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June 2015
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 Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Source and Naming Conventions
2.4.1 Variable - Source Crosswalk
2.4.2 Expenditure and Source of Payment Variables
2.5 File Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID, PID, DUPERSID)
2.5.1.2 Record Identifiers (EVNTIDX, FFEEIDX)
2.5.1.3 Round Indicator (EVENTRN)
2.5.1.4 Panel Indicator (PANEL)
2.5.2 Dental Event Variables
2.5.2.1 Date of Visit (DVDATEYR – DVDATEMM)
2.5.2.2 Type of Provider Seen (GENDENT - DENTYPE)
2.5.2.3 Treatment, Procedures, and Services (EXAMINE - DENTMED)
2.5.3 Flat Fee Variables (FFEEIDX, FFDVTYPE, FFBEF13, FFTOT14)
2.5.3.1 Definition of Flat Fee Payments
2.5.3.2 Flat Fee Variable Descriptions
2.5.3.2.1 Flat Fee ID (FFEEIDX)
2.5.3.2.2 Flat Fee Type (FFDVTYPE)
2.5.3.2.3 Counts of Flat Fee Events that Cross Years (FFBEF13, FFTOT14)
2.5.3.3 Caveats of Flat Fee Groups
2.5.4 Condition, Procedure, and Clinical Classification Codes
2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
2.5.5.2 Data Editing and Imputation Methodologies of Expenditure Variables
2.5.5.2.1 General Data Editing Methodology
2.5.5.2.2 Imputation Methodologies
2.5.5.2.3 Dental Data Editing and Imputation
2.5.5.3 Imputation Flag Variable (IMPFLAG)
2.5.5.4 Flat Fee Expenditures
2.5.5.5 Zero Expenditures
2.5.5.6 Sources of Payment
2.5.5.7 Dental Expenditure Variables (DVSF13X- DVTC13X)
2.5.5.8 Rounding
3.0 Sample Weight (PERWT13F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 17 Weight Development Process
3.2.2 MEPS Panel 18 Weight Development Process
3.2.3 The Final Weight for 2013
3.2.4 Coverage
3.3 Using MEPS Data for Trend Analysis
4.0 Strategies for Estimation
4.1 Developing Event-Level Estimates
4.2 Person-Based Estimates for Dental Care
4.3 Variables with Missing Values
4.4 Variance Estimation (VARPSU, VARSTR)
5.0 Merging/Linking MEPS Data Files
5.1 Linking to the Person-Level File
5.2 Linking to the Prescribed Medicines File
5.3 Linking to the Medical Conditions File
References
D. Variable-Source Crosswalk
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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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. 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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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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MEPS HC and MPC data are collected under the authority
of the Public Health Service Act. Data are collected under contract with Westat,
Inc. (MEPS HC) and Research Triangle Institute (MEPS MPC). 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:
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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This documentation describes one in a series of public
use event files from the 2013 Medical Expenditure Panel Survey (MEPS) Household
Component (HC). Released as an ASCII data file (with related SAS, SPSS, and
Stata programming statements) and a SAS transport file, the 2013 Dental public
use file provides detailed information on dental events for a nationally
representative sample of the civilian noninstitutionalized population of the
United States. Data from the Dental file can be used to make estimates of dental
event utilization and expenditures for calendar year 2013. The file contains 79
variables and has a logical record length of 318 with an additional 2-byte
carriage return/line feed at the end of each record. As illustrated below, this
file consists of MEPS survey data obtained in the 2013 portion of Round 3 and
Rounds 4 and 5 for Panel 17, as well as Rounds 1, 2 and the 2013 portion of
Round 3 for Panel 18 (i.e., the rounds for the MEPS panels covering calendar
year 2013).
Each record on this event file represents a unique
dental event; that is, a dental event reported by the household respondent.
Counts of dental event utilization are based entirely on household reports.
Dental events were not included in the Medical Provider Component (MPC);
therefore, all expenditure and payment data on the Dental event file are
reported by the household.
Data from this event file can be merged with other
2013 MEPS HC data files for the purposes of appending person-level data such as
demographic characteristics or health insurance coverage to each dental record.
This file can also be used to construct summary
variables of expenditures, sources of payment, and related aspects of the dental
event. Aggregate annual person-level information on the use of dental events and
other health services is provided on the MEPS 2013 Full Year Consolidated Data
File where each record represents a MEPS sampled person.
This document offers a brief overview of the types and
levels of data provided, and the content and structure of the file and the
codebook. It contains the following sections:
- Data File Information
- Sample Weights
- Strategies for Estimation
- Merging/Linking MEPS Data Files
- References
- Variable - Source Crosswalk
For more information on MEPS HC survey design, see T.
Ezzati-Rice, et al. (1998-2007) and S. Cohen, 1996. A copy of the MEPS HC survey instrument used to collect the
information on the Dental file is available on the MEPS Web site at the
following address:
meps.ahrq.gov.
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The 2013 Dental public use data set consists of one
event-level data file. The file contains characteristics associated with the
dental event and imputed expenditure data.
The 2013 Dental public use data set contains 28,547
dental event records; of these records, 27,978 are associated with persons
having a positive person-level weight (PERWT13F). This file includes dental
event (DV) records for all household members who resided in eligible responding
households and reported at least one dental event. Each record represents one
household-reported dental event that occurred during calendar year 2013. Dental
visits known to have occurred before January 1, 2013 and after December 31, 2013
are not included on this file. Some household members may have multiple dental
events and thus will be represented in multiple records on this file. Other
household members may have had reported no dental events and thus will have no
records on this file. These data were collected during the 2013 portion of Round
3, and Rounds 4 and 5 for Panel 17, as well as Rounds 1, 2, and the 2013 portion
of Round 3 for Panel 18 of the MEPS HC. The persons represented on this file had
to meet either (a) or (b) below:
- Be classified as a key in-scope person who responded for his
or her entire period of 2013 eligibility (i.e., persons with a
positive 2013 full-year person-level weight (PERWT13F > 0)), or
- Be an eligible member of a family all of whose key in-scope
members have a positive person-level weight (PERWT13F > 0).
(Such a family consists of all persons with the same value for
FAMIDYR.) That is, the person must have a positive
full-year family-level weight (FAMWT13F > 0). Note that FAMIDYR
and FAMWT13F are variables on the 2013 Full Year Consolidated
Data File.
Persons with no dental events for 2013 are not
included on this event-level DV file but are represented on the person-level
2013 Full Year Population Characteristics file.
Each dental event record includes the following: date
of the dental event; type of provider seen; procedure(s) associated with the
dental event; whether or not medicines were prescribed; flat fee information;
imputed sources of payment; total payment and total charge of the dental event
expenditure; and a full-year person-level weight.
To append person-level information such as demographic
or health insurance coverage to each event record, data from this file can be
merged with 2013 MEPS HC person-level data (e.g. Full Year Consolidated or Full
Year Population Characteristics files) using the person identifier, DUPERSID.
Dental events can also be linked to the MEPS 2013 Prescribed Medicines File.
Please see section 5.0 or the 2013 Appendix for details on how to merge MEPS
data files.
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For most variables on the Dental event file, both
weighted and unweighted frequencies are provided in the accompanying codebook.
The exceptions to this are weight variables and variance estimation variables.
Only unweighted frequencies of these variables are included in the accompanying
codebook file. See the Weights Variables list in section D, Variable-Source
Crosswalk.
The codebook and data file sequence list variables in the following order:
- Unique person identifier
- Unique dental event identifier
- Dental characteristic variables
- Imputed expenditure variables
- Weight and variance estimation variables
Note that the person identifier is unique within this data year.
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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 |
Generally, values of -1, -7, -8, and -9 for
non-expenditure variables have not been edited on this file. The values of -1
and -9 can be edited by the data users/analysts by following the skip patterns
in the HC survey questionnaire (located on the MEPS Web site:
meps.ahrq.gov/survey_comp/survey_questionnaires.jsp).
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The codebook describes an ASCII data set (although the
data are also being provided in a SAS transport file). The following codebook
items are provided 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 |
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In general, variable names reflect the content of the
variable, with an eight-character limitation. All imputed/edited variables end
with an “X”.
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Variables were derived from the HC survey
questionnaire or from the CAPI. The source of each variable is identified in
Section D “Variable - Source Crosswalk” in one of four ways:
- Variables derived from CAPI or assigned in sampling are so
indicated as “CAPI derived” or “Assigned in sampling,”
respectively;
- Variables which come from one or more specific questions
have those questionnaire sections and question numbers indicated
in the “Source” column; questionnaire sections are identified
as:
- FF - Flat Fee section
- DN - Dental Event section
- CP - Charge Payment section
- Variables constructed from multiple questions using complex
algorithms are labeled “Constructed” in the “Source” column; and
- Variables that have been edited or imputed are so indicated.
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The names of the expenditure and source of payment
variables follow a standard convention, are seven characters in length, and end
in an “X” indicating edited/imputed. Please note that imputed means that a
series of logical edits, as well as an imputation process to account for missing
data, have been performed on the variable.
The total sum of payments and 12 source of payment
variables are named in the following way:
The first two characters indicate the type of event:
IP - inpatient stay
ER - emergency room visit
HH - home health visit
OM - other medical equipment
OB - office-based visit
OP - outpatient visit
DV - dental visit
RX - prescribed medicine
In the case of the source of payment variables, the
third and fourth characters indicate:
SF - self or family
MR - Medicare
MD - Medicaid
PV - private insurance
VA - Veterans Administration/CHAMPVA
TR - TRICARE
OF - other Federal Government
SL - State/local government
WC - Workers’ Compensation
OT - other insurance
OR - other private
OU - other public
XP - sum of payments
In addition, the total charge variable is indicated by TC in the variable name.
The fifth and sixth characters indicate the year (13).
The seventh character, “X”, indicates the variable is edited/imputed.
For example, DVSF13X is the edited/imputed amount paid
by self or family for 2013 dental expenditures.
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The dwelling unit ID (DUID) is a five-digit random
number assigned after the case was sampled for MEPS. The three-digit person
number (PID) uniquely identifies each person within the dwelling unit. The
eight-character variable DUPERSID uniquely identifies each person represented on
the file and is the combination of the variables DUID and PID. For detailed
information on dwelling units and families, please refer to the documentation
for the 2013 Full Year Population Characteristics File.
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EVNTIDX uniquely identifies each dental event (i.e.,
each record on the Dental file) and is the variable required to link dental
events to data files containing details on prescribed medicines (MEPS 2013
Prescribed Medicines file). For details on linking see Section 5.0 or the MEPS
2013 Appendix File, HC-160I.
FFEEIDX is a constructed variable that uniquely
identifies a flat fee group, that is, all events that were part of a flat fee
payment. For example, a charge for orthodontia is typically covered in a flat
fee arrangement where all visits are covered under one flat fee dollar amount.
These events would have the same value for FFEEIDX. FFEEIDX identifies a flat
fee payment that was identified using information from the Household Component.
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EVENTRN indicates the round in which the dental event
was reported. Please note: Rounds 3 (partial), 4, and 5 are associated with MEPS
survey data collected from Panel 17. Likewise, Rounds 1, 2, and 3 (partial) are
associated with data collected from Panel 18.
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PANEL is a constructed variable used to specify the
panel number for the person. PANEL will indicate either Panel 17 or Panel 18 for
each person on the file. Panel 17 is the panel that started in 2012, and Panel
18 is the panel that started in 2013.
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This file contains variables describing dental events
reported by household respondents in the Dental Section of the MEPS HC survey
questionnaire.
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There are variables that indicate the month and year a
dental event occurred (DVDATEMM and DVDATEYR, respectively). These variables
have not been edited or imputed.
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Respondents were asked about the type of provider seen
during the dental visit (e.g., general dentist, dental hygienist, or
orthodontist). More than one type of provider may have been identified on an
event record.
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Respondents were asked about the types of services or
treatments received during the visit (EXAMINE - TMDTMJ), such as root canal or
x-rays. More than one type of service or treatment may have been identified on
an event record. Some procedures or services identified in DENTOTHR as “Dental
services other specify” have been edited to appropriate procedure and service
categories. While the unedited versions of these variables are included in the
dental event file every year, an edited version of a particular variable is
included only if editing was done for that category. Please note that the
crosswalk in this document lists all possible edited procedure and service
category variables; the edited variables in the data file will differ by year.
The DENTMED variable indicates whether or not the household member received a
prescription medication during the dental visit.
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A flat fee is the fixed dollar amount a person is
charged for a package of services provided during a defined period of time.
Examples would be an orthodontist’s fee, which covers multiple visits; or a
dental surgeon’s fee, which covers surgical procedure and post-surgical care. A
flat fee group is the set of medical services that are covered under the same
flat fee payment. The flat fee groups represented on the dental file include
flat fee groups where at least one of the health care events, as reported by the
HC respondent, occurred during 2013. By definition, a flat fee group can span
multiple years. Furthermore, a single person can have multiple flat fee groups.
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As noted earlier in Section 2.5.1.2 “Record
Identifiers,” the variable FFEEIDX uniquely identifies all events that are part
of the same flat fee group for a person. On any 2013 MEPS event file, every
event that is part of a specific flat fee group will have the same value for
FFEEIDX. Note that prescribed medicine and home health events are never included
in a flat fee group and none of the flat fee variables is on those event files.
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FFDVTYPE indicates whether the 2013 dental event is
the “stem” or “leaf” of a flat fee group. A stem (records with FFDVTYPE = 1) is
the initial dental service (event) which is followed by other dental events that
are covered under the same flat fee payment. The leaves of the flat fee group
(records with FFDVTYPE = 2) are those dental events that are tied back to the
initial medical event (the stem) in the flat fee group. These “leaf” records
have their expenditure variables set to zero. For the dental visits that are not
part of a flat fee payment, the FFDVTYPE is set to -1, “INAPPLICABLE”.
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As described in Section 2.5.3.1, a flat fee payment
covers multiple events and the multiple events could span multiple years. For
situations where a 2013 dental visit is part of a group of events, and some of
the events occurred before or after 2013, counts of the known events are
provided on the dental record. Variables that indicate events occurring before
or after 2013 are the following:
FFBEF13 – indicates total number of pre-2013 events in
the same flat fee group as the 2013 dental event. This count would not include
2013 dental events.
FFTOT14 – indicates the number of 2014 medical events
expected to be in the same flat fee group as the 2013 dental event record.
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Data users/analysts should note that flat fee payments
are common on the dental file. There are 3,998 dental events that are identified
as being part of a flat fee payment group. In general, every flat fee group
should have an initial visit (stem) and at least one subsequent visit (leaf).
There are some situations where this is not true. For some of these flat fee
groups, the initial visit reported occurred in 2013, but the remaining visits
that were part of this flat fee group occurred in 2014. In this case, the 2013
flat fee group represented on this file would consist of one event (the stem).
The 2014 “leaf” events that are part of this flat fee group are not represented
on the file. Similarly, the household respondent may have reported a flat fee
group where the initial visit began in 2012 but subsequent visits occurred
during 2013. In this case, the initial visit would not be represented on the
file. This 2013 flat fee group would then only consist of one or more leaf
records and no stem. Please note that the crosswalk in this document lists all
possible flat fee variables.
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Conditions data are not collected for dental events;
therefore, this file cannot be linked to the Conditions File.
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Expenditures on this file refer to what is paid for
dental services. More specifically, expenditures in MEPS are defined as the sum
of payments for care received, including out-of-pocket payments and payments
made by private insurance, Medicaid, Medicare, and other sources. The definition
of expenditures used in MEPS differs slightly from its predecessors, 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. Although measuring expenditures as
the sum of payments incorporates discounts in the MEPS expenditure estimates,
the estimates do not incorporate any payment not directly tied to specific
medical care visits, such as bonuses or retrospective payment adjustments paid
by third party payers. Another general 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
charge data are provided on this file, data users/analysts should use caution
when working with these data because a charge does not typically represent
actual dollars exchanged for services or the resource costs of those services,
nor are they directly comparable to the resource costs of those services, nor
are they directly comparable to the expenditures defined in the 1987 NMES. For
details on expenditure definitions, please reference the following, “Informing
American Health Care Policy” (Monheit et al., 2000). AHRQ has developed factors
to apply to the 1987 NMES expenditure data to facilitate longitudinal analysis.
These factors can be accessed via the CFACT data center. For more information
see the Data Center section of the MEPS Web site at
meps.ahrq.gov/data_stats/onsite_datacenter.jsp.
If examining trends in MEPS expenditures, please refer to Section C, sub-section
3.3 for more information.
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The general methodology used for editing and imputing
expenditure data is described below. The MPC did not include either the dental
events or other medical expenditures (such as glasses, contact lenses, and
hearing devices). Therefore, although the general procedures remain the same for
dental and other medical expenditures, editing and imputation methodologies were
applied only to household-reported data. Please see below for details on the
differences between these editing/imputation methodologies. Separate imputations
were performed for flat fee and simple events, as well.
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Logical edits were used to resolve internal
inconsistencies and other problems in the HC survey-reported data. The edits
were designed to preserve partial payment data from households and providers,
and to identify actual and potential sources of payment for each
household-reported event. In general, these edits accounted for 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 HMOs and private HMOs as payment sources. These edits produced a
complete vector of expenditures for some events, and provided the starting point
for imputing missing expenditures in the remaining events.
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The predictive mean matching imputation method was
used to impute missing expenditures. This procedure uses regression models
(based on events with completely reported expenditure data) to predict total
expenses for each event. Then, for each event with missing payment information,
a donor event with the closest predicted payment with the same pattern of
expected payment sources as the event with missing payment was used to impute
the missing payment value. The imputations for the flat fee events were carried
out separately from the simple events.
The weighted sequential hot-deck procedure was used to
impute the missing total charges. This procedure uses survey data from
respondents to replace missing data while taking into account the persons’
weighted distribution in the imputation process.
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Expenditures on visits to dentists were developed in a
sequence of logical edits and imputations. The household edits were used to
correct obvious errors in the reporting of expenditures, and to identify actual
and potential sources of payments. Some of the edits were global (i.e., applied
to all events); others were hierarchical and mutually exclusive. One of the more
important edits separated flat fee events from simple events. This edit was
necessary because groups of events covered by a flat fee (i.e., a flat fee
bundle) were edited and imputed separately from individual events each covered
by a single charge (i.e., simple events). Dental services were imputed as flat
fee events if the charges covered a package of health care services (e.g.,
orthodontia), and all of the services were part of the same event type (i.e., a
pure bundle). If a bundle contained more than one type of event, the services
were treated as simple events in the imputations (See Section 2.5.3 for more
detail on the definition and imputation of events in flat fee bundles.)
Logical edits were also used to sort each event into a
specific category for the imputations. Events with complete expenditures were
flagged as potential donors for the predictive mean matching imputations, while
events with missing expenditure data were assigned to various recipient
categories. Each event with missing expenditure data was assigned to a recipient
category based on the extent of its missing charge and expenditure data. For
example, an event with a known total charge but no expenditure information was
assigned to one category, while an event with a known total charge and partial
expenditure information was assigned to a different category. Similarly, events
without a known total charge and no or partial expenditure information were
assigned to various recipient categories.
The logical edits produced nine recipient categories
for events with missing data. Eight of the categories were for events with a
common pattern of missing data and a primary payer other than Medicaid. Medicaid
events were imputed separately because persons on Medicaid rarely know the
provider’s charge for services or the amount paid by the state Medicaid program.
As a result, the total charge for Medicaid-covered services was imputed and
discounted to reflect the amount that a state program would pay for the care.
Separate predictive mean matching imputations were
used to impute missing data in each of the eight recipient categories. The donor
pool included “free events” because, in some instances, providers are not paid
for their services. These events represent charity care, bad debt, provider
failure to bill, and third party payer restrictions on reimbursement in certain
circumstances. If free events were excluded from the donor pool, total
expenditures would be over-counted because the distribution of free event among
complete events (donors) is not represented among incomplete events
(recipients).
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IMPFLAG is a six-category variable that indicates if
the event contains complete Household Component (HC) or Medical Provider
Component (MPC) data, was fully or partially imputed, or was imputed in the
capitated imputation process (for OP and MV events only). The following list
identifies how the imputation flag is coded; the categories are mutually
exclusive.
IMPFLAG = 0 not eligible for imputation (includes zeroed out and flat fee leaf events)
IMPFLAG = 1 complete HC data
IMPFLAG = 2 complete MPC data (not applicable to DV events)
IMPFLAG = 3 fully imputed
IMPFLAG = 4 partially imputed
IMPFLAG = 5 complete MPC data through capitation imputation (not applicable to DV events)
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The approach used to count expenditures for flat fees
was to place the expenditure on the first visit of the flat fee group. The
remaining visits have zero payments. Thus, if the first visit in the flat fee
group occurred prior to 2013, all of the events that occurred in 2013 will have
zero payments. Conversely, if the first event in the flat fee group occurred at
the end of 2013, the total expenditure for the entire flat fee group will be on
that event, regardless of the number of events it covered after 2013. See
Section 2.5.3 for details on the flat fee variables.
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As noted above, there are some dental events reported
by respondents where the payments were zero. This could occur for several
reasons including (1) the visit was covered under a flat fee arrangement (flat
fee payments are included only on the first event covered by the arrangement),
(2) there was no charge for a follow-up visit, (3) the provider was never paid
directly for services provided by an individual, insurance plan, or other
source, (4) charges were included in another bill, or (5) event was paid through
government or privately funded research or clinical trial. If all of the medical
events for a person fell into one of these categories, then the total annual
expenditures for that person would be zero.
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In addition to total expenditures, variables are
provided which itemize expenditures according to major source of payment
categories. These categories are:
- Out-of-pocket by User or Family,
- Medicare,
- Medicaid,
- Private Insurance,
- Veterans Administration/CHAMPVA, excluding TRICARE,
- TRICARE,
- Other Federal Sources - includes Indian Health Service,
military treatment facilities, and other care by the federal
government,
- Other State and Local Source - includes community and
neighborhood clinics, state and local health departments, and
state programs other than Medicaid,
- Workers’ Compensation, and
- Other Unclassified Sources - includes sources such as
automobile, homeowner’s, and liability insurance, and other
miscellaneous or unknown sources.
Two additional source of payment
variables were created to classify payments for events with
apparent inconsistencies between insurance coverage and sources
of payment based on data collected in the survey. These
variables include:
- Other Private - 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, and
- Other Public - Medicare/Medicaid payments reported for
persons who were not reported to be enrolled in the
Medicare/Medicaid program at any time during the year.
Though relatively small in magnitude, data
users/analysts should exercise caution when interpreting the expenditures
associated with these two additional sources of payment. While these payments
stem from apparent inconsistent responses to 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
sampled 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 from persons who were not enrolled in Medicaid, but
were presumed eligible by a provider who ultimately received payments from the
public payer.
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DVSF13X - DVOT13X are the 12 sources of payment.
DVXP13X is the sum of the 12 sources of payment for the dental expenditures, and
DVTC13X is the total charge. The 12 sources of payment are: self/family
(DVSF13X), Medicare (DVMR13X), Medicaid (DVMD13X), private insurance (DVPV13X),
Veterans Administration/CHAMPVA (DVVA13X), TRICARE (DVTR13X), other Federal
sources (DVOF13X), State and Local (non-federal) government sources (DVSL13X),
Workers’ Compensation (DVWC13X), other private insurance (DVOR13X), other public
insurance (DVOU13X), and other insurance (DVOT13X).
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Expenditure variables on the 2013 dental file have
been rounded to the nearest penny.
Person-level expenditure information to be released on the MEPS 2013 Full Year
Consolidated File will be rounded to the nearest dollar. It should be noted that
using the MEPS event files to create person-level totals will yield slightly
different totals than those found on the full-year consolidated file. These
differences are due to rounding only. Moreover, in some instances, the number of
persons having expenditures on the event files for a particular source of
payment may differ from the number of persons with expenditures on the
person-level expenditure file for that source of payment. This difference is
also an artifact of rounding only.
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There is a single full year person-level weight
(PERWT13F) assigned to each record for each key, in-scope person who responded
to MEPS for the full period of time that he or she was in-scope during 2013. A
key person was either a member of a responding NHIS household at the time of
interview or joined a family associated with such a household after being
out-of-scope at the time of the NHIS (the latter circumstance includes newborns
as well as those returning from military service, an institution, or residence
in a foreign country). A person is in-scope whenever he or she is a member of
the civilian noninstitutionalized portion of the U.S. population.
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The person-level weight PERWT13F was developed in
several stages. Person-level weights for Panel 17 and Panel 18 were created
separately. The weighting process for each panel included an adjustment for
nonresponse over time and calibration to independent population figures. The
calibration was initially accomplished separately for each panel by raking the
corresponding sample weights for those in-scope at the end of the calendar year
to Current Population Survey (CPS) population estimates based on five variables.
The five variables used in the establishment of the initial person-level control
figures were: census region (Northeast, Midwest, South, West); MSA status (MSA,
non-MSA); race/ethnicity (Hispanic; Black, non-Hispanic; Asian, non-Hispanic;
and other); sex; and age. A 2013 composite weight was then formed by
multiplying each weight from Panel 17 by the factor .506 and each weight from
Panel 18 by the factor .494. The choice of factors reflected the relative sample
sizes of the two panels, helping to limit the variance of estimates obtained
from pooling the two samples. The composite weight was raked to the same set of
CPS-based control totals. Control totals were established using poverty status (five categories: below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty) the other five variables previously used in the weight calibration, and a variable associated with number of hospital stays for those under the age of 65.
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The person-level weight for MEPS Panel 17 was
developed using the 2012 full year weight for an individual as a “base” weight
for survey participants present in 2012. For key, in-scope members who joined an
RU some time in 2013 after being out-of-scope in 2012, the initially assigned
person-level weight was the corresponding 2012 family weight. The weighting
process included an adjustment for person-level nonresponse over Rounds 4 and 5
as well as raking to population control totals for December 2013 for key,
responding persons in-scope on December 31, 2013. These control figures were
derived by scaling back the population distribution obtained from the March 2014
CPS to reflect the December 31, 2013 estimated population total (estimated based
on Census projections for January 1, 2014). Variables used for person-level
raking included: census region (Northeast, Midwest, South, West); MSA status
(MSA, non-MSA); race/ethnicity (Hispanic; Black, non-Hispanic; Asian,
non-Hispanic; and other); sex; and age. (Poverty
status is not included in this version of the MEPS full year database because of
the time required to process the income data collected and then assign persons
to a poverty status category).The final weight for key, responding
persons who were not in-scope on December 31, 2013 but were in-scope earlier in
the year was the person weight after the nonresponse adjustment.
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The person-level weight for MEPS Panel 18 was
developed using the 2013 MEPS Round 1 person-level weight as a “base” weight.
For key, in-scope members who joined an RU after Round 1, the Round 1 family
weight served as a “base” weight. The weighting process included an adjustment
for nonresponse over the remaining data collection rounds in 2013 as well as
raking to the same population control figures for December 2013 used for the
MEPS Panel 17 weights for key, responding persons in-scope on December 31, 2013.
The same five variables employed for Panel 17 raking (census region, MSA status,
race/ethnicity, sex, and age) were used for Panel 18 raking. Again, the final
weight for key, responding persons who were not in-scope on December 31, 2013
but were in-scope earlier in the year was the person weight after the
nonresponse adjustment.
Note that the MEPS Round 1 weights for both panels
incorporated the following components: a weight reflecting the original
household probability of selection for the NHIS and an adjustment for NHIS
nonresponse; a factor representing the proportion of the 16 NHIS panel-quarter
combinations eligible for MEPS; the oversampling of certain subgroups for MEPS
among the NHIS household respondents eligible for MEPS; ratio-adjustment to
NHIS-based national population estimates at the household (occupied DU) level;
adjustment for nonresponse at the DU level for Round 1; and poststratification
to U.S. civilian noninstitutionalized population estimates at the family and
person level obtained from the corresponding March CPS databases.
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The final raking of those in-scope at the end of the
year has been described above. In addition, the composite weights of two groups
of persons who were out-of-scope on December 31, 2013 were poststratified.
Specifically, the weights of those who were in-scope some time during the year,
out-of-scope on December 31, and entered a nursing home during the year were
poststratified to a corresponding control total obtained from the 1996 MEPS
Nursing Home Component. Those who died while in-scope during 2013 were
poststratified to corresponding estimates derived using data obtained from the
Medicare Current Beneficiary Survey (MCBS) and Vital Statistics information
provided by the National Center for Health Statistics (NCHS). Separate decedent
control totals were developed for the “65 and older” and “under 65” civilian
noninstitutionalized populations.
In developing the final person-level weight for 2013 (PERWT13F), an additional raking dimension was included to adjust the proportion of persons under age 65 with at least one inpatient discharge based on independent sources of data reviewed by AHRQ. The table below shows ratios of weighted numbers of non-elderly persons that resulted from including this additional raking dimension to that of corresponding estimates without the additional dimension.
Ratio of Adjusted to Unadjusted Weights
| Number of Inpatient Discharges (IPDIS13) |
Non-elderly (AGE13X < 65) |
| 0 |
0.98938 |
| 1+ |
1.21587 |
Overall, the weighted population estimate for the
civilian noninstitutionalized population for December 31, 2013 is 312,098,312
(PERWT13F>0 and INSC1231=1). The sum of person-level weights across all persons
assigned a positive person-level weight is 315,721,982.
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The target population for MEPS in this file is the
2013 U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2011 (Panel 17)
and 2012 (Panel 18). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2011 (Panel 17) or after 2012 (Panel 18) are not covered by
MEPS. Neither are previously out-of-scope persons who join an existing household
but are unrelated to the current household residents. Persons not covered by a
given MEPS panel thus include some members of the following groups: immigrants;
persons leaving the military; U.S. citizens returning from residence in another
country; and persons leaving institutions. The set of uncovered persons
constitutes only a small segment of the MEPS target population.
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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 modification to the weight based on hospital stays potentially could affect some analyses of trends. 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.
With respect to methodological considerations, in 2013
MEPS introduced an effort to obtain more complete information about health care
utilization from MEPS respondents with full implementation in early 2014 at the
start of the final rounds of data collection for 2013. This effort likely
resulted in improved data quality and a reduction in underreporting in 2013, but
could have some modest impact on analyses involving trends in utilization across
years.
There are also statistical factors to consider in
interpreting trend analyses. 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 evaluate, smooth, or stabilize analyses of trends
using MEPS data such as comparing pooled time periods (e.g. 1996-97 versus
2012-13), 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 concluding that a change has taken place when one
has not.
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The data in this file can be used to develop national
2013 event-level estimates for the U.S. civilian noninstitutionalized population
on dental visits as well as expenditures, and sources of payment for these
visits. The weight assigned to each dental visit reported is the person-level
weight of the person who visited the dentist. If a person reported several
visits, each visit is assigned that individual’s person-level weight. Estimates
of total visits are the sum of the weight variable (PERWT13F) across relevant
event records while estimates of other variables must be weighted by PERWT13F to
be nationally representative. For example, the appropriate estimate for the mean
out-of-pocket payment per dental visit can be represented as follows (the
subscript ‘j’ identifies each event and represents a numbering of events from 1
through the total number of events in the file):
(Σ Wj Xj)/(Σ
Wj), where,
Wj = PERWT13Fj (full year person
weight for the person associated with event j), and
Xj = DVSF13Xj (amount
paid by self/family for event j)
Estimates and corresponding standard errors (SE) can
be derived using an appropriate computer software package for complex survey
analysis such as SAS, Stata, SUDAAN or SPSS (meps.ahrq.gov/survey_comp/standard_errors.jsp).
The tables below contain the correct event-level estimates for several key
variables on this file.
Selected Event-Level Estimates
Visits
| Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate Excluding
Zero Payment Events (SE) |
| Total number of dental
visits (in millions) |
PERWT13F |
307.6 (8.83) |
261.5 (7.03) |
| Proportion of dental
visits with expenditures > 0* |
DVXP13X |
0.850 (0.0051) |
N / A |
*Zero payment events can occur in MEPS for the
following reasons: (1) the visit was covered under a flat fee arrangement (flat
fee payments are included only on the first event covered by the arrangement),
(2) there was no charge for a follow-up visit, (3) the provider was never paid
directly for services provided by an individual, insurance plan, or other
source, (4) charges were included in another bill, or (5) event was paid through
government or privately funded research or clinical trial.
Expenditures
| Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate Excluding
Zero Payment Events (SE) |
| Mean total payments per visit |
DVXP13X |
$299 ($6.9) |
$351 ($8.5) |
| Mean out-of-pocket payment per visit |
DVSF13X |
$135 ($4.5) |
$158 ($5.6) |
| Mean proportion of total expenditures
paid by private insurance per visit |
DVPV13X/
DVXP13X |
N / A |
0.485 (0.0084) |
Expenditures: Dental Hygienist Visits (DENTHYG = 1)
| Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate Excluding
Zero Payment Events (SE) |
| Mean total payments
per visit where person saw hygienist |
DVXP13X |
$196 ($5.7) |
$204 ($5.9) |
| Mean out-of-pocket
payment per visit where person saw hygienist |
DVSF13X |
$68 ($3.4) |
$71 ($3.6) |
| Mean proportion of
total expenditures per visit paid by private
insurance where person saw hygienist |
DVPV13X/
DVXP13X |
N / A |
0.558 (0.0113) |
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To enhance analyses of dental care, analysts may link
information about dental visits by sample persons in this file to the annual
full year consolidated file (which has data for all MEPS sample persons), or
conversely, link person-level information from the full year consolidated file
to this event-level file (see Section 5 below for more details). Both this file
and the full year consolidated file may be used to derive estimates for persons
with dental care and annual estimates of total expenditures. However, if the
estimate relates to the entire population, this file cannot be used to calculate
the denominator, as only those persons with at least one dental visit are
represented on this data file. Therefore, the full year consolidated file must
be used for person-level analyses that include both persons with and without
dental care.
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It is essential that the analyst examine all variables
for the presence of negative values used to represent missing values. For
continuous or discrete variables, where means or totals may be estimated, it may
be necessary to set negative values to values appropriate to the analytic needs.
That is, the analyst should either impute a value or set the value to one that
will be interpreted as missing by the computing language used. For categorical
and dichotomous variables, the analyst may want to consider whether to recode or
impute a value for cases with negative values or whether to include or exclude
such cases in the numerator and/or denominator when calculating proportions.
Methodologies used for the editing/imputation of
expenditure variables (e.g., sources of payment, flat fee, and zero
expenditures) are described in Section 2.5.5.2.
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MEPS has a complex sample design. To obtain estimates
of variability (such as the standard error of sample estimates or corresponding
confidence intervals) for MEPS estimates, analysts need to take into account the
complex sample design of MEPS for both person-level and family-level analyses. Several methodologies have been developed for estimating
standard errors for surveys with a complex sample design, including the
Taylor-series linearization method, balanced repeated replication, and jackknife
replication. Various software packages provide analysts with the capability of
implementing these methodologies. Replicate weights have not been developed for
the MEPS data. Instead, the variables needed to calculate appropriate standard
errors based on the Taylor-series linearization method are included on this file
as well as all other MEPS public use files. Software packages that permit the
use of the Taylor-series linearization method include SUDAAN, Stata, SAS
(version 8.2 and higher), and SPSS (version 12.0 and higher). For complete
information on the capabilities of each package, analysts should refer to the
corresponding software user documentation.
Using the Taylor-series linearization method, variance
estimation strata and the variance estimation PSUs within these strata must be
specified. The variables VARSTR and VARPSU on this MEPS data file serve to
identify the sampling strata and primary sampling units required by the variance
estimation programs. Specifying a “with replacement” design in one of the
previously mentioned computer software packages will provide estimated standard
errors appropriate for assessing the variability of MEPS survey estimates. It
should be noted that the number of degrees of freedom associated with estimates
of variability indicated by such a package may not appropriately reflect the
number available. For variables of interest distributed throughout the country
(and thus the MEPS sample PSUs), one can generally expect to have at least 100
degrees of freedom associated with the estimated standard errors for national
estimates based on this MEPS database.
Prior to 2002, MEPS variance strata and PSUs were
developed independently from year to year, and the last two characters of the
strata and PSU variable names denoted the year. However, beginning with the 2002
Point-in-Time PUF, the variance strata and PSUs were developed to be compatible
with all future PUFs until the NHIS design changed. Thus, when pooling data
across years 2002 through the Panel 12 component of the 2007 files, the variance
strata and PSU variables provided can be used without modification for variance
estimation purposes for estimates covering multiple years of data. There were
203 variance estimation strata, each stratum with either two or three variance
estimation PSUs.
From Panel 12 of the 2007 files, a new set of variance
strata and PSUs were developed because of the introduction of a new NHIS design.
There are 165 variance strata with either two or three variance estimation PSUs
per stratum, starting from Panel 12. Therefore, there are a total of 368
(203+165) variance strata in the 2007 Full Year file as it consists of two
panels that were selected under two independent NHIS sample designs. Since both
MEPS panels in the Full Year 2008 file and beyond are based on the new NHIS
design, there are only 165 variance strata. These variance strata (VARSTR
values) have been numbered from 1001 to 1165 so that they can be readily
distinguished from those developed under the former NHIS sample design in the
event that data are pooled for several years.
If analyses call for pooling MEPS data across several
years, in order to ensure that variance strata are identified appropriately for
variance estimation purposes, one can proceed as follows:
- When pooling any year from 2002 or later, one can use the
variance strata numbering as is.
- When pooling any year from 1996 to 2001 with any year from
2002 or later, use the H36 file.
- A new H36 file will be constructed in the future to allow
pooling of 2007 and later years with 1996 to 2006.
Return To Table Of Contents
Data from this file can be used alone or in
conjunction with other files for different analytic purposes. This section
summarizes various scenarios for merging/linking MEPS event files. The set of
households selected for MEPS is a subsample of those participating in the
National Health Interview Survey (NHIS), thus, each MEPS panel can also be
linked back to the previous year’s NHIS public use data files. For information
on obtaining MEPS/NHIS link files please see
meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
Return To Table Of Contents
Merging characteristics of interest from other MEPS
files (e.g., 2013 Full Year Consolidated File or 2013 Prescribed Medicines File)
expands the scope of potential estimates. For example, to estimate the total
number of dental events of persons with specific demographic characteristics
(such as age, race, and sex), population characteristics from a person-level
file need to be merged onto the Dental file. This procedure is shown below. The
MEPS 2013 Appendix File, HC-160I, provides additional details of how to merge
other MEPS data files.
- Create data set PERSX by sorting the 2013 Full Year
Consolidated File, by the person identifier, DUPERSID. Keep only
variables to be merged onto the Dental file and DUPERSID.
- Create data set DENT by sorting the dental event file by
person identifier, DUPERSID.
- Create final data set NEWDENT by merging these two files by
DUPERSID, keeping only records on the dental event file.
The following is an example of SAS code which
completes these steps:
PROC SORT DATA=HCXXX (KEEP=DUPERSID AGE31X AGE42X
AGE53X SEX RACEV1X EDRECODE EDUYRDG) OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA=DENT;
BY DUPERSID;
RUN;
DATA NEWDENT;
MERGE DENT (IN=A) PERSX (IN=B);
BY DUPERSID;
IF A;
RUN;
The MEPS 2013 Appendix File, HC-160I, provides
examples of how to merge other MEPS data files.
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The RXLK file provides a link from the MEPS event
files to the 2013 Prescribed Medicines Event File. When using RXLK, data
users/analysts should keep in mind that one dental visit can link to more than
one prescribed medicine record. Conversely, a prescribed medicine event may link
to more than one dental visit or different types of events. When this occurs, it
is up to the data user/analyst to determine how the prescribed medicine
expenditures should be allocated among those medical events. For detailed
linking examples, including SAS code, data users/analysts should refer to the
MEPS 2013 Appendix File, HC-160I.
Return To Table Of Contents
Conditions data are not collected for Dental events;
therefore, this file cannot be linked to the Conditions File.
Return To Table Of Contents
Cohen, S.B. (1996). The Redesign of the Medical
Expenditure Panel Survey: A Component of the DHHS Survey Integration Plan.
Proceedings of the COPAFS Seminar on Statistical Methodology in the Public
Service.
Ezzati-Rice, T.M., Rohde, F., Greenblatt, J., Sample
Design of the Medical Expenditure Panel Survey Household Component, 1998–2007.
Methodology Report No. 22. March 2008. Agency for Healthcare Research and
Quality, Rockville, MD.
Monheit, A.C., Wilson, R., and Arnett, III, R.H.
(Editors) (1999). Informing American Health Care Policy. Jossey-Bass Inc, San
Francisco.
Shah, B.V., Barnwell, B.G., Bieler, G.S., Boyle, K.E.,
Folsom, R.E., Lavange, L., Wheeless, S.C., and Williams, R. (1996). Technical
Manual: Statistical Methods and Algorithms Used in SUDAAN Release 7.0,
Research Triangle Park, NC: Research Triangle Institute.
Return To Table Of Contents
VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-160B: 2013 DENTAL VISITS
Survey Administration Variables
| Variable |
Description |
Source |
| DUID |
Dwelling unit ID |
Assigned in sampling |
| PID |
Person number |
Assigned in sampling |
| DUPERSID |
Person ID (DUID + PID) |
Assigned in sampling |
| EVNTIDX |
Event ID |
Assigned in sampling |
| EVENTRN |
Event round number |
CAPI derived |
| FFEEIDX |
Flat fee ID |
CAPI derived |
| PANEL |
Panel Number |
Constructed |
Return To Table Of Contents
Dental Events Variables
| Variable |
Description |
Source |
| DVDATEYR |
Event date – year |
CAPI derived |
| DVDATEMM |
Event date – month |
CAPI derived |
| GENDENT |
General dentist seen |
DN03 |
| DENTHYG |
Dental hygienist seen |
DN03 |
| DENTTECH |
Dental technician seen |
DN03 |
| DENTSURG |
Dental surgeon seen |
DN03 |
| ORTHODNT |
Orthodontist seen |
DN03 |
| ENDODENT |
Endodontist seen |
DN03 |
| PERIODNT |
Periodontist seen |
DN03 |
| DENTYPE |
Other dental specialist seen |
DN03 |
| EXAMINE |
General exam or consultation |
DN04 |
| CLENTETX |
Edited CLENTETH |
DN04 (Edited) |
| CLENTETH |
Cleaning, prophylaxis, or polishing |
DN04 |
| JUSTXRYX |
Edited JUSTXRAY |
DN04 (Edited) |
| JUSTXRAY |
X-rays, radiographs or bitewings |
DN04 |
| FLUORIDE |
Fluoride treatment |
DN04 |
| SEALANTX |
Edited SEALANT |
DN04 (Edited) |
| SEALANT |
Sealant application |
DN04 |
| FILLINGX |
Edited FILLING |
DN04 (Edited) |
| FILLING |
Fillings |
DN04 |
| INLAY |
Inlays |
DN04 |
| CROWNSX |
Edited CROWNS |
DN04 (Edited) |
| CROWNS |
Crowns or caps |
DN04 |
| ROOTCANX |
Edited ROOTCANL |
DN04 (Edited) |
| ROOTCANL |
Root canal |
DN04 |
| GUMSURGX |
Edited GUMSURG |
DN04 (Edited) |
| GUMSURG |
Periodontal scaling, root planing or gum |
DN04 |
| RECLVISX |
Edited RECLVIS |
DN04 (Edited) |
| RECLVIS |
Periodontal recall visit |
DN04 |
| EXTRACT |
Extraction, tooth pulled |
DN04 |
| IMPLANTX |
Edited IMPLANT |
DN04 (Edited) |
| IMPLANT |
Implants |
DN04 |
| ABSCESS |
Abscess or infection treatment |
DN04 |
| ORALSURX |
Edited ORALSURG |
DN04 (Edited) |
| ORALSURG |
Oral surgery |
DN04 |
| BRIDGESX |
Edited BRIDGES |
DN04 (Edited) |
| BRIDGES |
Bridges |
DN04 |
| DENTUREX |
Edited DENTURES |
DN04 (Edited) |
| DENTURES |
Dentures or partial dentures |
DN04 |
| REPAIRX |
Edited REPAIR |
DN04 (Edited) |
| REPAIR |
Repair of bridges/dentures or relining |
DN04 |
| ORTHDONX |
Edited ORTHDONT |
DN04 (Edited) |
| ORTHDONT |
Orthodontia, braces or retainers |
DN04 |
| WHITENX |
Edited WHITEN |
DN04 (Edited) |
| WHITEN |
Bonding, whitening or bleaching |
DN04 |
| TMDTMJ |
Treatment for TMD or TMJ |
DN04 |
| DENTPROX |
Edited DENTPROC |
DN04OV (Edited) |
| DENTPROC |
Other dental procedures |
DN04OV |
| DENTOTHX |
Edited DENTOTHR |
DN04OV (Edited) |
| DENTOTHR |
Other specified dental procedures |
DN04OV |
| DENTMED |
Received medicine including free sample |
DN05 |
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Flat Fee Variables
| Variable |
Description |
Source |
| FFDVTYPE |
Flat Fee Bundle |
Constructed |
| FFBEF13 |
Total # of visits in FF before 2013 |
FF05 |
| FFTOT14 |
Total # of visits in FF after 2013 |
FF10 |
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Imputed Expenditure Variables
| Variable |
Description |
Source |
| DVSF13X |
Amount paid, self/family (Imputed) |
CP Section (Edited) |
| DVMR13X |
Amount paid, Medicare (Imputed) |
CP Section (Edited) |
| DVMD13X |
Amount paid, Medicaid (Imputed) |
CP Section (Edited) |
| DVPV13X |
Amount paid, private insurance (Imputed) |
CP Section (Edited) |
| DVVA13X |
Amount paid, Veterans/CHAMPVA (Imputed) |
CP Section (Edited) |
| DVTR13X |
Amount paid, TRICARE (Imputed) |
CP Section (Edited) |
| DVOF13X |
Amount paid, other federal (Imputed) |
CP Section (Edited) |
| DVSL13X |
Amount paid, state & local government (Imputed) |
CP Section (Edited) |
| DVWC13X |
Amount paid, workers’ comp (Imputed) |
CP Section (Edited) |
| DVOR13X |
Amount paid, other private (Imputed) |
Constructed |
| DVOU13X |
Amount paid, other public (Imputed) |
Constructed |
| DVOT13X |
Amount paid, other insurance (Imputed) |
CP Section (Edited) |
| DVXP13X |
Sum of DVSF13x – DVOT13x (Imputed) |
Constructed |
| DVTC13X |
Household reported total charge (Imputed) |
CP Section (Edited) |
| IMPFLAG |
Imputation status |
Constructed |
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Weights
| Variable |
Description |
Source |
| PERWT13F |
Expenditure File
Person weight, 2013 |
Constructed |
| VARSTR |
Variance estimation
stratum, 2013 |
Constructed |
| VARPSU |
Variance estimation
PSU, 2013 |
Constructed |
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|
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