Loading MEPS data
SAS transport files (1996-2017)
ASCII (.dat) files
Automating file download
Saving Stata data (.dta)
Stata svy commands
Stata examples
Workshop Exercises
Summary tables examples
IMPORTANT! Starting in 2018, the SAS Transport formats for MEPS Public Use Files were converted from the SAS XPORT to the SAS CPORT engine (excluding the 2018 Point-in-Time file, HC-036, and HC-036BRR). These CPORT data files cannot be read directly into Stata at this time. The ASCII data file format (.dat) must be used instead. This requirement also applies to the 2017 Full-Year Consolidated file (HC-201).
Stata users can download MEPS files using the SAS transport (.ssp) format for data years 1996-2017, or the ASCII (.dat) data files. Note that the case of variable names may differ depending on which type of data file is used. Loading SAS transport (.ssp) files typically results in all lowercase variable names, while the Stata programming statements used to import ASCII (.dat) files will generally create uppercase variable names. Users may wish to use the rename *, lower command to convert all variables to lowercase for consistency.
In Stata, SAS transport (.ssp) files can be loaded using the import command (for 1996-2017 PUFs). In the following example, the transport file for the 2017 Dental Visits file h197b.ssp has been downloaded from the MEPS website, unzipped, and saved in the local directory C:\MEPS\DATA (click here for details).
/* Note: for Stata version 15 or earlier, use sasxport instead of sasxport5 */
set more off
import sasxport5 "C:\MEPS\DATA\h197b.ssp"
/* View dataset */
browseStarting in 2018, design changes in the MEPS survey instrument resulted in SAS transport files being converted from the XPORT to the CPORT format (excluding the 2018 Point-in-Time file, HC-036, and HC-036BRR). These CPORT file types are not readable by Stata at this time. Thus, the ASCII (.dat) files must be used instead. This requirement also applies to the 2017 Full-Year Consolidated file (HC-201).
The following example imports the 2018 Dental visits ASCII file (h206b.dat) by running the Stata programming statements provided on the MEPS website.
IMPORTANT! The Stata programming statements in the .txt file below require that the ASCII (.dat) file is stored in the C:/MEPS/DATA directory. If that is not possible, the user must navigate to the Stata programming statements (.txt file) for each needed MEPS data file, and follow the instructions for loading the ASCII file into Stata. For example, for the 2018 dental visits file, instructions can be found at: https://meps.ahrq.gov/data_stats/download_data/pufs/h206b/h206bstu.txt
set more off
do "https://meps.ahrq.gov/data_stats/download_data/pufs/h206b/h206bstu.txt"
/* View dataset */
browse
/* Optional: convert all variable names to lower-case */
rename *, lowerInstead of having to manually download, unzip, and store MEPS data files in a local directory, it may be beneficial to automatically download MEPS data directly from the MEPS website. This can be accomplished using the copy and unzipfile commands.
The following code downloads the 2017 Dental Visits (h197b.ssp) directly from the MEPS website and stores it in the "C:/MEPS/DATA" folder. The import command is then used to read the .ssp file into Stata:
/* 2017 Dental Visits */
copy "https://meps.ahrq.gov/mepsweb/data_files/pufs/h197bssp.zip" ///
"C:/MEPS/DATA/h197bssp.zip"
/* Note: for Stata version 15 or earlier, use sasxport instead of sasxport5 */
unzipfile "C:/MEPS/DATA/h197bssp.zip"
import sasxport5 "h197b.ssp", clear
/* View dataset */
browseThis example downloads the 2018 Dental Visits file (h206b.dat) and calls the Stata programming statements from the MEPS website to load the ASCII (.dat) file.
IMPORTANT! The Stata programming statements in the .txt file below require that the ASCII (.dat) file is stored in the C:/MEPS/DATA directory. If that is not possible, the user must navigate to the Stata programming statements (.txt file) for each needed MEPS data file, and follow the instructions for loading the ASCII file into Stata. For example, for the 2018 dental visits file, instructions can be found at: https://meps.ahrq.gov/data_stats/download_data/pufs/h206b/h206bstu.txt
/* 2018 Dental Visits */
copy "https://meps.ahrq.gov/mepsweb/data_files/pufs/h206bdat.zip" ///
"C:/MEPS/DATA/h206bdat.zip"
unzipfile "C:/MEPS/DATA/h206bdat.zip"
do "https://meps.ahrq.gov/data_stats/download_data/pufs/h206b/h206bstu.txt"
/* View dataset */
browse
/* Optional: convert all variable names to lower-case */
rename *, lower
To download additional files programmatically, replace 'h197b' (for 1996-2017 data) or 'h206b' (for 2018 and later) with the desired filename (see meps_files_names.csv for a list of MEPS file names by data type and year).
Once the MEPS data has been loaded into R using either of the two previous methods, it can be saved as a permanent Stata dataset (.dta). In the following code, the h197b dataset is saved in the 'Stata\data' folder (first create the 'Stata\data' folder if needed):
save "C:\MEPS\Stata\data\h197b.dta"
clearTo analyze MEPS data using Stata, svy commands should be used to ensure unbiased estimates. As an example, the following code will estimate the total dental expenditures in 2017:
use dupersid perwt17f varpsu varstr dvxp17x using "C:\MEPS\Stata\data\h197b.dta", clear
svyset varpsu [pweight=perwt17f], str(varstr)
svy: total dvxp17xIn order to run the example codes, you must download the relevant MEPS files from the MEPS website and save them to your local computer, as described above.
The following example codes from previous MEPS workshops are provided in the workshop_exercises folder:
Exercise1a.do: National health care expenses by age group, 2016
Exercise1b.do: National health care expenses by age group and type of service, 2015
Exercise1c.do: National health care expenses by age group, 2018
Exercise2a.do: Trends in antipsychotics purchases and expenses, 2015
Exercise2b.do: Purchases and expenses for narcotic analgesics or narcotic analgesic combos, 2016
Exercise2c.do: Purchases and expenses for narcotic analgesics or narcotic analgesic combos, 2018
Exercise3a.do: Use and expenditures for persons with diabetes, 2015
Exercise3b.do: Expenditures for all events associated with diabetes, 2015
Exercise4a.do: Pooling MEPS FYC files, 2015 and 2016
Exercise4b.do: Pooling longitudinal files, panels 17-19
Exercise4b.do: Pooling MEPS FYC files, 2017 and 2018: People with joint pain, using JTPAIN31 for 2017 and JTPAIN31_M18 for 2018
Exercise5a.do: Constructing family-level variables from person-level data, 2015
Exercise5b.do: Constructing insurance status from monthly insurance variables, 2015
Exercise6.do: Logistic regression to identify demographic factors associated with receiving a flu shot in 2018 (using SAQ population)
The following codes provided in the summary_tables_examples folder re-create selected statistics from the MEPS online summary tables. These example codes are written under the assumption that the .ssp files are saved in the local directory "C:/MEPS/". However, you can customize the programs to point to an alternate directory.
care1_child_dental.do: Children with dental care, by poverty status, 2016
care2_diabetes_a1c.do: Adults with diabetes receiving hemoglobin A1c blood test, by race/ethnicity, 2016
care3_access.do: Ability to schedule a routine appointment, by insurance coverage, 2016
cond1_expenditures.do: Utilization and expenditures by medical condition, 2015
ins1_age.do: Health insurance coverage by age group, 2016
pmed1_therapeutic_class.do: Purchases and expenditures by Multum therapeutic class, 2016
pmed2_prescribed_drug.do: Purchases and expenditures by generic drug name, 2016
use1_race_sex.do: Utilization and expendiutres by race and sex, 2016
use2_expenditures.do: Expenditures for office-based and outpatient visits, by source of payment, 2016
use3_events.do: Number of events and mean expenditure per event, for office-based and outpatient events, by source of payment, 2016