MEPS HC-059I: Appendix to MEPS 2001 Event Files HC-059A - HC-059H
April 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 (HC)
2.0 Medical Provider Component (MPC)
3.0 Insurance Component (IC)
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 2001 Condition-Event Frequency Table
2.7 2001 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-059), the Prescribed Medicines and Office-Based
Medical Provider Visits Event Files (HC-059A and HC-059G)
3.2 Example B: Using the CLNK File with the Medical Conditions File
(HC-059) and the Prescribed Medicines Event File (HC-059A)
3.3 Example C: Using the CLNK File with the Medical Conditions
File (HC-059) and Office-Based Medical Provider Visits Event File
(HC-059G)
3.4 Example D: Using the RXLK File with the Other Medical Expenses
Event File (HC-059C)
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-059I, which is
the Appendix to MEPS releases HC-059A through HC-059H. 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 H59IF1CB.PDF and H59IF2CB.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 2001 event-level data files. File
1, the H59IF1 or CLNK file, is used for linking the MEPS condition file with the
MEPS event files; File 2, the H59IF2 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 expenditures 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 trends
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 trends increases the likelihood of inappropriately concluding a change
is statistically significant.
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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, (H59IF1) or the CLNK file, contains the variables needed to link each
record on the MEPS 2001 condition file, HC-061, with one or more records on the
MEPS 2001 event files, HC-059A through HC-059H. 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 2001 Condition file, HC-061. 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 2001 event files,
HC-059B through HC-059H. (EVNTIDX is not included on the 2001 Prescription
Medicines event file, HC-059A; 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-059G
2 = OPAT - outpatient department visit event contained on MEPS release
HC-059F
3 = EROM - emergency room visit event contained on MEPS release HC-059E
4 = STAZ - hospital inpatient stay event contained on MEPS release
HC-059D
7 = HVIS - home health visit event contained on MEPS release HC-059H
8 = PMED - prescribed medicines event contained on MEPS release HC-059A
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2.5 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)
File 2, (H59IF2) or the RXLK file, contains the variables needed to link each
record on the MEPS 2001 prescribed medicines file, HC-059A, with one or more
records on the MEPS 2001 event files, HC-059B through HC-059H. 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 2001 event files,
HC-059B through HC-059H. 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-059A 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-059A 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-059G
2 = OPAT - outpatient department visit event contained on MEPS release
HC-059F
3 = EROM - emergency room visit event contained on MEPS release HC-059E
4 = STAZ - hospital inpatient stay event contained on MEPS release
HC-059D
5 = DVIS - dental visit event contained on MEPS release HC-059B
6 = OMED - other medical expense event contained on MEPS release HC-059C
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2.6 2001 Condition-Event Frequency Table
The files H59IT1.HTM and H59IT1.PDF contain the MEPS 2001 Condition-Event
Frequency table. This table contains unweighted and weighted counts of records
on the MEPS 2001 event files, HC-059A through HC-059H, for each of the
condition, procedure and clinical classification codes contained on the MEPS
2001 condition file, HC-061. Attachment 1 contains a crosswalk of the clinical
classification codes to ICD-9-CM codes. See the HC-061 document for additional
information on these codes.
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2.7 2001 Utilization and Expenditures Summary Table
The files H59IT2.HTM and H59IT2.PDF contain the MEPS 2001 Utilization and
Expenditures Summary table. This table contains statistics for all of the
utilization and expenditure variables contained on the MEPS 2001 Full Year Use
and Expenditure Data file, HC-060. For each of these variables, the following
statistics are provided from the HC-060 file, and from the corresponding
event-level file(s) HC-059A through HC-059H:
Number of persons with positive person-level weight (PERWT01F) 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-060 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-059I files,
RXLK and CLNK, to link with the files contained in MEPS releases HC-061 and
HC-059A through HC-059H. 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-061), the Prescribed Medicines and Office-Based Medical Provider
Visits Event Files (HC-059A and HC-059G)
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-061), the CLNK file, the office-based medical
provider visit event file (HC-059G), the RXLK file, and the prescribed medicines
event file (HC-059A). It includes the following major steps:
- From HC-061 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-059G 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-059G 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-059A linked to those visits.
- Using these record IDs obtain the linked records from the HC-059A
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-059) and the Prescribed Medicines Event File (HC-059A)
This example calculates the total expenditure for prescribed medicines
associated with asthma, using the condition file (HC-061), the CLNK file and the
prescribed medicines event file (HC-059A). It includes the following major
steps:
- From HC-061 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-059A 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-059) and Office-Based Medical Provider Visits Event File (HC-059G)
This example calculates the total expenditures for office-based medical
provider visits associated with asthma, using the condition file (HC-061), the
CLNK file and the office-based medical provider visits event file (HC-059G). It
includes the following major steps:
- From HC-061 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-059G 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-059G 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-059C)
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-059C). It includes the following major steps:
- From HC-059C 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-059A 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.
Attachment 1: Clinical Classification Code to ICD-9-CM Code Crosswalk (link to separate file)
Attachment 2: Sample SAS Jobs for Linking Example (link to separate file)
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