Health Dome
AI-powered hub for pandemic preparedness and response, optimising patient flow, prioritising critical cases during pandemics, and managing resources.
Created on 19th January 2025
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Health Dome
AI-powered hub for pandemic preparedness and response, optimising patient flow, prioritising critical cases during pandemics, and managing resources.
The problem Health Dome solves
- Optimizes Patient Flow: Optimizes patient flow, reducing hospital overcrowding and directing non- critical cases to telemedicine consultations , mohalla clinics or isolation centers, preventing strain on healthcare systems.
- Centralized Data Access: Integrates hospitals and clinics city-wide, improving coordination and resource allocation.
- Real-Time Decision Making: AI-based symptom analysis speeds up triage and improves response efficiency.
- AI-Driven Triage: LLAMA 3.1 AI collects symptoms via chatbots. Automated severity classification.(Prioritization of urgent cases)
- Real-Time Bed & Admission Management: Real-time visibility of beds, ventilators, and facilities for better patient
admissions. NIC integration allows seamless patient data sharing across hospitals, ensure patients are directed to the most appropriate care during surges. - Inventory & Medicine Management: Tracks critical supplies like vaccines, antiviral medications, PPE, and
oxygen supplies. Ensures availability of pandemic-response essentials across hospitals. - The proposed AI-driven healthcare disaster management system utilises LLAMA 3.1 to analyse patient symptoms and classify the severity of healthcare emergencies, directing patients to the most appropriate care—whether it's isolation centres, hospitals, or remote treatment options based on real-time data. A heuristic algorithm optimizes decision-making, minimising time complexity and ensuring rapid triage and efficient allocation of critical resources such as beds, medical supplies and other facilities. By integrating multiple healthcare touch points and leveraging continuous feedback loops, the system refines patient routing dynamically, improving resource allocation, reducing overcrowding, and enhancing the overall efficiency of healthcare delivery during healthcare disasters.
Challenges I ran into
- Private Hospital Resistance: Concerns over data sharing and competitive interests.
- Data Privacy: Handling sensitive health data securely, adhering to legal requirements.
- Interoperability Issues: Disparate systems across hospitals creating data silos.
- GPU Intensive
Technologies used
Discussion
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