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MEPS Home Medical Expenditure Panel Survey
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MEPS HC-0016B: 1997 Dental Visits
June 2001
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 (EVNTIDX, FFEEIDX, 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 (EXAMINE - DENTMED)
2.5.2.4 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
2.5.3.3 Flat Fee Type (FFDVTYPE)
2.5.3.4 Counts of Flat Fee Events that Cross Years (FFBEF97 ­ FFTOT98)
2.5.3.5 Caveats of Flat Fee Groups
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
2.5.4.8 Dental Expenditures (DVFS97X- DVTC97X)
2.5.4.9 Rounding
2.5.4.10 Imputation Flags
2.6 File 2 Contents: Pre-imputed Expenditure Variables
3.0 Sample Weights and Variance Estimation Variables (WTDPER97-VARPSU97)
3.1 Overview
3.2 Details on Person Weights Construction
3.2.1 MEPS Panel 1 Weight
3.2.2 MEPS Panel 2 Weight
3.2.3 The Final Weight for 1997
3.2.4 Coverage
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 to the Medical Conditions File and/or the Prescribed Medicines File
5.2.1 Limitations/Caveats of RXLK (the Prescribed Medicine Link File)
5.2.2 Limitations/Caveats of CLNK (the Medical Conditions Link File)
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:

  1. No one is to use the data in this data set in any way except for statistical reporting and analysis.
  2. 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.
  3. 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 an 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 1997 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 1997. This file consists of MEPS survey data obtained in the 1997 portion of Round 3 and Rounds 4 and 5 for Panel 1, as well as Rounds 1,2 and the 1997 portion of Round 3 for Panel 2 (i.e., the rounds for the MEPS panels covering calendar year 1997). 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 will be provided on a public use file 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 codebooks. It contains the following sections:

Data File Information

Sample Weights and Variance Estimation Variables

Merging MEPS Data Files

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 31,194 dental event records. Of the 31,194, dental event records, 30,558 are associated with persons having a positive person-level weight (WTDPER97). 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 1997. Dental visits known to have occurred after December 31, 1997 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 1997 portion of round 3, and rounds 4 and 5 for Panel 1, as well as rounds 1, 2, and the 1997 portion of round 3 for Panel 2 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 1997 eligibility (i.e., persons with a positive 1997 full-year person-level sampling weight (WTDPER97 > 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 1997 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 1997 eligibility, and at least one family member had a positive 1997 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 1997 full-year family-level weight).

Please refer to Attachment 1 for definitions of key, non-key, in-scope 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; 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 consists of 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 1997 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 1997 Prescribed Medicine File. Please see section 5.0 for details on how to link MEPS data files.

Panel 1 cases (PANEL97 = 1 on 1997 person level file) can also be linked back to the 96 MEPS HC public use data files. However, the user should be aware that at this time no weight is being provided to facilitate 2 year analysis of panel 1 data.

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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

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 - 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; (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.

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 (97). The seventh character indicates whether or not the variable was edited/imputed (ends with 'X') or reported by the household (ends in 'H').

For example: DVSF97X is the edited/imputed amount paid by self or family for 1997 dental expenditures.

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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 attachment 1.

2.5.1.2 Record Identifiers (EVNTIDX, FFEEIDX, EVENTRN)

EVNTIDX 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. For details on linking see Section 5.0.

FFEEIDX 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 FFEEIDX. FFEEIDX identifies a flat fee payment situation that was identified using information from the Household Component. Please note that FFEEIDX 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. Please note: Rounds 3, 4, and 5 are associated with MEPS survey data collected from Panel 1. Likewise, Rounds 1, 2, and 3 are associated with data collected from Panel 2.

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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, DVDATEMM, DVDATEYR, respectively). These variables have not been edited or imputed.

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 (EXAMINE - DENTMED)

Respondents were asked about the types of services or treatments they received during the visit (EXAMINE - 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 Record Count Variable (NUMCOND)

The variable NUMCOND indicates the total number of records that can be linked from the Medical Conditions file to each dental event.

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 services that are covered under the same flat fee payment situation. The flat fee groups represented on this file, includes flat fee groups where at least one of the health care events, as reported by the HC respondent, occurred during 1997. By definition a flat fee group can span multiple years and a single person can have multiple flat fee groups.

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 FFEEIDX can be used to identify all events, that are part of the same flat fee group. To identify such events, FFEEIDX should be used to link events from all 1997 MEPS event files (excluding prescribed medicines). 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).

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2.5.3.3 Flat Fee Type (FFDVTYPE)

FFDVTYPE indicates whether the 1997 dental event is the "stem" or "leaf" of a flat fee group. A stem (records with FFDVTYPE = 1) is the initial medical service (event) which is followed by other medical events that are covered under the same flat fee payment. The leaves of the flat fee group (records with FFDVTYPE = 2) are those medical events that are tied back to the initial medical event (the stem) in the flat fee group.

2.5.3.4 Counts of Flat Fee Events that Cross Years (FFBEF97 ­ FFTOT98)

As described above, a flat fee payment situation covers multiple events and the multiple events could span multiple years. For situations where a 1997 dental visit is part of a group of events, and some of the events occurred before or after 1997, counts of the known events are provided on the dental record. Indicator variables are provided if some of the events occurred before or after 1997. These variables are:

FFBEF97 -- total number of pre-1997 events in the same flat fee group as the 1997 dental event. This count would not include 1997 dental events.

FFTOT98 -- indicates whether or not there are 1998 medical events in the same flat fee group as the 1997 dental event record.

2.5.3.5 Caveats of Flat Fee Groups

The user should note that flat fee payment situations are common with respect to dental events. There are 5,955 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 1997 but the remaining visits that were part of this flat fee group occurred in 1998. In this case, the 1997 flat fee group represented on this file would consist of one event (the stem). The 1998 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 1996 but subsequent visits occurred during 1997. In this case, the initial visit would not be represented on the file. This 1997 flat fee group would then only consist of one or more leaf records and no stem.

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2.5.4 Expenditure Data

2.5.4.1 Definition of Expenditures

Expenditures on files 1 and 2 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 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, 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 see 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 MPC. 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.

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 correct for missing non-respondent data, while preserving 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.

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 1997, all of the events that occurred in 1997 will have zero payments. Conversely, if the first event in the flat fee group occurred at the end of 1997, the total expenditure for the entire flat fee group will be on that event, regardless of the number of events it covered after 1997.

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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2.5.4.8 Dental Expenditures (DVFS97X- DVTC97X)

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. DVFS97X - DVOT97X are the 12 sources of payment, DVTC97X is the total charge, and DVXP97X 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.

2.5.4.9 Rounding

Expenditure variables on File 1 have been rounded to the nearest penny. Person level expenditure information to be released 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 1997 Appendix File for details on such rounding differences.

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2.5.4.10 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. In cases where an amount is 0 and the imputation flag is 1, the 0 payment is because either it is imputed to be zero or its potential source is imputed as not paying for the service. Therefore the corresponding amount is set to zero.

2.6 File 2 Contents: Pre-imputed Expenditure Variables

Pre-imputed expenditure data are provided on file 2. 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 on File 2 is the variable HHSFFID, 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 should 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. Uncollected liability was not used in imputation.

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3.0 Sample Weights and Variance Estimation Variables (WTDPER97-VARPSU97)

3.1 Overview

There is a single full year person-level weight (WTDPER97) 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 1997. 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 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.

3.2 Details on Person Weights Construction

The person-level weight WTDPER97 was developed in three stages. A person level weight for panel 2 was created, including both an adjustment for nonresponse over time and poststratification, controlling to Current Population Survey (CPS) population estimates based on five variables. Variables used in the establishment of person-level poststratification control figures included: census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and age. Then a person level weight for Panel 1 was created, again including an adjustment for nonresponse over time and poststratification, again controlling to CPS population estimates based on the same five variables. When poverty status information derived from income variables became available, a 1997 composite weight was formed from the panel 1 and panel 2 weights by multiplying the Panel weights by .5. Then a final poststratification was done on this composite weight variable, including 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) as well as the original five poststratification variables in the establishment of control totals.

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3.2.1 MEPS Panel 1 Weight

The person level weight for MEPS Panel 1 was developed using the 1996 full year weight for an individual as a "base" weight for survey participants present in 1996. For key, inscope respondents who joined an RU some time in 1997 after being out-of-scope in 1996, the 1996 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 poststratification to population control figures for December, 1997. These control figures were derived by scaling back the population totals obtained from the March 1998 CPS to reflect the December, 1997 CPS estimated population distribution across age and sex categories as of December, 1997. Variables used in the establishment of person level poststratification control figures included: 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, noninstitutionalized population on December 31, 1997 is 267,704,802. Key, responding persons not inscope on December 31, 1997 but inscope earlier in the year retained, as their final Panel 1 weight, the weight after the nonresponse adjustment.

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3.2.2 MEPS Panel 2 Weight

The person level weight for MEPS Panel 2 was developed using the MEPS Round 1 person-level weight as a "base" weight. For key, inscope 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 1997 portion of Round 3 as well as poststratification to the same population control figures for December 1997 used for the MEPS Panel 1 weights. The same five variables employed for Panel 1 poststratification (census region, MSA status, race/ethnicity, sex, and age) were used for Panel 2 poststratification. Similarly, for Panel 2, key, responding persons not inscope on December 31, 1997 but inscope earlier in the year retained, as their final Panel 2 weight, the weight after the nonresponse adjustment.

Note that the MEPS round 1 weights (for both panels with one exception as noted below) 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; the probability of selection of dwelling units associated with the oversampling of five population domains of analytic interest (for Panel 2 only); 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 1997 CPS data base. The five oversampled domains for Panel 2 were households with: persons with functional impairments; children with limitations in activity; individuals 18-64 expected to incur high medical expenditures based on a statistical model; persons with family incomes expected to be below 200 percent of poverty based on a statistical model; and adults with other impairments.

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3.2.3 The Final Weight for 1997

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, noninstitutionalized population for December 31, 1997 is 267,704,802 (WTDPER97>0 and INSC1231=1). The inclusion of key, inscope persons who were not inscope on December 31, 1997 brings the estimated total number of persons represented by the MEPS respondents over the course of the year up to 271,278,585 (WTDPER97>0). The weighting process included poststratification to population totals obtained from the 1996 MEPS Nursing Home Component for the number of individuals admitted to nursing homes. For the 1996 full year file an additional poststratification was done to population totals obtained from the 1996 Medicare Current Beneficiary Survey (MCBS) for the number of deaths among Medicare beneficiaries experienced in the 1996 MEPS. However, in 1997 the difference between the MEPS and MCBS estimates was not statistically significant, and no adjustment was made.

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3.2.4 Coverage

The target population for MEPS in this file is the 1997 U.S. civilian, noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 1995 (Panel 1) and 1996 (Panel 2). New households created after the NHIS interviews for the respective Panels and consisting exclusively of persons who entered the target population after 1995 (Panel 1) or after 1996 (Panel 2) are not covered by MEPS. These would include families consisting solely of: immigrants; persons leaving the military; U.S. citizens returning from residence in another country; and persons leaving institutions. It should be noted that this set of uncovered persons constitutes only a tiny proportion of the MEPS target population.

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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 1997.

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 2.5.4.2.

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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 (WTDPER97) 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 1997 is estimated as the sum of the weight (WTDPER97) across all dental visit records. That is,

Sum of Wj = 286,891,834                                   (1)

Example 2:

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 mean of amount paid by self/family. That is,

X bar = (Sum of WjXj) / (Sum of Wj) = $98.57,                                   (2)

where Sum of Wj = 230,761,058 and

Xj = DVSF97Xj for all records with DVXP97Xj>0.

This gives $98.57 as the estimated mean amount of out-of-pocket payment of expenditures associated with dental visits and 230,761,058 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 1997.

Example 3:

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 expenditures paid by private insurance at the dental visit level. That is,

Y bar = (Sum of WjYj) / (Sum of Wj) = 0.4665,                                   (3)

where Sum of Wj = 230,761,058

and Yj = DVPV97Xj/DVXP97Xj for all records with DVXP97Xj>0.

This gives 0.4665 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 1997.

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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-020: 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 1997 because of accident or injury, this event file must be used. This would be estimated as

Sum of WiXi

across all unique persons i on this file                                   (4)

where Wi is the sampling weight (WTDPER97) for person i and

Xi = 1 if DENTINJ = 1 for any visit of person i.

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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 WiZi) / (Sum of Wi) across all unique persons i on this file,                                   (5)

where Wi is the sampling weight (WTDPER97) for person i and

Zi = Sum of DVXP97Xj 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-020, 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 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-020 person-level file. That is,

(Sum of WiZi) / (Sum of Wi) across all unique persons i on the MEPS HC-020  file,              (6)

where Wi is the sampling weight (WTDPER97) for person i and

Zi = 1 if DENTINJj = 1 for any event of person i on the event-level file and

Zi = 0 otherwise for all remaining persons on the MEPS HC-020 file.

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 1997 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 VARSTR97 and VARPSU97, 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 VARSTR97 and VARPSU97 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 $3.55 for the estimated mean of out-of-pocket payment.

Example 3 from Section 4.2

Using a Taylor Series approach, specifying VARSTR97 and VARPSU97 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 0.0075 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., 1997 Full Year Population Characteristics File or 1997 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 1997 Appendix File provides additional detail on how to merge MEPS data files.

1. Create data set PERSX by sorting the Full Year Population Characteristics File (file HCXXX), 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=HCXXX(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 to the Medical Conditions File and/or the Prescribed Medicines File

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 the 1997 Prescribed Medicine Event File. 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. 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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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 (IN-SCOPE) 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 a MEPS Panel 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.

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D. Codebooks (link to separate file)

E. Variable-Source Crosswalk

 MEPS HC-016B: 1997 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

EVNTIDX

Event ID

Assigned in Sampling

EVENTRN

Event round number

CAPI derived

FFEEIDX

Flat fee ID

Constructed

Return To 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

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

ORALSURX

Edited ORALSURG

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

NUMCOND

Total number condition records linked to this event.

Constructed

Return To Table Of Contents

Expenditure Variables

Variable

Description

Source

FFDVTYPE

Flat fee bundle

Constructed

FFBEF97

Total # of visits in flat fee before 1997

FF05

FFTOT98

Total # of visits in flat fee after 1997

FF02

DVSF97X

Amount paid, family ( Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVMR97X

Amount paid, Medicare (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVMD97X

Amount paid, Medicaid (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVPV97X

Amount paid, private insurance (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVVA97X

Amount paid, Veterans (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVCH97X

Amount paid, CHAMPUS/CHAMPVA (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVOF97X

Amount paid, other federal (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVSL97X

Amount paid, state and local gov’t (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVWC97X

Amount paid, worker’s comp (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVOR97X

Amount paid, other private (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVOU97X

Amount paid, other public (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVOT97X

Amount paid, other insurance (Imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVXP97X

Sum of DVSF97X – DVOT97X (Imputed)

Constructed

DVTC97X

Household reported total charge ( Imputed)

CP09A,CP09OV (Edited)

IMPDVSLF

Imputation flag for DVSF97X

Constructed

IMPDVMCR

Imputation flag for DVMR97X

Constructed

IMPDVMCD

Imputation flag for DVMD97X

Constructed

IMPDVPRV

Imputation flag for DVPV97X

Constructed

IMPDVVA

Imputation flag for DVVA97X

Constructed

IMPDVCHM

Imputation flag for DVCH97X

Constructed

IMPDVOFD

Imputation flag for DVOF97X

Constructed

IMPDVSTL

Imputation flag for DVSL97X

Constructed

IMPDVWCP

Imputation flag for DVWC97X

Constructed

IMPDVOPR

Imputation flag for DVOR97X

Constructed

IMPDVOPU

Imputation flag for DVOU97X

Constructed

IMPDVOTH

Imputation flag for DVOT97X

Constructed

IMPDVCHG

Imputation flag for DVTC97X

Constructed

Return To Table Of Contents

Weights

Variable

Description

Source

WTDPER97

Poverty/mortality adjusted person weight, 1997

Constructed

VARPSU97

Variance estimation PSU,1997

Constructed

VARSTR97

Variance estimation stratum, 1997

Constructed

Return To 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 Table Of Contents

Pre-imputed Expenditure Variables

Variable

Description Source

DVSF97H

Household reported amt. paid, family ( Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVMR97H

Household reported amt. paid, Medicare (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVMD97H

Household reported amt. paid, Medicaid (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVPV97H

Household reported amt. paid, private insurance (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVVA97H

Household reported amt. paid, Veterans (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVCH97H

Household reported amt. paid, CHAMPUS/CHAMPVA (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVOF97H

Household reported amt. paid, other federal (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVSL97H

Household reported amt paid, state and local gov’t (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVWC97H

Household reported amt paid, worker’s comp (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVOT97H

Household reported amt paid, other insurance (Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited)

DVTC97H

Household reported total charge ( Pre-imputed)

CP09A,CP09OV (Edited)

DVUC97H

Household reported amount paid, uncollected liability ( Pre-imputed)

CP07,CP09A, CP11-CP34OV2 (Edited

Return To Table Of Contents

Weights

Variable

Description

Source

WTDPER97

Poverty/mortality adjusted person weight, 1997

Constructed

VARPSU97

Variance estimation PSU,1997

Constructed

VARSTR97

Variance estimation stratum, 1997

Constructed

Return To Table Of Contents

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