Texas Association of Health Plans Recap: From Claims to Prior Auth: How AI, Automation & Data Are Revolutionizing Payer Operations

The Texas Association of Health Plans (TAHP) session, "From Claims to Prior Auth: How AI, Automation & Data Are Revolutionizing Payer Operations," provided critical insights into how technology is fundamentally reshaping healthcare administration. The discussion, moderated by Mark Netoskie, MD, MBA, FAAP from Cigna Healthcare , centered on leveraging AI as a strategic partner to eliminate friction, ensure compliance, and maximize payment accuracy. The panelists affirmed that the industry is moving from reactive processes to a proactive stance, driven by modern technological capabilities. 

Mark Noel's Focus: Payment Integrity, AI, and Fiduciary Responsibility  

Mark Noel, PMP , GM and SVP of ClaimInsight at Advanced Medical Pricing Solutions AMPS , provided a detailed commentary on how AI and advanced data tools are transforming the high-stakes world of payment integrity (PI). Noel positioned ClaimInsight as a nimble, results-driven partner dedicated to helping payers address costs, waste, and crucial fiduciary obligations. 

The Three Core Pillars of ClaimInsight 

Noel outlined ClaimInsight's comprehensive approach to payment integrity, which combines automation with expert review: 

1. Intelligent Policy Update (IPU): Prepayment Editing: This is the core rules engine that allows for proactive cost savings by stopping errors before payment. Noel emphasized the necessity of a continuously updated policy library, a critical differentiator for ClaimInsight. 

"One of our biggest differentiators is our ability to create policy and keep that policy updated as of the date it's effective... On the day that it's effective, we have it updated in our library. It's a big, big differentiator." 

1. High Dollar Bill Review (HDR): For complex, high-cost inpatient claims, AI plays a crucial supporting role. While physicians still perform the manual, line-by-line review, AI helps pinpoint the best sections of the itemized bill for the reviewer to focus on, increasing efficiency and maximizing the discovery of overpayments. 

1. Retro Review and Recovery (RRR): This newer component addresses the growing pressure on self-insured employers and plans regarding their fiduciary duties under regulations like ERISA and CAA. ClaimInsight leverages its rules engine to audit the past few years of payments, identifying overpayments and utilizing a recovery unit to reclaim funds. Noel noted this allows clients to check the box of being a good fiduciary and puts money back in their pockets. 

AI as an Enabler of Speed, Agility, and Partnership  

Noel stressed that AI is primarily an enabler that drives internal efficiency, which ClaimInsight then shares with clients through flexible service models. 

• Customized Solutions: The ability to move faster allows ClaimInsight to build unique solutions quickly. He cited a remarkable example of rapid deployment: 

"A Medicaid client came to us and wanted us to implement some payment integrity for them... In a matter of four weeks, we built the entire policy set for two states of Medicaid, and we were live." 

• Flexible Pricing: Because AI-driven efficiency reduces the dependency on manual efforts, ClaimInsight can offer flexible pricing models, such as PMPM (per-member-per-month), moving away from the costly, less predictable percentage-of-savings model traditionally used in payment integrity. 

• Addressing Waste and Abuse: Noel discussed how all data, from the automated IPU to the manual HDR, flows into a central dashboard, providing transparency and enabling payers to combat complex waste and abuse schemes, a problem often limited by a lack of internal staff to investigate. 

Administrative Automation and the Integration Hurdle  

While Sam Schwager (SuperDial) and Sumant Kawale (Sagility) focused on other operational areas, their core findings intersected with Noel's on the reality of AI deployment. 

Frictionless Communication with Voice AI 

Sam Schwager detailed SuperDial's use of voice AI agents to automate high-volume, repetitive payer-provider communication (eligibility, prior auth status, credentialing). His long-term vision is AI-to-AI communication, where agents transact via efficient API-based mechanisms, rather than wasting time on the telephone network. 

The Integration Challenge 

The panelists were unanimous that the greatest current barrier to success is not the AI technology, but the integration with legacy payer systems. 

• RPA Workarounds: Schwager noted that because existing systems use Graphical User Interfaces (GUIs) built for humans, AI is often forced to use RPA (Robotic Process Automation) on a human-facing screen. 

• Strategic Deployment: This led to a consensus on strategic adoption: organizations should focus on "picking one system, one specific workflow and trying to, you know, optimize for that and get value quickly," rather than waiting for a multi-year, holistic AI strategy. 

Human-AI Collaboration and Training 

Sumant Kawale (Sagility) emphasized that AI should be treated as a colleague and that a human-in-the-loop is always necessary where complexity, compliance, or empathy is required. Sagility applies AI internally as a training engine, using virtual simulators and knowledge tools to quickly train new agents, ensuring the human workforce is more accurate and efficient when they do take calls. Kawale cautioned that organizations should be AI skeptics and require comprehensive testing before deployment. 

Conclusion: From Reactive to Proactive Healthcare  

The session concluded that AI is moving the industry toward a proactive model across all payer operations, from claims payment and administrative communication to policy compliance. By strategically implementing AI to handle high-volume, low-complexity tasks and assisting humans on the most complex cases, organizations like AMPS are setting a new standard for accuracy, efficiency, and fiduciary responsibility.