MEPS HC-110B: 2007 Dental Visits
August 2009
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 – DVDATEDD)
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, FFBEF07, FFTOT08)
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 (FFBEF07, FFTOT08)
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 General Hot-Deck Imputation
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 (DVSF07X-DVTC07X)
2.5.5.8 Rounding
3.0 Sample Weight (PERWT07F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 11 Weight
3.2.2 MEPS Panel 12 Weight
3.2.3 The Final Weight for 2007
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
A. Data Use Agreement
Individual identifiers have been removed from the
micro-data contained in these files. Nevertheless, under sections 308 (d) and
903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1),
data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or
the National Center for Health Statistics (NCHS) may not be used for any purpose
other than for the purpose for which they were supplied; any effort to determine
the identity of any reported cases is prohibited by law.
Therefore in accordance with the above referenced
Federal Statute, it is understood that:
No one is to use the data in this data set in any way except for
statistical reporting and analysis; and If the identity of any person or establishment should be discovered
inadvertently, then (a) no use will be made of this knowledge, (b) the
Director Office of Management AHRQ will be advised of this incident, (c) the
information that would identify any individual or establishment will be
safeguarded or destroyed, as requested by AHRQ, and (d) no one else will be
informed of the discovered identity; and - No one will attempt to link this data set with individually identifiable
records from any data sets other than the Medical Expenditure Panel Survey
or the National Health Interview Survey.
By using these data you signify your agreement to
comply with the above stated statutorily based requirements with the knowledge
that deliberately making a false statement in any matter within the jurisdiction
of any department or agency of the Federal Government violates Title 18 part 1
Chapter 47 Section 1001 and is punishable by a fine of up to $10,000 or up to 5
years in prison.
The Agency for Healthcare Research and Quality
requests that users cite AHRQ and the Medical Expenditure Panel Survey as the
data source in any publications or research based upon these data.
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B. Background
1.0 Household Component
The Medical Expenditure Panel Survey (MEPS) provides
nationally representative estimates of health care use, expenditures, sources of
payment, and health insurance coverage for the U.S. civilian
non-institutionalized population. The MEPS Household Component (HC) also
provides estimates of respondents’ health status, demographic and socio-economic
characteristics, employment, access to care, and satisfaction with health care.
Estimates can be produced for individuals, families, and selected population
subgroups. The panel design of the survey, which includes 5 Rounds of interviews
covering 2 full calendar years, provides data for examining person level changes
in selected variables such as expenditures, health insurance coverage, and
health status. Using computer assisted personal interviewing (CAPI) technology,
information about each household member is collected, and the survey builds on
this information from interview to interview. All data for a sampled household
are reported by a single household respondent.
The MEPS-HC was initiated in 1996. Each year a new
panel of sample households is selected. Because the data collected are
comparable to those from earlier medical expenditure surveys conducted in 1977
and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample
size is about 15,000 households. Data can be analyzed at either the person or
event level. Data must be weighted to produce national estimates.
The set of households selected for each panel of the
MEPS HC is a subsample of households participating in the previous year’s
National Health Interview Survey (NHIS) conducted by the National Center for
Health Statistics. The NHIS sampling frame provides a nationally representative
sample of the U.S. civilian non-institutionalized population and reflects an
oversample of blacks and Hispanics. In 2006, the NHIS implemented a new sample
design, which included Asian persons in addition to households with black and
Hispanic persons in the oversampling of minority populations. MEPS further
oversamples additional policy relevant sub-groups such as low income households.
The linkage of the MEPS to the previous year’s NHIS provides additional data for
longitudinal analytic purposes.
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2.0 Medical Provider Component
Upon completion of the household CAPI interview and
obtaining permission from the household survey respondents, a sample of medical
providers are contacted by telephone to obtain information that household
respondents can not accurately provide. This part of the MEPS is called the
Medical Provider Component (MPC) and information is collected on dates of visit,
diagnosis and procedure codes, charges and payments. The Pharmacy Component
(PC), a subcomponent of the MPC, does not collect charges or diagnosis and
procedure codes but does collect drug detail information, including National
Drug Code (NDC) and medicine name, as well as date filled and sources and
amounts of payment. The MPC is not designed to yield national estimates. It is
primarily used as an imputation source to supplement/replace household reported
expenditure information.
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3.0 Survey Management and Data Collection
MEPS HC and MPC data are collected under the authority
of the Public Health Service Act. Data are collected under contract with Westat,
Inc. Data sets and summary statistics are edited and published in accordance
with the confidentiality provisions of the Public Health Service Act and the
Privacy Act. The National Center for Health statistics (NCHS) provides
consultation and technical assistance.
As soon as data collection and editing are completed,
the MEPS survey data are released to the public in staged releases of summary
reports, micro data files, and tables via the MEPS Web site:
www.meps.ahrq.gov.
Selected data can be analyzed through MEPSnet, an on-line interactive tool
designed to give data users the capability to statistically analyze MEPS data in
a menu-driven environment.
Additional information on MEPS is available from the
MEPS project manager or the MEPS public use data manager at the Center for
Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality,
540 Gaither Road, Rockville, MD 20850 (301-427-1406).
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C. Technical and Programming Information
1.0 General Information
This documentation describes one in a series of public
use event files from the 2007 Medical Expenditure Panel Survey (MEPS) Household
Component (HC). Released as an ASCII data file (with related SAS and SPSS
programming statements) and a SAS transport file, the 2007 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 2007. The file contains 74
variables and has a logical record length of 305 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 2007 portion of Round 3 and
Rounds 4 and 5 for Panel 11, as well as Rounds 1, 2 and the 2007 portion of
Round 3 for Panel 12 (i.e., the rounds for the MEPS panels covering calendar
year 2007).
301 Moved Permanently
301 Moved Permanently
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
2007 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 use is provided on the MEPS 2007 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 S.
Cohen, 1997; J. Cohen, 1997; 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:
www.meps.ahrq.gov.
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2.0 Data File Information
The 2007 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 2007 Dental public use data set contains 26,112
dental event records; of these records, 25,620 are associated with persons
having a positive person-level weight (PERWT07F). This file includes dental
event records for all household survey respondents 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 2007. Dental visits known to have occurred before January 1, 2007 and after
December 31, 2007 are not included on this file. Some household respondents may
have multiple dental events and thus will be represented in multiple records on
this file. Other household respondents may have reported no dental events and
thus will have no records on this file. These data were collected during the
2007 portion of Round 3, and Rounds 4 and 5 for Panel 11, as well as Rounds 1,
2, and the 2007 portion of Round 3 for Panel 12 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 2007 eligibility (i.e., persons with a positive 2007
full-year person-level weight (PERWT07F > 0)), or - Be an eligible member of a family all of whose key in-scope members have
a positive person-level weight (PERWT07F > 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 (FAMWT07F > 0). Note that FAMIDYR
and FAMWT07F are variables on the 2007 Population Characteristics file.
Persons with no dental events for 2007 are not
included on this event-level DV file but are represented on the person-level
2007 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 2007 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 2007 Prescribed Medicine File. Please see section 5.0
or the 2007 Appendix for details on how to merge MEPS data files.
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2.1 Codebook Structure
For each variable on the Dental event file, both
weighted and unweighted frequencies are provided in the accompanying codebook.
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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2.2 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 |
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:
www.meps.ahrq.gov/survey_comp/survey_questionnaires.jsp).
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2.3 Codebook Format
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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2.4 Variable Source and Naming Conventions
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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2.4.1 Variable - Source Crosswalk
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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2.4.2 Expenditure and Source of Payment Variables
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 |
OB - office-based visit |
| ER - emergency room visit |
OP - outpatient visit |
| HH - home health visit |
DV - dental visit |
| OM - other medical equipment |
RX - prescribed medicine |
In the case of the source of payment variables, the third and fourth characters indicate:
| SF - self or family |
OF - other Federal Government |
| MR - Medicare |
SL - State/local government |
| MD - Medicaid |
WC - Workers’ Compensation |
| PV - private insurance |
OT - other insurance |
| VA - Veterans Administration |
OR - other private |
| TR - TRICARE/CHAMPVA |
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 (07).
The seventh character, "X", indicates the variable is edited/imputed.
For example, DVSF07X is the edited/imputed amount paid
by self or family for 2007 dental expenditures.
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2.5 File Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID, PID, DUPERSID)
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 2007 Full Year Population Characteristics File.
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2.5.1.2 Record Identifiers (EVNTIDX, FFEEIDX)
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 2007
Prescribed Medicines file). For details on linking see Section 5.0 or the MEPS
2007 Appendix File, HC-110I.
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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2.5.1.3 Round Indicator (EVENTRN)
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 11. Likewise, Rounds 1, 2, and 3 (partial) are
associated with data collected from Panel 12.
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2.5.1.4 Panel Indicator (PANEL)
PANEL is a constructed variable used to specify the
panel number for the person. PANEL will indicate either Panel 11 or Panel 12 for
each person on the file. Panel 11 is the panel that started in 2006, and Panel
12 is the panel that started in 2007.
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2.5.2 Dental Event Variables
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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2.5.2.1 Date of Visit (DVDATEYR – DVDATEDD)
There are three variables that indicate the day, month,
and year a dental event occurred (DVDATEDD, DVDATEMM, and DVDATEYR, respectively).
These variables have not been edited or imputed.
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2.5.2.2 Type of Provider Seen (GENDENT - DENTYPE)
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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2.5.2.3 Treatment, Procedures, and Services (EXAMINE - DENTMED)
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
DV 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 respondent received a prescription medication
during the dental visit.
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2.5.3 Flat Fee Variables (FFEEIDX, FFDVTYPE, FFBEF07, FFTOT08)
2.5.3.1 Definition of Flat Fee Payments
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 2007. By definition, a flat fee group can span
multiple years. Furthermore, a single person can have multiple flat fee groups.
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2.5.3.2 Flat Fee Variable Descriptions
2.5.3.2.1 Flat Fee ID (FFEEIDX)
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 2007 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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2.5.3.2.2 Flat Fee Type (FFDVTYPE)
FFDVTYPE indicates whether the 2007 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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2.5.3.2.3 Counts of Flat Fee Events that Cross Years (FFBEF07, FFTOT08)
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 2007 dental visit is part of a group of events, and some of
the events occurred before or after 2007, counts of the known events are
provided on the dental record. Variables that indicate events occurring before
or after 2007 are the following:
FFBEF07 – indicates total number of pre-2007
events in the same flat fee group as the 2007 dental event. This count
would not include 2007 dental events.
FFTOT08 – indicates the number of 2008 medical
events expected to be in the same flat fee group as the 2007 dental
event record.
If there are no 2006 events on the file, FFBEF07 will
be omitted. Likewise, if there are no 2008 events on the file, FFTOT08 will be
omitted. If there are no flat fee data related to the records in this file,
FFEEIDX and FFDVTYPE will be omitted as well. Please note that the crosswalk in
this document lists all possible flat fee variables.
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2.5.3.3 Caveats of Flat Fee Groups
Data users/analysts should note that flat fee payments
are common on the dental file. There are 3,730 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 2007, but the remaining visits
that were part of this flat fee group occurred in 2008. In this case, the 2007
flat fee group represented on this file would consist of one event (the stem).
The 2008 "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 2006 but subsequent visits occurred
during 2007. In this case, the initial visit would not be represented on the
file. This 2007 flat fee group would then only consist of one or more leaf
records and no stem.
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2.5.4 Condition, Procedure, and Clinical Classification Codes
Conditions data are not collected
for Dental events; therefore, this file cannot be linked to the Conditions File.
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2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
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 this 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 assessed via the CFACT data center. For more information see the
Data Center section of the MEPS Web site at
www.meps.ahrq.gov/data_stats/onsite_datacenter.jsp.
If examining trends in MEPS expenditures or performing longitudinal analysis on
MEPS expenditures, please refer to section C, sub-section 3.3 for more
information.
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2.5.5.2 Data Editing and Imputation Methodologies of Expenditure Variables
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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2.5.5.2.1 General Data Editing Methodology
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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2.5.5.2.2 General Hot-Deck Imputation
A weighted sequential hot-deck procedure was used to
impute for missing expenditures as well as total charge. This procedure uses
survey data from respondents to replace missing data, while taking into account
the respondents’ weighted distribution in the imputation process. Classification
variables vary by event type in the hot-deck imputations, but total charge and
insurance coverage are key variables in all of the imputations. Separate
imputations were performed for nine categories of medical provider care:
inpatient hospital stays, outpatient hospital department visits, emergency room
visits, visits to physicians, visits to non-physician providers, dental
services, home health care by certified providers, home health care by paid
independents, and other medical expenses. Within each event type file, separate
imputations were performed for flat fee and simple events. After the imputations
were finished, visits to physician and non-physician providers were combined
into a single medical provider file. The two categories of home care also were
combined into a single home health file.
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2.5.5.2.3 Dental Data Editing and Imputation
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 hot-deck 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 hot-deck imputations were used to impute
missing data in each of the other 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).
Return To Table Of Contents
2.5.5.3 Imputation Flag Variable (IMPFLAG)
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)
Return To Table Of Contents
2.5.5.4 Flat Fee Expenditures
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 2007, all of the events that occurred in 2007 will have
zero payments. Conversely, if the first event in the flat fee group occurred at
the end of 2007, the total expenditure for the entire flat fee group will be on
that event, regardless of the number of events it covered after 2007. See
Section 2.5.3 for details on the flat fee variables.
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2.5.5.5 Zero Expenditures
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.
Return To Table Of Contents
2.5.5.6 Sources of Payment
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, excluding TRICARE/CHAMPVA,
- TRICARE/CHAMPVA,
- 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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2.5.5.7 Dental Expenditure Variables (DVSF07X - DVTC07X)
DVSF07X - DVOT07X are the 12 sources of payment.
DVTC07X is the total charge, and DVXP07X is the sum of the 12 sources of payment
for the Dental expenditures. The 12 sources of payment are: self/family
(DVSF07X), Medicare (DVMR07X), Medicaid (DVMD07X), private insurance (DVPV07X),
Veterans Administration (DVVA07X), TRICARE/CHAMPVA (DVTR07X), other Federal
sources (DVOF07X), State and Local (non-federal) government sources (DVSL07X),
Workers’ Compensation (DVWC07X), other private insurance (DVOR07X), other public
insurance (DVOU07X), and other insurance (DVOT07X).
Return To Table Of Contents
2.5.5.8 Rounding
Expenditure variables on the 2007 dental file have
been rounded to the nearest penny. Person-level expenditure information to be
released on the MEPS 2007 Person-Level Expenditure 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
person-level expenditure 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. Please see the
MEPS 2007 Appendix File, HC-110I, for details on such rounding differences.
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3.0 Sample Weight (PERWT07F)
3.1 Overview
There is a single full year person-level weight
(PERWT07F) 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 2007. A
key person either was a member of an NHIS household at the time of the NHIS
interview, or became a member of 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 persons returning from military service, an institution, or
living outside the United States). A person is in-scope whenever he or she is a
member of the civilian noninstitutionalized portion of the U.S. population.
There has been an important change in the MEPS sample
design that is worth noting. The MEPS sample of households for Round 1 of a
given MEPS panel is a subsample of the responding households to the previous
year’s National Health Interview Survey (NHIS). A new NHIS sample design was
implemented in 2006 with a new sample of PSUs and segments, independent of the
sample design used from 1995-2005. Thus, MEPS Panel 12 households fielded
initially in 2007, selected from the 2006 NHIS household respondents, are from a
sample design independent of those sampled for MEPS Panel 11 from among 2005
NHIS household respondents. As a result, with two national samples of PSUs and
segments fielded for MEPS and with a somewhat reduced sample size for Panel 12,
the amount of clustering is reduced with the expectation of some increase in
precision for 2007 MEPS estimates. There will also be more degrees of freedom
due to more variance strata available for variance estimation purposes. The
trade-off for these expected increases in precision and degrees of freedom is
that it is more expensive to field a sample that is less concentrated. In 2008
both MEPS panels will have been sampled from the new NHIS sample design, with
corresponding reductions in survey costs, precision, and degrees of freedom.
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3.2 Details on Person Weight Construction
The person-level weight PERWT07F was developed in
several stages. Person-level weights for Panels 11 and 12 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 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,
non-Hispanic with black as sole reported race, non-Hispanic with Asian as sole
reported race, and other); sex; and age. A 2007
composite weight was then formed by multiplying each weight from Panel 11 by the
factor .56 and each weight from Panel 12 by the factor .44. 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 again raked to the same set of CPS-based control totals. When poverty
status information derived from income variables became available, a final
raking was undertaken on the previously established weight variable. 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) as well as the
original five variables used in the previous calibrations.
Return To Table Of Contents
3.2.1 MEPS Panel 11 Weight
The person-level weight for MEPS Panel 11 was
developed using the 2006 full year weight for an individual as a "base" weight
for survey participants present in 2006. For key, in-scope respondents who
joined an RU some time in 2007 after being out-of-scope in 2006, the 2006 family
weight associated with the family the person joined served as a "base" weight.
The weighting process included an adjustment for nonresponse over Rounds 4 and 5
as well as raking to population control figures for December 2007. These control
figures were derived by scaling back the population totals obtained from the
March 2008 CPS to correspond to a national estimate for the civilian
noninstitutionalized population provided by the Census Bureau for December 2007.
Variables used in the establishment of person-level control figures included:
census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA);
race/ethnicity (Hispanic, black but non-Hispanic, Asian but non-Hispanic,
and other); sex; and age. Overall, the weighted population estimate for
the civilian noninstitutionalized population on December 31, 2007 is
297,823,930. Key, responding persons not in-scope on December 31, 2007 but
in-scope earlier in the year retained, as their final Panel 11 weight, the
weight after the nonresponse adjustment.
Return To Table Of Contents
3.2.2 MEPS Panel 12 Weight
The person-level weight for MEPS Panel 12 was
developed using the MEPS Round 1 person-level weight as a "base" weight. For
key, in-scope respondents 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 Round 2 and the 2007 portion of Round 3 as well as raking
to the same population control figures for December 2007 used for the MEPS Panel
11 weights. The same five variables employed for Panel 11 raking (census region,
MSA status, race/ethnicity, sex, and age) were used for Panel 12 raking.
Similarly, for Panel 12, key, responding persons not in-scope on December 31,
2007 but in-scope earlier in the year retained, as their final Panel 12 weight,
the weight after the nonresponse adjustment.
Note that the MEPS Round 1 weights incorporated the
following components: the original household probability of selection for the
NHIS; ratio-adjustment to NHIS-based national population estimates at the
household (occupied dwelling unit) level; adjustment for nonresponse at the
dwelling unit level for Round 1; and poststratification to figures at the family
and person level obtained from the March CPS data base of the corresponding year
(i.e., 2006 for Panel 11 and 2007 for Panel 12).
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3.2.3 The Final Weight for 2007
Variables used in the establishment of person-level
control figures included: poverty status (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); census region (Northeast, Midwest,
South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, non-Hispanic
with black as sole reported race, non-Hispanic with Asian as sole reported race,
and other); sex; and age. Overall, the weighted population estimate for the
civilian noninstitutionalized population for December 31, 2007 is 297,823,930
(PERWT07F>0 and INSC1231=1). In addition, the weights of two groups of persons
who were out-of-scope on December 31, 2007 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 2007 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 control
totals were developed for the "65 and older" and "under 65" civilian
noninstitutionalized populations. The sum of the person-level weights across all
persons assigned a positive person level weight is 301,309,149.
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3.2.4 Coverage
The target population for MEPS in this file is the
2007 U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2005 (Panel 11)
and 2006 (Panel 12). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2005 (Panel 11) or after 2006 (Panel 12) 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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3.3 Using MEPS Data for Trend Analysis
MEPS began in 1996, and the utility of the survey for
analyzing health care trends expands with each additional year of data. However,
it is important to consider a variety of factors when examining trends over time
using MEPS. Statistical significance tests should be conducted to assess the
likelihood that observed trends may be attributable to sampling variation. The
length of time being analyzed should also be considered. In particular, large
shifts in survey estimates over short periods of time (e.g. from one year to the
next) that are statistically significant should be interpreted with caution,
unless they are attributable to known factors such as changes in public policy,
economic conditions, or MEPS survey methodology. Looking at changes over longer
periods of time can provide a more complete picture of underlying trends.
Analysts may wish to consider using techniques to smooth or stabilize analyses
of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97
versus 2004-05), working with moving averages, or using modeling techniques with
several consecutive years of MEPS data to test the fit of specified patterns
over time. Finally, researchers should be aware of the impact of multiple
comparisons on Type I error. Without making appropriate allowance for multiple
comparisons, undertaking numerous statistical significance tests of trends
increases the likelihood of concluding that a change has taken place when one
has not.
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4.0 Strategies for Estimation
4.1 Developing Event-Level Estimates
The data in this file can be used to develop national
2007 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 (PERWT07F) across relevant
event records while estimates of other variables must be weighted by PERWT07F 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):
 , where,
 = PERWT07Fi (full year person weight for the
person associated with event j), and
 = DVSF07Xj (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 (www.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) |
PERWT07F |
304.6 (7.73) |
258.5 (6.48) |
Proportion of dental visits with
expenditures > 0* |
DVXP07X |
0.849 (0.0060) |
-------- |
*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 |
DVXP07X |
$269 ($4.9) |
$317 ($6.1) |
| Mean out-of-pocket payment per visit |
DVSF07X |
$132 ($3.4) |
$156 ($4.3) |
Mean proportion of total expenditures
paid by private insurance per visit |
DVPV07X/
DVXP07X |
------- |
0.477 (0.0068) |
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 |
DVXp07X |
$172 ($4.9) |
$178 ($5.2) |
Mean out-of-pocket payment per visit
where person saw hygienist |
DVSf07X |
$66 ($3.2) |
$69 ($3.4) |
Mean proportion of total expenditures
per visit paid by private insurance
where person saw hygienist |
DVPV07X/
DVXP07X |
------- |
0.568 (0.0102) |
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4.2 Person-Based Estimates for Dental Care
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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4.3 Variables with Missing Values
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.
Return To Table Of Contents
4.4 Variance Estimation (VARPSU, VARSTR)
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 variance
strata variable is named VARSTR, while the variance PSU variable is named
VARPSU. Specifying a "with replacement" design in a computer software package,
such as SUDAAN, provides 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 actual number available. For MEPS
sample estimates for characteristics generally distributed throughout the
country (and thus the sample PSUs), one can expect at least 100 degrees of
freedom for the 2007 full year data associated with the corresponding estimates
of variance and usually substantially more.
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 MEPS data associated with the NHIS sample design used through 2006. Such
data can be pooled and the variance strata and PSU variables provided can be
used without modification for variance estimation purposes for estimates
covering multiple years of data.
As a result of the change in the NHIS sample design in 2006, a new set of variance
strata and PSUs have been established for variance estimation purposes for use
with MEPS Panel 12 and subsequent MEPS panels. There were 203 variance
estimation strata associated with MEPS Panel 11 and 165 variance strata
associated with MEPS Panel 12, or 368 variance strata in all, providing a
substantial number of degrees of freedom for subgroups as well as the nation as
a whole. Each variance stratum contains either two or three variance estimation
PSUs.
Return To Table Of Contents
5.0 Merging/Linking MEPS Data Files
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
www.meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
Return To Table Of Contents
5.1 Linking to the Person-Level File
Merging characteristics of interest from other MEPS
files (e.g., 2007 Full Year Consolidated File or 2007 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 needs to be merged onto the dental file. This procedure is
shown below. The MEPS 2007 Appendix File, HC-110I, provides additional details
of how to merge other MEPS data files.
Create data set PERSX by sorting the 2007 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 RACEX EDUCYR) 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 2007 Appendix File, HC-110I, provides
examples of how to merge other MEPS data files.
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5.2 Linking to the Prescribed Medicines File
The RXLK file provides a link from the MEPS event
files to the 2007 Prescribed Medicine 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 2007 Appendix File, HC-110I.
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5.3 Linking to the Medical Conditions File
Conditions data are not collected for Dental events;
therefore, this file cannot be linked to the Conditions File.
Return To Table Of Contents
References
Cohen, S.B. (1997). Sample Design of the 1996 Medical
Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health
Care Policy and Research; 1997. MEPS Methodology Report, No. 2.
AHCPR Pub. No. 97-0027.
Cohen, J.W. (1997). Design and Methods of the Medical
Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health
Care Policy and Research; 1997. MEPS Methodology Report, No. 1.
AHCPR Pub. No. 97-0026.
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.
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.
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D. Variable-Source Crosswalk
VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-110B: 2007 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 |
DVDATEDD
|
Event date – day
|
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 |
FFBEF07 |
Total # of visits in FF before 2007 |
FF05 |
FFTOT08 |
Total # of visits in FF after 2007 |
FF10 |
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Imputed Expenditure Variables
Variable |
Description |
Source |
DVSF07X |
Amount paid, self/family (Imputed) |
CP Section (Edited) |
DVMR07X |
Amount paid, Medicare (Imputed) |
CP Section (Edited) |
DVMD07X |
Amount paid, Medicaid (Imputed) |
CP Section (Edited) |
DVPV07X |
Amount paid, private insurance (Imputed) |
CP Section (Edited) |
DVVA07X |
Amount paid, Veterans Administration (Imputed) |
CP Section (Edited) |
DVTR07X |
Amount paid, TRICARE/CHAMPVA (Imputed) |
CP Section (Edited) |
DVOF07X |
Amount paid, other federal (Imputed) |
CP Section (Edited) |
DVSL07X |
Amount paid, state & local government
(Imputed) |
CP Section (Edited) |
DVWC07X |
Amount paid, workers’ comp (Imputed) |
CP Section (Edited) |
DVOR07X |
Amount paid, other private (Imputed) |
Constructed |
DVOU07X |
Amount paid, other public (Imputed) |
Constructed |
DVOT07X |
Amount paid, other insurance (Imputed) |
CP Section (Edited) |
DVXP07X |
Sum of DVSF07X – DVOT07X (Imputed) |
Constructed |
DVTC07X |
Household reported total charge (Imputed) |
CP Section (Edited) |
IMPFLAG |
Imputation status |
Constructed |
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Weights
Variable |
Description |
Source |
PERWT07F |
Expenditure File Person Weight, 2007 |
Constructed |
VARSTR |
Variance estimation stratum, 2007 |
Constructed |
VARPSU |
Variance estimation PSU, 2007 |
Constructed |
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|
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