Beyond payment integrity: An AI-driven approach to affordability

Affordability has become one of the most discussed topics in modern health care. Medical spend is shifting, and health plans are looking for realistic strategies to control costs and maintain financial viability.

To better move the needle on affordability, health plans should look to adopting an artificial intelligence (AI)-driven approach that connects payment integrity functions to other cost control efforts throughout the enterprise.

Medical spend is shaped by a combination of care delivery practices, financial agreements and systemic waste. There are multiple points where costs can escalate throughout the lifecycle of a health care encounter, from the moment a member seeks care to the completion of billing and appeals.

Factors that can impact cost include the intensity and quality of care delivered, provider contracts and reimbursement rates, benefits design, coding and payment accuracy, regulatory requirements and fraud, waste and abuse.

Emerging trends impacting payment integrity are accelerating shifts in health care costs. Inflation and rising utilization have led to significant increases in medical spend, with areas like dental, pharmacy and specialty care seeing notable growth.

Regulatory changes, including shifts in government programs and reimbursement models, have introduced new operational challenges. Additionally, providers are increasingly adopting AI to optimize documentation, coding and appeals, which can impact health plan cost structures and payment integrity programs.

With medical spend shifting, cost control is a top priority for health plans, and payment integrity may be top of mind. While payment integrity will always be an important lever for cost control, it’s not the only lever available to health plans. Health plans are likely already deploying a wide range of cost control measures throughout their enterprises. Common examples include network management, utilization management and technology-driven process improvements.

However, these various cost control tactics often operate in silos. Rather than focusing solely on implementing these individual tactics, the next step is to build stronger connections between payment integrity and other cost control levers across the enterprise to optimize value.

Many new affordability strategies open up when payment integrity is connected to other cost control levers within the health plan:

• Combine payment integrity with network management – Use insights from payment integrity analytics to inform network contracting decisions, while ensuring payment integrity is positioned to enforce updated contract terms.
• Integrate utilization management and claims analytics – Leverage automated claim review and advanced analytics to identify patterns in utilization, enabling more targeted clinical programs that include back-end enforcement from payment integrity.
• Align clinical programs with fraud detection – Coordinate care management and prior authorization efforts with fraud, waste and abuse detection systems to steer members toward appropriate care while minimizing exposure to providers driving up unnecessary costs.
• Embed technology solutions across functions – Implement digital platforms that streamline administrative processes, connect payment integrity with utilization management and provide real-time data for decision-making.
• Institute enterprise-wide data sharing – Facilitate cross-functional reporting and insights so teams responsible for payment integrity, network management and clinical programs can collaborate using shared data to identify cost drivers and respond proactively.

These collaborative strategies help health plans move beyond isolated cost control efforts, creating a holistic approach that maximizes value and supports long-term affordability.

Once these connections are in place, health plans should begin introducing more AI insights and strategies to help with affordability.

• AI tools can provide a deep analysis of medical spend, identifying emerging risks and costly inefficiencies.
• Machine learning models can streamline claims processing, which improves accuracy and reduces manual effort.
• AI-powered fraud detection can flag unusual patterns and behavioral anomalies in real time.
• Advanced analytics prescribe next-best actions to help health plans respond proactively to market shifts.

Health care affordability is a complex, evolving challenge for health plans. With a different approach to affordability, health plans can position themselves to manage costs effectively and deliver greater value to members and stakeholders.

The future of affordability lies in holistic, data-driven strategies that harness the power of AI for smarter, more resilient operations.