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How Health Plans Are Adding Up Real Value From AI

3 months ago 33

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Now that AI tools are everywhere, the question making headlines is whether businesses will see substantial returns from their AI investments. The answer for health plans is a definite yes. Health plans are using AI to solve perennial pain points and productivity bottlenecks in their claims operations, contact centers, training, and more. They are using AI capabilities to create better member experiences and outcomes while reducing costs with more accurate, automated processes. 

Autonomous AI agents, AI co-pilots, generative AI capabilities, and machine learning algorithms are among the AI tools health plans are assembling. These can work together across the payer value chain, exchanging information, collaborating and making autonomous decisions based on business rules. These “agentic workflows” allow health plans to push AI capabilities deeper into their business and operating models. Here are just a few examples of how their bottom lines are benefiting.

  • Improving claims adjudication speed and accuracy – The entire claims process is a natural fit for AI agents and AI co-pilots and their ability to coordinate actions. For one health plan, an agentic flow verifies member data on a claim is accurate; checks edit codes and corrects them if needed; then evaluates whether the claim will adjudicate successfully. If the co-pilot isn’t confident a claim is accurate, it routes the claim to a human claims examiner for review. Another health plan uses AI co-pilots to help ensure claims adjudication teams follow a health plan’s standard operating procedures (SOP). Instead of adjudicators taking ten minutes to research a claim scenario and the plan’s requirements, the AI tool can quickly highlight claim line items that need attention, such as incorrect diagnosis or procedure codes. Then it can provide a link to the health plan’s SOP related to the claim. Now the adjudicators can take just two to three minutes per claim while an audit trail shows exactly what SOP applied to the claim. Leading health plans also are building out agentic workflows beyond core claims operations to include AI agents in enrollment, prior authorization, medical records, appeals and grievances and correspondence. 
  • Automating prior authorization and appeals – Health plans are using AI co-pilots to orchestrate multiple AI agents to review, validate, and triage incoming appeals and prior authorization requests. In one plan’s operations, the co-pilot validates the request against member and provider records, the member’s benefits, and the plan’s guidelines and SOP. The co-pilot will generate and transmit correspondence with providers. It routes complex requests to human agents, complete with summarized notes and relevant information. The plan estimates its clinicians spend 46% less time reviewing authorizations while meeting CMS’ requirements for prior authorizations and appeals.
  • Improving member experiences – AI chatbots can respond to a variety of questions – including inquiries about benefits, claims status and prior authorizations – to provide members with faster service at lower costs to the health plan. AI co-pilots can assist human agents by suggesting next-best actions based on near-instant analysis of a caller’s sentiment. During a call, the co-pilot can anticipate and deliver the data the agent will need to answer a member’s questions, so the agent doesn’t have to toggle between screens and applications. When calls are complete, the AI co-pilot reviews them, both for its own training and to identify where to improve the quality of member interactions. Health plans can use this data to find and mitigate the root causes of member calls. 
  • Training – Generative AI tools can digest training manuals and presentations and create custom learning material with games and video presentations in as little as a week vs. months of traditional scripting and production. Health plan service representatives become competent more quickly with personalized, AI-based training tools. Plans can quickly roll out training on new regulatory practices or internal rules, helping to improve compliance and consistent practices. 
  • Communications – A leading health plan is saving an estimated $5 million annually by using an AI co-pilot to read and route messages from members and providers from nearly 100 email inboxes. The AI co-pilot reads the message, identifies its intent, then acts. For example, the AI co-pilot reads an email that a provider is leaving the plan’s network and, without prompting or manual intervention, generates a ticket within the plan’s customer relationship management system to remove the physician’s listing. The co-pilot tackles multiple emails per minute, eradicating email backlogs. When an email’s intent is unclear, the AI co-pilot routes it to the provider operations team, which now has the time to review and respond to complicated communications.

AI tools are giving health plans new ways to improve operations, from incorporating autonomous AI agent decision-makers into workflows to AI co-pilots helping claims adjudicators and service representatives do their jobs more effectively. Plans that waited for proof of AI’s utility now have it. They can benefit from lessons learned by early adopters and gain the time and cost savings that plans quicker to recognize AI’s potential already are experiencing.

Photo: IvelinRadkov, Getty Images

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.

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