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MEPSnet/HC Documentation for 2008 Full Year Data
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406
The purpose of this documentation is to assist the user in identifying and utilizing MEPS public use variables through MEPSnet, an online interactive statistical tool. Users should note that the MEPSnet data file is a subset of public use file HC121: 2008 Full Year Consolidated Data File. The contents of the MEPSnet data file are limited to variables that can be used in descriptive analyses only. Hence, variables that require further data editing or are the building blocks for more analytic variables are not included in the MEPSnet data file. Analyses requiring such variables should be performed using the full HC121 public use data file. Similarly, this documentation focuses on the variables available in MEPSnet only. Detailed documentation is available for all 2008 public use variables in the codebook and documentation for HC121: 2008 Full Year Consolidated Data File.
Table of Contents
Background
Household Component
General Information
Codebook Structure
Reserved Codes
Codebook Format
Variable Naming Conventions
MEPSnet Data File Contents
Family Composition
Geographic Variables
Demographic Variables
Age
Sex
Race, Race/Ethnicity, Hispanic Ethnicity, and Hispanic Ethnicity Group
Marital Status
Student Status and Educational Attainment
Income Variables
Income Top-Coding
Poverty Status
Employment Variables
Health Insurance Variables
Health Status Variables
Utilization, Expenditures and Source of Payment
Variables
Expenditure Definition
Data Sources on Expenditures
Imputation for Missing Expenditures and Data Adjustments
Methodology for Flat Fee Expenditures
Zero Expenditures
Source of Payment Categories
Charge Variables
Utilization and Expenditure Variables by Type of Medical Service
Medical Provider Visits (i.e., Office-Based Visits)
Hospital Events
Hospital Outpatient Visits
Hospital Emergency Room Visits
Hospital Inpatient Stays
Dental Visits
Home Health Care
Vision Aids
Other Medical Equipment and Services
Prescribed Medicines
Prescribed Medicines Data Collected
Prescribed Medicines Data Editing and Imputation
Variable Description Summary
Survey Administration Variables
Demographic Variables
Income Variables
Employment Variables
Health Insurance Variables
Health Status Variables
Background
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 noninstitutionalized 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.
General Information
This documentation
describes 2008 full-year data from the Medical Expenditure
Panel Survey Household Component (MEPS HC). This data file
provides information collected on a nationally
representative sample of the civilian non-institutionalized
population of the United States for calendar year 2008.
This dataset contains
variable and frequency distributions for a total of 33,066
persons who participated in the MEPS Household Component of
the Medical Panel Expenditure Survey in 2008. This count
includes all household survey respondents who resided in
eligible responding households. The persons were part of one
of the two MEPS panels that collected data about 2008:
Rounds 3, 4, and 5 of Panel 12 or Rounds 1, 2, and 3 of Panel
13. Of these persons, 31,262 were assigned a positive person
level weight. Both weighted and unweighted frequencies are
provided for each variable. Using MEPSnet, data for
these persons can be used to make national estimates for the
civilian non-institutionalized U. S. population for 2008.
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Codebook Structure
The codebook and data file sequence lists variables in the following order:
- Unique person identifiers
- Geographic variables
- Demographic variables
- Income and Tax Filing variables
- Employment variables
- Health Insurance variables
- Health Status variables
- Utilization and Expenditure variables
- Weight and variance estimation variables
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Reserved Codes
The following reserved code values are used:
| VALUE |
|
DEFINITION |
| -1 |
INAPPLICABLE |
Question was not asked due to skip pattern |
| -7 |
REFUSED |
Question was asked and respondent refused to answer question. |
| -8 |
DK |
Question was asked and respondent did not know answer |
| -9 |
NOT ASCERTAINED |
Interviewer did not record the data |
Codebook Format
This codebook provides the following programming identifiers for each variable:
| IDENTIFIER |
DESCRIPTION |
| Name |
Variable name (maximum of 8 characters) |
| Description |
Variable descriptor (maximum 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 |
Variable Naming Conventions
In general, variable
names reflect the content of the variable, with an
eight-character limitation. Edited variables end in an X, and
are so noted in the variable label. The last two characters in
round-specific variables denote the rounds of data collection,
Round 3, 4, or 5 of Panel 12 and Round 1, 2, or 3 of Panel 13.
Unless otherwise noted, variables that end in 08 represent
status as of December 31, 2008.
Variables contained in
this delivery were derived either from the questionnaire
itself or from the CAPI. The source of each variable is
identified in the section entitled "Appendix D.
Variable-Source Crosswalk" of the full public use file
documentation. Sources for each variable are indicated in one
of four ways: (1) variables derived from CAPI or assigned in
sampling are so indicated; (2) variables derived from complex
algorithms associated with re-enumeration are labeled "RE
Section"; (3) variables that are collected by one or more
specific questions in the instrument have those question
numbers listed in the Source column; (4) variables constructed
from multiple questions using complex algorithms are labeled
"Constructed."
Please note that variables names in
MEPSnet may not always correspond to the variable names found
on the corresponding public use file. Users are encouraged to
read the documentation for detailed information on individual
variables.
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Family Composition
Many variables were constructed using data from specific
rounds, if available. If data were missing from the target round, but were
available in another round, data from that other round were used in the variable
construction. If no valid data were available during any round of data
collection, an appropriate reserved code was assigned.
Reporting Units and Families
A Reporting Unit (RU) is a person or
group of persons in the sampled dwelling unit who are related
by blood, marriage, adoption, foster care or other family
association. Each RU was interviewed as a single entity for
MEPS. Thus, the RU serves chiefly as a family-based
"survey" operations unit rather than an analytic
unit. Regardless of the legal status of their association, two
persons living together as a "family" unit were
treated as a single reporting unit if they chose to be so
identified. Examples of different types of reporting units
are:
1. A married daughter and her husband living with her parents in the same dwelling unit constitute a single reporting unit.
2. A husband and wife and their unmarried daughter, age 18, who is living away from home while at college constitute two reporting units.
3. Three unrelated persons living in the same dwelling unit would each constitute a distinct reporting unit (a total of three reporting units).
Unmarried college
students (less than 24 years of age) who usually live in the
sampled household, (but were living away from home and going
to school at the time of the Round 3/1 MEPS interview) were
treated as a reporting unit separate from that of their
parents for the purpose of data collection. The end-of-year
status variable RUSIZE08 indicates the number of persons in
each RU, treating each student as a single RU separate from
their parents. Thus, students are not included in the RUSIZE
count of their parents RU. However, for many analytic
objectives, the student reporting units would be combined with
their parents' reporting unit, treating the combined entity as
a single family. Family identifier and size variables are
described below and include students with their parent’s
reporting unit.
PANEL is a constructed
variable used to specify the panel number for the interview.
PANEL will indicate either Panel 12 or Panel 13 for each
interview.
The end-of-year status
variable FAMSZE08 indicates the number of persons associated
with a single family unit (i.e., persons related to one
another by blood, marriage, adoption, foster care, or
self-identified as a single unit) after students are linked to
their associated parent RUs for analytical purposes. FCSZ1231
indicates the number of persons associated with a single
CPS-like family unit. Some of the distinctions between CPS and
MEPS defined families are that MEPS families include and CPS
families do not include: non-married partners, foster
children, and in-laws. These persons are considered as members
of separate families for CPS-like families. The reason
CPS-like families are defined is so that a poverty status
classification variable consistent with established
definitions of poverty can be assigned to the CPS-like
families and used for weight poststratification purposes.
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Geographic Variables
The variable REGION indicates the Census
region for the RU for 2008. MSA indicates whether or not the RU is found in a
metropolitan statistical area in 2008.
Demographic Variables
Demographic variables
provide information about the demographic characteristics of
each person from the MEPS-HC. The characteristics include age,
sex, race, ethnicity, educational attainment, marital status,
and military service.
The variables describing
demographic status [i.e., related to marital status (MARRY),
educational attainment (EDUCAT)], of the person for 2008 were
developed using the following algorithm: data were taken from
Round 5/3 counterpart if non-missing; else, if missing, data
were taken from the Round 4/2 counterpart; else from the Round
3/1 counterpart. If no valid data was available during any of
these Rounds of data collection, the same algorithm was
followed to assign a missing value other than -1
(Inapplicable).
Age
Date of birth and age
for each RU member were asked or verified during each MEPS
interview.
If date of birth was
available, age was calculated based on the difference between
date of birth and date of interview (or the date of death, if
the person died prior to the interview date). Inconsistencies
between the calculated age and the age reported during the
CAPI interview were reviewed and resolved. For purposes of
confidentiality, the variables AGE was top coded at 90 years.
When date of birth was
not provided but age was provided (either from the MEPS
interviews or the 2006-2007 NHIS data), the month and year of
birth were assigned randomly from among the possible valid
options. For any cases still not accounted for, age was
imputed using
- the mean age difference between MEPS
participants with certain family relationships (where
available) or
- the mean age value for MEPS
participants.
For example, a mother’s
age is imputed as the average age of her children plus 26,
where 26 is the mean age difference between MEPS mothers and
their children. Or a wife’s age is imputed as the husband’s
age minus 3, where 3 is the mean age difference between MEPS
wives and husbands.
AGE was constructed using the following algorithm: Age was taken from the Dec 31st variable if non-missing; else, if missing, age was taken from Round 4/2 counterpart; else from the Round 3/1 counterpart. If no valid data was available during any of these Rounds of data collection, the same algorithm was followed to assign a missing value other than -1 (Inapplicable).
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Sex
Data on the gender of each RU member (SEX) were initially determined from the
2006 NHIS for Panel 12 and from the 2007 NHIS for Panel 13. The SEX variable was verified and,
if necessary, corrected during each MEPS interview. The data for new RU members (persons who
were not members of the RU at the time of the NHIS interviews) were also obtained during each
MEPS Round. When gender of the RU member was not available from the NHIS interviews and was
not ascertained during one of the subsequent MEPS interviews, it was assigned in the
following way. The person’s first name was used to assign gender if obvious (no cases were
resolved in this way). If the person’s first name provided no indication of gender, then
family relationships were reviewed. If neither of these
approaches made it possible to determine the individual’s gender, gender was
randomly assigned.
Race, Race/Ethnicity, Hispanic Ethnicity, and Hispanic Ethnicity Group
Race (RACEX) and Hispanic ethnicity (HISPANX)
questions were initially asked for each RU member during the Round 1 MEPS
interview. If this information was not obtained in Round 1, the questions were
asked in subsequent rounds. When race and/or ethnicity was not reported in the
Rounds, values for these variables were obtained based on the following priority
order. When available, they were obtained from the originally collected NHIS
data (2006 or 2007, depending on the Panel). If not ascertained, the race,
and/or ethnicity were assigned based on relationship to other members of the RU
using a priority ordering that gave precedence to blood relatives in the
immediate family. The variable RACETHNX indicating both race and ethnicity
(e.g., with categories such as "Hispanic" and "black but not
Hispanic") reflects the imputations done for RACEX and HISPANX. The
specific Hispanic ethnicity group is given in the unedited variable HISPCAT.
Marital Status
Current marital status
was collected and/or updated during every round of the MEPS
interview. This information was obtained in RE13 and RE97 and
summarized as MARRY. Persons under the age of 16 were coded as
6 (under 16 – inapplicable). If marital status of a
specified round differed from that of the previous round, then
the marital status of the specified round was edited to
reflect a change during the round (e.g., married in round,
divorced in round, separated in round, or widowed in round).
In instances where there
were discrepancies between the marital status of two
individuals within a family, other person-level variables were
reviewed to determine the edited marital status for each
individual. Thus, when one spouse was reported as married and
the other spouse reported as widowed, the data were reviewed
to determine if one partner should be coded as 8 (Widowed in
Round).
Edits were
performed to ensure minimal consistency
across rounds. First, a person could not be coded as
"Never Married" after previously being coded as any
other marital status (e.g. "Widowed"). Second, a
person could not be coded as "Under 16 –
Inapplicable" after being previously coded as any other
marital status. Third, a person could not be coded as
"Married in Round" after being coded as
"Married" in the round immediately preceding.
Fourth, a person could not be coded as an "in Round"
code (e.g., "widowed in Round") in two subsequent
rounds. Since marital status can change across rounds and it was not
feasible to edit every combination of values across rounds, unlikely sequences
for marital status across the round-specific variables do
exist.
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Student Status and Educational Attainment
Completed years of education are summarized
in the variable EDUCAT. Information was obtained from
questions RE 103-105. Children who are 5 years of age or older
and who never attended school were coded as 0; children under
the age of 5 years were coded as -1 (Inapplicable) regardless
of whether or not they attended school. However, among the
cases coded as inapplicable, there is no distinction between
those who were under the age of five and others who were
inapplicable, such as persons who may be institutionalized for
an entire round.The user should note that the EDUCAT is an
unedited variable and minimal data cleaning was performed on
this variable.
Income Variables
Income related variables
were constructed primarily from data collected in the Panel 12 Round 5 and Panel 13 Round 3
Income Sections. Person-level income amounts have been edited
and imputed for every record on the full-year file.
During imputation, logical editing and
weighted, sequential hot-decks were used to estimate
income amounts for missing values (both for item nonresponse
and for persons in the full-year file who were not in the income rounds).
Reported income components were generally left unedited
(with the few exceptions noted below). Thus, analysts using
these data may wish to apply additional checks for outlier
values that would appear to stem from mis-reporting.
Total person-level
income (TTLP08X) is the sum of all income components with the exception of
REFDP08X and SALEP08X (to match as closely as possible the CPS definition
of income).
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Income Top-Coding
All person-level income amounts on the file,
including both total income and the separate sources of income, were top coded
to preserve confidentiality. For each income source, top codes were applied to
the top percentile of all cases (including negative amounts that exceeded income
thresholds in absolute value). In cases where less than one percent of all persons
received a particular income source, all recipients were top-coded.
Top-coded income amounts were masked using
a regression-based approach. The regressions relied on many of the same variables
used in the hot-deck imputations, with the dependent variable in each case being
the natural logarithm of the amount that the income component was in excess of
its top-code threshold. Predicted values from this regression were reconverted
from logarithms to levels using a smearing correction, and these predicted amounts
were then added back to the top-code thresholds. This approach preserves the
component-by-component weighted means (both overall and among top-coded cases),
while also preserving much of the income distribution conditional on the variables
contained in the regressions. At the same time, this approach ensures that every
reported amount in excess of its respective threshold is altered on the public use
file. The process of top-coding income amounts in this way inevitably introduces
measurement error in cases where income amounts were reported correctly by respondents.
Note, however, that top-coding can also help to reduce the impact of outliers that
occur due to reporting errors.
Total person-level income is constructed
as the sum of the adjusted person-level income components. Having constructed
total income in this manner, this total was then top-coded using the same
regression-based procedure described above (again masking the top percentile of cases).
Finally, the components of income were scaled up or down in order to make the
sources of income consistent with the newly-adjusted totals.
Poverty Status
POVCAT08 is a categorical variable for
2008 family income as a percentage of poverty. This variable was constructed
primarily from data collected in the income rounds. Logical editing and
weighted, sequential hot-deck imputation was used to impute income amounts for
missing values (both for item non-response and or persons in the full-year file
who were not in the income rounds). Round-level data on employment status, hours worked,
and wages were used to supplement earnings data collected in the Income Section.
Family income was derived by constructing person-level total income comprising
annual earnings from wages, salaries, bonuses, tips, commissions; business and
farm gains and losses; unemployment and workman’s compensation; interest and
dividends; alimony, child support, and other private cash transfers; private
pensions, IRA withdrawals, social security, and veterans payments; supplemental
security income and cash welfare payments from public assistance, Temporary Assistance for Needy Families,
and related programs; gains or losses
from estates, trusts, partnerships, S corporations, rent, and royalties; and a
small amount of "other" income. Person-level income excluded tax refunds and
capital gains. Person-level income totals were then summed over family members,
as defined by the CPS, to yield CPS family-level total income. POVCAT08 is constructed
by dividing CPS family income by the applicable poverty line (based on family size
and composition), with the resulting percentages grouped into 5 categories;
negative or poor (less than 100%), near poor (100 to less than 125%), low income
(125 to less than 200%), middle income (200 to less than 400%), and high income
(400%+). Persons missing CPSFAMID were treated as one-person families
in constructing POVCAT08. Family income, as well as
the components of person level income, have been subjected to internal editing
patterns and derivation methods that are in accordance to specific definitions,
and are not being released at this time.
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Employment Variables
Employment questions were asked of all
persons 16 years and older at the time of the interview. Employment status was
summarized using the following: data were taken from Round 5/3 counterpart if
non-missing; else, if missing, data were taken from the Round 4/2 counterpart;
else from the Round 3/1 counterpart. If no valid data was available during any
of these Rounds of data collection, the same algorithm was followed to assign a
missing value other than -1 (Inapplicable).
Health Insurance Variables
Question on health insurance
coverage are asked during every round. One edit to the
private insurance variables corrects for a problem concerning
covered benefits that occurred when respondents reported a change
in any of their private health insurance plan names. Additional edits
address issues of missing data on the time period of coverage for
both public and private coverage that was either reviewed or
initially reported in a given round. Additional edits, described in the full year
documentation,
were performed on the Medicare and Medicaid or State Children’s Health
Insurance Program (SCHIP) variables to assign persons to coverage from
these sources. Observations that contain edits assigning persons to
Medicare or Medicaid/SCHIP coverage can be identified by comparing the
edited and unedited versions of the Medicare and Medicaid/SCHIP variables.
Starting October 1, 2001, persons 65 years and older have been able to
retain TRICARE coverage in addition to Medicare. Therefore, unlike in
earlier MEPS public use files, persons 65 years and older do not have
their reported TRICARE coverage overturned.
TRICARE acts as a supplemental insurance for Medicare, similar to Medigap insurance.
Public sources include
Medicare, TRICARE, Medicaid, SCHIP, and other public
hospital/physician coverage.
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2008 Summary Insurance Coverage Indicators (PRVEV08 - INSURCOV)
The variables PRVEV08-UNINS08 summarize health
insurance coverage for the person in 2008 for the following types of
insurance: private (PRVEV08); TRICARE (TRIEV08); Medicaid or SCHIP
(MCDEV08); Medicare (MCREV08); other public A (OPAEV08); other
public B (OPBEV08). Each variable was constructed based on the
values of the corresponding 12 month-by-month health insurance
variables described above. A value of 1 indicates that the person
was covered for at least one day of at least one month during 2008.
A value of 2 indicates that the person was not covered for a given
type of insurance for all of 2008. The variable UNINS08 summarizes
PRVEV08-OPBEV08. Where PRVEV08-OPBEV08 are all equal to 2, then
UNINS08 equals 1; person was uninsured for all of 2008. Otherwise
UNINS08 is set to 2, not uninsured for some portion of 2008.
For user convenience this file contains a
constructed variable INSURCOV that summarizes health insurance
coverage for the person in 2008, with the following values:
| 1 |
<65, ANY PRIVATE |
(Person had any private insurance coverage (including Tricare) any time during
2008) |
| 2 |
<65, ANY PUBLIC |
( Person had any public insurance coverage any time during
2008) |
| 3 |
<65, UNINSURED |
( Person was uninsured during all of 2008) |
| 4 |
65+, MEDICARE ONLY |
( Person had only Medicare coverage during
2008) |
| 5 |
65+, MEDICARE AND PRIVATE |
( Person had private insurance coverage (including Tricare) and Medicare coverage during
2008) |
| 6 |
65+, MEDICARE AND OTHER PUBLIC |
( Person had Medicare coverage and some other public coverage during
2008) |
| 7 |
65+, UNINSURED |
( Person was over 65 and uninsured during all of
2008) |
| 8 |
65+, NO MEDICARE & OTHER INS |
( Person was over 65 and had no Medicare or other insurance during all of
2008) |
Please note this variable categorizes Tricare as private
coverage. If an analyst wishes to consider Tricare public coverage, the variable
can easily be reconstructed using the PRVEV08 and TRIEV08 variables.
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Health Status Variables
HEALTH is a summary variable that
describes general health status (excellent, good, fair, poor). It is asked of
all sampled persons each round. Data were taken from Round 5/3 counterpart if
non-missing; else, if missing, data were taken from the Round 4/2 counterpart;
else from the Round 3/1 counterpart. If no valid data was available during any
of these Rounds of data collection, the same algorithm was followed to assign a
missing value other than -1 (Inapplicable).
Utilization, Expenditures and Source of Payment Variables (TOTTCH08-RXOSR08)
The MEPS Household Component (HC) collects
data in each round on use and expenditures for office- and
hospital-based care, home health care, dental services, vision aids,
and prescribed medicines. Data were collected for each sample person
at the event level (e.g. doctor visit, hospital stay) and summed
across Rounds 3-5 for Panel 12 (excluding 2007 events covered in Round 3)
and Rounds 1-3 for Panel 13 (excluding 2009 events covered in Round 3) to
produce the annual utilization and expenditure data for 2008 in this
file. In addition, the MEPS Medical Provider Component (MPC) is a
follow-back survey that collected data from a sample of medical
providers and pharmacies that were used by sample persons in 2008.
Expenditure data collected in the MPC are generally regarded as more
accurate than information collected in the HC and were used to
improve the overall quality of MEPS expenditure data in this file
(see below for description of methodology used to develop
expenditure data).
This file contains utilization and
expenditure variables for several categories of health care
services. In general, there is one utilization variable (based on HC
responses only), 13 expenditure variables (derived from both HC and
MPC responses), and one charge variable for each category of health
care service. The utilization variable is typically a count of the
number of medical events reported for the category. The 13
expenditure variables consist of an aggregate total payments
variable, 10 main component source of payment category variables,
and two additional source of payment category variables (see below for
description of source of payment categories). Expenditure variables
for all categories of health care combined are also provided.
Please see the full public use file
documentation for a table in Appendix 1 which provides an overview
of the utilization and expenditure variables included in this file.
For each health service category, the table lists the
corresponding utilization variable(s) and provides a general key to
the expenditure variable names (13 per service category). The first
three characters of the expenditure variable names reflect the service
category (except only two characters for prescription medicines) while
the subsequent three characters (*** in table) reflect the naming
convention for the source of payment categories described below
(except only two characters for Veterans Administration). The last two
positions of all utilization and expenditure variable names reflect
the survey year (i.e. 08).
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Expenditures Definition
Expenditures on this file refer to what is paid
for health care services. More specifically, expenditures in MEPS are
defined as the sum of direct payments for care provided during the
year, including out-of-pocket payments and payments by private
insurance, Medicaid, Medicare, and other sources. Payments for over
the counter drugs are not included
in MEPS total expenditures. Indirect payments not related to specific
medical events, such as Medicaid Disproportionate Share and Medicare
Direct Medical Education subsidies, are also not included.
The definition of expenditures used in MEPS is
somewhat different from the 1987 NMES and 1977 NMCES surveys where charges
rather than sum of payments were used to measure expenditures.
This change was adopted because charges became a less appropriate
proxy for medical expenditures during the 1990s due to the
increasingly common practice of discounting charges. Another change
from the two prior surveys is that charges associated with uncollected
liability, bad debt, and charitable care (unless provided by a public
clinic or hospital) are not counted as expenditures because there are
no payments associated with those classifications.
While the concept of expenditures in MEPS has
been operationalized as payments for health care services, variables
reflecting charges for services received are also provided on the file
(see below). Analysts should use caution when working with the charge
variables because they do not typically represent actual dollars
exchanged for services or the resource costs of those services.
Data Sources on Expenditures
The expenditure data included on this file were
derived from the MEPS Household and Medical Provider Components. Only
HC data were collected for nonphysician visits, dental and vision
services, other medical equipment and services, and home health care
not provided by an agency while data on expenditures for care provided
by home health agencies were only collected in the MPC. In addition to
HC data, MPC data were collected for some office-based visits to
physicians (or medical providers supervised by physicians),
hospital-based events (e.g. inpatient stays, emergency room visits,
and outpatient department visits), and prescribed medicines. For these
types of events, MPC data were used if complete; otherwise HC data
were used if complete. Missing data for events where HC data were not
complete and MPC data were not collected or complete were derived
through an imputation process (see below).
A series of logical edits were applied to both
the HC and MPC data to correct for several problems including, but not limited to,
outliers, copayments or charges reported as total payments, and
reimbursed amounts that were reported as out of pocket payments. In
addition, edits were implemented to correct for misclassifications
between Medicare and Medicaid and between Medicare HMO’s and private
HMO’s as payment sources. Data were not edited to insure complete
consistency between the health insurance and source of payment
variables on the file.
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Imputation for Missing Expenditures and Data Adjustments
Expenditure data were imputed to 1) replace
missing data, 2) provide estimates for care delivered under capitated
reimbursement arrangements, and 3) to adjust household reported
insurance payments because respondents were often unaware that their
insurer paid a discounted amount to the provider. This section
contains a general description of the approaches used for these three
situations. A more detailed description of the editing and imputation
procedures is provided in the documentation for the
MEPS event level files.
Missing data on expenditures were imputed using
a weighted sequential hot-deck procedure for most medical visits and
services. In general, this procedure imputes data from events with
complete information to events with missing information but similar
characteristics. For each event type, selected predictor variables
with known values (e.g., total charge, demographic characteristics,
region, provider type, and characteristics of the event of care, such
as whether it involved surgery) were used to form groups of donor
events with known data on expenditures, as well as identical groups of
recipient events with missing data. Within such groups, data were
assigned from donors to recipients, taking into account the weights
associated with the MEPS complex survey design. Only MPC data were
used as donors for hospital-based events while data from both the HC
and MPC were used as donors for office-based physician visits.
Because payments for medical care provided under
capitated reimbursement arrangements and through public clinics and
Veterans’ Hospitals are not tied to particular medical events,
expenditures for events covered under those types of arrangements and
settings were also imputed. Events covered under capitated
arrangements were imputed from events covered under managed care
arrangements that were paid based on a discounted fee-for-service
method, while imputations for visits to public clinics and Veterans’
Hospitals were based on similar events that were paid on a
fee-for-service basis. As for other events, selected predictor
variables were used to form groups of donor and recipient events for
the imputations.
An adjustment was also applied to some HC
reported expenditure data because an evaluation of matched HC/MPC data
showed that respondents who reported that charges and payments were
equal were often unaware that insurance payments for the care had been
based on a discounted charge. To compensate for this systematic
reporting error, a weighted sequential hot-deck imputation procedure
was implemented to determine an adjustment factor for HC reported
insurance payments when charges and payments were reported to be
equal. As for the other imputations, selected predictor variables were
used to form groups of donor and recipient events for the imputation
process.
Methodology for Flat Fee Expenditures
Most of the expenditures for medical care
reported by MEPS participants are associated with single medical
events. However, in some situations there is one charge that covers
multiple contacts between a medical provider and patient (e.g.
obstetrician services, orthodontia). In these situations (generally
called flat or global fees), total payments for the flat or global fee
were included if the initial service was provided in 2008. For
example, all payments for an orthodontist’s fee that covered
multiple visits over three years were included if the initial visit
occurred in 2008. However, if a visit in 2008 to an orthodontist was
part of a flat fee in which the initial visit occurred in 2007,
then none of the payments for the flat fee were included.
The approach used to count expenditures for flat
fees may create what appear to be inconsistencies between utilization
and expenditure variables. For example, if several visits under a flat
fee arrangement occurred in 2008 but the first visit occurred in 2007,
then none of the expenditures were included, resulting in low
expenditures relative to utilization for that person. Conversely, the
flat fee methodology may result in high expenditures for some persons
relative to their utilization. For example, all of the expenditures
for an expensive flat fee were included even if only the first visit
covered by the fee had occurred in 2008. On average, the methodology
used for flat fees should result in a balance between overestimation
and underestimation of expenditures in a particular year.
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Zero Expenditures
There are some medical events reported by respondents
where the payments were zero. This could occur for several reasons including (1)
free care was provided, (2) bad debt was incurred, (3) care was covered under a
flat fee arrangement beginning in an earlier year, or (4) follow-up visits were
provided without a separate charge (e.g. after a surgical procedure). In
summary, these types of events have no impact on the person level expenditure
variables contained in this file.
Source of Payment Categories
In addition to total expenditures, variables are provided which itemize expenditures according to the major source of payment categories. These categories are:
- Out of pocket by user or family (SLF);
- Medicare (MCR);
- Medicaid (MCD);
- Private Insurance (PRV);
- Veterans’ Administration, excluding CHAMPVA (VA);
- TRICARE (TRI);
- Other Federal Sources--includes Indian Health Service, Military Treatment Facilities, and other care provided by the Federal government (OFD);
- Other State and Local Source--includes community and neighborhood clinics, State and local health departments, and State programs other than Medicaid (STL);
- Worker’s Compensation (WCP);
- Other Unclassified Sources--includes sources such as automobile, homeowner’s, liability, and other miscellaneous or unknown sources (OSR).
Two additional source of payment variables were created to classify payments for particular persons that appear inconsistent due to differences between the survey questions on health insurance coverage and sources of payment for medical events. These variables include:
- Other Private (OPR): any type of private insurance payments reported for persons not reported to have any private health insurance coverage during the year as defined in MEPS (i.e. for hospital and physician services); and
- Other Public (OPU): Medicaid payments reported for persons who were not reported to be enrolled in the Medicaid program at any time during the year.
Though relatively small in magnitude, users
should exercise caution when interpreting the expenditures associated
with the OPR and OPU categories. While these payments stem from
apparent inconsistent responses to the health insurance and source of
payment questions in the survey, some of these inconsistencies may
have logical explanations. For example, private insurance coverage in
MEPS is defined as having a major medical plan covering hospital and
physician services. If a MEPS sample person did not have such coverage
but had a single service type insurance plan (e.g. dental insurance)
that paid for a particular episode of care, those payments may be
classified as ‘other private’. Some of the ‘other public’
payments may stem from confusion between Medicaid and other state and
local programs or may be for persons who were not enrolled in
Medicaid, but were presumed eligible by a provider who ultimately
received payments from the program.
The naming conventions used for the source of
payment expenditure variables are shown in parentheses in the list of
categories above and in the key to the attached table in Appendix 1 of
the 2008 Full Year Public Use File Documentation. In addition, total
expenditure variables (EXP in key) based on the sum of the 12 source
of payment variables above are provided.
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Charge Variables
In addition to the expenditure variables described above,
a variable reflecting total charges is provided for each type of service
category (except prescribed medicines). This variable represents the sum
of all fully established charges for care received and usually does not reflect
actual payments made for services, which can be substantially lower due to
factors such as negotiated discounts, bad debt, and free care (see above). The
naming convention used for the charge variables (TCH) is also included in the
key Appendix 1 of the 2008 Full Year Public Use File Documentation. The total
charge variable across services (TOTTCH08) excludes prescribed medicines.
Utilization and Expenditure Variables by Type of Medical Service
The following sections summarize definitional,
conceptual and analytic considerations when using the utilization and
expenditure variables in this file. Separate discussions are provided
for each MEPS medical service category.
Medical Provider Visits (i.e., Office-Based Visits)
Medical provider visits consist of encounters
that took place primarily in office-based settings and clinics. Care
provided in other settings such as a hospital, nursing home, or a
person’s home are not included in this category.
The total number of office based visits reported
for 2008 (OBTOTV08) as well as the number of such visits to physicians
(OBDRV08) and non-physician providers (OBOTHV08) are contained in this
file. For a small proportion of sample persons, the sum of the
physician and non-physician visit variables (OBDRV08+OBOTHV08) is less
than the total number of office-based visits variable (OBTOTV08)
because OBTOTV08 contains reported visits where the respondent did not
know the type of provider.
Non-physician visits (OBOTHV08) include visits
to the following types of providers: chiropractors, midwives, nurses
and nurse practitioners, optometrists, podiatrists, physician’s
assistants, physical therapists, occupational therapists,
psychologists, social workers, technicians,
receptionists/clerks/secretaries, or other medical providers. Separate
utilization variables are included for selected types of more commonly
seen non-physician providers including chiropractors (OBCHIR08),
nurses/nurse practitioners (OBNURS08), optometrists (OBOPTO08),
physician assistants (OBASST08), and physical or occupational
therapists (OBTHER08).
Expenditure variables associated with all
medical provider visits, physician visits, and non-physician visits in
office-based settings can be identified in Appendix 1 of the 2008 Full
Year Public Use File Documentation. As for the corresponding
utilization variables, the sum of the physician and non-physician
visit expenditure variables (e.g. OBDEXP08+OBOEXP08) is less than the
total office-based expenditure variable (OBVEXP08) for a small
proportion of sample persons. This can occur because OBVEXP08 includes
visits where the respondent did not know the type of provider seen.
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Hospital Events
Separate utilization variables for hospital care
are provided for each type of setting (inpatient, outpatient
department, and emergency room) along with two expense variables per
setting; one for basic hospital facility expenses and another for
payments to physicians who billed separately for services provided at
the hospital. These payments are referred to as "separately
billing doctor" or SBD expenses.
Hospital facility expenses include all expenses
for direct hospital care, including room and board, diagnostic and
laboratory work, x-rays, and similar charges, as well as any physician
services included in the hospital charge. Separately billing doctor (SBD)
expenses typically cover services provided to patients in hospital
settings by providers like radiologists, anesthesiologists, and
pathologists, whose charges are often not included in hospital bills.
Hospital Outpatient Visits
Variables for the total number of reported
visits to hospital outpatient departments in 2008 (OPTOTV08) as well
as the number of outpatient department visits to physicians (OPDRV08)
and non-physician providers (OPOTHV08) are contained in this file. For
a small proportion of sample persons, the sum of the physician and
non-physician visit variables (OPDRV08+OPOTHV08) is less than the
total number of outpatient visits variable (OPTOTV08) because OPTOTV08
contains reported visits where the respondent did not provide
information on the type of provider seen.
Expenditure variables (both facility and SBD)
associated with all medical provider visits, physician visits, and
non-physician visits in outpatient departments can be identified in
Appendix 1 of the 2008 Full Year Public Use File Documentation. As for
the corresponding utilization variables, the sum of the physician and
non-physician expenditure variables (e.g. OPVEXP08+OPOEXP08 for
facility expenses) is less than the variable for total outpatient
department expenditures (OPFEXP08) for a small proportion of sample
persons. This can occur because OBFEXP08 includes visits where the
respondent did not know the type of provider seen. No expenditure
variables are provided for health care consultations that occurred
over the telephone.
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Hospital Emergency Room Visits
The variable ERTOT08 represents a count of all emergency
room visits reported for the survey year. Expenditure variables associated with
ERTOT08 are identified in Appendix 1 of the 2008 Full Year Public Use File
Documentation. It should be noted that hospitals usually include expenses
associated with emergency room visits that immediately result in an inpatient
stay with the charges and payments for the inpatient stay. Therefore, to avoid
the potential for double counting when imputing missing expenses, separately
reported expenditures for emergency room visits that were identified in the MPC
as directly linked to an inpatient stay were included as part of the inpatient
stay only (see below). This strategy to avoid double counting resulted in $0
expenditures for these emergency room visits. However, these $0 emergency room
visits are still counted as separate visits in the utilization variable ERTOT08.
Hospital Inpatient Stays
Two measures of total inpatient utilization are
provided on the file: (1) total number of hospital discharges
(IPDIS08) and (2) the total number of nights associated with these
discharges (IPNGTD08). IPDIS08 includes hospital stays where the dates
of admission and discharge were reported as identical. These
"zero night stays" can be included or excluded from
inpatient analyses at the users’ discretion (see last paragraph of
this section). If the number of nights in the hospital could not be
computed for any reported stay for a person, then IPNGTD08 was
assigned a missing value.
Expenditure variables associated with hospital
inpatient stays are identified in Appendix 1 of the 2008 Full Year
Public Use File Documentation. To the extent possible, payments
associated with emergency room visits that immediately preceded an
inpatient stay are included with the inpatient expenditures (see
above) and payments associated with healthy newborns are included with
expenditures for the mother (see next paragraph for more detail).
Data used to construct the inpatient utilization
and expenditure variables for newborns were edited to exclude stays
where the newborn left the hospital on the same day as the mother.
This edit was applied because discharges for infants without
complications after birth were not consistently reported in the survey
and charges for newborns without complications are typically included
in the mother’s hospital bill. However, if the newborn was
discharged at a later date than the mother was discharged, then the
discharge was considered a separate stay for the newborn when
constructing the utilization and expenditure variables.
Some analysts may prefer to exclude zero night
stays from inpatient analyses and/or count these stays as ambulatory
visits. Therefore, a separate use variable is provided which contains
a count of the number of inpatient events where the reported dates of
admission and discharge were the same (IPZERO08). This variable can be
subtracted from IPDIS08 to exclude zero night stays from inpatient
utilization estimates. In addition, separate expenditure variables are
provided for zero night facility expenses (ZIFEXP08) and for
separately billing doctor expenses (ZIDEXP08). Analysts who choose to
exclude zero-night stays from inpatient expenditure analyses need to
subtract the zero-night expenditure variable from the corresponding
expenditure variable for total inpatient stays (e.g. IPFEXP08-ZIFEXP08
for facility expenses, IPDEXP08-ZIDEXP08 for separately billing doctor
expenses).
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Dental Visits
The total number of dental visits variable (DVTOT08)
includes those to any person(s) for dental care including general dentists,
dental hygienists, dental technicians, dental surgeons, orthodontists,
endodontists, and periodontists. Additional variables are provided for the
numbers of dental visits to general dentists (DVGEN08) and to orthodontists
(DVORTH08). For a small proportion of sample persons, the sum of the general
dentist and orthodontist visit variables (DVGEN08+DVORTH08) is greater than the
total number of dental visits (DVTOT08). This result can only occur for persons
who were reported to have seen both a general dentist and orthodontist in the
same visit(s). When this occurred, expenditures for the visit were included as
orthodontist expenses but not as general dentist expenses. Expenditure variables
for all three categories of dental providers can be identified in Appendix 1 of
the 2008 Full Year Public Use File Documentation.
Home Health Care
In contrast to other types of medical events where data were collected on a
per visit basis, information on home health care utilization is collected in
MEPS on a per month basis. Variables are provided which indicate the total
number of days in 2008 where home health care was received from any type of paid
or unpaid caregiver (HHTOTD08), agencies, hospitals, or nursing homes (HHAGD08),
self-employed persons (HHINDD08), and unpaid informal caregivers not living with
the sample person (HHINFD08). The number of provider days represents the sum
across months of the number of days on which home health care was received, with
days summed across all providers seen. For example, if a person received care in
one month from one provider on 2 different days, then the number of provider
days would equal 2. The number of provider days would also equal 2 if a person
received care from 2 different providers on the same day. However, if a person
received care from 1 provider 2 times in the same day, then the provider days
would equal 1. These variables were assigned missing values if the number of
provider days could not be computed for any month in which the specific type of
home health care was received.
Separate expenditure variables are provided for agency-sponsored home health
care (includes care provided by home health agencies, hospitals, and nursing
homes) and care provided by self-employed persons. A table in Appendix 1 of the
2008 Full Year Public Use File Documentation identifies the home health care
utilization and expenditure variables contained in the file.
Vision Aids
Expenditure variables for the purchase of glasses and/or
contact lenses are identified in Appendix 1 of the 2008 Full Year Public Use
File Documentation. Due to the data collection methodology, it was not possible
to determine whether vision items that were reported in round 3 had been
purchased in 2006 or 2008. Therefore, expenses reported in round 3 were only
included if more than half of the person’s reference period for the round was
in 2008.
Other Medical Equipment and Services
This category includes expenditures for ambulance
services, orthopedic items, hearing devices, prostheses, bathroom aids, medical
equipment, disposable supplies, alterations/modifications, and other
miscellaneous items or services that were obtained, purchased or rented during
the year. On this file, diabetic supplies and insulin are not considered to be
medical equipment. All use and expenditure information for these items are included
in the prescribed medicine variables. Respondents were only asked once (in round 3) about their total annual
expenditures and were not asked about their frequency of use of these services.
Expenditure variables representing the combined expenses for these supplies and
services are identified in Appendix 1 of the 2008 Full Year Public Use File
Documentation.
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Prescribed Medicines
There is one total utilization variable (RXTOT08) and 13
expenditure variables included on the 2008 full-year file relating to prescribed
medicines. These 13 expenditure variables include an annual total expenditure
variable (RXEXP08) and 12 corresponding annual source of payment variables
(RXSLF08, RXMCR08, RXMCD08, RXPRV08, RXVA08, RXTRI08, RXOFD08, RXSTL08, RXWCP08,
RXOSR08, RXOPR08, and RXOPU08). The total utilization variable is a count of
all prescribed medications purchased in 2008, and includes initial purchases
and refills. The total
expenditure variable sums all amounts paid out-of-pocket and by third party
payers for each prescription purchased in 2008. No variables reflecting charges
for prescription medicines are included because a large proportion of
respondents to the pharmacy component survey did not provide charge data (see
below).
Prescribed Medicines Data Collected
Data regarding prescription drugs were obtained
through the household questionnaire and a pharmacy component survey.
During each round of the MEPS HC, all respondents were asked to supply
the name of any prescribed medication they or their family members
purchased or otherwise obtained during that round. For each medication
and in each round, the following information was collected: whether
any free samples of the medication were received; the name(s) of any
health problems the medication was prescribed for; the number of times
the prescription drug was obtained or purchased; the year, month, and
day on which the person first used the medication; and a list of the
names, addresses, and types of pharmacies that filled the household’s
prescriptions. Also, during the Household Component, respondents were
asked if they send in claim forms for their prescriptions
(self-filers) or if their pharmacy providers do this automatically for
them at the point of purchase (non-self-filers). For non-self-filers,
charge and payment information was collected in the pharmacy component
survey, unless the purchase was an insulin or diabetic supply/equipment event.
However, charge and payment information was collected for
self-filers in the household questionnaire, because payments by
private third party payers for self-filers’ purchases would not be
available from a pharmacy component.
Pharmacy providers identified by the household were
contacted by telephone in the pharmacy component if permission was obtained
in writing from the person with the prescription to release their pharmacy
records. The signed permission forms were provided to the various establishments
prior to making any requests for information. Each establishment was informed of
all persons participating in the survey that had prescriptions filled there in
2008 and a computerized printout containing information about these prescriptions
was sought. For each medication listed, the following information was requested:
date filled; national drug code (NDC); medication name; strength of medicine
(amount and unit); quantity (package size and amount dispensed); and payments by source.
When diabetic supplies, such as syringes and
insulin, were reported in the other medical supply section of the MEPS-HC
questionnaire as having been obtained during the round, the
interviewer was directed to collect information on these items in the
prescription drug section of MEPS. Charge and payment information was asked for these
events.
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Prescribed Medicines Data Editing and Imputation
The general approach to preparing the household prescription
data for this file was to utilize the pharmacy component prescription data
to assign expenditure values to the household drug mentions. For events
that charge and payment data were collected from the household in the HC,
information on payment sources was retained to the extent that these data
were reported. A matching program was adopted to link pharmacy component
drugs and the corresponding drug information to household drug mentions.
To improve the quality of these matches, all drugs on the household and
pharmacy files were coded based on the medication names provided by the
household and pharmacy, and when available, the national drug code (NDC)
provided in the pharmacy survey. Considerable editing was done prior to
the matching to correct data inconsistencies in both data sets and fill in missing
data and correct outliers on the pharmacy file.
Drug price per unit outliers were analyzed on the
pharmacy file by first identifying the average wholesale unit price (AWUP)
of the drug by linkage through the NDC to a proprietary data base. In general,
prescription drug unit prices were deemed to be outliers by comparing unit
prices reported in the pharmacy data base to the AWUP and were edited, as
necessary. Beginning with the 2007 data, the rules used to identify outlier
prices for prescription medications in the PC changed. New outlier thresholds
were established based on the distribution of the ratio of retail unit prices
relative to the AWUP in the 2007 MarketScan Outpatient Pharmaceutical Claims
data base. Starting with the 2008 Prescribed Medicine file, improvements in the
data editing changed the distribution of payments by source: (1) more spending
on Medicare beneficiaries is by private insurance, rather than Medicare, and
(2) there are less out-of-pocket payments and more Medicaid payments among
Medicaid enrollees.
For those rounds that spanned two years, drugs mentioned
in that round were allocated between the years based on the number of times
the respondent said the drug was purchased in the respective year, the year
the person started taking the drug, the length of the person’s round, the dates
of the person’s round, and the number of drugs for that person in the round.
In addition, a “folded” version of the PC on an event level, as opposed to an
acquisition level, was used for these types of events to assist in determining
how many acquisitions of the drug should be allocated between the years.
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SURVEY ADMINISTRATION VARIABLES
VARIABLE |
LABEL |
DESCRIPTION |
PANEL |
Panel Number |
PANEL is a constructed variable used to specify the panel number (Panel 12 or 13) for each interview. |
FCSZ1231 |
Family Size Responding 12/31 CPS Family |
Number of persons in the CPS defined
Families in the Civilian Noninstitutionalized Population on 12/31/08 |
FAMSZEYR |
Size of Responding Annualized Family |
Number of persons in the MEPS Family in the
Civilian Noninstitutionalized Population on 12/31/08
|
REGION |
Census Region |
The variable REGION indicates the Census region for the RU for
2008. |
MSA |
Metropolitan Statistical Area |
The variable MSA indicates whether or not the RU is found in a metropolitan statistical area for
2008. |
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DEMOGRAPHIC VARIABLES
VARIABLE |
LABEL |
DESCRIPTION |
AGE |
Age |
Age was constructed from the round specific Age variables
using the algorithm: data was taken from the Dec 31st variable; if
missing then data from Round 5/3; else if missing then data was taken from Round
4/2; else if missing then data was taken from Round 3/1. |
SEX |
Sex |
Data on the sex of each RU member (SEX) were initially
determined from the 2006 NHIS for Panel 12 and from the 2007 NHIS for Panel 13.
The SEX variable was verified and, if necessary, corrected during each MEPS
interview. |
RACEX |
Race (Edited/Imputed) |
Race (RACEX) and Hispanic ethnicity (HISPANX) questions were
initially asked for each RU member during the Round 1 MEPS interview. If this
information was not obtained in Round 1, the questions were asked in subsequent
Rounds. |
RACETHNX |
Race/Ethnicity (Edited/Imputed) |
The variable RACETHNX indicating both race and ethnicity
(e.g., with categories such as "Hispanic" and "black but not
Hispanic") reflects the imputations done for RACEX and HISPANX. |
HISPANX |
Hispanic Ethnicity (Edited/Imputed) |
Race (RACEX) and Hispanic ethnicity (HISPANX) questions were
initially asked for each RU member during the Round 1 MEPS interview. If this
information was not obtained in Round 1, the questions were asked in subsequent
Rounds. |
HISPCAT |
Specific Hispanic Ethnicity Group |
HISPCAT is an unedited variable that provides the specific
Hispanic ethnicity group of the person. |
MARRY |
Marital Status for 2008 |
Current marital status was collected
and/or updated during every Round of the MEPS interview. This information was
obtained in RE13 and RE97 and summarized as MARRY. Persons under the age of 16
were coded as 6 (under 16 – inapplicable). If marital status of a specified
round differed from that of the previous Round, then the marital status of the
specified Round was edited to reflect a change during the Round (e.g., married
in Round, divorced in Round, separated in Round, or widowed in Round).
Marital status was constructed from the
round specific marital status variables using the algorithm: data was taken from
the Dec 31st variable; if missing then data from Round 5/3; else if
missing then data was taken from Round 4/2; else if missing then data was taken
from Round 3/1.
This variable corresponds to MARRY08X on the public use
file. |
EDUCAT |
Education Status for 2008 |
Completed years of education are
summarized in the variable EDUCAT. Information was obtained from questions RE
103-105. Children who are 5 years of age or older and who never attended school
were coded as 0; children under the age of 5 years were coded as -1
(Inapplicable) regardless of whether or not they attended school. However, among
the cases coded as inapplicable, there is no distinction between those who were
under the age of five and others who were inapplicable, such as persons who may
be institutionalized for an entire round.
Education status was constructed from the round specific education status variables using the algorithm: if data were collected in Round 3/1 then data was taken from the Round 3/1 variable; else if data were collected in Round 4/2 then data was taken from the Round 4/2 variable; else data was taken from the Round 5/3 variable. In short, EDUCYR is based on the first round in which years of education was collected for a person.
This variable corresponds to EDUCYR on the public use
file. |
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INCOME VARIABLES
VARIABLE |
LABEL |
DESCRIPTION |
TTLP08X |
PERSON’S TOTAL INCOME |
Total person-level income (TTLP08X) is the
sum of all income components: annual earnings from wages, salaries, bonuses,
tips, commissions; business and farm gains and losses; unemployment and workman’s
compensation; interest and dividends; alimony, child support, and other private
cash transfers; private pensions, IRA withdrawals, social security, and veterans
payments; supplemental security income and cash welfare payments from public
assistance, Aid to Families with Dependent Children, and Aid to Dependent
Children; gains or losses from estates, trusts, partnerships, S corporations,
rent, and royalties; and a small amount of "other"income.
Having constructed total income in this
manner, we then top-coded.Finally, we scaled the components of income up or down
in order to make the sources of income consistent with the newly-adjusted
totals. |
POVCAT08 |
FAMILY INCOME AS PERCENT OF POVERTY LINE |
POVCAT08 is a categorical variable for 2008 family income as
a percentage of poverty. Family income was derived by constructing person-level
total income comprising annual earnings from wages, salaries, bonuses, tips,
commissions; business and farm gains and losses; unemployment and workman’s
compensation; interest and dividends; alimony, child support, and other private
cash transfers; private pensions, IRA withdrawals, social security, and veterans
payments; supplemental security income and cash welfare payments from public
assistance, Aid to Families with Dependent Children, and Aid to Dependent
Children; gains or losses from estates, trusts, partnerships, S corporations,
rent, and royalties; and a small amount of "other"income. Family
income excluded tax refunds and capital gains. Person-level income totals were
then summed over family members as defined by the CPS to yield the family-level
total. POVCAT08 is constructed by dividing family income by the applicable
poverty line (based on family size and composition), with the resulting
percentages grouped into 5 categories; negative or poor (less than 100%), near
poor (100 to less than 125%), low income (125 to less than 200%), middle income
(200 to less than 400%), and high income (400%+). |
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EMPLOYMENT VARIABLES
VARIABLE |
LABEL |
DESCRIPTION |
EMPLOY |
Employment Status for 2008 |
Employment status was constructed from the round specific
employment status variables using the algorithm: data was taken from the Dec 31st variable; if missing then data from Round 5/3; else if missing then data was
taken from Round 4/2; else if missing then data was taken from Round 3/1. |
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HEALTH INSURANCE VARIABLES
VARIABLE |
LABEL |
DESCRIPTION |
PRVEV08 |
Ever have private insurance during 08 |
The variable PRVEV08 summarizes health insurance coverage
for the person in 2008 for private insurance. This variable was constructed
based on the values of the corresponding 12 month to month private health
insurance variables found on the public use file. A value of 1 indicates that
the person was covered for at least one day of at least one month during 2008. A
value of 2 indicates that the person was not covered by private health insurance
for all of 2008. |
TRIEV08 |
Ever have TRICARE during 08 |
The variable TRIEV08 summarizes health TRICARE
coverage for the person in 2008. This variable was constructed based on the
values of the corresponding 12 month to month TRICARE insurance
variables found on the public use file. A value of 1 indicates that the person
was covered for at least one day of at least one month during 2008. A value of 2
indicates that the person was not covered by TRICARE for all of 2008. |
MCDEV08 |
Ever have Medicaid during 08 |
The variable MCDEV08 summarizes Medicaid coverage for the
person in 2008. This variable was constructed based on the values of the
corresponding 12 month to month Medicaid variables found on the public use file.
A value of 1 indicates that the person was covered for at least one day of at
least one month during 2008. A value of 2 indicates that the person was not
covered by Medicaid for all of 2008. |
MCREV08 |
Ever have Medicare during 08 |
The variable MCREV08 summarizes Medicare coverage for the
person in 2008. This variable was constructed based on the values of the
corresponding 12 month to month Medicare insurance variables found on the public
use file. A value of 1 indicates that the person was covered for at least one
day of at least one month during 2008. A value of 2 indicates that the person
was not covered by Medicare for all of 2008. |
OPAEV08 |
Ever have other public A during 08 |
The variable OPAEV08 summarizes other public coverage for a
person where the person reported some type of managed care and paid something
(type A) in 2008. This variable was constructed based on the values of the
corresponding 12 month to month other public insurance (type A) variables found
on the public use file. A value of 1 indicates that the person was covered for
at least one day of at least one month during 2008. A value of 2 indicates that
the person was not covered by other public insurance (type A) for all of 2008. |
OPBEV08 |
Ever have other public B during 08 |
The variable OPBEV08 summarizes other public coverage for a
person where the person did not report any type of managed care (type B) in
2008. This variable was constructed based on the values of the corresponding 12
month to month other public insurance (type B) variables found on the public use
file. A value of 1 indicates that the person was covered for at least one day of
at least one month during 2008. A value of 2 indicates that the person was not
covered by other public insurance (type B) for all of 2008. |
UNINS08 |
Uninsured all of 08 |
The variable UNINS08 summarizes health insurance status as
being uninsured using PRVEV08-OPBEV08. Where PRVEV08-OPBEV08 are all equal to 2,
then UNINS08 equals 1; person was uninsured for all of 2008. Otherwise UNINS08
is set to 2, not uninsured for some portion of 2008. |
INSURCOV |
Full year insurance coverage status |
For user convenience this file contains a constructed
variable INSURCOV that summarizes health insurance coverage for the person in
2008, with the following values:
| 1 |
<65, ANY PRIVATE |
( Person had any private insurance coverage (including Tricare) any time during
2008) |
| 2 |
<65, ANY PUBLIC |
( Person had any public insurance coverage any time during
2008) |
| 3 |
<65, UNINSURED |
( Person was uninsured during all of 2008) |
| 4 |
65+, MEDICARE ONLY |
( Person had only Medicare coverage during
2008) |
| 5 |
65+, MEDICARE AND PRIVATE |
(Person had private insurance coverage (including Tricare) and Medicare coverage during
2008) |
| 6 |
65+, MEDICARE AND OTHER PUBLIC |
(Person had Medicare coverage and some other public coverage during
2008) |
| 7 |
65+, UNINSURED |
(Person was over 65 and uninsured during all of
2008) |
| 8 |
65+, NO MEDICARE & OTHER INS |
(Person was over 65 and had no Medicare or other insurance during all of
2008) |
Please note this variable categorizes Tricare as private
coverage. If an analyst wishes to consider Tricare public coverage, the variable
can easily be reconstructed using the PRVEV08 and TRIEV08 variables. |
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HEALTH STATUS VARIABLES
VARIABLE |
LABEL |
DESCRIPTION |
HEALTH |
Perceived Health Status for 2008 |
Perceived health status was constructed from the round
specific perceived health status variables using the algorithm: data was taken
from the Dec 31st variable; if missing then data from Round 5/3; else
if missing then data was taken from Round 4/2; else if missing then data was
taken from Round 3/1. |
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