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Introduction
Large Language Models or LLM’s (the tech behind ChatGPT) is revolutionizing the healthcare landscape. Payers are increasingly using AI to deny claims and providers are constantly playing catchup. There is a massive shortage of healthcare leaders who understand what the capabilities and limitations of these technologies. This 3 hour workshop (available both in-person or online) will quickly bring your team up to speed and enable you to make the right decisions when it comes to AI projects in healthcare.
Who Is This Workshop For?
Revenue Cycle Managers – Focused on optimizing billing, pre-authorization, and claims processing; interested in understanding how LLMs can streamline documentation, eligibility verification, and denials management.
Chief Medical Information Officers (CMIO) – Aims to integrate AI responsibly into clinical systems, with a focus on how LLMs can enhance clinical documentation and decision support while maintaining data security.
Patient Engagement Directors – Looks for ways to improve patient communication and satisfaction; interested in how LLMs can help personalize patient interactions and support 24/7 inquiries through chatbots.
Compliance Officers – Prioritizes data privacy and regulatory adherence; needs to understand how LLMs handle sensitive data and how to mitigate risks associated with AI in clinical workflows.
Clinical Operations Managers – Manages daily clinical workflows and seeks to improve operational efficiency; interested in how LLMs can help automate routine tasks, reducing administrative burdens on clinical staff.
Director of Quality and Patient Safety – Focused on improving care quality and patient outcomes; interested in how LLMs can analyze clinical data to identify risk factors and prevent adverse events.
Health Informatics Specialist – Works on data management and analytics within health IT systems; curious about how LLMs can streamline data extraction, coding, and analysis to support better decision-making.
Chief Financial Officer (CFO) – Oversees financial operations and resource allocation; interested in understanding the cost benefits of LLMs in reducing operational expenses, such as automating billing and claims processes.
Training and Development Manager – Responsible for staff training; interested in how LLMs can support continuing education, create tailored learning modules, and provide on-demand support for complex queries.
Population Health Manager – Works on community health initiatives; interested in using LLMs to analyze social determinants of health data, predict health trends, and support targeted intervention programs.
Workshop Modules
Evaluating LLM Performance - Understand metrics like ROUGE and BLEU to measure how well an LLM is doing.
LLM Use Cases - Understand what LLM’s can be used for and where you’re better off using other AI models.
LLM Contingencies - Understand how things can go wrong including issues like model hallucination, bias, prompt injection attacks, and more.
Calculating ROI for LLM Projects - Understand elements to measure in order to calculate Return on Investment.
What’s Around The Corner? - Understand healthcare applications of multimodal models and agentic systems.
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