An AI-augmented clinical interface that ensures smooth and complete nurse shift handovers.
HOP-11 is a smart handoff solution designed for hospitals and nursing teams. It helps nurses transition patients more safely by combining AI-driven summarization, real-time updates, and intuitive patient dashboards. The focus is on minimizing errors, saving time, and empowering empathy in clinical communication.
Nurse shift changes are often rushed. Verbal summaries can be incomplete or inconsistent. HOP-11 solves this with:
- ✍️ AI-generated handoff summaries
- 🗣️ Voice input support
⚠️ Risk and alert flags- 💊 Medication tracking
- 📋 Smart patient overview
Built with healthcare empathy at its core.
| Layer | Technology |
|---|---|
| Frontend | Next.js, TypeScript |
| Styling | Tailwind CSS, ShadCN UI, Lucide Icons |
| State / UI | React hooks, useState, conditional UI |
| Backend (dev) | Next.js API routes, In-memory mock data |
| AI (planned) | NLP-based summarization, rule-based checker |
| Voice Input | Web Speech API or Whisper (planned) |
.
├── app/
│ ├── api/
│ │ └── patient-details/
│ ├── globals.css
│ ├── layout.tsx
│ └── page.tsx
├── backend/
│ ├── api/
│ ├── lib/
│ ├── models/
│ ├── scripts/
│ ├── Server.ts
│ └── Users.ts
├── components/
│ ├── ui/
│ │ ├── add-medication-modal.tsx
│ │ ├── add-patient-modal.tsx
│ │ ├── clock.tsx
│ │ ├── edit-patient-modal.tsx
│ │ ├── patient-details-ai.tsx
│ │ ├── patient-details-client.tsx
│ │ ├── theme-provider.tsx
│ │ ├── update-vitals-modal.tsx
│ │ └── warm-patient-card.tsx
├── hooks/
├── lib/
├── public/
│ └── speech-web-api-wrapper/
├── styles/
├── types/
├── .gitignore
├── .hintrc
├── components.json
├── next-env.d.ts
├── next.config.mjs
├── package-lock.json- ✅ Add/Edit/View patients
- ✅ Add/Mark/Hold/Discontinue medications
- ✅ AI Assistant Modal (UX in place)
- ✅ Patient vitals + risk display
- 🧠 Handoff summary generation (NLP-based)
- 🗣️ Voice input for notes/summaries (planned)
git clone https://github.com/your-username/hop-11-nurse-handoff
cd hop-11-nurse-handoffnpm installnpm run devVisit http://localhost:3000 to view the application.
| Module | AI/ML Usage Idea |
|---|---|
| 🧠 Summary Generator | Convert brief inputs to full handoff summaries |
| ✅ Checklist Validator | Ensure no critical info is missed (allergies, labs etc.) |
| 🗣️ Voice Input | Use Web Speech API or Whisper to convert voice to text |
| Use heuristics/ML to highlight critical patients |
- We're solving a real-world clinical problem: nurse shift handoff errors.
- Built with a modular frontend, plug-in AI logic, and secure local processing.
- Using AI for NLP summaries and automated completeness checks.
- Offline-first, no OpenAI dependency, designed with privacy-first principles.
- Focus on human-first workflows: intuitive, fast, and supportive for nurses.
| 🏁 Status | 🛠️ Milestone | 🔍 What Was Done |
|---|---|---|
| ✅ | 📚 Requirements & Research Completed | Finalized the real-world problem of nurse shift handoff. Outlined key AI/NLP goals and user workflow. |
| ✅ | 🧠 AI Bot Design Finalized | Designed context-aware logic for converting brief nurse inputs into complete shift summaries. |
| ✅ | 🧪 Patient Modal & Input Form Built | Developed a modal form with sections: Basic Info, Risk Assessment, Allergies, Status Flags, and Initial Notes using React + Tailwind. |
| ✅ | ⚙️ Backend Integration Done | Integrated frontend with backend using Express and MongoDB. APIs built for patient management. |
| ✅ | 🧬 Local NLP Engine Implemented | Built a basic NLP parser (no OpenAI) for summarizing patient data into structured handoff notes. |
| ✅ | 💬 Shift Summary Generation Enabled | AI generates full handoff summary from short user input, ensuring critical details are never missed. |
| ✅ | 🛡️ Cross-Validation Added | Ensured system checks for missing data like risk flags, allergies, and other key fields. |
| ✅ | 🎨 UI Polished & Made Accessible | Finalized a clean, responsive UI with improved contrast and clarity for nurses under shift pressure. |
| ✅ | 📦 Testing Completed | Validated edge cases, form validations, and summary generation with real and dummy patient inputs. |
| ✅ | 🔒 Secured & Deployment Ready | Backend endpoints secured, token-based access setup. Code deployed on Vercel + MongoDB Atlas. |
| ✅ | 🚀 Live Demo Hosted | Project is now live with complete handoff workflow available end-to-end. |
| ✅ | 📄 Documentation & Presentation Ready | README.md written, license added, and demo walkthrough/video completed. Ready for academic submission. |
Created by Ansh Tank and team
📧 Contact via GitHub
“Great handoffs save lives. We built HOP-11 to make sure nothing gets missed.”