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A Deeper Dive Into Health Costs Data

Like the rest of the country, health care costs have been on our minds. How to "bend the cost curve." How to spend wisely. How much to spend. As national health care reform takes effect, these questions take on an urgency for the national economy, the federal budget deficit, and the Medicare Trust Fund.
The good news
The good news is that we are obtaining better data with which to gauge the drivers of costs, and therefore, better ways to address worrisome trends. As Martin Gaynor notes in an article in the new journal Health Management, Policy and Innovation, most of the information we have about health care costs in the U.S. comes from the Medicare program. However, more than 60% of insured Americans have private insurance, and until recently comprehensive data about their health care utilization have been unavailable. That is changing with the founding of the Health Care Cost Institute, a new center devoted to studying and sharing commercial claims data -- more than 6 billion claims for more than 50 million people.
The bad news

The bad news is that the latest report from HCCI shows that average spending for each person with employer-sponsored insurance rose to $4,547, a 4.6% increase from the previous year. This is higher than the 3.8% growth rate in 2010, raising doubts about whether the country had turned the corner on rapidly accelerating health care costs, as some economists have suggested (see, for example, Charles Roehrig and colleagues in an August 16, 2012 New England Journal of Medicine perspective). Rising prices, rather than increased utilization, seem to be the culprit in the latest HCCI reports. This growth outpaced the sluggish economy as well as employee wages. The U.S. now spends about 18% of its domestic product (GDP) on health care.

But perhaps we should not be surprised by this growth. At least that's the argument made by Robert Woodward and Le Wang in the August 2012 issue of Health Economics, as they strike a pessimistic note about the possibilities
Health Economics
for "bending the cost curve." They show that the curve (as represented by the relationship between per capita health spending and per capita GDP), is remarkably stable through time; health spending grows exponentially with GDP. In other words, our overall appetite for health care increases disproportionately as our income grows. Between 1960 and 2008, Woodward and Wang estimate that the "elasticity" of national health expenditures and GDP is about 1.38, and stable through times of great expansion (Medicare, Medicaid) and cost containment efforts (prospective payment, managed care reforms).

They propose two explanations for this stability: first, it might reveal a rational preference for spending higher proportions of our income on health care, even when we do not directly improve outcomes such as life expectancy. We might value other less measurable benefits of health care, such as hope, uncertainty-reducing information, and consumer amenities, all of which may be independent of improved health outcomes. Second, it might reflect a dynamic that makes new technologies highly dependent on rising incomes. By that account, new technologies are only introduced when there is an expected market for them, and that market is dependent on GDP per capita.

Technology and cost growth
But not all technology has the same effect on cost growth, as Amitabh Chandra and Jonathan Skinner point out in the September 2012 issue of the Journal of Economic Literature. They develop a model of patient demand and supplier behavior to explain parallel trends in technology growth and cost growth. The model implies a typology of medical technology with differing effects on cost growth: 1) highly cost-effective "home-run" innovations with little chance of overuse,
Journal Economic Literature
such as anti-retroviral treatment for HIV; 2) treatments highly effective for some, but not all patients, such as stents; and 3) "gray area" treatments with uncertain clinical value, such as ICU days among chronically ill patients. They note that much of the improvement in health outcomes is generated by the first category of treatments, while much of the cost growth is generated by the third. "Countries or systems of care that encourage the first group of innovations but discourage the third group are most likely to exhibit high aggregate productivity growth and a slower overall growth rate relative to GDP," they state.

However, even countries with strict cost containment measures and sophisticated technology assessments find that their health care costs rise faster than their GDPs. In a new book, "The Cost Disease: Why Computers Get Cheaper and Health Care Doesn't," William Baumol offers one explanation, based on a phenomenon to which he gave his name more than 50 years ago. "Baumol's Cost Disease" afflicts industries like health care, performing arts, and education, because they are labor-intensive and hard to make more efficient. So while other industries, such as manufacturing, become more productive, GDP rises, but health care takes up an increasing share of GDP.

Expanding the pie?
Is this a bad thing? Baumol says no. We can afford to devote a greater piece of the pie to health care
Baumol book
because the pie itself is growing. In his view, health care costs need not crowd out other important goods and services, especially if those goods and services are produced more efficiently than before.

Does this mean that we need not worry about health care costs? Well, no. But it does make us ask different questions, and may change our expectations about costs as health care reforms are implemented.

Six years after passing landmark health care reforms, Massachusetts recently tackled the stubborn problem of rising health care costs. Its solution? It ties the growth of health care spending to the growth of the state economy, as measured by the "gross state product" (GSP) adjusted for the business cycle. In effect, it will attempt to accomplish by legislation what has not occurred by happenstance or by design. For 2013, health care costs can grow at no more than 3.6%. For 2014 to 2017, the rate of growth is limited to the GSP growth rate, and for 2018 to 2022, it is limited to the GSP growth rate minus 0.5%. It remains to be seen how this legislation will be implemented, and how these savings will be achieved.

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Daniel Polsky, PhD, MPP, is Executive Director of the Leonard Davis Institute of Health Economics, a Professor of Medicine at Penn's Perelman School of Medicine and Professor of Health Care Management at The Wharton School.
Janet Weiner, MPH, is Associate Director for Health Policy at the Leonard Davis Institute of Health Economics.

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