AI's Price Tag on Healthcare: More Costs, Less Clarity

AI in healthcare promises many things, but reducing costs isn't one of them. Recent estimates suggest that next year, medical expenses will jump by 9% in the employer market and 8.5% in the individual market. At the core of these rising costs is the deployment of AI-enabled software and scribes by providers.

The Cost of Complexity

PricewaterhouseCoopers (PwC) highlights that the financial strain isn't driven by increased usage of medical services. Instead, it's about the changes in coded severity, case mix, and the paid amount per claim. In simple terms, AI tools are capturing more billing complexity, leading to higher costs for everyone.

Paul Markovich, CEO of Blue Shield of California's parent company Ascendiun, points out the current incentives. "The system is designed to do more and get paid for more," he notes. Companies are looking at AI through the lens of self-interest, aiming to enhance revenue rather than reduce costs. So what does workflow integration really mean when it's driving up expenses?

AI's Double-Edged Sword

Bob Kocher, a partner at Venrock, believes AI will make the system more efficient, albeit in a way that could increase healthcare spending. The focus right now is on revenue cycle management and drug development. While these advancements could introduce innovative treatments, they're likely to come with a high price tag.

The real cost, as Kocher suggests, is the potential for AI to flood the market with more services. While efficiency is touted as a benefit of AI, in practice, it's often efficiency for billing and coding rather than for patient care.

Shifting Towards Patient Outcomes

Not everyone is buying into the current narrative. Harvard Medical School's Hossein Estiri believes that the hype around administrative uses of AI will fade. He suggests that the real value of AI lies in enhancing patient outcomes, enabling proactive health measures, and making care more precise. But will this shift happen before costs spiral out of control?

As AI continues to shape the healthcare industry, a timely UBS report suggests that while insurers might see some efficiency gains, these will likely be neutralized over time. Big for-profit hospitals could tap into AI quickly, creating a temporary competitive edge, yet the industry as a whole is chasing the same efficiencies.

Reimagining Incentives

AI's real transformative potential may lie in changing how healthcare is paid for. Moving away from fee-for-service models to value-based care, where providers are rewarded for patient outcomes, could be the breakthrough. But it's a concept that's been discussed endlessly without materializing at scale. Could AI finally make it a reality?

The gap between pilot and production is where most fail. For AI in healthcare, it's key to close this gap by aligning incentives with patient health rather than billing complexity. Enterprises might not buy AI outright, but they'll invest in outcomes that truly matter. The ROI case requires specifics, not slogans.