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Health Care Satellite Account

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BEA is in the midst of a multiyear project to improve the way we measure health-care spending throughout the U.S. economy. Our goal is to develop a set of statistics that will provide a broad look at how much Americans spend on medical care, as well as a more detailed view over time.

Importantly, in this satellite account we redefine the commodity provided by the health-care sector as “treatment of disease” and group expenditures related to disease episodes, thus allowing insight into household consumption of care to treat specific diseases or ailments. This is an important shift from how health-care spending is currently measured.

In our new Health Care Satellite Account, specific costs associated with a treatment for a disease, such as cancer, will be grouped together and classified as a household consumption. Currently, different elements of cancer treatment are accounted for separately in different spending categories. For example, inpatient surgeries are recorded as part of hospital services, and prescription drugs are included in pharmaceutical preparations. The new account also will provide information on how much people spend on specific diseases based on the region of the country in which they receive treatment.

All this data will be helpful to researchers, businesses, and policymakers in the effort to better assess returns on medical-care spending. Information flowing from this new account also has potential implications for measuring inflation and productivity in the health-care sector.

As part of this project, BEA staff are researching important questions, including:

  • What’s the best method for determining treatment groupings and which treatments should be included in a specific disease category?
  • What are the relative merits of data sources currently available for this purpose? What advantages do large claims databases offer beyond what’s available in existing government surveys?
  • How can we best account for the impact of new technologies on patient outcomes? What methods are currently available for this purpose?


Publications and Working Papers