Please read the readme so that the potential of the project can be known
Our project addresses critical challenges in hospital management through innovative solutions that enhance efficiency, patient care, and inter-hospital coordination.
- Problem: Patient records are fragmented, making it difficult to access medical history seamlessly.
- Solution:
- Integration of ABHA ID:
- ABHA (Ayushman Bharat Health Account) ID is a unique identifier for medical records.
- Patient data, prescriptions, and test results are linked to their ABHA ID, enabling digitized and centralized medical history storage.
- Integration of ABHA ID:
- Problem: Long waiting times and disorganized queues lead to inefficiency and delayed patient care.
- Solution:
- Queue Management System:
- Patients can check-in via our portal for priority appointments or walk-in and register at the reception.
- Patients are classified into high or low priority to ensure urgent cases are attended to first.
- Streamlined queueing reduces waiting times and prevents overcrowding.
- Queue Management System:
- Problem: Ineffective communication between hospital departments and no system for inter-hospital data sharing.
- Solution:
- Intra-Hospital Coordination:
- Doctors can input prescriptions into the system, linked to the patient's ABHA ID.
- Patients can access their medications at the pharmacy using their ABHA ID.
- Lab tests can be ordered digitally, and results are accessible to doctors via the ABHA ID.
- Inter-Hospital Coordination:
- Enables seamless transfer of patient records between hospitals within a city for better continuity of care.
- Intra-Hospital Coordination:
- Problem: Overworked staff and under-optimized scheduling lead to inefficiency and poor patient experience.
- Solution:
- Predictive Resource Allocation:
- Use AI-based models to predict patient flow in OPDs based on factors like weather and day of the week.
- Implement a formula: Patients per Doctor per Hour (PPHD) to guide optimal doctor allocation.
- Reduces staff burnout and ensures appropriate resource availability.
- Predictive Resource Allocation:
- Problem: The HMIS developed by TCS failed due to centralized databases leading to slow data retrieval and time-consuming processes.
- Solution:
- Decentralized Database Architecture:
- Each hospital has its own dedicated database, enhancing data retrieval speed and system scalability.
- Improves computational efficiency compared to a centralized database system.
- Decentralized Database Architecture:
- Frontend: React.js,shadcn,accertinity
- Backend: Express.js, Django
- Database: PostgreSQL.
- AI/ML: Tabnet , blueBERT, XGBoost, Logistic Regression
- Modernized Approach: Solving outdated HMIS inefficiencies.
- Scalable Solutions: Tailored database and predictive analytics for better hospital management.
- Patient-Centric Design: Prioritizing patient convenience and care.