Atria Co-Pilot

Business Problem

  • Healthcare providers face challenges in synthesizing patient data from multiple sources, such as electronic health records (EHRs), diagnostic imaging systems, and laboratory information systems.
  • The fragmented nature of these data sources creates a disjointed data landscape, resulting in inefficiencies and delays in patient care.
  • A lack of seamless data integration and querying capabilities prevents healthcare professionals from gaining a comprehensive view of patient health.
  • This gap in data synthesis leads to suboptimal clinical decisions, impacting the quality of patient care.
  • Manual data retrieval and analysis processes increase the risk of errors, further compromising patient outcomes and overall healthcare quality.

About Atria

Atria Healthcare is a company focused on revolutionizing patient care through the power of Artificial Intelligence (AI). Recognizing the challenges faced by healthcare providers in managing and analyzing complex patient data, Atria has developed innovative GenAI-driven tools to enhance patient health assessment and streamline medical decision-making.

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Solution

1.

Health Insights & Diagnosis Assessment
Utilizes AI models such as OpenAI GPT-4, MedPaLM 2, and LLaMA 2 to analyze patient data and provide comprehensive health insights.
Suggests potential diagnoses based on an integrated view of patient records, ensuring informed clinical decisions.

4.

Summarization Generation
Generates concise, clear narratives of patient health journeys, helping healthcare professionals quickly interpret complex data and take action.
Summaries are seamlessly integrated into platforms like Google Docs for easy access and collaboration.

4.

Smart Query Generation
Optimizes data retrieval using AI-powered SQL query construction, ensuring rapid and accurate access to data stored in Snowflake.

2.

Knowledge Graph Creation
Constructs a detailed knowledge graph using NebulaGraph and Weaviate, linking patient data points like lab results, clinical notes, diagnostic imaging, and medication histories.
Offers a holistic view of patient health, enabling providers to explore relationships and patterns within the data.

5.

Conversational Interface
Features a real-time chatbot, enabling intuitive interaction with patient data.
The conversational interface provides instant access to needed information and actionable insights, enhancing efficiency during patient consultations.

3.

Relevant Data Fetching (RAG)
Employs a Retrieval-Augmented Generation (RAG) pipeline powered by AWS Bedrock, efficiently fetching relevant information from the knowledge graph to inform clinical decisions.

6.

Custom Visualizations
Creates dynamic visual representations of patient health trends and key metrics, simplifying data interpretation and enabling proactive care.
Visualizations are generated using integrated libraries and presented directly within the provider’s workflow.

Outcomes

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Enhanced Data Integration: Seamlessly integrates data from multiple sources, providing a unified and comprehensive view of patient health.

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Increased Operational Efficiency: Reduces the time and effort required for data retrieval and analysis, freeing up healthcare professionals to focus more on patient care.

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 Improved Accuracy: Minimizes errors associated with manual data handling, enhancing the accuracy of clinical assessments and decisions.