💡Built for #LeadWithAIAgents Hackathon by GenAI.Works

Product Name: CareGenix Version: 1.0.0

Table of Contents

Overview 📋

CareGenix is an AI-driven patient care management system developed for the GenAI.Works Agentic Hackathon (July 11-14, 2025). It leverages a cluster of autonomous AI agents to streamline healthcare processes, addressing challenges like fragmented data, manual workflows, and delays in patient care. This documentation outlines the system's architecture, agent functionalities, data flow, and alignment with sustainable development goals.

Introduction ℹ️

CareGenix is designed to transform patient care management by automating and optimizing key healthcare processes. Built using generative AI and agentic frameworks, it tackles inefficiencies in patient intake, medical record management, diagnostics, treatment planning, and communication. The system ensures timely, accurate, and personalized care, aligning with the hackathon's focus on AI-driven orchestration.

Problem Statement ⚠️

Healthcare systems face critical challenges:

• Fragmented Data: Patient information is scattered across systems, limiting accessibility and analysis.
• Manual Processes: Administrative tasks consume resources, diverting focus from patient care.
• Delays in Care: Inefficient workflows lead to delays in diagnosis, treatment, and communication, impacting outcomes.

CareGenix addresses these issues through a cluster of AI agents that streamline the patient care lifecycle.

Solution Architecture 🏗️

Agent Descriptions

CareGenix comprises five autonomous AI agents, each handling a specific task to ensure efficiency and accuracy in patient care management.

1. Patient Intake Agent 🧑‍⚕️

• Function: Automates patient registration, collects medical history, and performs initial triage based on symptoms.
• Tools:
  • AWS Bedrock for natural language processing (NLP)
  • Symptom checker API (e.g., Ada Health)
  • Triage algorithms
• Input: Patient demographic data, symptoms, medical history (via secure web forms or voice input)
• Output: Triage priority (low, medium, high), preliminary assessment, appointment scheduling
• Description: Uses NLP to parse free-text or voice inputs, ensuring rapid onboarding and prioritization of urgent cases.

2. Medical Records Agent 📂

• Function: Organizes and analyzes patient medical records, ensuring data integrity and extracting insights (e.g., chronic conditions, allergies).
• Tools:
  • Mock EHR integration (e.g., Epic/Cerner API)
  • Amazon Textract for document processing
  • Data validation algorithms
• Input: Medical documents, test results, patient intake data
• Output: Structured EHR entries in FHIR format, pattern analysis (e.g., recurring symptoms), data quality reports
• Description: Centralizes and structures patient data, enabling interoperability with healthcare systems using FHIR standards.

3. Diagnostic Assistant Agent 🔍

• Function: Analyzes symptoms and medical records to suggest possible diagnoses and recommend further tests.
• Tools:
  • Medical knowledge base (e.g., UpToDate API)
  • Symptom-diagnosis mapping
  • Machine learning models (fine-tuned on MIMIC-III dataset)
• Input: Patient symptoms, medical history, lab results
• Output: Top 3-5 differential diagnoses, recommended tests (e.g., blood work, imaging), confidence scores
• Description: Enhances diagnostic accuracy with generative AI, providing evidence-based recommendations and explainability features.

4. Treatment Plan Agent 💊

• Function: Generates personalized treatment plans, monitors progress, and adjusts recommendations based on new data.
• Tools:
  • Treatment guideline databases (e.g., NICE guidelines)
  • Drug interaction checkers
  • Progress tracking algorithms
• Input: Diagnoses, patient preferences, medical history
• Output: Treatment plans (e.g., medication, therapy), medication schedules, follow-up recommendations
• Description: Tailors treatments to patient-specific needs, integrating with pharmacy systems for prescription fulfillment.

5. Patient Communication Agent 📧

• Function: Manages patient communication, sends reminders, provides health education, and answers queries in real-time.
• Tools:
  • Twilio API for messaging
  • Amazon Lex for chatbot functionality
  • Curated educational content databases
• Input: Appointment schedules, treatment plans, patient queries (text or voice)
• Output: Appointment reminders, educational materials (e.g., condition-specific guides), query responses
• Description: Enhances engagement with timely, multilingual communication, reducing no-shows and improving satisfaction.

Agent Flow 🔄

The agents operate in a sequential pipeline to deliver a seamless patient experience:

• Flow: Patient Intake → Medical Records → Diagnostic Assistant → Treatment Plan → Patient Communication
• Data Pipeline: Agents share data via a secure, HIPAA-compliant AWS-based pipeline using DynamoDB for storage and FHIR for interoperability.
• Example Scenario:
  1. A patient inputs symptoms (e.g., fever, cough) via a web form.
  2. The Patient Intake Agent assigns high triage priority and schedules an appointment.
  3. The Medical Records Agent retrieves past records (e.g., asthma history).
  4. The Diagnostic Assistant suggests diagnoses (e.g., pneumonia, 80% confidence) and recommends a chest X-ray.
  5. The Treatment Plan Agent proposes antibiotics and follow-up care.
  6. The Patient Communication Agent sends a reminder and an asthma management guide.

Sustainable Development Goals (SDGs) 🌍

CareGenix aligns with the following United Nations SDGs:

• SDG 3: Good Health and Well-Being: Improves diagnostic accuracy, personalizes treatment, and enhances patient engagement.
• SDG 9: Industry, Innovation, and Infrastructure: Leverages advanced AI to innovate healthcare delivery and build resilient infrastructure.
• SDG 10: Reduced Inequalities: Enhances access to advanced healthcare, particularly in underserved areas.

Impact 🚀

CareGenix delivers measurable benefits to healthcare:

• Improved Diagnostic Accuracy: Reduces errors by analyzing complex medical data (BMC Medical Education, 2022).
• Personalized Treatment Plans: Enhances outcomes and satisfaction through tailored care.
• Enhanced Patient Engagement: Reduces no-shows and improves adherence with timely, multilingual communication.
• Streamlined Processes: Automates administrative tasks, allowing providers to focus on care.
• Cost Efficiency: Optimizes workflows, reducing operational costs.

Future Goals 🔮

CareGenix is designed for scalability and growth:

• Advanced AI Integration: Incorporate NLP for enhanced patient interaction and predictive analytics for proactive care.
• Expansion: Extend to chronic disease management, telemedicine, and mental health support.
• Global Reach: Develop versions for low-resource settings with limited infrastructure.