Agentic AI System for Healthcare Workflow Automation
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Solution Overview
Problem
Current healthcare systems face inefficiencies in clinician time utilization for treatment administration and bioindicator data analysis, and conversational AI systems struggle to handle complex or sensitive medical queries, often leaving users confused without adequate responses.
Innovation Solution
An agentic artificial intelligence system utilizing natural language processing, machine learning, and recursive AI reasoning to interpret user instructions, extract insights from structured and unstructured data, and autonomously execute healthcare tasks, with the ability to escalate to human experts when necessary, enhancing patient engagement and revenue cycle management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional conversational systems are used to handle user queries, then simple information retrieval is efficient, but complex or sensitive medical queries cannot be properly handled
Solution Approach 1:
The patent introduces an AI agent as an intermediary between users and healthcare professionals. The agent handles complex medical queries by interpreting user input, consulting medical knowledge bases, and escalating to human experts when needed, thereby resolving queries that conventional systems cannot handle while maintaining efficiency.
Solution Approach 2:
The patent replaces conventional keyword-based search mechanisms with AI-powered natural language processing and reasoning systems. This substitution enables the system to understand context, intent, and medical terminology, significantly improving the handling of complex medical queries while maintaining speed.
2Reliability
If more human experts are involved to handle complex queries, then query resolution accuracy improves, but system complexity and costs increase
Solution Approach 1:
The patent segments the query handling process into distinct levels: routine queries handled by automated systems, complex queries handled by AI agents, and critical queries escalated to human experts. This segmentation ensures that human experts are only involved when necessary, maintaining accuracy while controlling system complexity.
Solution Approach 2:
The AI agent is designed to autonomously handle complex medical queries by consulting medical knowledge bases, analyzing patient data, and providing responses without requiring human expert intervention for every query. This self-service capability reduces the burden on human experts while maintaining high resolution accuracy.
3Reliability
If clinicians spend more time on treatment administration and data analysis, then care quality improves, but clinician time efficiency decreases
Solution Approach 1:
The AI agent acts as an intermediary that handles time-consuming tasks such as data analysis, query interpretation, and initial assessment. This allows clinicians to focus on high-value activities like patient interaction and complex decision-making, improving both care quality and time efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-analyzing patient data, preparing query responses, and organizing information before clinician involvement. This preliminary processing reduces the time clinicians need to spend on routine tasks while maintaining high care quality.
Data Source
AI summary
The present invention relates to agentic artificial intelligence (AI) systems for automating healthcare workflows, particularly in patient engagement and revenue cycle management (RCM). It can utilize natural language processing (NLP), machine learning, and recursive AI reasoning to interpret user instructions, extract insights from structured and unstructured data, and autonomously execute tasks within electronic medical records (EMR) and insurance systems. The system enables real-time patient interactions, adaptive workflow modifications, automated insurance verification, and discrepancy resolution, enhancing efficiency and accuracy in healthcare operations. And enables human/patient continuity of conversation for completing/resolving the underlying workflows.