MEPS HC-110I: Appendix to MEPS 2007 Event Files HC-110A - HC-110H
November 2009
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 2007 Condition-Event Frequency Table
2.6 2007 Utilization and Expenditures Summary Table
3.0 Merging/Linking MEPS Data Files
3.1 Example A: Using the CLNK (HC-110IF1) and RXLK (HC-110IF2) Files with the Medical Conditions File (HC-112),
the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-110A and HC-110G)
3.2 Example B: Using the CLNK File (HC-110IF1) with the Medical Conditions File (HC-112) and the Prescribed
Medicines Event File (HC-110A)
3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-112) and Office-Based Medical Provider
Visits Event File (HC-110G)
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
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:
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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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
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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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 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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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. 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:
www.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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C. Technical and Programming Information
1.0 General Information
This documentation describes the MEPS Public Use
Release HC-110I, which is the Appendix to MEPS releases HC-110A through HC-110H.
This release contains two data files, both of which are provided in ASCII (with
related SAS and SPSS programming statements) and SAS versions: 1) the
condition-event link file; and 2) the prescribed medicines-event link file. Also
included in this release are two tables provided as PDF files: 1) the
condition-event frequency table and 2) the utilization and expenditures summary
table.
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 S.
Cohen, 1997; J. Cohen, 1997; and S. Cohen, 1996. For information on the MEPS MPC
design, see S. Cohen, 1998. Both 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:
www.meps.ahrq.gov.
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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 2007 event-level data files. File
1, the H110IF1 or CLNK file, is used for linking the MEPS condition file with
the MEPS event files; File 2, the H110IF2 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:
| Identifier |
Description |
| Name |
Variable name (maximum of 8 characters) |
| Description |
Variable descriptor (maximum of 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 (H110IF1) or the CLNK file, contains the
variables needed to link each record on the MEPS 2007 condition file, HC-112,
with one or more records on the MEPS 2007 event files, HC-110A through HC-110H.
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 2007
Condition file, HC-112. 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 2007 event files, HC-110B through HC-110H. (EVNTIDX is not included on
the 2007 Prescription Medicines event file, HC-110A; 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-110G
2 = OPAT – outpatient department visit event contained on MEPS release HC-110F
3 = EROM – emergency room visit event contained on MEPS release HC-110E
4 = STAZ – inpatient hospital stay event contained on MEPS release HC-110D
7 = HVIS – home health visit event contained on MEPS release HC-110H
8 = PMED – prescribed medicines event contained on MEPS release HC-110A
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 11 or Panel 12.
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2.4 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)
File 2 (H110IF2) or the RXLK file, contains the
variables needed to link each record on the MEPS 2007 prescribed medicines file,
HC-110A, with one or more records on the MEPS 2007 event files, HC-110B and
HC-110D through HC-110G. 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 2007 event files, HC-110B through HC-110G. 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-110A which 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-110A 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-110G
2 = OPAT – outpatient department visit event contained on MEPS release HC-110F
3 = EROM – emergency room visit event contained on MEPS release HC-110E
4 = STAZ – inpatient hospital stay event contained on MEPS release HC-110D
5 = DVIS – dental visit event contained on MEPS release HC-110B
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 11 or Panel 12.
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2.5 2007 Condition-Event Frequency Table
Table 1 contains the MEPS 2007 Condition-Event
Frequency table. This table contains unweighted and weighted counts of records
on the MEPS 2007 event files, HC-110A through HC-110H, for each of the
condition, procedure, and clinical classification codes contained on the MEPS
2007 Condition file, HC-112. 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-112) and the Appendix to the Event
Files (HC-110I) 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 2007 MEPS PUFs, these updates
will not be reflected in the 2007 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-112 documentation.
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2.6 2007 Utilization and Expenditures Summary Table
Table 2 contains the MEPS 2007 Utilization and
Expenditures Summary table. This table contains statistics for all of the
utilization and expenditure variables contained on the MEPS 2007 Full Year Use
and Expenditure Data file, HC-113. For each of these variables, the following
statistics are provided from the HC-113 file, and from the corresponding
event-level file(s) HC-110A through HC-110H:
Number of persons with positive person-level
weight (PERWT07F) and with value GT 0 for that variable
Weighted sum of the variable
Weighted mean of the variable
The table also includes the technical specifications
used to construct each of the person-level HC-113 variables from the event-level
files.
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3.0 Merging/Linking MEPS Data Files
This section provides information on using each of the
two HC-110I files, RXLK and CLNK, to link with the files contained in MEPS
releases HC-112 and HC-110A through HC-110H. 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-110IF1) and RXLK (HC-110IF2) Files with the Medical Conditions
File (HC-112), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-110A and HC-110G)
This example calculates the total expenditures for
prescribed medicines associated with office-based medical provider visits for
asthma, using these files: the condition file (HC-112), the CLNK file
(HC-110IF1), the office-based medical provider visit event file (HC-110G), the
RXLK file (HC-110IF2), and the prescribed medicines event file (HC-110A). It
includes the following major steps:
From HC-112, 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-110G 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-110G 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-110A
linked to those visits. Using these record IDs, obtain the linked records from the HC-110A 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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3.2 Example B: Using the CLNK File (HC-110IF1) with the Medical Conditions File
(HC-112) and the Prescribed Medicines Event File (HC-110A)
This example calculates the total expenditure for
prescribed medicines associated with asthma, using the condition file (HC-112),
the CLNK file (HC-110IF1) and the prescribed medicines event file (HC-110A). It
includes the following major steps:
From HC-112 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-110A 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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3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-112) and
Office-Based Medical Provider Visits Event File (HC-110G)
This example calculates the total expenditures for
office-based medical provider visits associated with asthma, using the condition
file (HC-112), the CLNK file (HC-110IF1) and the office-based medical provider
visits event file (HC-110G). It includes the following major steps:
From HC-112 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-110G 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-110G 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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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
condition 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
www.meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
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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,
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 smooth or stabilize analyses
of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97
versus 2005-06), 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 inappropriately concluding that a change has taken
place.
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3.8 Longitudinal Analysis
For Panels 1 through 8, panel-specific files (called
Longitudinal Weight Files) containing estimation variables to facilitate
longitudinal analysis are available for downloading in the data section of the
MEPS Web site. To create longitudinal files for these panels, it is necessary to
link data from two subsequent annual files that contain data for the first and
second years of the panel, respectively. Starting with Panel 9, it is not
necessary to link files for longitudinal analysis because Longitudinal Data
Files have been constructed and are available for downloading on the Web.
Attachment 1: Clinical Classification Code to ICD-9-CM Code Crosswalk (link to separate file)
Attachment 2: Sample SAS Jobs for Linking Examples (link to separate file)
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