MEPS HC-036: 1996-2008 Pooled Estimation File
December
2010
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
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
3.0 Linking Instructions
4.0 Adjustment of Analytic Weight Variable
5.0 Subpopulation Analysis Caveat
6.0 Further Information
A. Data Use Agreement
Direct individual identifiers have been removed from the micro-data contained in these files. Nevertheless, under data
Section 308(d) of the Public Health Service Act (42, U.S. Code, 242m(d)) and the Confidential Information Protection and Statistical
Efficiency Act (CIPSEA) (Title 5 of PL 107-347), National Center for Health Statistics (NCHS) data must be used for statistical purposes only
and no attempt must be made to identify individuals. The provisions of CIPSEA provide for a felony conviction and/or fine of up to $250,000
if this promise is violated. In addition, data collected by the Agency for Healthcare Research and Quality (AHRQ) and /or the NCHS may not
be used for any purpose other than for the purpose for which it was supplied; any effort to determine the identity of any reported cases, is
prohibited by law.
Unauthorized disclosure of confidential information is also subject to penalty under Title IX of the Public Health
Service Act, 42 U.S.C. 299, Section 924(d), which reads as follows:
"Any person who violates subsection (c) shall be subject to a civil monetary penalty of not more the same manner as civil
money penalties under subsection (a) of section 1128A of the Social Security Act are imposed and collected."
Therefore in accordance with the above referenced Federal Statutes, 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 noninstitutionalized 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
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
To facilitate analysis of subpopulations and/or
low prevalence events, it may be desirable to pool together (i.e.
combine) more than one year of MEPS-HC data to yield sample sizes large
enough to generate reliable estimates. MEPS-HC samples in most
years are not completely independent because households are drawn
from the same sample geographic areas and many persons are in the
sample for two consecutive years (see MEPS-HC Methodology Reports for
more details at http://www.meps.ahrq.gov).
Despite this lack of independence, it is valid to pool multiple years of
MEPS-HC data and keep all observations in the analysis because each year
of the MEPS-HC is designed to be nationally representative. However,
to obtain appropriate standard errors when pooling years of MEPS-HC
data, it is necessary to specify a common variance structure that properly reflects the complex sample design of the MEPS.
This HC-036 file contains the proper
variance structure to use when making estimates from MEPS data
that have been pooled over multiple years and where one or more years
are from 1996-2001. Prior to 2002, each annual MEPS public use
file was released with a variance structure unique to the particular
MEPS sample in that year. The variance structure in this HC-036 file
reconciles the differences in the variance units between the units on
the released annual MEPS public use files.
Starting in 2002, the annual MEPS public
use files were released with a common variance structure that allows users to pool data from 2002 and forward. This
common variance structure is neither compatible with the
structure on the annual PUFs released prior to 2002 nor is it compatible
with the structure on this HC-036 dataset. Therefore, it is only
necessary to use the variance structure on this HC-036
dataset when pooling data from MEPS years prior to 2002. The following
scenarios provide some guidelines for when analysts should use the
variance structure in this HC-036 file.
|
MEPS Years Pooled |
|
|
< 2001 |
2001 |
2002 |
2003 |
2004+ |
Which variance structure to use |
| |
|
|
|
|
HC-036 |
| |
|
|
|
|
HC-036 |
| |
|
|
|
|
Annual PUFs |
| |
|
|
|
|
Annual PUFs |
In the first scenario, only MEPS data from years
prior to 2002 are pooled together. In this case,
analysts must use the variance structure in HC-036. In the second scenario,
data from years prior
to 2002 is pooled together with data from 2002 and forward. The variance
structure from HC-036
must be used in this circumstance as well. In the last two scenarios,
no data from years prior to
2002 are pooled. In both of these cases, analysts should use the variance
structure on the released
annual public
use files. In no circumstance should the variance structure on the annual
PUFs be combined with the variance structure on the HC-036 dataset.
The variables STRA9608 (stratum of the primary sampling unit) and PSU9608
(primary sampling
unit) in this HC-036 dataset provide the appropriate sample design
information needed by survey
procedures in software packages that implement the with-replacement
Taylor series linearization
method to obtain estimates of complex sample variances. The variables BRR1 – BRR128 in
the HC-036BRR dataset (http://www.meps.ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036BRR)
provide a comparable replicate sample design structure. These replicates
can be
incorporated in software package survey procedures that implement
the balanced repeated
replication (BRR) method to produce estimates of complex sample variances.
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2.0 Data File Information
Released as an ASCII data file (with SAS® and
SPSS® user statements) and in SAS Transport
version, the HC-036 file contains 222,900 records corresponding to the
number of unique persons
in MEPS from 1996-2008. These records contain the standard MEPS-HC person
level ID
variables (DUPERSID + PANEL), as well as the pooled variance estimation
structure
(STRA9608 and PSU9608).
There is a record for each unique person appearing in any of the 1996-2008
MEPS HC full year
person level public use files: HC-012, HC-020, HC-028, HC-038, HC-050,
HC-060, HC-070,
HC-079, HC-089, HC-097, HC-105, HC-113, and HC-121. Thirteen data sets
have a combined
total of 404,413 records; however, as each person may appear in one
or two of these data sets, the
number of unique persons (222,900) is fewer than the total number of
records on the annual files.
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3.0 Linking Instructions
The following steps should be taken to create a
pooled analysis dataset.
- Create a dataset for each year containing the person- and/or event-level
records of all persons to be included in the analysis. Keep
the unique person identifier (DUPERSID and PANEL), the person-level
sampling weight, any classification variables (e.g., sex, race/ethnicity)
and response variables (e.g., total expenditure amount, number of prescription drug purchases, etc) to be used in the data analysis.
- Reconcile the discrepancies in variable names. For all years, most
variable names on the annual public use files contain a 2-digit
year suffix. For instance, in the 1997 consolidated person-level
file (HC-020) the panel variable is called PANEL97, the total annual expenditure
amount variable is called TOTEXP97 and the sampling weight variable
is called WTDPER97. But in the 2003 dataset (HC-079) these
same variables are named PANEL03, TOTEXP03 and PERWT03F, respectively,
and in the 1996 dataset (HC-012) the total expenditure and sampling
weight variables are named TOTEXP96 and WTDPER96, respectively,
and the panel variable is missing (users should assign a value of
1 for each record in HC-012). Starting in 2005, the panel variable
is simply named PANEL (no year suffix). As illustrated below,
the variable names must be made consistent before pooling
the data.
- Create a pooled analysis dataset by simply combining the individual-year
datasets (e.g., the records from the 1996 and 1997 files).
In other words, the number of records in the pooled file will
equal the sum of the record counts for the individual annual files
being pooled.
- Attach the pooled variance structure to the pooled analysis dataset
by merging the variables STRA9608 and PSU9608 from this HC-036
file to the pooled analysis dataset by DUPERSID and PANEL
keeping all records in the pooled analysis dataset only. Depending
on the software being used to manage the datasets, the pooled analysis
dataset may need to be sorted by DUPERSID and PANEL prior
to merging. This step will add two additional variables to
the pooled file (STRA9608 and PSU9608) but have no impact on the number of records.
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4.0 Adjustment of Analytic
Weight Variable
It is generally recommended that analysts adjust
the analytic weight variable by dividing it by the number of years
being pooled. The sum of these adjusted weights represents the average
annual population size for the pooled period (rather than the
sum of the population sizes across multiple years that would result
from unadjusted weights). Although this adjustment will have no effect
on estimated means, proportions or regression coefficients because
the weight variable is being divided by a constant (i.e. number
of years), estimates of totals based on adjusted weights will reflect
an “average annual” basis rather than the entire
pooled period. On the other hand, if the objective is to produce
an estimated total for the entire pooled period (e.g. total medical expenditures
across multiple years rather than average per year), then the analytic
weight
variable should not be divided by the number of years in the pooled period.
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5.0 Subpopulation Analysis
Caveat
When pooling data over several years to increase
sample sizes for small subdomains of the population (e.g., obtaining
the total and mean expenditures for prescription drugs among children with
asthma), users must be careful to maintain the integrity of the MEPS
survey design. The MEPS design is accounted for by the full set
of survey stratum and PSU values on both the annual files and
this HC-036 pooled linkage file.1 When users create analytic subfiles
that contain only respondents in the subdomain of interest (e.g.,
children with asthma), it is very unlikely that there will be
all combinations of stratum and PSU that properly account for the MEPS
survey design in a linearized estimate of the sampling variances.
Therefore, the following approach is recommended for analyzing subpopulations in MEPS:
- Construct a flag variable for all survey respondents that can be
used to identify persons in the subdomain of interest,
- Using a with-replacement design option for a Taylor Series procedure
in a complex survey design statistical software package, read
in records from all respondents (i.e., not just those in the
subdomain of interest) and specify the analytic subdomain using the
flag variable (see step 1 above).2
6.0 Further Information
For any question regarding the HC-036 file or pooling
of data, please contact Sadeq Chowdhury by e-mail at: sadeq.chowdhury@ahrq.hhs.gov or
Fred Rohde by e-mail at: frederick.rohde@ahrq.hhs.gov.
1 The MEPS design is also accounted for by the full set of
replicates in the HC-036BRR data set (http://www.meps.ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036BRR).
2 The syntax for specifying survey designs and analytic subdomains
varies across
software packages (see section IB at http://www.meps.ahrq.gov/mepsweb/survey_comp/standard_errors.jsp for
examples).
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