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September 2015
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 2013 Condition-Event Frequency Table
3.0 Merging/Linking MEPS Data Files
3.1 Example A: Using the CLNK (HC-160IF1) and RXLK (HC-160IF2) Files with the Medical Conditions File (HC-162), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-160A and HC-160G)
3.2 Example B: Using the CLNK File (HC-160IF1) with the Medical Conditions File (HC-162) and the Prescribed Medicines Event File (HC-160A)
3.3 Example C: Using the CLNK File (HC-160IF1) with the Medical Conditions File (HC-162) and Office-Based Medical Provider Visits Event File (HC-160G)
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-160I, which is the Appendix to MEPS releases HC-160A through HC-160H.
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 2013 event-level data files. File
1, the H160IF1 or CLNK file, is used for linking the MEPS Conditions file with
the MEPS event files; File 2, the H160IF2 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 (H160IF1) or the CLNK file, contains the
variables needed to link each record on the MEPS 2013 Conditions file, HC-162,
with one or more records on the MEPS 2013 event files, HC-160A, and HC-160D
through HC-160H. 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 2013
Conditions file, HC-162. 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 2013 event files, HC-160B through HC-160H. (EVNTIDX is not included on the 2013 Prescribed Medicines event file,
HC-160A; 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-160G
2 = OPAT – outpatient department visit event contained
on MEPS release HC-160F
3 = EROM – emergency room visit event contained on
MEPS release HC-160E
4 = STAZ – inpatient hospital stay event contained on
MEPS release HC-160D
7 = HVIS – home health visit event contained on MEPS
release HC-160H
8 = PMED – prescribed medicines event contained on
MEPS release HC-160A
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 17 or Panel 18.
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File 2 (H160IF2) or the RXLK file, contains the
variables needed to link each record on the MEPS 2013 Prescribed Medicines file,
HC-160A, with one or more records on the MEPS 2013 event files, HC-160B and
HC-160D through HC-160G. 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 2013 event files, HC-160B through HC-160G. 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-160A 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-160A 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-160G
2 = OPAT – outpatient department visit event contained
on MEPS release HC-160F
3 = EROM – emergency room visit event contained on
MEPS release HC-160E
4 = STAZ – inpatient hospital stay event contained on
MEPS release HC-160D
5 = DVIS – dental visit event contained on MEPS
release HC-160B
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 17 or Panel 18.
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Table 1 contains the MEPS 2013 Condition-Event
Frequency table. This table contains unweighted and weighted counts of records
on the MEPS 2013 event files, HC-160A through HC-160H, for each of the
condition, procedure, and clinical classification codes contained on the MEPS
2013 Conditions file, HC-162. 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-162) and the Appendix to the Event Files (HC-160I) 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 2013 MEPS PUFs, these updates will not be reflected in the 2013
MEPS data.
Note that, through FY2012 for conditions related to
certain medical events, the ICD-9-CM codes on the Conditions file were also
released in the Prescribed Medicines, Emergency Room Visits, Office-based
Medical Provider Visits, Outpatient Department Visits, and Inpatient Hospital
Stays Event Files. In FY2013, ICD-9-CM condition and procedure codes variables
were released only on the Conditions file. For more information on ICD-9-CM
codes, see the HC-162 documentation.
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This section provides information on using each of the
two HC-160I files, RXLK and CLNK, to link with the files contained in MEPS
releases HC-162 and HC-160A through HC-160H. 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-162), the CLNK file
(HC-160IF1), the office-based medical provider visit event file (HC-160G), the
RXLK file (HC-160IF2), and the prescribed medicines event file (HC-160A). It
includes the following major steps:
- From HC-162 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-160G 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-160G 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-160A linked to those visits.
- Using these record IDs, obtain the linked records from the
HC-160A 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-162),
the CLNK file (HC-160IF1) and the prescribed medicines event file (HC-160A). It
includes the following major steps:
- From HC-162 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-160A 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-162), the CLNK file (HC-160IF1) and the office-based medical
provider visits event file (HC-160G). It includes the following major steps:
- From HC-162 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-160G 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-160G 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.
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 at the
start of the final rounds of data collection for 2013. This effort likely
resulted in improved data quality and a reduction in underreporting in 2013, but
could have some modest impact on analyses involving trends in utilization across
years.
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 evaluate, smooth, or stabilize analyses of trends
using MEPS data such as comparing pooled time periods (e.g. 1996-97 versus
2012-13), 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
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.
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