Unleashing AI in Healthcare: Transforming Payer Efficiency and Member Experience
At the 2023 Becker’s Payer Issues Roundtable, Lyric's Chief AI Officer, Akshay Sharma, led an executive discussion on why generative AI and large language models hold enormous potential for payers. Unlike older AI attempts, today’s generative AI excels at natural language understanding, allowing systems to reason across data silos and improve decision-making processes without requiring perfect data centralization.
Akshay emphasizes that operational efficiency is a top use case. By applying large language models to read policies, interpret claims, and clarify denials, payers can drastically cut down on human effort and time lost in sifting through complicated documents. He highlights the concept of “co-pilots”—intelligent assistants that support users right in their existing workflows. For instance, a co-pilot can help product managers or clinicians speed through repetitive tasks by understanding rules encoded in PDFs and other documents.
He acknowledges that building trust, ensuring data security, and maintaining privacy remain critical. While generative AI can improve both member and provider experiences—like quickly explaining why a claim was denied—organizations must guard against hallucinations and enforce responsible AI governance. Akshay notes that retrieval augmented generation (RAG) techniques can link large language models to curated data sources for added reliability.
For payers, improving administrative processes, reducing customer support burden, and fostering better relationships with providers is now more feasible. LLM-powered tools can “reason” with policy data, give instant context, and make complex healthcare transactions more transparent. While not every challenge is solved, Akshay believes this new wave of AI can handle much of the heavy lifting that previously required large teams, freeing stakeholders to focus on what truly matters: delivering efficient, member-friendly, and provider-friendly care.
Additional Videos
