MEPS HC-026B: 1998 Dental Visits

MEPS HC-026B: 1998 Dental Visits
October 2001
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406

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:

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.

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 three component surveys: the Household Component (HC), the Medical Provider Component (MPC), and the Insurance Component (IC). 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.

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 2 ½ -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 over sampling of Hispanics and blacks.

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:

Data are collected on medical and financial characteristics of medical and pharmacy events reported by HC respondents, including:

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.

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:

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.

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.

This documentation describes one in a series of public use event files from the 1998 Medical Expenditure Panel Survey (MEPS) Household Component (HC). 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. Data from the dental file can be used to make estimates of dental event utilization and expenditures for calendar year 1998. As illustrated below, this file consists of MEPS survey data obtained in the 1998 portion of Round 3 and Rounds 4 and 5 for Panel 2, as well as Rounds 1,2 and the 1998 portion of Round 3 for Panel 3 (i.e., the rounds for the MEPS panels covering calendar year 1998).

Each record on this event file represents a unique dental event; that is, a dental event reported by the household respondent. Counts of dental event utilization are based entirely on household reports. Dental events were not included in the Medical Provider Component (MPC); therefore, the household reports all expenditure and payment data on the dental file.

Data from this event file can be merged with other 1998 MEPS HC data files, for the purposes of appending person-level data such as demographic characteristics or health insurance coverage to each dental event record on the current file.

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 the MEPS 1998 full year Person Level Expenditure 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:

For more information on MEPS HC survey design, see S. Cohen, 1997; J. Cohen, 1997; and S. Cohen, 1996. A copy of the MEPS HC survey instrument used to collect the information on the dental file is available on the MEPS web site at the following address: <http://www.meps.ahrq.gov>.

The1998 dental 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 the pre-imputed expenditure data from the Household Component for all dental events on File 1. See Attachment 1 for definitions of imputed, and pre-imputed expenditure variables.

Both Files 1 and 2 of the dental public use data set contain 21,511 dental event records; of these records, 21,151 are associated with persons having a positive person-level weight (WTDPER98). 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 1998. Dental visits known to have occurred after December 31, 1998 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 1998 portion of round 3, and rounds 4 and 5 for Panel 2, as well as rounds 1, 2, and the 1998 portion of round 3 for Panel 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 1998 eligibility (i.e., persons with a positive 1998 full-year person-level sampling weight (WTDPER98 > 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 1998 eligibility, and belonged to a family (i.e., all persons with the same value for FAMID) in which all eligible family members responded for their entire period of 1998 eligibility, and at least one family member had a positive 1998 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 1998 full-year family-level weight (WTFAM98>0)).

Please refer to Attachment 1 for definitions of keyness, in-scope and eligibility.

Each dental event record on File 1 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 the dental public use data set is intended for data users/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 both Files 1 and 2 can be merged the MEPS 1998 Full Year Population Characteristics file 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 1998 Prescribed Medicine File. Please see section 5.0 for details on how to merge MEPS data files.

Panel 2 cases (PANEL98 = 2 on 1998 person level file) can also be linked back to the 97 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 2 data.

For each variable on the Dental Visits files, both weighted and unweighted frequencies are provided in codebooks. The codebook and data file sequence list variables in the following order:

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 the data users/analysts by following the skip patterns in the HC survey questionnaire (located on the MEPS web site: <http://www.meps.ahrq.gov/survey_comp/survey.jsp>).

The dental 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

In general, variable names reflect the content of the variable, with an 8 character limitation. All imputed/edited variables end with an "X."

Variables contained on Files 1 and 2 were derived from the HC survey questionnaire. The source of each variable is identified in Section D, the "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 as "capi derived" or "assigned in sampling;"
(2)	variables which come from one or more specific questions have those questionnaire sections and question numbers indicated in the "Source" column EV - Event Roster section FF - Flat Fee section CP - Charge Payment section;
(3)	variables constructed from multiple questions using complex algorithms are labeled "Constructed" in the "Source" column; and
(4)	variables which have been edited or imputed are so indicated.

Pre-imputed and imputed versions of the expenditure and sources of payment variables are provided on two 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.

All imputed variables on File 1 end with an "X" indicating they are fully edited and imputed.

The pre-imputed expenditure variables on File 2 end with an "H" indicating that the data source was the MEPS Household Component.

The total sum of payments variables, 12 sources of payment variables, and the total charge variables are named consistently in the following way:

RX - prescribed medicine In the case of the source of payment variables, the third and fourth characters indicate:

The fifth and sixth characters indicate the year (98). 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: DVSF98X is the edited/imputed amount paid by self or family for 1998 dental expenditures.

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 for the 1998 Full Year Population Characteristics file or to definitions listed in Attachment 1.

EVNTIDX uniquely identifies each dental event (i.e., each record on the dental file) and is the variable required to link dental events to data files containing details on conditions and/or prescribed medicines (MEPS 1998 Medical Condition File and MEPS 1998 Prescribed Medicines file; respectively). For details on linking see Section 5.0 or the Appendix File MEPS 1998.

FFEEIDX is a constructed variable which 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 would 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 2. Likewise, Rounds 1, 2, and 3 are associated with data collected from Panel 3.

File 1 contains variables describing dental events reported by household respondents in the Dental Section of the MEPS HC survey 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.

Respondents were asked about the type of provider seen during the dental visit, e.g. general dentist, dental hygienist, or orthodontist. More than one type of provider may have been identified on an event record.

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 File 1. DENTMED indicates whether or not the respondent received a prescription medication, including free samples, during the dental visit.

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 the dental file, includes flat fee groups where at least one of the health care events, as reported by the HC respondent, occurred during 1998. By definition, a flat fee group can span multiple years. Furthermore, a single person can have multiple flat fee groups.

There are four variables on the dental file that describe a flat fee payment situation and the number of medical events that are part of a flat fee group.

As noted earlier in the Section 2.5.1.2 "Record Identifiers," for a person, the variable FFEEIDX can be used to uniquely identify all events that are part of the same flat fee group. It can identify such events from all of the1998 MEPS event files (excluding the prescribed medicines file) because FFEEIDX is the same value on all of the MEPS event files. For the dental events that are not part of a flat fee payment situation, the flat fee variables described below are all set to –1 INAPPLICABLE.

FFDVTYPE indicates whether the 1998 dental event is the "stem" or "leaf" of a flat fee group. A stem (records with FFDVTYPE = 1) is the initial dental service (event) which is followed by other dental events that are covered under the same flat fee payment. The leaves of the flat fee group (records with FFDVTYPE = 2) are those dental events that are tied back to the initial medical event (the stem) in the flat fee group. These "leaf" records have their expenditure variables set to zero.

As described in Section 2.5.3.1, a flat fee payment situation covers multiple events and the multiple events could span multiple years. For situations where a 1998 dental visit is part of a group of events, and some of the events occurred before or after 1998, counts of the known events are provided on the dental record. Indicator variables are provided if some of the events occurred before or after 1998. These variables are:

FFBEF98 -- total number of pre-1998 events in the same flat fee group as the 1998 dental event. This count would not include 1998 dental events.

FFTOT99 -- indicates whether or not there are 1998 medical events in the same flat fee group as the 1998 dental event record.

Data users/analysts should note that flat fee payment situations are common on the dental file. There are 3,568 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 1998, but the remaining visits that were part of this flat fee group occurred in 1999. In this case, the 1998 flat fee group represented on this file would consist of one event (the stem). The 1999 "leaf" events that are part of this flat fee group are not represented on the file. Similarly, the household respondent may have reported a flat fee group where the initial visit began in 1997 but subsequent visits occurred during 1998. In this case, the initial visit would not be represented on the file. This 1998 flat fee group would then only consist of one or more leaf records and no stem.

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, data users/analysts should use caution when working with this data because a charge does not typically represent actual dollars exchanged for services or the resource costs of those services, nor are they directly comparable to the resource costs of those services, nor are they directly comparable to the expenditures defined in the 1987 NMES (for details on expenditure definitions see Monheit et al, 1999). AHRQ has developed factors to apply to the 1987 NMES expenditure data to facilitate longitudinal analysis. These factors can be assessed via CCFS data center. For more information see the data center section of the MEPS web site <http://www.meps.ahrq.gov>.

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 expenditure follows.

Logical edits were used to resolve internal inconsistencies and other problems in the HC survey-reported data. The edits were designed to preserve partial payment data from households and providers, and to identify actual and potential sources of payment for each household-reported event. In general, these edits accounted for outliers, copayments or charges reported as total payments, and reimbursed amounts that were reported as out of pocket payments. In addition, edits were implemented to correct for misclassifications between Medicare and Medicaid and between Medicare HMOs and private HMOs as payment sources. These edits produced a complete vector of expenditures for some events, and provided the starting point for imputing missing expenditures in the remaining events.

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.

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.

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 1998, all of the events that occurred in 1998 will have zero payments. Conversely, if the first event in the flat fee group occurred at the end of 1998, the total expenditure for the entire flat fee group will be on that event, regardless of the number of events it covered after 1998.

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.

In addition to total expenditures, variables are provided which itemize expenditures according to major source of payment categories. These categories are:

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.

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, data users/analysts should exercise caution when interpreting the expenditures associated with these two additional sources of payment. While these payments stem from apparent inconsistent responses to health insurance and source of payment questions in the survey, some of these inconsistencies may have logical explanations. For example, private insurance coverage in MEPS is defined as having a major medical plan covering hospital and physician services. If a MEPS sampled person did not have such coverage but had a single service type insurance plan (e.g. dental insurance) that paid for a particular episode of care, those payments may be classified as "other private". Some of the "other public" payments may stem from confusion between Medicaid and other state and local programs or may be from persons who were not enrolled in Medicaid, but were presumed eligible by a provider who ultimately received payments from the program.

Data users/analysts 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.

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. DVFS98X - DVOT98X are the 12 sources of payment, DVTC98X is the total charge, and DVXP98X 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.

Expenditure variables on File 1 have been rounded to the nearest penny. Person level expenditure information to be released on the MEPS 1998 Person Level Expenditure File will be rounded to the nearest dollar. It should be noted that using the MEPS event files to create person level totals will yield slightly different totals than those found on the person level expenditure file. These differences are due to rounding only. Moreover, in some instances, the number of persons having expenditures on the event files for a particular source of payment may differ from the number of persons with expenditures on the person level expenditure file for that source of payment. This difference is also an artifact of rounding only. Please see the 1998 Appendix File for details on such rounding differences.

If the data user/analyst desires to identify whether sources of payment and total charge have been imputed, simply compare the expenditure variable of interest from File 2 with the corresponding variable from File 1. An imputed value would be one having a missing value on File 2 while the value on File 1 would be zero or greater. In a small number of cases, an imputed value on File 1 will have a corresponding value of zero rather than missing on File 2.

As explained in section 2.5.4.5 "Sources of Payment," there are 10 sources of payment variables in the pre-imputed expenditure data on File 2, 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 sources of payment categories were constructed to resolve apparent inconsistencies between individuals’ reported insurance coverage and their sources of payment for specific events, such as where the insurance variables indicated uninsured all year but the person reported private insurance as a payor source.

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 HMOs and private HMOs 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 data user/analysts are interested in performing their own expenditure imputation.

The data user/analyst 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 sources 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.

There is a single full year person-level weight (WTDPER98) assigned to each record for each key, in-scope person who responded to MEPS for the full period of time that he or she was in-scope during 1998. 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.

The final person-level weight WTDPER98 was developed in three stages. A person level weight for Panel 3 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 2 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 1998 composite weight was formed from the Panel 2 and Panel 3 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.

The person level weight for MEPS Panel 2 was developed using the 1997 full year weight for an individual as a "base" weight for survey participants present in 1997. For key, in-scope respondents who joined a RU some time in 1998 after being out of scope in 1997, the 1997 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 1998. These control figures were derived by scaling back the population totals obtained from the March 1998 CPS to reflect the December, 1998 CPS estimated population distribution across age and sex categories as of December, 1998. 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, 1998 is 270,114,457. Key, responding persons not in-scope on December 31, 1998 but in-scope earlier in the year retained, as their final Panel 2 weight, the weight after the nonresponse adjustment.

The person level weight for MEPS Panel 3 was developed using the MEPS Round 1 person-level weight as a ‘base" weight. For key, in-scope respondents who joined a 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 1998 portion of Round 3 as well as poststratification to the same population control figures for December 1998 used for the MEPS Panel 2 weights. The same five variables employed for Panel 2 poststratification (census region, MSA status, race/ethnicity, sex, and age) were used for Panel 3 poststratification. Similarly, for Panel 3, key, responding persons not in-scope on December 31, 1998 but in-scope earlier in the year retained, as their final Panel 3 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; 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 1998 CPS data base.

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, 1998 is 270,114,457 (WTDPER98>0 and INSC1231=1). The inclusion of key, in-scope persons who were not in-scope on December 31, 1998 brings the estimated total number of persons represented by the MEPS respondents over the course of the year up to 273,533,690 (WTDPER98>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 1998 full year file an additional poststratification was done to population totals obtained from the 1997 Medicare Current Beneficiary Survey (MCBS) for the number of deaths among Medicare beneficiaries experienced in the 1998 MEPS.

The target population for MEPS in this file is the 1998 U.S. civilian, noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 1997 (Panel 2) and 1998 (Panel 3). New households created after the NHIS interviews for the respective Panels and consisting exclusively of persons who entered the target population after 1997 (Panel 2) or after 1998 (Panel 3) 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 .

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 in 1998.

It is essential that the analyst examine all variables for the presence of negative values used to represent missing values. For continuous or discrete variables, where means or totals may be 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

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 (WTDPER98) contained on that record.

For example, the total number of dental visits, for the civilian non-institutionalized population of the U.S. in 1998 is estimated as the sum of the weight (WTDPER98) across all dental visit event records. That is,

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 (for those who had such expense greater than 0) should be calculated as the weighted mean of amount paid by self/family. That is,

This gives $106.04 as the estimated mean amount of out-of-pocket payment of expenditures associated with dental visits and 239,004,932 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 1998.

Another example would be to estimate the average proportion of total expenditures (where event expense is greater than 0) 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,

When calculating an estimate of the total number of persons with dental visits, users can use a person-level file 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 1998 because of accident or injury, this event file must be used. This would be estimated as

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

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 the 1998 person level file, 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 person-level file. That is

4.5 Sampling Weights for Merging Previous Releases of MEPS Household Data with this Event File

There have been several previous releases of MEPS Household Survey public use data. Unless a variable name common to several files 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.

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.

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 1998 data. Variables needed to implement a Taylor series estimation approach are provided in the file and 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 VARSTR98 and VARPSU98, respectively. Specifying a "with replacement" design in a computer software package such as SUDAAN (Shah et al, 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.

Using a Taylor Series approach, specifying VARSTR98 and VARPSU98 as the variance estimation strata and PSUs (within these strata) respectively and specifying a Awith replacement@ design in a computer software package SUDAAN will yield standard error estimate of $4.20 and 0.0100 for the estimated mean of out-of-pocket payment and the estimated mean proportion of total expenditures paid by private insurance respectively.

Data from the dental 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.

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., 1998 Full Year Population Characteristics File or 1998 Prescribed Medicines File) expands the scope of potential estimates. For example, to estimate the total number of dental events of persons with specific demographic characteristics (such as age, race, and sex), population characteristics from a person-level file need to be merged onto the dental file. This procedure is shown below. The 1998 Appendix File provides examples of how to merge MEPS other data files.

PROC SORT DATA=1998 Full Year Population Characteristics File (KEEP=DUPERSID AGE SEX EDUC)
OUT=PERSX;
BY DUPERSID;
RUN;

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 data users/analyst must keep in mind when linking the different files. Those limitations/caveats are listed below. For detailed linking examples, including SAS code, data users/analysts should refer to the 1998 Appendix File.

The RXLK file provides a link from the MEPS event files to the prescribed medicine records on the 1998 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.

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.

American Psychiatric Association. Task Force on DSM-IV. Diagnostic and Statistical Manual of Mental Disorders: DSM-IV. 4th ed. Washington, DC: American Psychiatric Association, 1994.

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.

Health Care Financing Administration (1980). International Classification of Diseases, 9^th 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.

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 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.

301 Moved Permanently

Connect With Us

Sign up for Email Updates

Agency for Healthcare Research and Quality