Anidra Healthcare Project – Enhancing Data Visualization for Healthcare Vital Signs Monitoring
Project Overview
The Anidra Healthcare Project is an innovative solution designed to improve real-time patient monitoring by integrating a digital ADDS (Adult Deterioration Detection System) Chart into Anidra’s existing platform. The project transforms traditional paper-based monitoring into an interactive digital solution, enhancing healthcare providers’ ability to detect early warning signs of patient deterioration.
Key Features & Technologies
✅ Digital ADDS Chart – A real-time, color-coded visualization for tracking patient vitals (heart rate, respiration, temperature, oxygen saturation, blood pressure).
✅ MEWS (Modified Early Warning Score) Pattern Chart – Detects early warning signs for critical patient conditions.
✅ Manual Data Entry – Enables healthcare providers to input consciousness levels, pain levels, and urine output, which integrates dynamically with the ADDS chart.
✅ Dynamic Chart Updates – The system updates instantly when new data is entered or received from monitoring devices.
✅ Data Export & Reporting – Enables real-time data review, trend analysis, and patient record generation.
✅ Real-Time Alerts & Risk Indicators – Color-coded risk levels for immediate action on critical cases.
✅ Interactive UI/UX – Designed with Figma, ensuring a familiar and efficient interface for healthcare professionals.
Tech Stack
- Frontend: React.js (with TypeScript)
- Backend: Node.js, Express.js
- Database: MySQL
- APIs & Libraries: Recharts, Axios, Firebase, D3.js
- Tools Used: GitHub, Figma
Development & Testing
- Followed the Agile Development Process with three iterative sprints, incorporating continuous feedback from healthcare professionals.
- Conducted unit testing, API validation, and real-time data simulation to ensure system accuracy.
- Used React’s state management and data visualization tools to optimize real-time patient data tracking.
Achievements
✅ Successfully digitized the ADDS chart, improving accessibility and usability.
✅ Developed a MEWS-based early detection system, reducing response time to critical conditions.
✅ Integrated real-time manual data entry, enhancing patient monitoring beyond automated device tracking.
✅ Optimized data transmission and visualization, ensuring seamless interaction for healthcare providers.
✅ Created detailed user and technical manuals for smooth deployment and future scalability.