MEPS HC-094I: Appendix to MEPS 2005 Event Files
HC-094A - HC-094H
November 2007
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 2005 Condition-Event Frequency Table
2.6 2005 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-096), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-094A and HC-094G)
3.2 Example B: Using the CLNK File with the Medical Conditions File (HC-096) and the Prescribed Medicines Event File (HC-094A)
3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-096) and Office-Based Medical Provider Visits Event File (HC-094G)
3.4 Limitations/Caveats of the CLNK File
3.5 Limitations/Caveats of the RXLK File
3.6 Pooling Annual Files
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 Examples
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. MEPS oversamples additional policy relevant sub-groups
such as Asians and 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-094I, which is the Appendix to MEPS releases HC-094A through HC-094H. 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 2005 event-level data files. File
1, the H94IF1 or CLNK file, is used for linking the MEPS condition file with the
MEPS event files; File 2, the H94IF2 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 (H94IF1) or the CLNK file, contains the variables
needed to link each record on the MEPS 2005 condition file, HC-096, with one or
more records on the MEPS 2005 event files, HC-094A through HC-094H. 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 2005 Condition file,
HC-096. 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
2005 event files, HC-094B through
HC-094H. (EVNTIDX is not included on the 2005 Prescription
Medicines event file, HC-094A; 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-094G
2 = OPAT – outpatient department visit event contained on MEPS release HC-094F
3 = EROM – emergency room visit event contained on MEPS release HC-094E
4 = STAZ – inpatient hospital stay event contained on MEPS release HC-094D
7 = HVIS – home health visit event contained on MEPS release HC-094H
8 = PMED – prescribed medicines event contained on MEPS release HC-094A
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2.4 Contents of File 2: Prescribed Medicines-Event
Link File (RXLK)
File 2 (H94IF2) or the RXLK file, contains the variables needed to link each
record on the MEPS 2005 prescribed medicines file, HC-094A, with one or more
records on the MEPS 2005 event files, HC-094B and HC-094D through HC-094G.
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 2005 event files, HC-094B through
HC-094G. 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-094A 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-094A 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-094G
2 = OPAT – outpatient department visit event contained on MEPS release HC-094F
3 = EROM – emergency room visit event contained on MEPS release HC-094E
4 = STAZ – inpatient hospital stay event contained on MEPS release HC-094D
5 = DVIS – dental visit event contained on MEPS release HC-094B
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.
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2.5 2005 Condition-Event Frequency Table
Table 1 contains the MEPS 2005 Condition-Event Frequency
table. This table contains unweighted and weighted counts of records on the MEPS
2005 event files, HC-094A through HC-094H, for each of the condition, procedure
and clinical classification codes contained on the MEPS 2005 condition file,
HC-096. 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-096) and the Appendix to the Event
Files (HC-094I) 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 2005 MEPS PUFs, these updates
will not be reflected in the 2005 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-096 documentation.
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2.6 2005 Utilization and Expenditures Summary Table
Table 2 contains the MEPS 2005 Utilization and Expenditures Summary table.
This table contains statistics for all of the utilization and expenditure
variables contained on the MEPS 2005 Full Year Use and Expenditure Data file,
HC-097. For each of these variables, the following statistics are provided from
the HC-097 file, and from the corresponding event-level file(s) HC-094A through
HC-094H:
Number of persons with positive person-level weight
(PERWT05F) 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-097 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-094I files, RXLK and CLNK, to link with the files contained in MEPS releases
HC-096 and HC-094A through HC-094H. 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-096), the Prescribed Medicines and Office-Based
Medical Provider Visits Event Files (HC-094A and HC-094G)
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-096), the CLNK file
(HC-094IF1), the office-based medical provider visit event file (HC-094G), the
RXLK file (HC-094IF2), and the prescribed medicines event file (HC-094A). It
includes the following major steps:
- From HC-096 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-094G 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-094G 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-094A linked to those visits.
- Using these record IDs obtain the linked records
from the HC-094A 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-094IF1)
with the Medical Conditions File (HC-096) and the Prescribed Medicines
Event File (HC-094A)
This example calculates the total expenditure for
prescribed medicines associated with asthma, using the condition file (HC-096),
the CLNK file (HC-094IF1) and the prescribed medicines event file (HC-094A). It
includes the following major steps:
- From HC-096 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-094A 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-096) and Office-Based Medical Provider
Visits Event File (HC-094G)
This example calculates the total expenditures for
office-based medical provider visits associated with asthma, using the condition
file (HC-096), the CLNK file (HC-094IF1) and the office-based medical provider
visits event file (HC-094G). It includes the following major steps:
- From HC-096 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-094G 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-094G 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 Pooling Annual Files
To facilitate analysis of subpopulations and/or low prevalence events, it may
be desirable to pool together more than one year of data to yield sample sizes
large enough to generate reliable estimates. For more details on pooling
MEPS data files see www.meps.ahrq.gov/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036.Starting in Panel 9, values for DUPERSID from previous panels will
occasionally be re-used. Therefore, it is necessary to use the panel variable
(PANEL) in combination with DUPERSID to ensure unique person-level identifiers
across panels. Creating unique records in this manner is advised when pooling
MEPS data across multiple annual files that have one or more identical values
for DUPERSID.
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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
2004-05), 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
MEPS Panel Longitudinal Weight files containing estimation variables to
facilitate longitudinal analysis are available for downloading in the data
section of the MEPS Web site.
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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