Medical conditions pulse

These MEPS summary tables provide statistics on the number of people with care for medical conditions, health care utilization, total expenditures, and mean expenditures per person by medical condition. Data can be viewed over time or for a single year by event type (such as prescription medicines or outpatient events), source of payment (such as Medicare or Medicaid), or demographic characteristics (such as age, race, or sex).

Use the options below to select a statistic of interest, data view ("Trends over time" or "Cross-sectional"), and data years. If you select "Trends over time", you can choose a range of years. The "Cross-sectional" view displays a single year, which can be stratified by a grouping variable. Once a grouping variable is selected, a dropdown will appear, enabling selection of specific levels in each group.

After you select the available options, the table will automatically be updated. The table can be sorted by condition name or data value by clicking on the column header. To view the data as a plot, with line graphs for trends over time and grouped bar graphs for the cross-sectional view, select up to 10 rows by clicking in the table. The "Code" tab displays R and SAS code needed to replicate the data shown in the table. The generated table, plot, and codes can be downloaded with the download button under each tab. To view standard errors in the table or 95% confidence intervals in the plot, select the "Show standard errors" checkbox.

Select data view:
Select years
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To activate the 'plot' tab, select up to 10 rows by clicking in the table below.

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Please choose items to plot by selecting rows under the Table tab.

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Download code

To run the code, first download and unzip the required public use data files from the MEPS data files page, and save them to your computer. More information on downloading and analyzing MEPS data in R, SAS, and Stata can be found at the AHRQ GitHub site External Link. Note that some standard error estimates may differ between R and SAS, since SAS doesn't support any options to adjust for lonely PSUs.

The following code can be used to generate the selected estimates, where the SAS transport data files (.ssp) have been saved to the folder 'C:\MEPS'. For trend estimates, example code is shown for the most recent year selected:



This tool is provided as a convenience. It is the responsibility of the user to review results for statistical significance and overall reasonableness.

About the data

The MEPS Household Component collects data on all members of sample households who are in-scope for the survey. These data can be used to produce nationally representative estimates of medical conditions, health status, use of medical care services, charges and payments, access to care, experience with care, health insurance coverage, income, and employment. The target population represented in the tables and figures is persons in the U.S. civilian non-institutionalized population for all or part of the year.

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