. An AI-powered model analyzes this data to generate a severity score, categorizing patients into risk levels. Healthcare providers access a portal that sorts patients based on these scores, allowing for prioritized care. The platform also offers data visualization tools to track health trends over time, facilitating early detection and intervention.
How We Built It
We developed a custom neural network using PyTorch to analyze patient data and assess severity levels. The backend is supported by MongoDB for secure and scalable data storage. The provider portal was designed with user experience in mind, featuring risk-level sorting and intuitive data visualization through charts and graphs. We emphasized data security and compliance with healthcare regulations throughout the development process.
Challenges We Ran Into
One of the main challenges was ensuring the accuracy of the AI model in assessing patient severity based on variable and sometimes incomplete data inputs. Balancing data privacy with the need for actionable insights required meticulous attention to healthcare compliance standards like HIPAA. Integrating the AI model with the provider portal in a meaningful way also presented technical hurdles. Encouraging consistent patient engagement for regular data input was another significant challenge.
Accomplishments That We're Proud Of
We're proud to have created a functional prototype that integrates patient data input, AI analysis, and provider tools within a secure platform. Successfully developing an AI model that provides actionable severity assessments is a significant achievement. Additionally, addressing complex data privacy issues and ensuring regulatory compliance are accomplishments that underscore the robustness of our solution.
What We Learned
This project taught us the complexities of applying AI in healthcare, especially concerning data security and patient privacy. We learned the importance of user-centered design in creating tools for both patients and providers. The experience highlighted the challenges of interdisciplinary collaboration and the need for effective communication across different areas of expertise.
What's Next for Healthy Jackets
Future developments include integrating wearable IoT devices for real-time monitoring of vital signs, enhancing the system's ability to detect sudden changes and alert providers promptly. We plan to implement a regulated notification system to remind patients to input data and inform providers of critical updates. Full integration with hospital systems and the development of a mobile application featuring direct communication between patients and providers are also on the roadmap.
Built With
- flask
- javascript
- mongodb
- next.js
- openai
- python
- react
- tailwind
- typeform
- typescript
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