$5.3 Trillion in Healthcare. Are We Getting Enough Back?

The United States spent $5.3 trillion on healthcare in 2024, approximately $15,474 per person. Healthcare spending represented nearly 18% of the entire U.S. economy.

With a figure of this magnitude, one question is hard to ignore: what are we getting in return?

This was one of the central questions in the conversation between Mario Carrasco and Aaron Fields, MHA, ACC, on The New Mainstream Podcast. For Fields, understanding where value is being created within all this spending is fundamental to thinking strategically about the future of healthcare.

Spending More Doesn't Mean Better Outcomes

The United States dedicates an extraordinary amount of resources to healthcare. Yet the level of spending does not necessarily translate into better health outcomes compared with other industrialized countries.

Fields suggests that part of the answer lies in changing where we focus our attention.

Rather than waiting until people arrive at the hospital with advanced illnesses, healthcare systems have an opportunity to identify risks, needs, and opportunities for intervention earlier.

That requires a much deeper understanding of the populations they serve.

The Problem with Looking Only at Averages

One of the biggest challenges in healthcare decision-making is that averages can hide enormous differences.

Fields recalls a conversation at a population health conference in Minnesota. A healthcare system leader showed a map of Minneapolis-St. Paul and explained how health conditions could change dramatically between communities located only a few miles apart.

In the example he shared, life expectancy could vary from approximately 82 to 61 years depending on the community.

The example illustrates a fundamental idea: a citywide average can hide completely different realities between communities.

When we look only at the average, we understand what is happening in general. When we analyze data at a more granular level, we can begin to understand where it is happening, who is experiencing it, and what factors may be behind it.

From Data to Decisions

For years, other industries have used data to identify patterns, test different strategies, and determine which actions produce better results. Healthcare has been moving in this direction, while continuing to face challenges around data integration and utilization.

Clinical, financial, operational, patient, and qualitative information has historically lived across separate systems.

When these data sources remain isolated, it becomes harder to build a complete picture of the people and populations a healthcare system is trying to serve.

Bringing these pieces together allows leaders to ask more useful questions:

• Which populations are facing the greatest challenges?
• Where are there significant differences in outcomes?
• What factors may be contributing to those differences?
• Where is there an opportunity to intervene earlier?
• Which strategies are producing results that could be replicated?

Intervention Can Start Earlier

Consider a challenge such as diabetes.

Data can show where there is a higher concentration of patients or where outcomes differ. That information can open the door to much broader questions.

• What factors are influencing those outcomes?
• Are there barriers related to nutrition, education, access, transportation, or follow-up care?
• What resources already exist within those communities?

Could different forms of support help people before their condition requires a more costly intervention?

This approach creates opportunities to identify where earlier intervention could make a difference.

Technology Helps. Interpretation Still Matters.

The amount of information available to healthcare systems continues to grow. Artificial intelligence is also transforming the ability to process large volumes of data.

But data alone does not create a strategy.

Leaders need to connect different sources of information, identify which signals matter, and turn those signals into decisions.

Fields shares a story about an informatics leader who decided to turn off some of the reports his organization was producing on a regular basis.

The idea was simple: wait and see who actually needed them.

The exercise helped reveal which information was truly useful for decision-making and which information was simply adding noise.

The lesson is relevant to any organization working with large amounts of data: more information does not necessarily mean more clarity.

In the latest episode of The New Mainstream, Mario Carrasco speaks with Aaron Fields, MHA, ACC, about healthcare strategy, population health, data, artificial intelligence, and how healthcare systems can make better use of information to inform decision-making.