September 2013
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406
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 2011 Condition-Event Frequency Table
3.0 Merging/Linking MEPS Data Files
3.1 Example A: Using the CLNK (HC-144IF1) and RXLK (HC-144IF2) Files with the Medical Conditions File (HC-146),
the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-144A and HC-144G)
3.2 Example B: Using the CLNK File (HC-144IF1) with the Medical Conditions File
(HC-146) and the Prescribed Medicines Event File (HC-144A)
3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-146) and Office-Based Medical Provider Visits Event File (HC-144G)
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: Clinical Classification Code to ICD-9-CM Code Crosswalk
Attachment 2: Sample SAS Jobs for Linking Example
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:
- No one is to use the data in this data set in any way except for statistical reporting and analysis; and
- 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
- 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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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 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 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 non-institutionalized 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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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 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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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 Web site: 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, 540 Gaither Road, Rockville, MD 20850 (301-427-1406).
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This documentation describes the MEPS Public Use Release HC-144I, which is the Appendix to MEPS releases HC-144A through HC-144H. 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 is a PDF file of the condition-event frequency table. Note that, as of 2008, Table 2, a utilization and expenditures summary table, is no longer available.
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
Crosswalk of Clinical Classification Codes to ICD-9-CM Codes
Sample SAS 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 Web site at the following address: meps.ahrq.gov.
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This public use data set consists of two data files containing variables for linkage of the MEPS 2011 event-level data files. File 1, the H144IF1 or CLNK file, is used for linking the MEPS Conditions file with the MEPS event files; File 2, the H144IF2 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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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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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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File 1 (H144IF1) or the CLNK file, contains the variables needed to link each record on the MEPS 2011 Conditions file, HC-146, with one or more records on the MEPS 2011 event files, HC-144A through HC-144H. 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 2011 Conditions file, HC-146. 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 2011 event files, HC-144B through HC 144H. (EVNTIDX is not included on the 2011 Prescribed Medicines event file, HC-144A; 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-144G
2 = OPAT – outpatient department visit event contained on MEPS release HC-144F
3 = EROM – emergency room visit event contained on MEPS release HC-144E
4 = STAZ – inpatient hospital stay event contained on MEPS release HC-144D
7 = HVIS – home health visit event contained on MEPS release HC-144H
8 = PMED – prescribed medicines event contained on MEPS release HC-144A
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 15 or Panel 16.
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File 2 (H144IF2) or the RXLK file, contains the variables needed to link each record on the MEPS 2011 Prescribed Medicines file, HC-144A, with one or more records on the MEPS 2011 event files, HC-144B and HC-144D through HC-144G. 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 2011 event files, HC-144B through HC 144G. 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-144A 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-144A 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-144G
2 = OPAT – outpatient department visit event contained on MEPS release HC-144F
3 = EROM – emergency room visit event contained on MEPS release HC-144E
4 = STAZ – inpatient hospital stay event contained on MEPS release HC-144D
5 = DVIS – dental visit event contained on MEPS release HC-144B
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 15 or Panel 16.
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Table 1 contains the MEPS 2011 Condition-Event Frequency table. This table contains unweighted and weighted counts of records on the MEPS 2011 event files, HC-144A through HC-144H, for each of the condition, procedure, and clinical classification codes contained on the MEPS 2011 Conditions file, HC-146. Attachment 1 contains a crosswalk of the clinical classification codes to ICD-9-CM codes.
Analysts should use the clinical classification codes listed in the Conditions PUF document (HC-146) and the Appendix to the Event Files (HC-144I) document when analyzing MEPS conditions data. Although there is a list of clinical classification codes and labels on the Healthcare Cost and Utilization Project (HCUP) Web site, if updates to these codes and/or labels are made on the HCUP Web site after the release of the 2011 MEPS PUFs, these updates will not be reflected in the 2011 MEPS data.
Note that, for conditions related to certain medical events, the ICD-9-CM codes on the Conditions file are also released in the Prescribed Medicines, Emergency Room Visits, Office-based Medical Provider Visits, Outpatient Department Visits, and Inpatient Hospital Stays Event Files. ICD-9-CM codes are collapsed into broader codes to ensure confidentiality. Because of this collapsing, it is possible for there to be duplicate ICD-9-CM condition or procedure codes linked to a single medical event when different fully-specified codes are collapsed into the same code. For more information on ICD-9-CM codes, see the HC-146 documentation.
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This section provides information on using each of the two HC-144I files, RXLK and CLNK, to link with the files contained in MEPS releases HC-146 and HC-144A through HC-144H. 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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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-146), the CLNK file (HC-144IF1), the office-based medical provider visit event file (HC-144G), the RXLK file (HC-144IF2), and the prescribed medicines event file (HC-144A). It includes the following major steps:
- From HC-146 file, select only records with condition coded as asthma.
- Use the CLNK file to obtain unique record IDs of events which are linked to each of the selected asthma condition records.
- From the HC-144G file, select only records for non-telephone office-based medical provider visits for persons with a positive weight.
- Using the selected record IDs obtained from the CLNK file, with the selected HC-144G records, identify only those visits which were for asthma.
- 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-144A linked to those visits.
- Using these record IDs, obtain the linked records from the HC-144A file and calculate the weighted mean of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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This example calculates the total expenditure for prescribed medicines associated with asthma, using the Conditions file (HC-146), the CLNK file (HC-144IF1) and the prescribed medicines event file (HC-144A). It includes the following major steps:
- From HC-146 file, select only records with condition coded as asthma.
- Use the CLNK file to obtain unique record IDs of events which are linked to each of the asthma condition records.
- Using these record IDs, obtain linked records from the HC-144A file and calculate the weighted mean of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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This example calculates the total expenditures for office-based medical provider visits associated with asthma, using the Conditions file (HC-146), the CLNK file (HC-144IF1) and the office-based medical provider visits event file (HC-144G). It includes the following major steps:
- From HC-146 file, select only records with condition coded as asthma.
- Use the CLNK file to obtain unique record IDs of events which are linked to each of the asthma condition records.
- From the HC-144G file, select only records for non-telephone office-based medical provider visits for persons with a positive weight.
- Using the selected record IDs obtained from the CLNK file, with the selected HC-144G records, identify only those visits which were for asthma and calculate the weighted mean of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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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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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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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 meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
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MEPS began in 1996, and the utility of the survey for analyzing health care trends expands with each additional year of data. However, it is important to consider a variety of factors when examining trends over time using MEPS. Statistical significance tests 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. 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 evaluate, smooth, or stabilize analyses of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97 versus 2010-11), 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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Panel specific longitudinal files are available for each panel. The longitudinal files consists of
MEPS survey data obtained in Rounds 1-5 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.
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