MEPS HC-010B:
1996 Dental Visits
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 Insurance Component
4.0 Nursing Home Component
5.0 Survey Management
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 Naming
2.4.1 General
2.4.2 Expenditure and Sources of Payment Variables
2.5 File 1 Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers
(DUID - DUPERSID
2.5.1.2 Record Identifiers
(EVNTID, FFID11X, EVENTRN)
2.5.2 Characteristics of Dental Events
2.5.2.1 Date of Dental Visit
(DVDATEYR - DVDATEDD)
2.5.2.2 Type of Provider Seen
(GENDENT - DENTYPE)
2.5.2.3 Treatment, Procedures, and Services
(EXAMINEX - DENTMED)
2.5.2.4 ICD-9 Condition (DVICD1X, DVICD2X) and Procedure Codes
(DVPRO1X, DVPRO2X) and Clinical Classification Codes
(DVCCC1X, VCCC2X)
2.5.2.5 Record Count Variable
(NUMCOND
2.5.3 Flat Fee Variables
2.5.3.1 Definition of Flat Fee Payments
2.5.3.2 Flat Fee Variable Descriptions
2.5.4 Expenditure Data
2.5.4.1 Definition of Expenditures
2.5.4.2 Data Editing/Imputation Methodologies of Expenditure Variables
2.5.4.3 General Imputation Methodology
2.5.4.4 Dental Imputation
2.5.4.5 Flat Fee Expenditures
2.5.4.6 Zero Expenditures
2.5.4.7 Sources of Payment
2.5.4.9 Imputed Dental Expenditures (DVFS96X-DVOT96X, DVXP96X,
DVTC96X)
2.5.4.10 Rounding
2.5.4.11 Imputation Flags
2.6 File 2 Contents: Pre-imputed Expenditure Variables
3.0 Sample Weights and Variance Estimation Variables (WTDPER96-VARPSU96)
3.1 Overview
3.2 Details on Person Weights Construction
4.0 Strategies for Estimation
4.1 Variables with Missing Values
4.2 Basic Estimates of Utilization, Expenditure and Sources of Payment
4.3 Estimates of the Number of Persons with Dental Visits
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with Dental Visits
4.4.2 Person-Based Ratio Estimates Relative to the Entire Population
4.5 Sampling Weights for Merging Previous Releases of MEPS Household Data with the
Current Data File
4.6 Variance Estimation
5.0 Merging/Linking MEPS Data Files
5.1 Linking a Person-Level File to the Dental File
5.2 Linking the Dental File (HC-010B) to the Medical Conditions File (HC-006) and/or the Prescribed Medicines File (HC-010A)
5.2.1 Limitations/Caveats of RXLK (the Prescribed Medicine Link File)
5.2.2 Limitations/Caveats of CLNK (the Medical Conditions Link File)
6.0 Programming Information
References
Attachment 1
D. Codebooks
(link to separate file)
E. Variable-Source Crosswalk
A. Data Use Agreement
Individual identifiers have been removed from the microdata contained in the files on this CD-ROM. 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.
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.
- 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 18 U.S.C. 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
This documentation describes one in a series of public use files from the Medical Expenditure
Panel Survey (MEPS). The survey provides a new and extensive data set on the use of health
services and health care in the United States.
MEPS is conducted to provide nationally representative estimates of health care use, expenditures,
sources of payment, and insurance coverage for the U.S. civilian noninstitutionalized population.
MEPS also includes a nationally representative survey of nursing homes and their residents.
MEPS is cosponsored by the Agency for Healthcare Research and Quality (AHRQ) (formerly the
Agency for Health Care Policy and Research (AHCPR)) and the National Center for Health
Statistics (NCHS).
MEPS comprises four component surveys: the Household Component (HC), the Medical Provider
Component (MPC), the Insurance Component (IC), and the Nursing Home Component (NHC).
The HC is the core survey, and it forms the basis for the MPC sample and part of the IC sample.
The separate NHC sample supplements the other MEPS components. Together these surveys
yield comprehensive data that provide national estimates of the level and distribution of health
care use and expenditures, support health services research, and can be used to assess health care
policy implications.
MEPS is the third in a series of national probability surveys conducted by AHRQ on the financing
and use of medical care in the United States. The National Medical Care Expenditure Survey
(NMCES, also known as NMES-1) was conducted in 1977. The National Medical Expenditure
Survey (NMES-2) was conducted in 1987. Beginning in 1996, MEPS continues this series with
design enhancements and efficiencies that provide a more current data resource to capture the
changing dynamics of the health care delivery and insurance system.
The design efficiencies incorporated into MEPS are in accordance with the Department of Health
and Human Services (DHHS) Survey Integration Plan of June 1995, which focused on
consolidating DHHS surveys, achieving cost efficiencies, reducing respondent burden, and
enhancing analytical capacities. To accommodate these goals, new MEPS design features include
linkage with the National Health Interview Survey (NHIS), from which the sampling frame for the
MEPS HC is drawn, and continuous longitudinal data collection for core survey components. The
MEPS HC augments NHIS by selecting a sample of NHIS respondents, collecting additional data
on their health care expenditures, and linking these data with additional information collected
from the respondents' medical providers, employers, and insurance providers.
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1.0 Household Component
The MEPS HC, a nationally representative survey of the U.S. civilian noninstitutionalized
population, collects medical expenditure data at both the person and household levels. The HC
collects detailed data on demographic characteristics, health conditions, health status, use of
medical care services, charges and payments, access to care, satisfaction with care, health
insurance coverage, income, and employment.
The HC uses an overlapping panel design in which data are collected through a preliminary
contact followed by a series of five rounds of interviews over a 2½-year period. Using computer-assisted personal interviewing (CAPI) technology, data on medical expenditures and use for two
calendar years are collected from each household. This series of data collection rounds is
launched each subsequent year on a new sample of households to provide overlapping panels of
survey data and, when combined with other ongoing panels, will provide continuous and current
estimates of health care expenditures.
The sampling frame for the MEPS HC is drawn from respondents to NHIS, conducted by NCHS.
NHIS provides a nationally representative sample of the U.S. civilian noninstitutionalized
population, with oversampling of Hispanics and blacks.
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2.0 Medical Provider Component
The MEPS MPC supplements and validates information on medical care events reported in the
MEPS HC by contacting medical providers and pharmacies identified by household respondents.
The MPC sample includes all hospitals, hospital physicians, home health agencies, and
pharmacies reported in the HC. Also included in the MPC are all office-based physicians who:
- were identified by the household respondent as providing care for HC respondents
receiving Medicaid.
- were selected through a 75-percent sample of HC households receiving care through
an HMO (health maintenance organization) or managed care plan.
- were selected through a 25-percent sample of the remaining HC households.
Data are collected on medical and financial characteristics of medical and pharmacy events
reported by HC respondents, including:
- Diagnoses coded according to ICD-9-CM (9th Revision, International Classification of
Diseases) and DSM-IV (Fourth Edition, Diagnostic and Statistical Manual of Mental
Disorders).
- Physician procedure codes classified by CPT-4 (Common Procedure Terminology,
Version 4).
- Inpatient stay codes classified by DRGs (diagnosis-related groups).
- Prescriptions coded by national drug code (NDC), medication name, strength, and quantity
dispensed.
- Charges, payments, and the reasons for any difference between charges and payments.
The MPC is conducted through telephone interviews and mailed survey materials. In some
instances, providers sent medical and billing records which were abstracted into the survey
instruments.
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3.0 Insurance Component
The MEPS IC collects data on health insurance plans obtained through employers, unions, and
other sources of private health insurance. Data obtained in the IC include the number and types of
private insurance plans offered, benefits associated with these plans, premiums, contributions by
employers and employees, eligibility requirements, and employer characteristics.
Establishments participating in the MEPS IC are selected through four sampling frames:
- A list of employers or other insurance providers identified by MEPS HC respondents who
report having private health insurance at the Round 1 interview.
- A Bureau of the Census list frame of private-sector business establishments.
- The Census of Governments from Bureau of the Census.
- An Internal Revenue Service list of the self-employed.
To provide an integrated picture of health insurance, data collected from the first sampling frame
(employers and insurance providers) are linked back to data provided by the MEPS HC
respondents. Data from the other three sampling frames are collected to provide annual national
and State estimates of the supply of private health insurance available to American workers and to
evaluate policy issues pertaining to health insurance.
The MEPS IC is an annual survey. Data are collected from the selected organizations through a
prescreening telephone interview, a mailed questionnaire, and a telephone follow up for
nonrespondents.
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4.0 Nursing Home Component
The 1996 MEPS NHC was a survey of nursing homes and persons residing in or admitted to
nursing homes at any time during calendar year 1996. The NHC gathered information on the
demographic characteristics, residence history, health and functional status, use of services, use of
prescription medicines, and health care expenditures of nursing home residents. Nursing home
administrators and designated staff also provided information on facility size, ownership,
certification status, services provided, revenues and expenses, and other facility characteristics.
Data on the income, assets, family relationships, and care-giving services for sampled nursing
home residents were obtained from next-of-kin or other knowledgeable persons in the community.
The 1996 MEPS NHC sample was selected using a two-stage stratified probability design. In the
first stage, facilities were selected; in the second stage, facility residents were sampled, selecting
both persons in residence on January 1, 1996, and those admitted during the period January 1
through December 31.
The sample frame for facilities was derived from the National Health Provider Inventory, which is
updated periodically by NCHS. The MEPS NHC data were collected in person in three rounds of
data collection over a 1½-year period using the CAPI system. Community data were collected by
telephone using computer-assisted telephone interviewing (CATI) technology. At the end of three
rounds of data collection, the sample consisted of 815 responding facilities, 3,209 residents in the
facility on January 1, and 2,690 eligible residents admitted during 1996.
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5.0 Survey Management
MEPS data are collected under the authority of the Public Health Service Act. They are edited and
published in accordance with the confidentiality provisions of this act and the Privacy Act. 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 and microdata files. Summary reports are released as
printed documents and electronic files. Microdata files are released on CD-ROM and/or as
electronic files.
Printed documents and CD-ROMs are available through the AHRQ Publications Clearinghouse.
Write or call:
AHRQ Publications Clearinghouse
Attn: (publication number)
P.O. Box 8547
Silver Spring, MD 20907
800/358-9295
410/381-3150 (callers outside the United States only)
888/586-6340 (toll-free TDD service; hearing impaired only)
Be sure to specify the AHRQ number of the document or CD-ROM you are requesting. Selected
electronic files are available from the Internet on the MEPS web site:
<http://www.meps.ahrq.gov/>
Additional information on MEPS is available from the MEPS project manager or the MEPS
public use data manager at the Center for Cost and Financing Studies, Agency for Healthcare
Research and Quality.
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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 1996 Medical
Expenditure Panel Survey Household (HC) and Medical Provider Components(MPC) . Released
as an ASCII data file and SAS transport file, this public use file provides detailed information on
dental events for a nationally representative sample of the civilian noninstitutionalized population
of the United States and can be used to make estimates of dental event utilization and
expenditures for calendar year 1996. Each record on this event file represents a unique dental
event; that is, a dental event reported by the household respondent.
Data from this event file can be merged with other MEPS HC data files, for the purposes of
appending person characteristics such as demographic or health insurance coverage to each dental
event record.
Counts of dental event utilization are based entirely on household reports. Dental events were not
included in the MPC, therefore all expenditure and payment data are reported by the household.
This file can be also 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 public use file HC-011, where each
record represents a MEPS sampled person.
The following documentation offers a brief overview of the types and levels of data provided, the
content and structure of the files and the codebook, and programming information. It contains the
following sections:
Data File Information
Sample Weights and Variance Estimation Variables
Merging MEPS Data Files
Programming Information
References
Codebook
Variable to Source Crosswalk
For more information on MEPS HC survey design see S. Cohen, 1997; J. Cohen, 1997; and S.
Cohen, 1996. For information on the MEPS MPC design, see S. Cohen, 1998. A copy of the
survey instrument used to collect the information on this file is available on the MEPS web site at
the following address: <http://www.meps.ahrq.gov>
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2.0 Data File Information
This public use data set consists of two event-level data files. File 1 contains characteristics
associated with the dental event and imputed expenditure data. File 2 contains pre-imputed
expenditure data from the Household Component for all dental events on File 1. Please see
Section 2.5.4 for definitions of imputed, and pre-imputed expenditure variables.
Both Files 1 and 2 of this public use data set contain 22,165 dental event records. Of the 22,165,
dental event records, 21,866 are associated with persons having a positive person-level weight
(WTDPER96). 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 1996. Dental
visits known to have occurred after December 31, 1996 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 rounds 1, 2, and 3 of the
MEPS HC. The persons represented on this file had to meet either (a) or (b) below:
a) Be classified as a key in-scope person who responded for his or her entire period
of 1996 eligibility (i.e., persons with a positive 1996 full-year person-level
sampling weight (WTDPER96 > 0)), or
b) Be classified as either an eligible non-key person or an eligible out-of-scope
person who responded for his or her entire period of 1996 eligibility, and belonged
to a family (i.e., all persons with the same value for a particular FAMID) in which
all eligible family members responded for their entire period of 1996 eligibility,
and at least one family member has a positive 1996 full-year person weight (i.e.,
eligible non-key or eligible out-of-scope persons who are members of a family all
of whose members have a positive 1996 full-year MEPS family-level weight
(WTFAM96 >0)).
Please refer to Attachment 1 for definitions of key, non-key, inscope and eligible.
Each dental event record on this file includes the following: date of the dental event; type of
provider seen, if visit was due to an accident; reason for dental event; condition(s) and
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.
File 2 of this public use data set is intended for analysts who want to perform their own
imputations to handle missing data. This file contains one set of pre-imputed expenditure
information from the Household Component. Expenditure data have been subject to minimal
logical editing that 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 HMO's and private HMO's as payment sources. However, missing data were not
imputed.
Data from these files can be merged with previously released 1996 MEPS HC person level data
using the unique person identifier, DUPERSID, to append person characteristics such as
demographic or health insurance characteristics to each record. Dental events can also be linked
to the MEPS 1996 Medical Conditions File (HC-006) and MEPS 1996 Prescribed Medicine File
(HC-010A). Please see File HC-010I: The Appendix File for details on how to link MEPS data
files.
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2.1 Codebook Structure
For each variable on these files, both weighted and unweighted frequencies are provided. The
codebook and data file sequence list variables in the following order:
File 1
Unique person identifiers
Unique dental event identifiers
Other survey administration variables
Dental characteristics
ICD-9 codes
Clinical Classification Software codes
Imputed expenditure variables
Weight and variance estimation variables
File 2
Unique person identifiers
Unique dental event identifiers
Pre-imputed expenditure variables
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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 have not been edited on this file. The values of -1 and -9 can
be edited by analysts by following the skip patterns in the questionnaire.
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2.3 Codebook Format
This 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 Naming
In general, variable names reflect the content of the variable, with an 8 character limitation.
For questions asked in a specific round, the end digit in the variable name reflects the round in
which the question was asked. All imputed/edited variables end with an "X."
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2.4.1 General
Variables contained on Files 1 and 2 were derived from the HC questionnaire. The source of
each variable is identified in the Section E, entitled, "Variable to Source Crosswalk". Sources for
each variable are indicated in one of four ways: (1) variables which are derived from CAPI or
assigned in sampling are so indicated; (2) variables which come from one or more specific
questions have those numbers and the questionnaire section indicated in the "Source" column; and
(3) variables constructed from multiple questions using complex algorithms are labeled
"Constructed" in the "Source" column; and (4) variables which have been imputed are so
indicated.
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2.4.2 Expenditure and Sources of Payment Variables
Pre-imputed and imputed versions of the expenditure and sources of payment variables are
provided on 2 separate files. Variables on Files 1 and 2 follow a standard naming convention and
are 8 characters in length. Please note that pre-imputed means that a series of logical edits have
been performed on the variable but missing data remain. The imputed versions incorporate the
same edits but also have undergone an imputation process to account for missing data.
The pre-imputed expenditure variables on File 2 end with an "H" indicating that the data source
was the MEPS Household Component. All imputed variables on File 1 end with an "X"indicating
they are fully edited and imputed.
The total sum of payments, 12 sources of payment variables, and total charge variables are named
consistently 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
XP - sum of payments
MR - Medicare
SL - State/local government
MD - Medicaid
WC - Worker's Compensation
PV - private insurance
OT - other insurance
VA - Veterans
OR - other private
CH - CHAMPUS/CHAMPVA
OU - other public
The fifth and sixth characters indicate the year (96). The last character of all imputed/edited
variables is an " X".
For example, DVSF96X is the edited/imputed amount paid by self or family for the 1996 dental
expenditure.
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2.5 File 1 Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID - DUPERSID)
The dwelling unit ID (DUID) is a 5-digit random number assigned after the case was sampled for
MEPS. The 3-digit person number (PID) uniquely identifies each person within the dwelling unit.
The 8-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 on public use file HC-008.
2.5.1.2 Record Identifiers (EVNTID, FFID11X, EVENTRN)
EVNTID uniquely identifies each event (i.e., each record on the file) and is the variable required
to link events to data files containing details on conditions and/or prescribed medicines (HC-006
and HC-010A, respectively). For details on linking see Section 5.0.
FFID11X uniquely identifies a flat fee group, that is, all events that were part of a flat fee payment
situation. 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 have the same value
for FFID11X. FFID11X identifies a flat fee payment situation that was identified using
information from the Household Component. Please note that FFID11X should be used to link up
all MEPS event files (excluding prescribed medicines) in order to determine the full set of events
that are part of a flat fee group.
EVENTRN indicates the round in which the dental event was first reported.
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2.5.2 Characteristics of Dental Events
2.5.2.1 Date of Dental Visit (DVDATEYR - DVDATEDD)
File 1 contains variables describing dental events reported by household respondents in the Dental
Section of the MEPS HC questionnaire. There are three variables which indicate the day, month
and year a dental event occurred (DVDATEDD, DVBEGMM, 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 visit, e.g. general dentist,
dental hygienist, or orthodontist. More than one type of provider may have been identified on an
event record.
2.5.2.3 Treatment, Procedures, and Services (EXAMINEX - DENTMED)
Respondents were asked about the types of services or treatments they received during the visit
(EXAMINEX - TMDTMJ), such as root canal or x-rays, and whether or not the visit was because
of an accident (DENTINJ). 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. Both the edited
and unedited versions of these variables are included on this file. DENTMED indicates whether
or not the respondent received a prescription medication, including free samples, during the dental
visit.
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2.5.2.4 ICD-9 Condition (DVICD1X, DVICD2X) and Procedure Codes (DVPRO1X,
DVPRO2X) and Clinical Classification Codes (DVCCC1X, DVCCC2X)
Information on household reported medical conditions, procedures, and clinical classification
codes associated with each dental event are provided on this file. There are up to two condition
codes (DVICD1X, DVICD2X), procedure codes(DVPRO1X, DVPRO2X), and clinical
classification codes (DVCCC1X, DVCCC2X) listed for each dental event. This represents 100%
of the conditions, procedures, and clinical classification codes that can be linked to the current file
from the 1996 Medical Condition File (HC-006). Not all dental records on this file are associated
with a medical condition or procedure. Only 492 records (approximately 2.2%) can be linked to
the Medical Condition Public Use File (HC-006).
The medical conditions and procedures reported by the household respondent were recorded by
the interviewer as verbatim text, which were then coded to fully-specified 1996 ICD-9-CM codes,
including medical condition and V codes (see Health Care Financing Administration, 1980), by
professional coders. For details regarding the coding and editing procedures used for ICD-9
condition and procedure codes, and clinical classification codes see HC-006 (1996 Medical
Conditons) documentation. Weighted and unweighted frequencies for DVCCC1X-DVCCC2X
are provided in the Appendix File.
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2.5.2.5 Record Count Variable (NUMCOND)
The variable NUMCOND indicates the total number of records on the condition file that can be
linked from HC-006: Medical Conditions File to each dental event. For events with no condition
records linked (NUMCOND=0), the condition, procedure, and clinical classification code
variables all have a value of -1 INAPPLICABLE. Similarly, for events without a linked second
condition, procedure record, the corresponding second condition and clinical classification code
variable was set to -1 INAPPLICABLE.
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2.5.3 Flat Fee Variables
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 covering surgical procedure and post-surgical care. A flat fee group is
the set of medical events (that can vary by type of event) that are covered under the same flat fee
payment situation. The flat fee groups represented on this file (and all of the other 1996 MEPS
event files), include flat fee groups where at least one of the health care events, as reported by the
HC respondent, occurred during 1996. By definition a flat fee group can span multiple years
and/or event types (e.g., hospital stay, physician office visit), and a single person can have
multiple flat fee groups.
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2.5.3.2 Flat Fee Variable Descriptions
There are several variables on this file
that describe a flat fee payment situation and the number of medical
events that are part of a flat fee group. As noted previously, for
a person, the variable
FFID11X can be used to identify all events, that are part of the same
flat fee group. To identify such events, FFID11X should be used to
link events from all MEPS event files (excluding
presscribed medicines): HC-010B through HC-010H. For the dental
events that are not part of a flat fee payment situation, the flat
fee variables described below are all set to inapplicable (-1).
Flat Fee Type (FFDVTYPX)
FFDVTYPX indicates whether the 1996 dental event is the "stem" or "leaf" of a flat fee group. A
stem (records with FFDVTYPX = 1) is the initial medical service (event) which is followed by
other medical events that are covered under the same flat fee payment. The leaf of the flat fee
group (records with FFDVTYPX = 2) are those medical events that are tied back to the initial
medical event (the stem) in the flat fee group.
Total Number of 1996 Events in Group (FFTOT96)
If a dental event is part of a flat fee group, the variable FFTOT96 counts the total number of all
known events, that occurred during 1996 you are covered under a single flat fee payment
situation.
Counts of Flat Fee Events that Cross Years (FFBEF96 FFTOT97)
As described above, a flat fee payment situation covers multiple events and the multiple events
could span multiple years. For situations where a 1996 dental visit is part of a group of events,
and some of the events occurred before or after 1996, counts of the known events are provided on
the dental record. Indicator variables are provided if some of the events occurred after 1996.
These variables are:
FFBEF96 -- total number of pre-1996 events in the same flat fee group as
the 1996 dental event. This count would not include 1996 dental events.
FFDV97 indicates whether or not there are 1997 dental events in the
same flat fee group as the1996 dental event record.
FFTOT97 -- indicates whether or not there are 1997 medical events in the
same flat fee group as the 1996 dental event record.
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2.5.3.3 Caveats of Flat Fee Groups
The user should note that flat fee payment situations are common with respect to dental events.
There are 4,346 dental events that are identified as being part of a flat fee payment group. This
yields 1,138 flat fee payment groups. In order to correctly identify all events that are part of a flat
fee group, the user should link all MEPS event files (excluding the prescribed medicines file)
using the variable FFID11X.
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 1996 but the remaining visits that were part of this flat fee group
occurred in 1997. In this case, the 1996 flat fee group represented on this file would consist of
one event (the stem). The 1997 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 1995 but subsequent visits occurred during 1996. In this case, the initial visit would
not be represented on the file. This 1996 flat fee group would then only consist of one or more
leaf records and no stem. Another reason for which a flat fee group would not have a stem and a
leaf record is that the stems or leaves could have been reported as different event types. In a small
number of cases, there are flat fee bundles that span various event types. The stem may have been
reported as one event type and the leaves may have been reported as another event type. In order
to determine this, the analyst must link all event files (excluding the prescribed medicines files)
using the variable FFID11X to create the flat fee group.
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2.5.4 Expenditure Data
2.5.4.1 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 1990's 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 payments 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. For details on expenditure definitions, please reference the following, "Informing
American Health Care (Monheit et al, 1999 )."
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2.5.4.2 Data Editing/Imputation Methodologies of Expenditure Variables
The general methodology used for editing and imputing expenditure data is described below.
Neither the dental events nor other medical expenditures (such as glasses, contact lenses, and
hearing devices) were included in the Medical Provider Component. 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. Specific methodologies
for editing and imputing dental expenditures follows the General Imputation Methodology
section.
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2.5.4.3 General Imputation Methodology
Logical edits were used to resolve internal inconsistencies and other problems in the HC and MPC
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 HMO's and private HMO's 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.
A weighted sequential hot-deck procedure was used to impute for missing expenditures as well as
total charge. The procedure uses survey data from respondents to replace missing, 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. 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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2.5.4.4 Dental Imputation
Expenditures on visits to dentists were developed in a sequence of logical edits and imputations.
Household edits were applied to sources and amounts of payment for all events reported by HC
respondents.
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 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 also were 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
was assigned to a recipient category based on its pattern of missing data. For example, an event
with a known total charge but no expenditures information was assigned to one category, while an
event with a known total charge and some expenditures information was assigned to a different
category. Similarly, events without a known total charge were assigned to various recipient
categories based on the amount of missing data.
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. These 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 for 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 cost of
free care would be implicitly included in paid events and explicitly included in events that should
have been treated as free from provider.
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2.5.4.5 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 1996, all of the events that occurred in 1996 will have zero
payments. Conversely, if the first event in the flat fee group occurred at the end of 1996, the total
expenditure for the entire flat fee group will be on that event, regardless of the number of events it
covered after 1996.
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2.5.4.6 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) free care was provided, (2) bad debt was
incurred, (3) care was covered under a flat fee arrangement beginning in an earlier year, or (4)
follow-up visits were provided without a separate charge (e.g. after a surgical procedure). If all of
the dental 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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2.5.4.7 Sources of Payment
In addition to total expenditures, variables are provided which itemize expenditures according to
major source of payment categories. These categories are:
1. Out of pocket by user or family
2. Medicare
3. Medicaid
4. Private Insurance
5. Veteran's Administration, excluding CHAMPVA
6. CHAMPUS or CHAMPVA
7. Other Federal sources - includes Indian Health Service, Military Treatment Facilities, and other
care by the Federal government
8. Other State and Local Source - includes community and neighborhood clinics, State and local
health departments, and State programs other than Medicaid.
9. Worker's Compensation
10. Other Unclassified Sources - includes sources such as automobile, homeowner's, liability, and
other miscellaneous or unknown sources.
Two additional source of payment variables were created to classify payments for particular
persons that appear inconsistent due to differences between survey questions on health insurance
coverage and sources of payment for medical events. These variables include:
11. 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
12. Other Public - Medicaid payments reported for persons who were not reported to be enrolled
in the Medicaid program at any time during the year.
Though relatively small in magnitude, users should exercise caution when interpreting the
expenditures associated with 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 program.
Users should also note that the Other Public and Other private source of payment categories only
exist on File 1 for imputed expenditure data since they were created through the
editing/imputation process. File 2 reflects source of payment as it was collected through the
survey.
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2.5.4.9 Imputed Dental Expenditures (DVFS96X-DVOT96X, DVXP96X, DVTC96X)
Dental expenses include all expenses for direct dental care.
Dental expenditures were obtained only through the Household Component Survey. For cases
with missing expenditure data, dental expenditures were imputed using the procedures described
above. There are a number of expenditure variables provided on this file. DVFS96X -
DVOT96X are the 12 sources of payment, DVTC96X is the total charge, and DVXP96X is the
sum of the 12 sources of payments for the dental expenditure. The 12 sources of payment are:
self/family, Medicare, Medicaid, private insurance, Veterans Administration,
CHAMPUS/CHAMPVA, other federal, state/local governments, Workman's Compensation,
other private insurance, other public insurance and other insurance.
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2.5.4.10 Rounding
Expenditure variables on File 1 have been rounded to the nearest penny. Person level expenditure
information released on HC-011 were rounded to the nearest dollar. It should be noted that using
the MEPS event files HC-010A through HC-010H to create person level totals will yield slightly
different totals than those found on HC-011. These differences are due to rounding only.
Moreover, in some instances, the number of persons having expenditures on the event files (HC-010A - HC-010H) for a particular source of payment may differ from the number of persons with
expenditures on the person level expenditure file (HC-011) for that source of payment. This
difference is also an artifact of rounding only. Please see the Appendix File for details on such
rounding differences.
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2.5.4.11 Imputation Flags
The variables IMPDVSLF - IMPDVCHG identify
records where the expenditures have been imputed using the methodologies
outlined in this document. When a record was identified as
being the leaf of a flat fee the values of all imputation flags were
set to "0" (not imputed) since
they were not included in the imputation process
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2.6 File 2 Contents: Pre-imputed Expenditure Variables
Pre-imputed expenditure data are provided on this file. Pre-imputed means that only a series of
logical edits were applied to the data to correct for several problems including outliers,
copayments or charges reported as total payments, and reimbursed amounts counted as out of
pocket payments. Edits were also implemented to correct for misclassifications between Medicare
and Medicaid and between Medicare HMO's and private HMO's as payment sources as well as a
number of other data inconsistencies that could be resolved through logical edits. This file
contains no imputed data.
Included in File 2 is the variable HHSFFIDX, which is the original flat fee identifier that was
derived during the household interview. This identifier should only be used if the analyst is
interested in performing their own expenditure imputation.
The user shall note that there are 10 sources of payment variables in the pre-imputed expenditure
data, while the imputed expenditure data on File 1 contains 12 sources of payment variables. The
additional two sources of payment (which are not reported as separate sources of payment through
the data collection) are Other Private and Other Public. These source of payment categories were
constructed to resolve apparent inconsistencies between individuals' reported insurance coverage
and their sources of payment for specific events File 2 also includes a variable indicating
uncollected liability.
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3.0 Sample Weights and Variance Estimation Variables (WTDPER96-VARPSU96)
3.1 Overview
There is a single full year person-level weight (WTDPER96) included on this file. A person-level
weight was assigned to each dental events reported by a key, in-scope person who responded to
MEPS for the full period of time that he or she was in scope during 1996. A key person either was
a member of an NHIS household at the time of the NHIS interview, or became a member of such
a household after being out-of-scope at the time of the 1995 NHIS (examples of the latter situation
include newborns and 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 Weights Construction
The person-level weight WTDPER96 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 RU weight served as a base weight). The weighting process included an adjustment for
nonresponse over Round 2 and the 1996 portion of Round 3, as well as poststratification to
population control figures for December 1996 (these figures were derived by scaling the
population totals obtained from the March 1997 Current Population Survey (CPS) to reflect the
Census Bureau estimated population distribution across age and sex categories as of December,
1996). Variables used in the establishment of person-level poststratification 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, black but non-Hispanic, and other); sex; and age. Overall, the weighted population
estimate for the civilian non-institutionalized population for December 31, 1996 is 265,439,511
persons. The inclusion of key, in scope persons who were not in scope on December 31,1996
brings the estimated total number of persons represented by the MEPS respondents over the
course of the year up to 268,905,490 (WTDPER96 > 0). The weighting process included
poststratification to population totals obtained from the 1996 Medicare Current Beneficiary
Survey (MCBS) for the number of deaths among Medicare beneficiaries in 1996, and
poststratification to population totals obtained from the 1996 MEPS Nursing Home Component
for the number of individuals admitted to nursing homes.
The MEPS Round 1 weights incorporated the following components: the original household
probability of selection for the NHIS; ratio-adjustment to NHIS 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 1996 CPS database.
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4.0 Strategies for Estimation
This file is constructed for efficient estimation of utilization, expenditure, and sources of payment
for dental events and to allow for estimates of number of persons with dental utilization for 1996.
4.1 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 example, a record with a value of -8 for the first ICD9 condition
code (DVICD1X) indicates that the condition was reported as unknown.
For continuous or discrete variables, where means or totals may be taken, it may be necessary to
set minus 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 exclude or
include 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 2.5.4.
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4.2 Basic Estimates of Utilization, Expenditure and Sources of Payment
While the examples described below illustrate the use of event level data in constructing person
level total expenditures, these estimates can also be derived from the person level expenditure file
unless the characteristic of interest is event specific.
In order to produce national estimates related to dental visits utilization, expenditure and sources
of payment, the value in each record contributing to the estimates must be multiplied by the
weight (WTDPER96) contained on that record.
Example 1:
For example, the total number of dental visits, for the civilian non-institutionalized population of
the U.S. in 1996 is estimated as the sum of the weight (WTDPER96) across all dental visit
records. That is,
Sum of Wj=294,539,798 (1)
Subsetting to records based on characteristics of interest expands the scope of potential estimates.
For example, the estimate for the mean out-of-pocket payment per dental visit should be
calculated as the weighted average of amount paid by self/family. That is,
X bar=(Sum of WjXj) / (Sum of Wj) = $93.90 (2)
where Sum of Wj=236,556,599 and Xj= DVSF96Xj for all records with DVXP96Xj>0
This gives $93.90 as the estimated mean amount of out-of-pocket payment of expenditures
associated with dental visits and 236,556,599 as an estimate of the total number of dental visits
with expenditure. Both of these estimates are for the civilian non-institutionalized population of
the U.S. in 1996.
Another example would be to estimate the average proportion of total expenditures paid by
private insurance per dental visit. This should be calculated as the weighted mean of the
proportion of the total dental visit paid by private insurance at the dental visit . That is,
Y bar = (Sum of Wj Yj) / (Sum of Wj) = 0.4566
(3)
where Sum of Wj = 236,556,599 and Yj= DVPV96Xj/DVXP96Xj for all records with DVXP96Xj>0
This gives 0.4566 as the estimated mean proportion of total expenditures paid by private
insurance for dental visits for the civilian non-institutionalized population of the U.S. in 1996.
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4.3 Estimates of the Number of Persons with Dental Visits
When calculating an estimate of the total number of persons with dental visits, users can use a
person-level file (MEPS HC-011: Person Level Expenditures and Utilization) or this event file.
However, this event file must be used when the measure of interest is defined at the event level.
For example, to estimate the number of persons in the civilian non-institutionalized population of
the U.S., with a dental visit in 1996 because of accident or injury, this event file must be used.
This would be estimated as
Sum of Wj Xj across all unique persons i on
this file, (4)
where Wj is the sampling weight (WTDPER96) for person i
and
Xj=1 if DENTINJ=1 for any visit of person i
and
Xj=0 otherwise
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4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with Dental Visits
This file may be used to derive person-based ratio estimates. However, when calculating ratio
estimates where the denominator is persons, care should be taken to properly define and estimate
the unit of analysis up to person level. For example, the mean expense for persons with dental
visits is estimated as,
(Sum of Wj Zj) / (Sum of Wj)
across all unique
persons i on this file, (5)
where
Wj is the sampling weight (WTDPER96) for person i
and
Zj= Sum of DVXP96Xj across all dental visits for person i
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4.4.2 Person-Based Ratio Estimates Relative to the Entire Population
If the ratio 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. In this case
MEPS File HC-011, which has data for all sampled persons, must be used to estimate the total
number of persons (i.e. those with use and those without use). For example, to estimate the
proportion of civilian non-institutionalized population of the U.S. with at least one dental visit
with at least one dental visit due to accident or injury, the numerator would be derived from data
on this event file, and the denominator would be derived from data on the MEPS HC-011 person-level file. That is,
(Sum of Wj Zj) / (Sum of Wj) across
all unique persons i on the MEPS HC-011 file, (6)
where Wj is the sampling weight (WTDPER96) for person i and
Zj = 1 if DENTINJj = 1 for any event of person i on the event-level file
= 0 otherwise for all remaining persons on the MEPS HC-011 file.
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4.5 Sampling Weights for Merging Previous Releases of MEPS Household Data
with the Current Data File
There have been several previous releases of MEPS Household Survey public use data. Unless a
variable name common to several tapes is provided, the sampling weights contained on these data
files are file-specific. The file-specific weights reflect minor adjustments to eligibility and
response indicators due to birth, death, or institutionalization among respondents.
In general for estimates from a MEPS data file that do not require merging with variables from
other MEPS data files, the sampling weight(s) provided on that data file are the appropriate
weight(s). When merging a MEPS Household data file to another, the major analytical variable
(i.e. the dependent variable) determines the correct sampling weight to use.
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4.6 Variance Estimation
To obtain estimates of variability (such as the standard error of sample estimates or corresponding
confidence intervals) for estimates based on MEPS survey data, one needs to take into account the
complex sample design of MEPS. Various approaches can be used to develop such estimates of
variance including use of the Taylor series or various replication methodologies. Replicate
weights have not been developed for the MEPS 1996 data. Variables needed to implement a
Taylor series estimation approach are described in the paragraph below.
Using a Taylor Series approach, variance estimation strata and the variance estimation PSUs
within these strata must be specified. The corresponding variables on the MEPS full year
utilization database are VARSTR96 and VARPSU96, respectively. Specifying a "with
replacement" design in a computer software package such as SUDAAN (Shah, 1996) should
provide 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), there are over 100 degrees of freedom associated with the corresponding estimates
of variance. The following illustrates these concepts using two examples from section 4.2.
Example 2 from Section 4.2
Using a Taylor Series approach, specifying VARSTR96 and VARPSU96 as the variance
estimation strata and PSUs (within these strata) respectively and specifying a "with replacement"
design in a computer software package SUDAAN will yield the estimate of standard error of
$2.91 for the estimated mean of out-of-pocket payment.
Example 3 from Section 4.2
Using a Taylor Series approach, specifying VARSTR96 and VARPSU96 as the variance
estimation strata and PSUs (within these strata) respectively and specifying a "with replacement"
design in a computer software package SUDAAN will yield the estimate of standard error of
0.0084 for the weighted mean proportion of total expenditures paid by private insurance.
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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. This section provides
instructions for linking the dental file with other MEPS public use files, including: the conditions
file, the prescribed medicines file, and a person-level file.
5.1 Linking a Person-Level File to the Dental File
Data from the dental event file can be used alone or in conjunction with other files. Merging
characteristics of interest from other MEPS files (e.g., HC-008: 1996 Full Year Population
Characteristics File or HC-010A:1996 Prescribed Medicines File) expands the scope of potential
estimates. For example, to estimate the total number of dental events of persons with specific
characteristics such as age, race, and sex, population characteristics from a person-level file need
to be merged onto the dental file. This procedure is shown below. The Appendix File (HC:010I)
provides additional detail on how to merge MEPS data files.
1. Create data set PERSX by sorting the person level file, HC008, by the person
identifier, DUPERSID. Keep only variables to be merged on to the dental file and
DUPERSID.
2. Create data set DENT by sorting the dental events file by person identifier,
DUPERSID.
3. Create final data set NEWDENT by merging these two files by DUPERSID,
keeping only records on the dental file.
The following is an example of SAS code which completes these steps:
PROC SORT DATA=HC008(KEEP=DUPERSID AGE SEX EDUC)
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;
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5.2 Linking the Dental File (HC-010B) to the Medical Conditions File (HC-006)
and/or the Prescribed Medicines File (HC-010A)
Due to survey design issues, there are limitations/caveats that an analyst must keep in mind when
linking the different files. Those limitations/caveats are listed below. For detailed linking
examples, including SAS code, analysts should refer to the Appendix File.
5.2.1 Limitations/Caveats of RXLK (the Prescribed Medicine Link File)
The RXLK file provides a link from the MEPS event files to the prescribed medicine records on
HC-010A. When using RXLK, 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 analyst to
determine how the prescribed medicine expenditures should be allocated among those dental
and/or medical events.
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5.2.2 Limitations/Caveats of CLNK (the Medical Conditions Link File)
The CLNK provides a link from MEPS event files to the Medical Conditions File (HC-006).
When using the CLNK, analysts should keep in mind that (1) conditions are self-reported and (2)
there may be multiple conditions associated with a dental visit. Users should also note that not all
dental visits link to the condition file.
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6.0 Programming Information
The following are the technical specifications for the HC-010B data files, which are provided in
ASCII and SAS formats.
ASCII versions:
File Name: HC10BF1.DAT
Number of Observations: 22,165
Number of Variables: 97
Record Length: 339
Record Format: fixed
Record Identifier and Sort Key: EVNTIDX
File Name: HC10BF2.DAT
Number of Observations: 22,165
Number of Variables: 20
Record Length: 131
Record Format: fixed
Record Identifier and Sort Key: EVNTIDX
SAS Transport versions:
File Name: HC10BF1.SSP
SAS Name: HC10BF1
Number of Observations: 22,165
Number of Variables: 97
Record Identifier and Sort Key: EVNTIDX
File Name: HC10BF2.SSP
SAS Name: HC10BF2
Number of Observations: 22,165
Number of Variables: 20
Record Identifier and Sort Key: EVNTIDX
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References
Cohen, S.B. (1998). Sample Design of the 1996 Medical Expenditure Panel Survey Medical
Provider Component. Journal of Economic and Social Measurement. Vol 24, 25-53.
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.
Cox, B.G. and Cohen, S.B. (1985). Chapter 8: Imputation Procedures to Compensate for Missing
Responses to Data Items. In Methodological Issues for Health Care Surveys. Marcel Dekker,
New York.
Health Care Financing Administration (1980). International Classification of Diseases, 9th Revision, Clinical Modification (ICD-CM). Vol. 1. (DHHS Pub. No. (PHS) 80-1260). DHHS:
U.S. Public Health Services.
Monheit, A.C., Wilson, R., and Arnett, III, R.H. (Editors). Informing American Health Care
Policy. (1999). 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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Attachment 1
Definitions
Dwelling Units, Reporting Units, Families, and Persons The definitions of Dwelling Units
(DUs) and Group Quarters in the MEPS Household Survey are generally consistent with the
definitions employed for the National Health Interview Survey. The dwelling unit ID (DUID) is a
five-digit random ID number assigned after the case was sampled for MEPS. The person number
(PID) uniquely identifies all persons within the dwelling unit. The variable DUPERSID is the
combination of the variables DUID and PID.
A Reporting Unit (RU) is a person or group of persons in the sampled dwelling unit who are
related by blood, marriage, adoption or other family association, and who are to be interviewed as
a group in MEPS. Thus, the RU serves chiefly as a family-based "survey operations" unit rather
than an analytic unit. Regardless of the legal status of their association, two persons living
together as a "family" unit were treated as a single reporting unit if they chose to be so identified.
Unmarried college students under 24 years of age who usually live in the sampled household, but
were living away from home and going to school at the time of the Round 1 MEPS interview,
were treated as a Reporting Unit separate from that of their parents for the purpose of data
collection. These variables can be found on MEPS person level files.
In-Scope A person was classified as in-scope (INSCOPE) if he or she was a member of the U.S.
civilian, non-institutionalized population at some time during the Round 1 interview. This
variable can be found on MEPS person level files.
Keyness The term "keyness" is related to an individual's chance of being included in MEPS. A
person is key if that person is appropriately linked to the set of 1995 NHIS sampled households
designated for inclusion in MEPS. Specifically, a key person either was a member of an NHIS
household at the time of the NHIS interview, or became a member of such a household after being
out-of-scope prior to joining that household (examples of the latter situation include newborns and
persons returning from military service, an institution, or living outside the United States).
A non-key person is one whose chance of selection for the NHIS (and MEPS) was associated with
a household eligible but not sampled for the NHIS, who happened to have become a member of a
MEPS reporting unit by the time of the MEPS Round 1 interview. MEPS data, (e.g., utilization
and income) were collected for the period of time a non-key person was part of the sampled unit
to permit family level analyses. However, non-key persons who leave a sample household would
not be recontacted for subsequent interviews. Non-key individuals are not part of the target
sample used to obtain person level national estimates.
It should be pointed out that a person may be key even though not part of the civilian, non-institutionalized portion of the U.S population. For example, a person in the military may be
living with his or her civilian spouse and children in a household sampled for the 1995 NHIS.
The person in the military would be considered a key person for MEPS. However, such a person
would not receive a person-level sample weight so long as he or she was in the military. All key
persons who participated in the first round of the 1996 MEPS received a person level sample
weight except those who were in the military. The variable indicating "keyness" is KEYNESS.
This variable can be found on MEPS person level files.
Eligibility The eligibility of a person for MEPS pertains to whether or not data were to be
collected for that person. All key, in-scope persons of a sampled RU were eligible for data
collection. The only non-key persons eligible for data collection were those who happened to be
living in the same RU as one or more key persons, and their eligibility continued only for the time
that they were living with a key person. The only out-of-scope persons eligible for data collection
were those who were living with key in-scope persons, again only for the time they were living
with a key person. Only military persons meet this description. A person was considered eligible
if they were eligible at any time during Round 1. The variable indicating "eligibility" is
ELIGRND1, where 1 is coded for persons eligible for data collection for at least a portion of the
Round 1 reference period, and 2 is coded for persons not eligible for data collection at any time
during the first round reference period. This variable can be found on MEPS person level files.
Pre-imputed - This means that only a series of logical edits were applied to the HC data to correct
for several problems including outliers, copayments or charges reported as total payments, and
reimbursed amounts counted as out of pocket payments. Missing data remains.
Unimputed - This means that only a series of logical edits were applied to the MPC data to
correct for several problems including outliers, copayments or charges reported as total payments,
and reimbursed amounts counted as out of pocket payments. This data was used as the imputation
source to account for missing HC data.
Imputation -Imputation is more often used for item missing data adjustment through the use of
predictive models for the missing data, based on data available on the same (or similar) cases.
Hot-deck imputation creates a data set with complete data for all nonrespondent cases, often by
substituting the data from a respondent case that resembles the nonrespondent on certain known
variables.
Household Reported Drug (mention) A household reported drug is a unique prescribed
medication reported by a household respondent. A household reported drug is checked on the
prescribed medicines roster as being created during that round or selected from a roster from a
previous round. Associated with each household reported drug mention in a given round may be
multiple acquisitions of the medication during that round. Due to the editing and imputation
procedures for these data, cases with multiple purchases of the same medication may be assigned
more than one variant of the medication based on its form, strength, manufacturer, or package size
(i.e., its National Drug Code). Thus, what originally was reported as a single medication in the
Household Component may appear as multiple unique medications on the prescribed medicines
event file.
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D. Codebooks (link to separate file)
Return To The Table Of Contents
E. Variable-Source Crosswalk
MEPS HC010B: 1996 DENTAL VISITS
File 1:
Survey Administration Variables
Variable |
Description |
Source |
DUID |
Dwelling unit ID |
Assigned in sampling |
PID |
Person number |
Assigned in sampling |
DUPERSID |
Sample person ID (DUID + PID) |
Assigned in sampling |
EVENTIDX |
Event ID |
Assigned in Sampling |
EVENTRN |
Event round number |
CAPI derived |
FFID11X |
Flat fee ID |
Constructed |
Return To The Table Of Contents
Dental Events Variables
Variable |
Description |
Source |
DVDATEYR |
Event start date year |
CAPI derived |
DVDATEMM |
Event start date month |
CAPI derived |
DVDATEDD |
Event start 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 |
EXAMINEX |
Edited EXAMINE |
DN04 (Edited) |
EXAMINE |
General exam or consultation |
DN04 |
CLENTETX |
Edited CLENTETH |
DN04 (Edited) |
CLENTETH |
Cleaning, prophylaxis, or polishing |
DN04 |
JUSTXRAY |
X-rays, radiographs or bitewings |
DN04 |
FLUORIDE |
Fluoride treatment |
DN04 |
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 |
Perdtl scaling/root planing or gum |
DN04 |
RECLVISX |
Edited RECLIVIS |
DN04 (Edited) |
RECLIVIS |
Periodontal recall visit |
DN04 |
EXTRACT |
Extraction, tooth pulled |
DN04 |
IMPLANT |
Implants |
DN04 |
ABSCESS |
Abscess or infection treatment |
DN04 |
ORALSURG |
Oral surgery |
DN04 |
BRIDGESX |
Edited BRIDGES |
DN04 (Edited) |
BRIDGES |
Bridges |
DN04 |
DENTUREX |
Edited DENTURES |
DN04 (Edited) |
DENTURES |
Dentures or partial dentures |
DN04 |
REPAIR |
Repair bridges/dentures or relining |
DN04 |
ORTHDONX |
Edited ORTHDONT |
DN04 (Edited) |
ORTHDONT |
Orthodontia, braces or retainers |
DN04 |
WHITEN |
Bonding, whitening or bleaching |
DN04 |
TMDTMJ |
Treatment for TMD or TMJ |
DN04 |
DENTPROX |
Edited DENTPOC |
DN04OV |
DENTPROC |
Other dental procedures |
DN04OV |
DENTOTHX |
Edited DENTOTHR |
DN04 (Edited) |
DENTOTHR |
Other specify dental procedures |
DN04 |
DENTINJ |
Visit because of accident or injury |
DN01 |
DENTMED |
Receive medicine including free sample |
DN05 |
DVICD1X |
3 digit ICD-9 condition code |
DN02 (Edited) |
DVICD2X |
3 digit ICD-9 condition code |
DN02 (Edited) |
DVPRO1X |
2 digit ICD-9 procedure code |
DN02 (Edited) |
DVPRO2X |
2 digit ICD-9 procedure code |
DN02 (Edited) |
DVCCC1X |
Modified Clinical Classification Code |
Constructed/Edited |
DVCCC2X |
Modified Clinical Classification Code |
Constructed/Edited |
NUMCOND |
Total number condition records linked to this event. |
Constructed |
Return To The Table Of Contents
Expenditure Variables
Variable |
Description |
Source |
FFDVTYPX |
Edited flat fee group (stem or leaf) |
Constructed |
FFDV96 |
Edited total # dental visits in FF in 1996 |
FF02 |
FFTOT96 |
Total # visits (pure/mixed) in flat fee for 1996 |
FF02 |
FFBEF96 |
Number dental visits in flat fee before 1996 |
FF05 |
FFDV97 |
Number dental visits in flat fee: Rd3, 1997 |
FF10 |
FFTOT97 |
Number visits (pure/mixed)in flat fee: Rd3,1997 |
FF10 |
DVSF96X |
Amount paid, family ( Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVMR96X |
Amount paid, Medicare (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVMD96X |
Amount paid, Medicaid (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVPV96X |
Amount paid, private insurance (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVVA96X |
Amount paid, Veterans (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVCH96X |
Amount paid, CHAMPUS/CHAMPVA (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVOF96X |
Amount paid, other federal (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVSL96X |
Amount paid, state and local govt (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVWC96X |
Amount paid, workers comp (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVOR96X |
Amount paid, other private (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVOU96X |
Amount paid, other public (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVOT96X |
Amount paid, other insurance (Imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVXP96X |
Sum of DVSF96X DVOT96X (Imputed) |
Constructed |
DVTC96X |
Household reported total charge ( Imputed) |
CP09A,CP09OV (Edited) |
IMPDVSLF |
Imputation flag for DVSF96X |
Constructed |
IMPDVMCR |
Imputation flag for DVMR96X |
Constructed |
IMPDVMCD |
Imputation flag for DVMD96X |
Constructed |
IMPDVPRV |
Imputation flag for DVPV96X |
Constructed |
IMPDVVA |
Imputation flag for DVVA96X |
Constructed |
IMPDVCHM |
Imputation flag for DVCH96X |
Constructed |
IMPDVOFD |
Imputation flag for DVOF96X |
Constructed |
IMPDVSTL |
Imputation flag for DVSL96X |
Constructed |
IMPDVWCP |
Imputation flag for DVWC96X |
Constructed |
IMPDVOPR |
Imputation flag for DVOR96X |
Constructed |
IMPDVOPU |
Imputation flag for DVOU96X |
Constructed |
IMPDVOSR |
Imputation flag for DVOT96X |
Constructed |
IMPDVCHG |
Imputation flag for DVTC96X |
Constructed |
Return To The Table Of Contents
Weights
Variable |
Description |
Source |
WTDPER96 |
Poverty/mortality adjusted person weight, 1996 |
Constructed |
VARPSU96 |
Variance estimation PSU,1996 |
Constructed |
VARSTR96 |
Variance estimation stratum, 1996 |
Constructed |
Return To The Table Of Contents
File 2:
Survey Administration Variables
Variable |
Description |
Source |
DUID |
Dwelling unit ID |
Assigned in sampling |
PID |
Person number |
Assigned in sampling |
DUPERSID |
Sample person ID (DUID + PID) |
Assigned in sampling |
EVNTIDX |
Event ID |
Assigned in Sampling |
HHSFFIDX |
Household reported flat fee ID |
Constructed |
Return To The Table Of Contents
Pre-imputed Expenditure Variables
Variable |
Description |
Source |
DVSF96H |
Household reported amt. paid, family ( Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVMR96H |
Household reported amt. paid, Medicare (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVMD96H |
Household reported amt. paid, Medicaid (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVPV96H |
Household reported amt. paid, private insurance (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVVA96H |
Household reported amt. paid, Veterans (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVCH96H |
Household reported amt. paid, CHAMPUS/CHAMPVA (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVOF96H |
Household reported amt. paid, other federal (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVSL96H |
Household reported amt paid, state and local govt (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVWC96H |
Household reported amt paid, workers comp (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVOT96H |
Household reported amt paid, other insurance (Pre-imputed) |
CP07,CP09A, CP11-CP34OV2 (Edited) |
DVTC96H |
Household reported total charge ( Pre-imputed) |
CP09A,CP09OV (Edited) |
Return To The Table Of Contents
Weights
Variable |
Description |
Source |
WTDPER96 |
Poverty/mortality adjusted person weight, 1996 |
Constructed |
VARPSU96 |
Variance estimation PSU,1996 |
Constructed |
VARSTR96 |
Variance estimation stratum, 1996 |
Constructed |
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