Xtended_Meridian

Medical Insurance claim evaluation? Don't fear Xtended_Meridian is here!Smart AI advisor which can make Medical insurance claim evaluations in a snap and also provide comprehensive claim analysis.

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Inspiration

Delays in medical insurance claims processing can have significant consequences for patients and healthcare providers. For patients, prolonged approval times can lead to financial strain, as they may need to cover medical expenses out-of-pocket while awaiting reimbursement. This financial burden can deter individuals from seeking necessary medical care, potentially worsening health outcomes. For healthcare providers, delayed payments disrupt cash flow, complicate revenue cycle management, and may result in increased administrative costs due to the need for follow-ups and appeals. These challenges can strain the provider-patient relationship and hinder the overall efficiency of healthcare delivery.

Recognizing these issues, we saw an opportunity to leverage Generative AI to streamline the claims process, aiming to reduce approval times and alleviate the associated financial and operational burdens.

What it does

The Xtended_Meridian is a simple platform that takes in medical insurance claim data and reports how the claim can be justified based on historical data. It provides claim analysis, settlement recommendation, risk assessment and policy validation.

How we built it

In order to provide the best results we combined smart search techniques like RAG (Retrieval-Augmented Generation) with Agentic framework. We used historical insurance claim data to perform the retrieval from. Using tools like Python and Streamlit for the interface, we created agents to analyze claims and policies and make intelligent recommendations.

Challenges we ran into

  1. One of our biggest challenges was deciding between the CrewAI and LangChain agent frameworks, as both offered unique strengths. Attending Infosys' sessions helped us gain clarity and make the right choice.
  2. Understanding the complexities of medical insurance claims evaluation, including policy details and compliance, felt overwhelming given the limited time.
  3. Finally, working as a two-person team demanded intense focus and effort.

Accomplishments that we're proud of

  1. We’re proud of rebuilding our agents from scratch in LangChain after initially developing them in CrewAI, turning the challenge into an opportunity for growth.
  2. Successfully deploying our project on Streamlit was a significant milestone, showcasing its practical application.
  3. Most importantly, we’re proud of maintaining our optimism and consistently motivating each other throughout the hurdles, proving that teamwork and resilience can overcome any challenge.

What we learned

  1. We deepened our understanding of Generative AI and Multi-Agentic frameworks, particularly CrewAI and LangChain, learning valuable lessons even through initial setbacks with CrewAI.
  2. Additionally, we gained insights into the functionality of various Large Language Model APIs, vector databases, and embedding libraries, enhancing both our technical expertise and problem-solving abilities.
  3. We realized that resilience, optimism, motivation, and focus are just as crucial as technical skills in achieving success. These qualities helped us overcome challenges and stay driven throughout the project.

What's next for Xtended Meridian

  1. Key enhancements include integrating real-time data sources and APIs for dynamic updates.
  2. Implement stronger security measures and audit trails for compliance and data protection.
  3. scaling the solution for global adoption across diverse insurance markets.
  4. Enabling enhanced agent-to-agent communication for seamless collaboration
  5. Introducing more specialized agents to deliver personalized features to ensure a tailored and efficient user experience.

Built With

  • chromadb
  • crewai
  • langchain
  • llm
  • openai
  • openaiapi
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