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Improving Patient Outcomes with Gen AI-Assisted Healthcare
Gen AI helped a healthcare provider auto-generate SOAP (Subjective, Objective, Assessment, Plan) notes from doctor-patient conversations helping improve patient care decisions, optimize referral process, and generate drug recommendations.
The Challenge
Our client, a healthcare provider, wanted to enhance doctor-patient conversations for better patient care:
- Labor-Intensive: Creating and entering SOAP notes into EHR systems was time-consuming.
- Lack of Insights: Doctor patient conversations were recorded but lacked further analysis and insights from data.
- Need for Automation: Client wanted to reduce note creation time and enable real-time documentation i.e. more time spent on patient care.
- Referral Process: Manual categorization and referral of non-specialized cases was time consuming.
Our Solution
We developed and deployed a comprehensive solution leveraging Gen AI and cloud technology:
- REST API: Secure, high-performance API developed to convert doctor-patient conversations into SOAP notes with a response time of less than 30 seconds.
- LLM Integration: Self-hosted Large Language Model (LLM) utilized for generating medical SOAP notes.
- Cloud Deployment: HIPAA-compliant solution hosted on AWS in the Australia region, ensuring scalability and performance.
- Quality Assurance: Rigorous testing to ensure API functionality, LLM accuracy, and overall system performance under concurrent usage.
The Impact
Gen AI delivered significant improvements across various aspects of healthcare delivery:
- Automated Note Generation: Eliminated manual tasks, enabling real-time documentation and allowing practitioners to focus on patient care.
- Time Savings: Reduced response time to less than 60 seconds for SOAP note generation and other AI-assisted tasks.
- Scalability: Cloud-based infrastructure supports growth and increasing interaction volumes, allowing 30+ doctors to use the system concurrently.
- Improved Decision Support: Automated drug recommendations and follow-up questions enhanced the quality of patient care and clinical decision-making.
- Optimized Referral Process: AI-driven categorization and automated referral letter generation streamlined the process of directing patients to appropriate specialists.
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