The 5 Trillion Dollar ‘Agency Problem’

According to various estimates, the United States spent nearly $5 trillion on healthcare in 2023. That amounts to about $14,000 per person. To put that into perspective, just the rounding error in this figure is staggering: rounding $4.9 trillion to $5 trillion creates a $100 billion gap—an amount large enough to fund entire government programs or businesses for years.
Yet, despite this enormous expenditure, the U.S. lags behind many other developed nations in key health outcomes. Why does a country that spends so much on healthcare struggle to produce healthier citizens? Many have attempted to diagnose and solve this issue, but most have failed to pinpoint the root cause. It’s unrealistic to assume that a single “silver bullet” can resolve such a complex problem. However, in this two-part blog series, I will explore one significant dimension of this issue. While the ideas presented are my personal observations, this is not an obscure problem; it is widely recognized but rarely discussed in depth.

From the Eyes of a Software Engineer

Recently, I was explaining the intricacies of the U.S. healthcare system to a group of software engineers as we worked on refining our technology solutions for this space. Specifically, I was breaking down the financial flow of healthcare—how money moves from patients to insurers as premiums, then how payments are made to providers for services. After a 45-minute lecture, complete with multimedia tools (and admittedly some poor handwriting and questionable drawing skills), I arrived at a final diagram that attempted to capture the flow of funds in the healthcare system. See below, I am sure your reaction would be ‘What a mess!’

When I turned to my audience, I saw a room full of starry-eyed engineers, their expressions mirroring my own when I first encountered the Revenue Cycle Management (RCM) process two decades ago.
Even after working in healthcare IT for years, I remain astonished at how a relatively simple process has been made extraordinarily complex by layers upon layers of intermediaries. One thing I admire about software engineers is their ability to think logically and solve problems efficiently. However, when confronted with the convoluted mess that is the U.S. healthcare system, even they were at a loss for where to begin.

Following the Money

In the USA, if you want to solve a problem, you always start by following the money! Perceptions shape how people understand complex systems. When you “follow the money” in healthcare based on perception alone, you quickly find yourself going in circles. Consider this common perception cycle:

• Patients believe doctors make all the money.
• Doctors believe hospitals make all the money.
• Hospitals believe insurance companies make all the money.
• Insurance companies believe doctors and hospitals make all the money.
• And somewhere in the background, Big Pharma is often blamed for everything.

So, where does the truth lie? The reality is, no one seems to be making money the way people assume.

I have personally spoken with knowledgeable professionals across these categories, and here is what I have found:

• Doctors work tirelessly and often carry enormous student loan debt. Many are under-compensated relative to the risks and pressures they endure.
• Hospitals are struggling to stay afloat. If you see a hospital expanding, it’s often not a sign of prosperity, but a desperate attempt to increase patient volume because margins per patient are razor-thin.
• Insurance companies face financial hits whenever unpredictable events arise: spikes in flu cases, emerging cancers, experimental treatments, or natural disasters like fires and floods.

Patients feel they are the only ones shouldering the cost burden. They pay for insurance premiums, deductibles, copays, and coinsurance. And when insurance refuses to cover services, patients are forced to pay out-of-pocket, or their families step in as caregivers out of necessity.

Conclusion

So, if no one is truly making money, where is the $5 trillion going? We cannot conclude blog post like this, right? In Part 2, I will use my Sherlock Holmes skills to uncover one key piece of this mystery. Stay tuned!