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MEPS HC-202: Panel 21 Longitudinal Data File

September 2019

Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
5600 Fishers Ln
Rockville, MD 20857
(301) 427-1406


NOTE: The MEPS instrument design changed beginning in Spring of 2018, affecting Panel 23 Round 1, Panel 22 Round 3, and Panel 21 Round 5. For the Full-Year 2017 PUFs, the Panel 22 Round 3 and Panel 21 Round 5 data were transformed to the degree possible to conform to the previous design. Data users should be aware of possible impacts on the data and especially trend analysis for these data years due to the design transition.

TABLE OF CONTENTS

A. Data Use Agreement
B. Background
B.1 Household Component
B.2 Medical Provider Component
B.3 Survey Management and Data Collection
C. Technical and Programming Information
C.1 General Information
C.2 Data File Information
C.2.1 Variables
C.2.1.1 Variables from Annual Full-year Consolidated Files
C.2.1.2 Constructed Variables for Selection of Group
C.2.1.3 Estimation Variables


A. Data Use Agreement

Individual identifiers have been removed from the micro data contained in these files. Nevertheless, under sections 308 (d) and 903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or the National Center for Health Statistics (NCHS) may not be used for any purpose other than for the purpose for which they were supplied; any effort to determine the identity of any reported cases is prohibited by law.

Therefore in accordance with the above referenced Federal Statute, it is understood that:

  1. No one is to use the data in this data set in any way except for statistical reporting and analysis; and

  2. If the identity of any person or establishment should be discovered inadvertently, then (a) no use will be made of this knowledge, (b) the Director Office of Management AHRQ will be advised of this incident, (c) the information that would identify any individual or establishment will be safeguarded or destroyed, as requested by AHRQ, and (d) no one else will be informed of the discovered identity; and

  3. No one will attempt to link this data set with individually identifiable records from any data sets other than the Medical Expenditure Panel Survey or the National Health Interview Survey.

By using these data you signify your agreement to comply with the above stated statutorily based requirements with the knowledge that deliberately making a false statement in any matter within the jurisdiction of any department or agency of the Federal Government violates Title 18 part 1 Chapter 47 Section 1001 and is punishable by a fine of up to $10,000 or up to 5 years in prison.

The Agency for Healthcare Research and Quality requests that users cite AHRQ and the Medical Expenditure Panel Survey as the data source in any publications or research based upon these data.

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B. Background

B.1 Household Component

The Medical Expenditure Panel Survey (MEPS) provides nationally representative estimates of healthcare use, expenditures, sources of payment, and health insurance coverage for the U.S. civilian non-institutionalized population. The MEPS Household Component (HC) also provides estimates of respondents' health status, demographic and socio economic characteristics, employment, access to care, and satisfaction with health care. Estimates can be produced for individuals, families, and selected population sub-groups. The panel design of the survey, which includes 5 Rounds of interviews covering 2 full calendar years, provides data for examining person level changes in selected variables such as expenditures, health insurance coverage, and health status. Using computer assisted personal interviewing (CAPI) technology, information about each household member is collected, and the survey builds on this information from interview to interview. All data for a sampled household are reported by a single household respondent.

The MEPS-HC was initiated in 1996. Each year a new panel of sample households is selected. Because the data collected are comparable to those from earlier medical expenditure surveys conducted in 1977 and 1987, it is possible to analyze long-term trends. Each annual MEPS HC sample size is about 15,000 households. Data can be analyzed at either the person or event level. Data must be weighted to produce national estimates.

The set of households selected for each panel of the MEPS HC is a subsample of households participating in the previous year's National Health Interview Survey (NHIS) conducted by the National Center for Health Statistics. The NHIS sampling frame provides a nationally representative sample of the U.S. civilian noninstitutionalized population and reflects an oversample of blacks and Hispanics. In 2006, the NHIS implemented a new sample design, which included Asian persons in addition to households with black and Hispanic persons in the oversampling of minority populations. MEPS further oversamples additional policy relevant sub-groups such as low income households. The linkage of the MEPS to the previous year’s NHIS provides additional data for longitudinal analytic purposes.

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B.2 Medical Provider Component

Upon completion of the household CAPI interview and obtaining permission from the household survey respondents, a sample of medical providers are contacted by telephone to obtain information that household respondents cannot accurately provide. This part of the MEPS is called the Medical Provider Component (MPC) and information is collected on dates of visit, diagnosis and procedure codes, charges and payments. The Pharmacy Component (PC), a subcomponent of the MPC, does not collect charges or diagnosis and procedure codes but does collect drug detail information, including National Drug Code (NDC) and medicine name, as well as date filled and sources and amounts of payment. The MPC is not designed to yield national estimates. It is primarily used as an imputation source to supplement/replace household reported expenditure information.

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B.3 Survey Management and Data Collection

MEPS HC and MPC data are collected under the authority of the Public Health Service Act. Data are collected under contract with Westat, Inc. Data sets and summary statistics are edited and published in accordance with the confidentiality provisions of the Public Health Service Act and the Privacy Act. The National Center for Health Statistics (NCHS) provides consultation and technical assistance.

As soon as data collection and editing are completed, the MEPS survey data are released to the public in staged releases of summary reports, micro data files, and tables via the MEPS website: https://meps.ahrq.gov. Selected data can be analyzed through MEPSnet, an on-line interactive tool designed to give data users the capability to statistically analyze MEPS data in a menu driven environment.

Additional information on MEPS is available from the MEPS project manager or the MEPS public use data manager at the Center for Financing Access and Cost Trends, Agency for Healthcare Research and Quality, 5600 Fishers Ln, Rockville, MD 20857 (301-427-1406).

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C. Technical and Programming Information

C.1 General Information

This documentation describes the Panel 21 longitudinal data file from the Medical Expenditure Panel Survey Household Component (MEPS-HC). Released as an ASCII file (with related SAS, STATA, and SPSS programming statements and data use information) and a SAS transport dataset, this public use file provides information collected on a nationally representative sample of the civilian noninstitutionalized population of the United States for the two-year period 2016-2017. The file contains 3,324 variables and has a logical record length of 9,195 with an additional 2-byte carriage return/line feed at the end of each record.

This file consists of MEPS survey data obtained in Rounds 1-5 of MEPS Panel 21 and can be used to analyze changes over a two-year period. Variables in the file pertaining to survey administration, demographics, employment, health status, disability days, quality of care, patient satisfaction, health insurance and medical care use and expenditures were obtained from the MEPS 2016 and 2017 Full-Year Consolidated Files (HC-192 and HC-202, respectively).

The following documentation offers a brief overview of the contents and structure of the files and programming information. A codebook of all the variables included in the Panel 21 data file is provided in a separate file (H202CB.PDF). A database of all MEPS products released to date and a variable locator indicating the major MEPS data items on public use files that have been released to date can be found on the MEPS website: https://meps.ahrq.gov.

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C.2 Data File Information

This public use file contains records for 15,617 persons in Panel 21 who were respondents for the period they were in-scope for the survey (i.e., a member of the civilian non-institutionalized population) during the two-year period. Only persons with positive person-level weights (PERWT16F or PERWT17F) are included in the longitudinal PUF data. Data are available for all five rounds for 92.4% of the cases (14,431). The remaining 7.6% (1,186 persons) do not have data for one or more rounds but were in-scope for all rounds they participated in the survey. These persons are those who were born, died, were in the military or an institution, or left the country during the two-year period. In contrast, persons in the panel who participated in the survey for only part of the period they were in-scope are not included in this file. To compensate for this attrition, adjustments were made in the construction of the panel weight variable included in this file (LONGWT). The codebook provides both weighted and unweighted frequencies for each variable on the data file. The LONGWT variable should be used to produce national estimates for the two-year period.

Each MEPS panel can be linked back to the previous year's National Health Interview Survey public use data files. For information on obtaining MEPS/NHIS link files please see https://meps.ahrq.gov/mepsweb/data_stats/more_info_download_data_files.jsp.

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C.2.1 Variables

C.2.1.1 Variables from Annual Full-year Consolidated Files

Most variables on this file were obtained from the MEPS 2016 and 2017 Full-Year Consolidated Files (HC-192 and HC-202, respectively). However, names for time dependent variables from these files were modified in order to: 1) eliminate duplicate variable names for data reflecting different time periods during the panel, and 2) standardize variable names to facilitate pooling of multiple MEPS panels for analysis.1 Generally, annual variables with a suffix of “16” and “17” are renamed with a suffix of “Y1” and “Y2”, respectively. Variables with a suffix of “31”, “42”, and “53” are renamed with a suffix denoting the round the data was collected (i.e., “1” , “2” or “3” for variables originating from Rounds 1-3 on the 2016 full-year file and “3”, “4”, or “5” for variables originating from Rounds 3-5 on the 2017 full-year file).2 It is necessary to use this crosswalk in conjunction with documentation for the 2016 and 2017 full-year consolidated files to obtain a full description of variables on this file. Table 1 below provides the crosswalk summarizing the scheme used for renaming variables from the annual files.

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Table 1: Crosswalk of Variable Names between the Full-Year Consolidated Files and the Longitudinal File
Type of Variable Full-Year Consolidated File Variable Name Suffix Longitudinal File Variable Name Suffix Specific cases or examples
Constant (i.e., not round or year specific) No suffixes No suffixes All variables:
DOBMM=DOBMM
DOBYY=DOBYY
DUID=DUID
PID=PID
DUPERSID=DUPERSID
EDUCYR=EDUCYR
HIDEG=HIDEG
HISPANX=HISPANX
HISPNCAT=HISPNCAT
INTVLANG=INTVLANG
RACEAX=RACEAX
RACEBX=RACEBX
RACEWX=RACEWX
RACEV1X=RACEV1X
RACEV2X=RACEV2X
RACETHX=RACETHX
SEX=SEX
VARPSU=VARPSU
VARSTR=VARSTR
PANEL=PANEL
BORNUSA=BORNUSA
HWELLSPE=HWELLSPE
LANGSPK=LANGSPK
OTHLANG=OTHLANG
YRSINUS=YRSINUS
Annual, family related variables YR Y1 or YR1 All variables:
FAMIDYR=FAMIDYR1 (2016 file)
FAMRFPYR=FAMRFPY1 (2016 file)
FAMSZEYR=FAMSZYR1 (2016 file)
Y2 or YR2 All variables:
FAMIDYR=FAMIDYR2 (2017 file)
FAMRFPYR=FAMRFPY2 (2017 file)
FAMSZEYR=FAMSZYR2 (2017 file)
Annual, CPS family identifiers No suffix Y1 All variables:
CPSFAMID=CPSFAMY1 (2016)
Y2 All variables:
CPSFAMID=CPSFAMY2 (2017)
Annual, health insurance eligibility units No suffix Y1 All variables:
HIEUIDX=HIEUIDY1 (2016)
Y2 All variables:
HIEUIDX=HIEUIDY2 (2017)
Annual, inscope variables No suffixes YR1 All variables:
INSCOPE=INSCPYR1 (2016 file)
YR2 All variables:
INSCOPE=INSCPYR2 (2017 file)
12/31 status variables 1231 in 2016 file Y1 All variables:
FAMS1231=FAMSY1 (2016 file)
FCRP1231=FCRPY1 (2016 file)
FCSZ1231=FCSZY1 (2016 file)
FMRS1231=FMRSY1 (2016 file)
INSC1231=INSCY1 (2016 file)
1231 in 2017 file Y2 All variables:
FAMS1231=FAMSY2 (2017 file)
FCRP1231=FCRPY2 (2017 file)
FCSZ1231=FCSZY2 (2017 file)
FMRS1231=FMRSY2 (2017 file)
INSC1231=INSCY2 (2017 file)
Annual 16, 16X, 16F, or 16C Y1, Y1X, Y1F, or Y1C Examples:
TOTEXP16=TOTEXPY1
AGE16X=AGEY1X
17, 17X, 17F, or 17C Y2, Y2X, Y2F, or Y2C Examples:
TOTEXP17=TOTEXPY2
AGE17X=AGEY2X
Variables for health insurance prior to January 1, 2016 (data collected in round 1 only) No suffixes No suffixes All variables:
PREVCOVR=PREVCOVR
COVRMM=COVRMM
COVRYY=COVRYY
WASESTB=WASESTB
WASMCARE=WASMCARE
WASMCAID=WASMCAID
WASCHAMP=WASCHAMP
WASVA=WASVA
WASPRIV=WASPRIV
WASOTGOV=WASOTGOV
WASAFDC=WASAFDC
WASSSI=WASSSI
WASSTAT1=WASSTAT1
WASSTAT2=WASSTAT2
WASSTAT3=WASSTAT3
WASSTAT4=WASSTAT4
WASOTHER=WASOTHER
NOINSBEF=NOINSBEF
NOINSTM=NOINSTM
NOINUNIT=NOINUNIT
MORECOVR=MORECOVR
INSENDMM=INSENDMM
INSENDYY=INSENDYY
Annual No suffixes3 Y1 All variables:
KEYNESS=KEYNESY1 (2016 file)
SAQELIG=SAQELIY1 (2016 file)
EVRWRK=EVRWRKY1 (2016 file)
EVRETIRE=EVRETIY1 (2016 file)
AGELAST=AGELSTY1 (2016 file)
Y2 All variables:
KEYNESS=KEYNESY2 (2017 file)
SAQELIG=SAQELIY2 (2017 file)
EVRWRK=EVRWRKY2 (2017 file)
EVRETIRE=EVRETIY2 (2017 file)
AGELAST=AGELSTY2 (2017 file)
Monthly 2-character month + 16 2-character month + Y1 Examples:
PRIJA16=PRIJAY1 (2016 file)
2-character month + 17 2-character month + Y2 Examples:
PRIJA17=PRIJAY2 (2017 file)
Round Specific 31, 31X, or 31H in 2016
42, 42X, or 42H in 2016
53, 53X, or 53H in 2016
1, 1X, 1H for 2016
2, 2X, 2H for 2016
3, 3X, 3H for 2016
Examples:
RTHLTH31=RTHLTH1 (2016 file)
RTHLTH42=RTHLTH2 (2016 file)
RTHLTH53=RTHLTH3 (2016 file if YEARIND=2)
31, 31X, or 31H in 2017
42, 42X, or 42H in 2017
53, 53X, or 53H in 2017
3, 3X, 3H for 2017
4, 4X, 4H for 2017
5, 5X, 5H for 2017
Examples:
RTHLTH31=RTHLTH3 (2017 file if YEARIND=1 or 3)
RTHLTH42=RTHLTH4 (2017 file)
RTHLTH53=RTHLTH5 (2017 file)
Diabetes preventive care 1553, 1653, and 1753 in 2016 file Y0R3 for 2015
Y1R3 for 2016
Y2R3 for 2017
Examples:
DSEB1553=DSEBY0R3 (2016 file)
DSEY1553=DSEYY0R3 (2016 file)
DSEY1653=DSEYY1R3 (2016 file)
DSEY1753=DSEYY2R3 (2016 file)
1653, 1753, and 1853 in 2017 file Y1R5 for 2016
Y2R5 for 2017
Y3R5 for 2018
Examples:
DSEB1653=DSEBY1R5 (2017 file)
DSEY1653=DSEYY1R5 (2017 file)
DSEY1753=DSEYY2R5 (2017 file)
DSEY1853=DSEYY3R5 (2017 file)
Job Change 3142
4253
12 for 2016
23 for 2016
All cases:
CHGJ3142=CHGJ12 (2016 file)
CHGJ4253=CHGJ23 (2016 file)
YCHJ3142=YCHJ12 (2016 file)
YCHJ4253=YCHJ23 (2016 file)
34 for 2017
45 for 2017
All cases:
CHGJ3142=CHGJ34 (2017 file)
CHGJ4253=CHGJ45 (2017 file)
YCHJ3142=YCHJ34 (2017 file)
YCHJ4253=YCHJ45 (2017 file)
Cancer/Cancer in remission4 No suffixes5 Y1 for 2016 Example:
CALUNG=CALUNGY1 (2016 file)
Y2 for 2017 Example:
CALUNG=CALUNGY2 (2017 file)
Age of Diagnosis No suffixes5 Y1 for 2016 Example:
CHDAGED=CHDAGY1 (2016 file)
CHOLAGED=CHOLAGY1 (2016 file)
Y2 for 2017 Example:
CHDAGED=CHDAGY2 (2017 file)
CHOLAGED=CHOLAGY2 (2017 file)

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C.2.1.2 Constructed Variables for Selection of Group
The following eight variables were constructed and included on the file to facilitate the selection of appropriate cases for various analyses. Table 2 below contains descriptive statistics for these variables.

YEARIND 1=both years, 2=in 2016 only, and 3=in 2017 only
ALL5RDS Inscope and data collected in all 5 rounds (0=no, 1=yes)
DIED Died during the two-year survey period (0=no, 1=yes)
INST Institutionalized for some time during the two-year survey period (0=no, 1=yes)
MILITARY Active duty military for some time during the two-year survey period (0=no, 1=yes)
ENTRSRVY Entered survey after beginning of panel (mainly births; also includes persons
who had no initial chance of selection who moved into a MEPS sample household) (0=no, 1=yes)
LEFTUS Moved out of the country after beginning of panel (0=no, 1=yes)
OTHER Not identified in any of the above analytic groups (0=no, 1=yes)


Table 2: Frequencies and Percentage for Constructed Variables

Variable Number of Records Percentage of Records (N=15,617)
YEARIND=1 (i.e., person in both years) 15,252 97.7
ALL5RDS=1 (yes) 14,431 92.4
DIED=1 (yes) 185 1.2
INST=1 (yes) 44 0.3
MILITARY=1 (yes) 33 0.2
ENTRSRVY=1 (yes) 790 5.1
LEFTUS=1 (yes) 73 0.5
OTHER=1 (yes) 77 0.5

Following are examples of situations where these variables would be useful in selecting records for analysis:

  • Analysts interested in working only with persons who were in-scope and had data for all five rounds of the panel should subset to cases where ALL5RDS=1.
  • If a researcher wanted to include persons who were in-scope and had data for all five rounds of the panel as well as those in the survey at the beginning of the panel who subsequently died, then they would include cases where ALL5RDS=1 or (ENTRSRVY=0 and DIED=1).
  • If a researcher wanted to include persons who were in-scope and had data for all five rounds of the panel as well as those who died in the second year of the panel, then they would include cases where ALL5RDS=1 or (DIED=1 and YEARIND=1).

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C.2.1.3 Estimation Variables

Longitudinal Estimations for Panel 21
The file contains a weight variable (LONGWT) and variance estimation variables (VARSTR, VARPSU) that should be applied when producing national estimates for longitudinal analyses. For example, LONGWT applied to the 14,431 cases where ALL5RDS=1 produces a weighted population estimate of 303.3 million. This represents an estimate of the number of persons in the civilian noninstitutionalized population for the entire two-year period from 2016-2017. To obtain estimates of variability (such as the standard error of sample estimates or corresponding confidence intervals) for estimates based on MEPS survey data, one needs to take into account the complex sample design of MEPS by specifying the estimation variables including stratum of sample selection (VARSTR), primary sampling unit (VARPSU) and longitudinal weight (LONGWT).

This longitudinal file also contains a longitudinal SAQ weight variable (LSAQWT). This weight variable should be used to perform longitudinal analyses involving any variables from the self-administered questionnaire (SAQ) which was administered to persons age 18 and older in both rounds 2 and 4 of the survey. The variable SAQRDS24 can be used to identify which persons have SAQ data for both versus only one of the two rounds. The estimated population size (i.e. sum of LSAQWT values) for analyses based on the 9,486 cases with SAQ data for both rounds (i.e., SAQRDS24=1) is 228,056,818.

Pooled Estimations
When analyzing subpopulations and/or low prevalence events, it may be desirable to pool together more than one panel of MEPS-HC data to yield sample sizes large enough to generate reliable estimates. If only data from Panels 7 and beyond are being pooled, then simply use the strata and PSU variables (VARSTR, VARPSU) 6 provided on the longitudinal files for pooled estimation. However, because Panels 1-6 MEPS longitudinal weight files were released with panel-specific variance structures, it is necessary to obtain the set of appropriate variance estimation variables from the HC-036 Pooled Estimation File when pooling involves these panels.



1 A variable named PANEL is also included to facilitate pooling across panels. This variable is simply the panel number and is therefore constant across all records within a longitudinal file.

2 While round 3 values were obtained for most observations from the 2017 Full Year Consolidated File, they were obtained from the 20156 Full Year Consolidated File for sample persons where YEARIND=2 (i.e., in 2015 only).

3 To maintain the 8-character naming convention, some variable names had the last character or two dropped in the renaming process.

4 Starting in 2010, variables were added to indicate whether each reported cancer was in remission.

5 To maintain the 8-character naming convention, some variable names had the last character or two dropped in the renaming process.

6 Note that variable names for strata and PSU are VARSTR and VARPSU respectively in longitudinal files for panel 9 and beyond. These variables were named differently in the longitudinal files for panel 7 (VARSTRP7, VARPSUP7) and panel 8 (VARSTRP8, VARPSUP8) and need to be standardized when pooling with subsequent panels.

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