MEPS HC-102B: 2006 Dental Visits
August 2008
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 Sources 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, FFBEF06, FFTOT07)
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 (FFBEF06, FFTOT07)
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 (DVSF06X-DVTC06X)
2.5.5.8 Rounding
3.0 Sample Weight (PERWT06F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 10 Weight
3.2.2 MEPS Panel 11 Weight
3.2.3 The Final Weight for 2006
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
5.4 Pooling Annual Files
5.5 Longitudinal Analysis
_._ 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. MEPS oversamples additional policy relevant sub-groups
such as Asians and low income households. The linkage of the MEPS to the
previous year's NHIS provides additional data for longitudinal analytic
purposes.
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2.0 Medical Provider Component
Upon completion of the household CAPI interview and
obtaining permission from the household survey respondents, a sample of medical
providers are contacted by telephone to obtain information that household
respondents can not accurately provide. This part of the MEPS is called the
Medical Provider Component (MPC) and information is collected on dates of visit,
diagnosis and procedure codes, charges and payments. The Pharmacy
Component (PC), a subcomponent of the MPC, does not collect charges or diagnosis
and procedure codes but does collect drug detail information, including National
Drug Code (NDC) and medicine name, as well as date filled and sources and
amounts of payment. The MPC is not designed to yield national estimates.
It is primarily used as an imputation source to supplement/replace household
reported expenditure information.
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3.0 Survey Management and Data Collection
MEPS HC and MPC data are collected under the authority of
the Public Health Service Act. Data are collected under contract with
Westat, Inc. Data sets and summary statistics are edited and published in
accordance with the confidentiality provisions of the Public Health Service Act
and the Privacy Act. The National Center for Health statistics (NCHS)
provides consultation and technical assistance.
As soon as data collection and editing are completed, the
MEPS survey data are released to the public in staged releases of summary
reports, micro data files, and tables via the MEPS Web site:
www.meps.ahrq.gov. Selected data can be
analyzed through MEPSnet, an on-line interactive tool designed to give data
users the capability to statistically analyze MEPS data in a menu-driven
environment.
Additional information on MEPS is available from the MEPS
project manager or the MEPS public use data manager at the Center for Financing
Access and Cost Trends, Agency for Healthcare Research and Quality, 540 Gaither
Road, Rockville, MD 20850 (301-427-1406).
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C. Technical and Programming Information
1.0 General Information
This documentation describes one in a series of public use
event files from the 2006 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 2006 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 2006. The file contains 77
variables and has a logical record length of 310 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 2006 portion of Round 3 and
Rounds 4 and 5 for Panel 10, as well as Rounds 1, 2 and the 2006 portion of
Round 3 for Panel 11 (i.e., the rounds for the MEPS panels covering calendar
year 2006).
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 2006
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 2006 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 2006 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 2006 Dental public use data set contains 28,480 dental
event records; of these records, 27,986 are associated with persons having a
positive person-level weight (PERWT06F). 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 2006. Dental
visits known to have occurred before January 1, 2006 and after December 31, 2006
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 2006 portion
of Round 3, and Rounds 4 and 5 for Panel 10, as well as Rounds 1, 2, and the
2006 portion of Round 3 for Panel 11 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 2006 eligibility (i.e.,
persons with a positive 2006 full-year person-level weight (PERWT06F >
0)), or - Be an eligible member of a family all of whose key
in-scope members have a positive person-level weight (PERWT06F > 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
(FAMWT06F > 0). Note that FAMIDYR and FAMWT06F are variables on the 2006
Population Characteristics file.
Persons with no dental events for 2006 are not included on
this event-level DV file but are represented on the person-level 2006 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.
Data from this file can be merged with the MEPS 2006 Full
Year Population Characteristics File using the person identifier, DUPERSID, to
append person-level information such as demographic or health insurance
characteristics to each record. Dental events can also be linked to the MEPS
2006 Prescribed Medicine File. Please see section 5.0 or the 2006 Appendix for
details on how to merge MEPS data files.
Analysts should use the clinical classification codes
listed in the Conditions PUF document (HC-104) and the Appendix to the Event
Files (HC-102I) document when analyzing MEPS conditions data. Although there is
a list of clinical classification codes and labels on the Healthcare Cost and
Utilization Project (HCUP) Web site, if updates to these codes and/or labels are
made on the HCUP Web site after the release of the 2006 MEPS PUFs, these updates
will not be reflected in the 2006 MEPS data.
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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. See the section on pooling annual files, 5.4, for details.
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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 of 40 characters) |
Format |
Number of bytes |
Type |
Type of data: numeric (indicated by NUM) or character (indicated by CHAR) |
Start |
Beginning column position of variable in record |
End |
Ending column position of variable in record |
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2.4 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 (06). The
seventh character, "X", indicates the variable is edited/imputed.
For example, DVSF06X is the edited/imputed amount paid by
self or family for 2006 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 2006 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 2006 Prescribed
Medicines file). For details on linking see Section 5.0 or the MEPS 2006
Appendix File, HC-102I.
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 10. Likewise, Rounds 1, 2, and 3 (partial) are
associated with data collected from Panel 11.
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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 10 or Panel 11 for each
person on the file. Panel 10 is the panel that started in 2005, and Panel 11 is
the panel that started in 2006.
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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 which indicate the day, month,
and year a dental event occurred (DVDATEDD, DVDATEMM, 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, FFBEF06,
FFTOT07)
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 2006. 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 2006 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 2006 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
(FFBEF06, FFTOT07)
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 2006 dental visit is part of a group of events, and some of
the events occurred before or after 2006, counts of the known events are
provided on the dental record. Variables that indicate events occurring before
or after 2006 are the following:
FFBEF06 – indicates total number of pre-2006
events in the same flat fee group as the 2006 dental event. This count
would not include 2006 dental events.
FFTOT07 – indicates the number of 2007 medical
events expected to be in the same flat fee group as the 2006 dental
event record.
If there are no 2005 events on the file, FFBEF06 will be
omitted. Likewise, if there are no 2007 events on the file, FFTOT07 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 4,208 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 2006, but the remaining visits that were part
of this flat fee group occurred in 2007. In this case, the 2006 flat fee group
represented on this file would consist of one event (the stem). The 2007 "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 2005 but subsequent visits occurred during 2006. In this
case, the initial visit would not be represented on the file. This 2006 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.
Return To Table Of Contents
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 2006, all of the events that occurred in 2006 will have zero
payments. Conversely, if the first event in the flat fee group occurred at the
end of 2006, the total expenditure for the entire flat fee group will be on that
event, regardless of the number of events it covered after 2006. 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.
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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
(DVSF06X- DVTC06X)
DVSF06X - DVOT06X are the 12 sources of payment. DVTC06X
is the total charge, and DVXP06X is the sum of the 12 sources of payment for the
Dental expenditures. The 12 sources of payment are: self/family (DVSF06X),
Medicare (DVMR06X), Medicaid (DVMD06X), private insurance (DVPV06X), Veterans
Administration (DVVA06X), TRICARE/CHAMPVA (DVTR06X), other Federal sources
(DVOF06X), State and Local (non-federal) government sources (DVSL06X), Workers’
Compensation (DVWC06X), other private insurance (DVOR06X), other public
insurance (DVOU06X), and other insurance (DVOT06X).
Return To Table Of Contents
2.5.5.8 Rounding
Expenditure variables on the 2006 dental file have been
rounded to the nearest penny. Person-level expenditure information to be
released on the MEPS 2006 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 2006 Appendix File, HC-102I, for details on such rounding differences.
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3.0 Sample Weight (PERWT06F)
3.1 Overview
There is a single full year person-level weight (PERWT06F)
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 2006. 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.
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3.2 Details on Person Weight Construction
The person-level weight PERWT06F was developed in several
stages. Person-level weights for Panels 10 and 11 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 2006 composite weight was then formed by multiplying
each weight from Panel 10 by the factor .47 and each weight from Panel 11 by the
factor .53. 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.
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3.2.1 MEPS Panel 10 Weight
The person-level weight for MEPS Panel 10 was developed
using the 2005 full year weight for an individual as a "base" weight for survey
participants present in 2005. For key, in-scope respondents who joined an RU
some time in 2006 after being out-of-scope in 2005, the 2005 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 2006. These control
figures were derived by scaling back the population totals obtained from the
March 2007 CPS to correspond to a national estimate for the civilian
noninstitutionalized population provided by the Census Bureau for December 2006.
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, 2006 is 295,668,762. Key,
responding persons not in-scope on December 31, 2006 but in-scope earlier in the
year retained, as their final Panel 10 weight, the weight after the nonresponse
adjustment.
Return To Table Of Contents
3.2.2 MEPS Panel 11 Weight
The person-level weight for MEPS Panel 11 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 2006 portion of Round 3 as well as raking to the same
population control figures for December 2006 used for the MEPS Panel 10 weights.
The same five variables employed for Panel 10 raking (census region, MSA status,
race/ethnicity, sex, and age) were used for Panel 11 raking. Similarly, for
Panel 11, key, responding persons not in-scope on December 31, 2006 but in-scope
earlier in the year retained, as their final Panel 11 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., 2005 for Panel 10 and 2006 for Panel 11).
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3.2.3 The Final Weight for 2006
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, 2006 is 295,668,762
(PERWT06F>0 and INSC1231=1). In addition, the weights of two groups of persons
who were out-of-scope on December 31, 2006 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 2006 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 299,267,035.
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3.2.4 Coverage
The target population for MEPS in this file is the 2006
U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2004 (Panel 10)
and 2005 (Panel 11). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2004 (Panel 10) or after 2005 (Panel 11) 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 inappropriately concluding that a change has taken
place.
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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 2006
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 (PERWT06F) across relevant event
records while estimates of other variables must be weighted by PERWT06F 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,
 = PERWT06Fi (full year person weight for the person
associated with event j), and
 = DVSF06Xj (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 (SE)
Excluding 0s |
Total number of dental visits
(in millions) |
PERWT06F |
305.8 (8.83) |
257.4 (7.39) |
Proportion of dental visits with
expenditures > 0* |
DVXP06X |
0.842 (0.0061) |
-------- |
*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 (SE)
Excluding 0s |
Mean total payments per visit |
DVxp06X |
$250 ($4.9) |
$297 ($6.2) |
|
Mean out-of-pocket payment per visit |
DVsf06X |
$123 ($4.0) |
$146 ($5.0) |
Mean proportion of total expenditures
paid by private insurance per visit |
DVpv06X
/DVxp06X |
------- |
0.479 (0.0071) |
Expenditures: Dental Hygienist Visits (DENTHYG = 1)
Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate (SE)
Excluding 0s |
|
Mean total payments per visit where
person saw hygienist |
DVxp06X |
$166 ($5.5) |
$172 ($5.8) |
Mean out-of-pocket payment per visit
where person saw hygienist |
DVsf06X |
$66 ($3.3) |
$68 ($3.5) |
Mean proportion of total expenditures
per visit paid by private insurance
where person saw hygienist |
DVpv06X
/DVxp06X |
------- |
0.565 (0.0112) |
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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.
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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 2006 full year data associated with the corresponding estimates
of variance.
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. There are 203 variance estimation strata, each
stratum with either two or three variance estimation PSUs.
Note: A new NHIS sample design is being implemented
beginning in 2006. As a result, the MEPS variance estimation structure will be
modified for MEPS data collected in 2007 and beyond.
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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. Each MEPS panel can also
be linked back to the previous years’ National Health Interview Survey 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., 2006 Full Year Population Characteristics File or 2006 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 2006 Appendix File, HC-102I, provides additional details
of how to merge other MEPS data files.
Create data set PERSX by sorting the 2006 Full
Year Population Characteristics 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 2006 Appendix File, HC-102I, 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 2006 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 2006 Appendix
File, HC-102I.
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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.
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5.4 Pooling Annual Files
To facilitate analysis of subpopulations and/or low
prevalence events, it may be desirable to pool together more than one year of
data to yield sample sizes large enough to generate reliable estimates.
For more details on pooling MEPS data files see
www.meps.ahrq.gov/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036.
Starting in Panel 9, values for DUPERSID from previous
panels will occasionally be re-used. Therefore, it is necessary to use the panel
variable (PANEL) in combination with DUPERSID to ensure unique person-level
identifiers across panels. Creating unique records in this manner is advised
when pooling MEPS data across multiple annual files that have one or more
identical values for DUPERSID.
Return To Table Of Contents
5.5 Longitudinal Analysis
MEPS Panel Longitudinal Weight files containing estimation
variables to facilitate longitudinal analysis are available for downloading in
the data section of the MEPS Web site.
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-102B: 2006 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 |
FFBEF06 |
Total # of visits in FF before 2006 |
FF05 |
FFTOT07 |
Total # of visits in FF after 2006 |
FF10 |
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Imputed Expenditure Variables
Variable |
Description |
Source |
DVSF06X |
Amount paid, self/family (Imputed) |
CP Section (Edited) |
DVMR06X |
Amount paid, Medicare (Imputed) |
CP Section (Edited) |
DVMD06X |
Amount paid, Medicaid (Imputed) |
CP Section (Edited) |
DVPV06X |
Amount paid, private insurance(Imputed) |
CP Section (Edited) |
DVVA06X |
Amount paid, Veterans Administration (Imputed) |
CP Section (Edited) |
DVTR06X |
Amount paid, TRICARE/CHAMPVA (Imputed) |
CP Section (Edited) |
DVOF06X |
Amount paid, other federal (Imputed) |
CP Section (Edited) |
DVSL06X |
Amount paid, state & local government (Imputed) |
CP Section (Edited) |
DVWC06X |
Amount paid, workers’ comp(Imputed) |
CP Section (Edited) |
DVOR06X |
Amount paid, other private (Imputed) |
Constructed |
DVOU06X |
Amount paid, other public (Imputed) |
Constructed |
DVOT06X |
Amount paid, other insurance (Imputed) |
CP Section (Edited) |
DVXP06X |
Sum of DVSF06X – DVOT06X (Imputed) |
Constructed |
DVTC06X |
Household reported total charge (Imputed) |
CP Section (Edited) |
IMPFLAG |
Imputation status |
Constructed |
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Weights
Variable |
Description |
Source |
PERWT06F |
Expenditure File Person Weight, 2006 |
Constructed |
VARSTR |
Variance estimation stratum, 2006 |
Constructed |
VARPSU |
Variance estimation PSU, 2006 |
Constructed |
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