Where AI can deliver benefits in the payer value chain
Artificial intelligence technologies are transforming claims and contact center operations for measurable savings and productivity gains.
Healthcare payer organizations that began piloting generative artificial intelligence and its complementary technologies this past year are finding that AI can solve traditional pain points, improve productivity, and enable better member and provider experiences.
The key to success with AI implementations is choosing wisely. AI’s strengths currently are especially suited to claims operations, the contact center and audits. Here’s a look at how payers are deploying AI in those areas and achieving measurable results.
AI in claims operations
Autonomous AI agents work together throughout a process to exchange information, collaborate and act on business rules. These agents and their coordinated “agentic workflows” drive automation deeper into processes.
AI co-pilots work alongside humans, surfacing claims and questions that require expertise and experience. Agents and co-pilots together are powering real-world deployments for leading payers in the following areas.
Prior authorization and appeals. Generative AI agents can review, summarize and triage incoming prior authorization requests. In an agentic workflow, the agents check requests against member benefit plans and payer guidelines. The agents can generate emails to providers requesting additional supporting information, if necessary, and approve a prior authorization request automatically if it satisfies all payer conditions. A co-pilot can route complex requests to human agents for reviews. This AI-driven automation can reduce the time clinicians spend on prior authorization review by at least 46 percent, while faster responses reduce member and provider friction.
Intelligent adjudication. An agentic flow can verify member data on a claim is accurate; check edit codes and correct them if needed; and evaluate whether the claim will adjudicate successfully based on the specific provider contract and the member’s health plan and benefits. It can do all of this without manual intervention. If the AI agent has low confidence in a claim’s accuracy or believes its highly probable that it will be appealed, it will route the claim to a human adjudicator for review. Automating these processes can save payers millions of dollars in time, and avoid penalty and interest payments.
AI-enhanced contact centers
AI tools are powerful companions in contact centers, enabling more member self-service options and equipping service representatives with the information they need to accurately and swiftly respond to members and providers.
Communications management. AI chatbots are a lower-cost self-service channel to handle questions about benefits, claims status, prior authorizations and more. Gen AI tools can manage content extraction from multiple email inboxes or portals; then, AI agents can automatically take required actions, such as creating tickets within a CRM system to update provider contact information or network status. Deploying AI to manage communications is rapidly becoming a necessity, as more payers and providers increasingly use AI agents to generate emails and phone calls.
Accelerating time to competency. Where traditional approaches to training material development typically take weeks or months, gen AI tools can read and summarize extensive training manuals and generate custom training materials in minutes for review and fine-tuning. AI tools can monitor a trainee’s performance, reviewing all calls and interactions, helping pinpoint areas for improvement.
Next best actions. Within seconds of a member’s call, AI tools can deliver a summary of the member’s history and near-instant analysis of the caller’s sentiment to the service representative. During the call, AI agents can transcribe the caller’s voice, anticipate and retrieve data, then recommend actions for the agent to take to satisfy the caller’s needs.
Precision in audit and compliance
Gen AI scrutinizes agent interactions, ensuring adherence to quality standards and suggesting improvements.
Operations co-pilots. Plans are ensuring claims adjudication teams and clinicians follow standard operating procedures using AI copilots and agents. AI agents can review a complex claim in seconds, spotting any potentially incorrect procedural or diagnostic codes. An AI co-pilot can provide a link to documentation about the standard operating procedures required to properly process the claim. That eliminates the five to seven minutes adjudicators normally take to research the procedure. The resulting audit trail shows exactly what procedures should be applied to the claim.
Medicare risk adjustment audits. AI tools can automate and streamline data collection, aggregation and analysis at each step of the risk-adjustment process. For example, gen AI can suggest the most appropriate diagnosis and procedural codes for each member based on their clinical history, demographic data and other relevant factors. These capabilities augment coders’ own expertise to ensure comprehensive and precise code assignment, which helps prevent incorrect risk scores.
With AI tools rapidly becoming ubiquitous, the question for payers is not whether AI can deliver value, but where they should deploy it. That decision is critical because future AI implementations will build on and extend those capabilities. The above real-world use cases are just a sampling of where payers can lay the foundation to begin streamlining their value chains.
Anup Panthaloor is executive vice president of health plans and healthcare services for Firstsource.