MEPS HC-067I: Appendix to MEPS 2002 Event Files HC-067A - HC-067H
December 2004
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 Insurance Component
4.0 Survey Management
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Using MEPS Data for Trend and Longitudinal Analysis
2.2 Codebook Format
2.3 Variable Naming and Source
2.4 Contents of File 1: Condition-Event Link File (CLNK)
2.5 Contents of File 2: Prescribed Medicines-Event Link
File (RXLK)
2.6 2002 Condition-Event Frequency Table
2.7 2002 Utilization and Expenditures Summary Table
3.0 Merging/Linking MEPS Data Files
3.1 Example A: Using the RXLK and CLNK Files with the
Medical Conditions File (HC-069), the Prescribed Medicines and Office-Based
Medical Provider Visits Event Files (HC-067A and HC-067G)
3.2 Example B: Using the CLNK File with the Medical
Conditions File (HC-069) and the Prescribed Medicines Event File (HC-067A)
3.3 Example C: Using the CLNK File with the Medical
Conditions File (HC-069) and Office-Based Medical Provider Visits Event File
(HC-067G)
3.4 Example D: Using the RXLK File with the Other Medical
Expenses Event File (HC-067C)
3.5 Limitations/Caveats of the CLNK File
3.6 Limitations/Caveats of the RXLK File
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)
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
The Medical Expenditure Panel Survey (MEPS) provides
nationally representative estimates of health care use, expenditures, sources of
payment, and insurance coverage for the U.S. civilian non-institutionalized
population. MEPS is cosponsored by the Agency for Healthcare Research and
Quality (AHRQ) and the National Center for Health Statistics (NCHS).
MEPS is a family of three surveys. The Household Component
(HC) is the core survey and forms the basis for the Medical Provider Component (MPC)
and part of the Insurance Component (IC). Together these surveys yield
comprehensive data that provide national estimates of the level and distribution
of health care use and expenditures, support health services research, and can
be used to assess health care policy implications.
MEPS is the third in a series of national probability
surveys conducted by AHRQ on the financing and use of medical care in the United
States. The National Medical Care Expenditure Survey (NMCES, also known as
NMES-1) was conducted in 1977 and the National Medical Expenditure Survey
(NMES-2) in 1987. Since 1996, MEPS continues this series with design
enhancements and efficiencies that provide a more current data resource to
capture the changing dynamics of the health care delivery and insurance system.
The design efficiencies incorporated into MEPS are in
accordance with the Department of Health and Human Services (DHHS) Survey
Integration Plan of June 1995, which focused on consolidating DHHS surveys,
achieving cost efficiencies, reducing respondent burden, and enhancing
analytical capacities. To advance these goals, MEPS includes linkage with the
National Health Interview Survey (NHIS) - a survey conducted by NCHS from which
the sample for the MEPS HC is drawn - and enhanced longitudinal data collection
for core survey components. The MEPS HC augments NHIS by selecting a sample of
NHIS respondents, collecting additional data on their health care expenditures,
and linking these data with additional information collected from the
respondents' medical providers, employers, and insurance providers.
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1.0 Household Component
The MEPS HC, a nationally representative survey of the
U.S. civilian non-institutionalized population, collects medical expenditure
data at both the person and household levels. The HC collects detailed data on
demographic characteristics, health conditions, health status, use of medical
care services, charges and payments, access to care, satisfaction with care,
health insurance coverage, income, and employment.
The HC uses an overlapping panel design in which data are
collected through a preliminary contact followed by a series of five rounds of
interviews over a 2 ½-year period. Using computer-assisted personal interviewing
(CAPI) technology, data on medical expenditures and use for two calendar years
are collected from each household. This series of data collection rounds is
launched each subsequent year on a new sample of households to provide
overlapping panels of survey data and, when combined with other ongoing panels,
will provide continuous and current estimates of health care expenditures.
The sampling frame for the MEPS HC is drawn from
respondents to NHIS. NHIS provides a nationally representative sample of the
U.S. civilian non-institutionalized population, with oversampling of Hispanics
and blacks.
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2.0 Medical Provider Component
The MEPS MPC supplements and/or replaces information on
medical care events reported in the MEPS HC by contacting medical providers and
pharmacies identified by household respondents. The MPC sample includes all home
health agencies and pharmacies reported by HC respondents. Office-based
physicians, hospitals, and hospital physicians are also included in the MPC but
may be subsampled at various rates, depending on burden and resources, in
certain years.
Data are collected on medical and financial
characteristics of medical and pharmacy events reported by HC respondents. The
MPC is conducted through telephone interviews and record abstraction.
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3.0 Insurance Component
The MEPS IC collects data on health insurance plans
obtained through private and public-sector employers. Data obtained in the IC
include the number and types of private insurance plans offered, benefits
associated with these plans, premiums, contributions by employers and employees,
eligibility requirements, and employer characteristics.
Establishments participating in the MEPS IC are selected
through three sampling frames:
- A list of employers or other insurance providers
identified by MEPS HC respondents who report having private health insurance
at the Round 1 interview.
- A Bureau of the Census list frame of private sector
business establishments.
- The Census of Governments from the Bureau of the Census.
To provide an integrated picture of health insurance, data
collected from the first sampling frame (employers and insurance providers
identified by MEPS HC respondents) are linked back to data provided by those
respondents. Data from the two Census Bureau sampling frames are used to produce
annual national and state estimates of the supply and cost of private health
insurance available to American workers and to evaluate policy issues pertaining
to health insurance. National estimates of employer contributions to group
insurance from the MEPS IC are used in the computation of Gross Domestic Product
(GDP) by the Bureau of Economic Analysis.
The MEPS IC is an annual survey. Data are collected from
the selected organizations through a prescreening telephone interview, a mailed
questionnaire, and a telephone follow-up for nonrespondents.
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4.0 Survey Management
MEPS data are collected under the authority of the Public
Health Service Act. They are edited and published in accordance with the
confidentiality provisions of this act and the Privacy Act. 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, microdata files and compendiums of tables. Data are released through
MEPSnet, an online interactive tool developed to give users the ability to
statistically analyze MEPS data in real time. Summary reports and compendiums of
tables are released as printed documents and electronic files. Microdata files
are released on electronic files.
Selected printed documents are available through the AHRQ Publications
Clearinghouse. Write or call:
AHRQ Publications Clearinghouse
Attn: (publication number)
P.O. Box 8547
Silver Spring, MD 20907
800-358-9295
410-381-3150 (callers outside the United States only)
888-586-6340 (toll-free TDD service; hearing impaired only)
Be sure to specify the AHRQ number of the document you are
requesting.
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-067I, which is the Appendix to MEPS releases HC-067A through HC-067H. 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 both HTML and 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 codebooks (provided as files H67IF1CB.PDF and
H67IF2CB.PDF). It contains the following sections:
Data File Information
Merging MEPS Data Files
Crosswalk of Clinical Classification Code to ICD-9-CM
Code
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: <http://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 2002 event-level data files. File
1, the H67IF1 or CLNK file, is used for linking the MEPS condition file with the
MEPS event files; File 2, the H67IF2 or RXLK file, is used for linking the MEPS
prescribed medicines event file with other MEPS event files.
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2.1 Using MEPS Data for Trend and Longitudinal Analysis
MEPS began in 1996 and several annual data files have been released. As more
years of data are produced, MEPS will become increasingly valuable for examining
health care trends. 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 are
attributable to sampling variation. MEPS expenditure estimates are especially
sensitive to sampling variation due to the underlying skewed distribution of
expenditures. For example, 1 percent of the population accounts for about
one-quarter of all expenditures. The extent to which observations with extremely
high expenditures are captured in the MEPS sample varies from year to year
(especially for smaller population subgroups), which can produce substantial
shifts in estimates of means or totals that are simply an artifact of the
sample(s). 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 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 trend
analyses of MEPS data such as pooling time periods for comparison (e.g. 1996-97
versus 1998-99), 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 because performing numerous statistical significance
tests of trend increases the likelihood of inappropriately concluding a change
is statistically significant.
The records on this file can be linked to all other 2002 MEPS-HC public use
data sets by the sample person identifier (DUPERSID).
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2.2 Codebook Format
This 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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2.3 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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2.4 Contents of File 1: Condition-Event Link File (CLNK)
File 1 (H67IF1) or the CLNK file, contains the variables
needed to link each record on the MEPS 2002 condition file, HC-069, with one or
more records on the MEPS 2002 event files, HC-067A through HC-067H. 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 2002 Condition file,
HC-069. 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
2002 event files, HC-067B through HC-067H. (EVNTIDX is not included on the 2002
Prescription Medicines event file, HC-067A; 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 which 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-067G
2 = OPAT - outpatient department visit event contained on MEPS release HC-067F
3 = EROM - emergency room visit event contained on MEPS release HC-067E
4 = STAZ - inpatient hospital stay event contained on MEPS release HC-067D
7 = HVIS - home health visit event contained on MEPS release HC-067H
8 = PMED - prescribed medicines event contained on MEPS release HC-067A
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2.5 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)
File 2 (H67IF2) or the RXLK file, contains the variables needed to link each
record on the MEPS 2002 prescribed medicines file, HC-067A, with one or more
records on the MEPS 2002 event files, HC-067B through HC-067H. 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 which uniquely identifies
each event for a person and corresponds to a unique record on one of the MEPS
2002 event files, HC-067B through HC-067H. There may be more than one record on
the RXLK file for a specific EVNTIDX value.
LINKIDX is the 12-digit number which identifies the
record(s) on the prescribed medicines file, HC-067A 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-067A file for a
specific LINKIDX value.
RXLKIDX is the 24-digit number which 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-067G
2 = OPAT - outpatient department visit event contained on MEPS release HC-067F
3 = EROM - emergency room visit event contained on MEPS release HC-067E
4 = STAZ - inpatient hospital stay event contained on MEPS release HC-067D
5 = DVIS - dental visit event contained on MEPS release HC-067B
6 = OMED - other medical expense event contained on MEPS release HC-067C
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2.6 2002 Condition-Event Frequency Table
The files H67IT1.HTM and H67IT1.PDF contain the MEPS 2002
Condition-Event Frequency table. This table contains unweighted and weighted
counts of records on the MEPS 2002 event files, HC-067A through HC-067H, for
each of the condition, procedure and clinical classification codes contained on
the MEPS 2002 condition file, HC-069. Attachment 1 contains a crosswalk of the
clinical classification codes to ICD-9-CM codes. See the HC-069 document for
additional information on these codes.
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2.7 2002 Utilization and Expenditures Summary Table
The files H67IT2.HTM and H67IT2.PDF contain the MEPS 2002 Utilization and
Expenditures Summary table. This table contains statistics for all of the
utilization and expenditure variables contained on the MEPS 2002 Full Year Use
and Expenditure Data file, HC-070. For each of these variables, the following
statistics are provided from the HC-070 file, and from the corresponding
event-level file(s) HC-067A through HC-067H:
Number of persons with positive person-level
weight (PERWT02F) 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-070 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-067I files, RXLK and CLNK, to link with the files contained in MEPS releases
HC-069 and HC-067A through HC-067H. 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 RXLK and CLNK Files with the Medical Conditions
File (HC-069), the Prescribed Medicines and Office-Based Medical Provider
Visits Event Files (HC-067A and HC-067G)
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-069), the CLNK file
(HC-067I1), the office-based medical provider visit event file (HC-067G), the
RXLK file (HC-067I2), and the prescribed medicines event file (HC-067A). It
includes the following major steps:
- From HC-069 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-067G 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-067G 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-067A linked to those visits.
- Using these record IDs obtain the linked records
from the HC-067A 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 with the Medical Conditions File
(HC-069) and the Prescribed Medicines Event File (HC-067A)
This example calculates the total expenditure for
prescribed medicines associated with asthma, using the condition file (HC-069),
the CLNK file and the prescribed medicines event file (HC-067A). It includes the
following major steps:
- From HC-069 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-067A 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-069) and Office-Based Medical Provider Visits Event File (HC-067G)
This example calculates the total expenditures for
office-based medical provider visits associated with asthma, using the condition
file (HC-069), the CLNK file and the office-based medical provider visits event
file (HC-067G). It includes the following major steps:
- From HC-069 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-067G 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-067G 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 Example D: Using the RXLK File with the Other Medical Expenses Event
File (HC-067C)
This example calculates the total prescription
expenditures for other medical events reported by the household with type of
other medical expense indicated as insulin (OMTYPEX=2), using the RXLK file and
the other medical expenses event file (HC-067C). It includes the following major
steps:
- From HC-067C file select only records for other
medical expense type of insulin, for persons with a positive weight.
- Use the RXLK file to obtain unique record IDs of
prescribed medicine events which are linked to each of the selected
other medical expense records.
- Use the selected record IDs from the RXLK file to
obtain the linked prescribed medicines event records from the HC-067A
file, and calculate the weighted sum of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this
example.
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3.5 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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3.6 Limitations/Caveats of the RXLK File
When using RXLK, 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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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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