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MEPS HC-197I: Appendix to MEPS 2017 Event Files
HC-197A – HC-197H

August 2019

Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
5600 Fishers Lane
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
1.0 Household Component
2.0 Medical Provider Component
3.0 Survey Management and Data Collection
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Codebook Format
2.2 Variable Naming and Source
2.3 Contents of File 1: Condition-Event Link File (CLNK)
2.4 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)
2.5 2017 Condition-Event Frequency Table
3.0 Merging/Linking MEPS Data Files
3.1 Example A: Using the CLNK (HC-197IF1) and RXLK (HC-197IF2) Files with the Medical Conditions File (HC-199), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-197A and HC-197G)
3.2 Example B: Using the CLNK File (HC-197IF1) with the Medical Conditions File (HC-199) and the Prescribed Medicines Event File (HC-197A)
3.3 Example C: Using the CLNK File (HC-197IF1) with the Medical Conditions File (HC-199) and Office-Based Medical Provider Visits Event File (HC-197G)
3.4 Limitations/Caveats of the CLNK File
3.5 Limitations/Caveats of the RXLK File
3.6 National Health Interview Survey
3.7 Using MEPS Data for Trend Analysis
3.8 Longitudinal Analysis
Attachment 1: Sample SAS Jobs for Linking Example
Attachment 2: Sample STATA Jobs for Linking Example

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. Furthermore, linkage of the Medical Expenditure Panel Survey and the National Health Interview Survey may not occur outside the AHRQ Data Center, NCHS Research Data Center (RDC) or the U.S. Census RDC network.

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

1.0 Household Component

The Medical Expenditure Panel Survey (MEPS) provides nationally representative estimates of health care use, expenditures, sources of payment, and health insurance coverage for the U.S. civilian noninstitutionalized 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 subgroups. 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. NHIS introduced a new sample design in 2016 that discontinued oversampling of these minority groups. The linkage of the MEPS to the previous year’s NHIS provides additional data for longitudinal analytic purposes.

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2.0 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 can not accurately provide. This part of the MEPS is called the Medical Provider Component (MPC) and information is collected on dates of visits, 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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3.0 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. (MEPS HC) and Research Triangle Institute (MEPS MPC). 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. 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 Lane, Rockville, MD 20857 (301-427-1406).

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C. Technical and Programming Information

1.0 General Information

This documentation describes the MEPS Public Use Release HC-197I, which is the Appendix to MEPS releases HC-197A through HC-197H. This release contains two data files, both of which are provided in ASCII (with related SAS, SPSS, and Stata programming statements and data user information) and SAS versions: 1) the condition-event link file; and 2) the prescribed medicines-event link file. Also included in this release are the MEPS 2017 condition-event frequency tables.

This documentation offers a brief overview of the content and structure of the files and the accompanying codebook. It contains the following sections:

  • Data File Information
  • Merging/Linking MEPS Data Files
  • Sample SAS Jobs for Linking
  • Sample STATA Jobs for Linking

For more information on MEPS HC survey design see T. Ezzati-Rice, et al., 1998-2007 and S. Cohen, 1996. For information on the MEPS MPC design, see S. Cohen, 1998. These reports, along with a copy of the survey instruments used to collect the information on this file, are available on the MEPS website.

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2.0 Data File Information

This public use data set consists of two data files containing variables for linkage of the MEPS 2017 event-level data files. File 1, the H197IF1 or CLNK file, is used for linking the MEPS Conditions file with the MEPS event files; File 2, the H197IF2 or RXLK file, is used for linking the MEPS prescribed medicines event file with other MEPS event files.

The CLNK file contains 6 variables and has a logical record length of 59 with an additional 2-byte carriage return/line feed at the end of each record. The RXLK file contains 6 variables and has a logical record length of 59 with an additional 2-byte carriage return/line feed at the end of each record.

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2.1 Codebook Format

Each codebook describes an ASCII data set and provides the following programming identifiers for each variable:
Each codebook describes an ASCII data set and provides the following programming identifiers for each variable:

Identifier Description
Name Variable name (maximum of 8 characters)
Description Variable descriptor (maximum 40 characters)
Format Number of bytes
Type Type of data: numeric (indicated by NUM) or character (indicated by CHAR)
Start Beginning column position of variable in record
End Ending column position of variable in record

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2.2 Variable Naming and Source

In general, variable names reflect the content of the variable, with an 8 character limitation. All variables contained on Files 1 and 2 were derived from the CAPI.

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2.3 Contents of File 1: Condition-Event Link File (CLNK)

File 1 (H197IF1) or the CLNK file, contains the variables needed to link each record on the MEPS 2017 Conditions file, HC-199, with one or more records on the MEPS 2017 event files, HC-197A, and HC-197D through HC-197H. Section 3.0 contains additional information on completing this linkage.

The 8-character variable DUPERSID uniquely identifies each person represented on the file. There may be more than one record on the CLNK file for a specific DUPERSID value.

CONDIDX is the ID that uniquely identifies each condition for a person and corresponds to a unique record on the MEPS 2017 Conditions file, HC-199. There may be more than one record on the CLNK file for a specific CONDIDX value.

EVNTIDX is the 12-digit number that uniquely identifies each event for a person and corresponds to a unique record on one of the MEPS 2017 event files, HC-197B through HC-197H. (EVNTIDX is not included on the 2017 Prescribed Medicines event file, HC-197A; rather, on this file the variable for linking with EVNTIDX on the CLNK file is LINKIDX.) There may be more than one record on the CLNK file for a specific EVNTIDX value.

CLNKIDX is the 24-digit number that uniquely identifies each record on the CLNK file and is the combination of CONDIDX + EVNTIDX. There is just one record on this file for each value of CLNKIDX, i.e., each unique combination of CONDIDX + EVNTIDX.

The variable EVENTYPE indicates the type of event record identified by EVNTIDX, and has the following values:

  • 1 = MVIS – office-based medical provider visit event contained on MEPS release HC-197G
  • 2 = OPAT – outpatient department visit event contained on MEPS release HC-197F
  • 3 = EROM – emergency room visit event contained on MEPS release HC-197E
  • 4 = STAZ – inpatient hospital stay event contained on MEPS release HC-197D
  • 7 = HVIS – home health visit event contained on MEPS release HC-197H
  • 8 = PMED – prescribed medicines event contained on MEPS release HC-197A

PANEL is a constructed variable used to specify the panel number for the interview in which the condition was reported. PANEL will indicate either Panel 21 or Panel 22.

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2.4 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)

File 2 (H197IF2) or the RXLK file, contains the variables needed to link each record on the MEPS 2017 Prescribed Medicines file, HC-197A, with one or more records on the MEPS 2017 event files, HC-197B and HC-197D through HC-197G. Section 3.0 contains additional information on completing this linkage.

The 8-character variable DUPERSID uniquely identifies each person represented on the file. There may be more than one record on the RXLK file for a specific DUPERSID value.

EVNTIDX is the 12-digit number that uniquely identifies each event for a person and corresponds to a unique record on one of the MEPS 2017 event files, HC-197B through HC-197G. There may be more than one record on the RXLK file for a specific EVNTIDX value.

LINKIDX is the 12-digit number that identifies the record(s) on the prescribed medicines file, HC-197A that link to an event record. There may be more than one record on the RXLK file for a specific LINKIDX value, and there may be more than one record on the HC-197A file for a specific LINKIDX value.

RXLKIDX is the 24-digit number that uniquely identifies each record on the RXLK file, and is the combination of EVNTIDX + LINKIDX. There is just one record on this file for each value of RXLKIDX, i.e., each unique combination of EVNTIDX + LINKIDX.

The variable EVENTYPE indicates the type of event record identified by EVNTIDX, and has the following values:

  • 1 = MVIS – office-based medical provider visit event contained on MEPS release HC-197G
  • 2 = OPAT – outpatient department visit event contained on MEPS release HC-197F
  • 3 = EROM – emergency room visit event contained on MEPS release HC-197E
  • 4 = STAZ – inpatient hospital stay event contained on MEPS release HC-197D
  • 5 = DVIS – dental visit event contained on MEPS release HC-197B

For 1996-2004, records for purchases of insulin and diabetic supplies in a round were included in the Other Medical Expenses event files. Beginning with the 2005 file, these records are not included in the Other Medical Expenses file because the expenditures have always been included in the Prescribed Medicines file. As a consequence, there are no records in this file where the variable EVENTYPE = 6, the value used in 1996-2004 to identify OMED type of event record.

PANEL is a constructed variable used to specify the panel number for the interview in which the condition was reported. PANEL will indicate either Panel 21 or Panel 22.

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2.5 2017 Condition-Event Frequency Table

Table 1 included with this document contains the MEPS 2017 Condition-Event Frequencies. The frequency tables contain unweighted and weighted counts of records on the MEPS 2017 event files, HC-197A through HC-197H, for each of the condition codes contained on the MEPS 2017 Conditions file, HC-199.

Beginning FY16, condition names are no longer coded to procedure codes, and ICD9PROX has been dropped from the conditions file. Also beginning in FY16, ICD-9-CM codes are no longer used and the variable ICD9CODX has been dropped from the conditions file. Medical conditions now are coded to ICD-10-CM codes (ICD10CDX). For more information on ICD-10-CM codes, see the HC-199 documentation.

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3.0 Merging/Linking MEPS Data Files

This section provides information on using each of the two HC-197I files, RXLK and CLNK, to link with the files contained in MEPS releases HC-199 and HC-197A, HC-197B, and HC-197D through HC-197H. The linking procedure is described using several examples of deriving MEPS-based estimates. Also included in this section are several caveats related to using the RXLK and CLNK files.

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3.1 Example A: Using the CLNK (HC-197IF1) and RXLK (HC-197IF2) Files with the Medical Conditions File (HC-199), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-197A and HC-197G)

This example calculates the total expenditures for prescribed medicines associated with office-based medical provider visits for asthma, using these files: the Conditions file (HC-199), the CLNK file (HC-197IF1), the office-based medical provider visit event file (HC-197G), the RXLK file (HC-197IF2), and the prescribed medicines event file (HC-197A). It includes the following major steps:

  1. From the HC-199 file, select only records with condition coded as asthma.

  2. Use the CLNK file to obtain unique record IDs of events which are linked to each of the selected asthma condition records.

  3. From the HC-197G file, select only records for non-telephone office-based medical provider visits for persons with a positive weight.

  4. Using the selected record IDs obtained from the CLNK file, with the selected HC-197G records, identify only those visits which were for asthma.

  5. Use the RXLK file with the selected visit records which were for asthma to obtain unique record IDs of prescribed medicine records from file HC-197A linked to those visits.

  6. Using these record IDs, obtain the linked records from the HC-197A file and calculate the weighted mean of the expenditure variable.

Attachment 1 contains a copy of the SAS job for this example. Attachment 2 contains a copy of the STATA job for this example.

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3.2 Example B: Using the CLNK File (HC-197IF1) with the Medical Conditions File (HC-199) and the Prescribed Medicines Event File (HC-197A)

This example calculates the total expenditure for prescribed medicines associated with asthma, using the Conditions file (HC-199), the CLNK file (HC-197IF1) and the prescribed medicines event file (HC-197A). It includes the following major steps:

  1. From the HC-199 file, select only records with condition coded as asthma.

  2. Use the CLNK file to obtain unique record IDs of events which are linked to each of the asthma condition records.

  3. Using these record IDs, obtain linked records from the HC-197A file and calculate the weighted mean of the expenditure variable.

Attachment 1 contains a copy of the SAS job for this example. Attachment 2 contains a copy of the STATA job for this example.

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3.3 Example C: Using the CLNK File (HC-197IF1) with the Medical Conditions File (HC-199) and Office-Based Medical Provider Visits Event File (HC-197G)

This example calculates the total expenditures for office-based medical provider visits associated with asthma, using the Conditions file (HC-199), the CLNK file (HC-197IF1) and the office-based medical provider visits event file (HC-197G). It includes the following major steps:

  1. From the HC-199 file, select only records with condition coded as asthma.

  2. Use the CLNK file to obtain unique record IDs of events which are linked to each of the asthma condition records.

  3. From the HC-197G file, select only records for non-telephone office-based medical provider visits for persons with a positive weight.

  4. Using the selected record IDs obtained from the CLNK file, with the selected HC-197G records, identify only those visits which were for asthma and calculate the weighted mean of the expenditure variable.

Attachment 1 contains a copy of the SAS job for this example. Attachment 2 contains a copy of the STATA job for this example.

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3.4 Limitations/Caveats of the CLNK File

When using the CLNK file, analysts should keep in mind that (1) conditions are self-reported and (2) there may be multiple conditions associated with an event. Users should also note that not all events link to the Conditions file.

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3.5 Limitations/Caveats of the RXLK File

When using the RXLK file, analysts should keep in mind that one event record can link to more than one prescribed medicine record. Conversely, a prescribed medicine record may link to more than one event record in the same event file and/or more than one event record in other event files. When this occurs, it is up to the analyst to determine how the prescribed medicine expenditures should be allocated among those medical events.

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3.6 National Health Interview Survey

Data from this file can be used alone or in conjunction with other files for different analytic purposes. Each MEPS panel can also be linked back to the previous years’ National Health Interview Survey public use data files. For information on obtaining MEPS/NHIS link files please see the MEPS website.

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3.7 Using MEPS Data for Trend Analysis

MEPS began in 1996, and the utility of the survey for analyzing health care trends expands with each additional year of data; however, there are a variety of methodological and statistical considerations when examining trends over time using MEPS. Tests of statistical significance should be conducted to assess the likelihood that observed trends may be attributable to sampling variation. The length of time being analyzed should also be considered. In particular, large shifts in survey estimates over short periods of time (e.g. from one year to the next) that are statistically significant should be interpreted with caution, unless they are attributable to known factors such as changes in public policy, economic conditions, or MEPS survey methodology. For example, as a result of improved methods for collecting priority conditions data implemented in 2007, prevalence measures prior to 2007 are not comparable to those from 2007 and beyond for many conditions. Users should refer to the documentation for the conditions file (HC-199) for details.

With respect to methodological considerations, in 2013 MEPS introduced an effort to obtain more complete information about health care utilization from MEPS respondents with full implementation in early 2014. This effort likely resulted in improved data quality and a reduction in underreporting in 2014, but could have some modest impact on analyses involving trends in utilization across years.

Changes to the MEPS survey instrument should also be considered when analyzing trends. Thus, the note on the title page of this document is repeated here:

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.

There are also statistical factors to consider in interpreting trend analyses. Looking at changes over longer periods of time can provide a more complete picture of underlying trends. Analysts may wish to consider using techniques to smooth or stabilize analyses of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97 versus 2011-12), working with moving averages or using modeling techniques with several consecutive years of MEPS data to test the fit of specified patterns over time. Finally, researchers should be aware of the impact of multiple comparisons on Type I error. Without making appropriate allowance for multiple comparisons, undertaking numerous statistical significance tests of trends increases the likelihood of concluding that a change has taken place when one has not.

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3.8 Longitudinal Analysis

Panel-specific longitudinal files are available for downloading in the data section of the MEPS Web site. For each panel, the longitudinal file comprises MEPS survey data obtained in Rounds 1 through 5 of the panel 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 full-year Consolidated files from the two years covered by that panel.

For more details or to download the data files, please see Longitudinal Data Files at the AHRQ website.

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Attachment 1. Sample SAS Jobs for Linking Example

Attachment 2. Sample STATA Jobs for Linking Example

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