Feb 1, 2026

CriticalFirst

#healthcare #triage #queue-management #firebase #nextjs #healthtech #real-time #hackathon #hacknagpur2.0

Project Overview

CriticalFirst is a scalable, Firebase-powered patient queue and triage optimization system designed to manage high patient inflow in clinics and hospitals while ensuring accurate prioritization of critical cases.

The system leverages token-based queueing, rule-driven triage scoring, and real-time data synchronization to dynamically adapt to changing operational conditions such as patient surges and reduced staff availability.

 

Project Goals

  • Implement a priority-aware patient queue system

  • Ensure critical-condition patients are served first

  • Maintain queue stability during sudden load increases

  • Support staff shortage scenarios through adaptive scheduling

  • Provide an offline-first, fault-tolerant architecture

 

System Functionality

The build includes:

  • Patient registration with automatic token generation

  • Rule-based triage scoring using symptoms and urgency levels

  • Priority queue management with real-time updates

  • Dynamic queue reordering based on system mutations:

    • Mutation A: Patient volume doubling

    • Mutation B: 40% reduction in staff availability

  • Firebase Firestore for real-time, consistent state management

  • Offline data persistence with background synchronization

 

Design Rationale

Traditional clinical queue systems often rely on static ordering or manual triage, which becomes unreliable during peak loads.
CriticalFirst addresses this limitation by introducing a deterministic, data-driven triage mechanism that preserves prioritization correctness under stress conditions.

The project was built to model real-world healthcare constraints and demonstrate how cloud-native technologies can be applied to critical infrastructure systems.

 

Use Cases & Extensibility

This system can be adopted or extended for:

  • OPD and clinic queue digitization

  • Emergency triage simulations

  • Healthcare system prototyping

  • Academic and hackathon demonstrations

Future enhancements may include:

  • AI-assisted triage prediction models

  • Role-based dashboards for medical staff

  • Analytics and patient flow visualization

  • Integration with hospital information systems (HIS)

 

References & Links

This build was uploaded as a hackathon project

Hackathon

Hacknagpur 2.0

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