MEPS HC-0016C: 1997 Other Medical Expenses
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 Type of Other Medical Expenditure (OMTYPE - OMOTHOX)
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 (FFOMTYPE)
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 Other Medical Expenditure 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 Other Medical Expenditures (OMSF97X-OMTC97X)
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 Other Medical Expense Events
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with Other Medical Expense Events
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
References
Attachment 1
D. Codebooks (link to separate file)
E. Variable-Source Crosswalk
A. Data Use Agreement
Individual identifiers have been removed from the microdata contained in the files on this CD-ROM. Nevertheless, under sections 308 (d) and 903 (c) of the Public Health Service Act (42
U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the Agency for Healthcare Research and
Quality (AHRQ) and/or the National Center for Health Statistics (NCHS) may not be used for any
purpose other than for the purpose for which they were supplied; any effort to determine the
identity of any reported cases, is prohibited by law.
Therefore in accordance with the above referenced Federal statute, it is understood that:
- No one is to use the data in this data set in any way except for statistical reporting and
analysis.
- If the identity of any person or establishment should be discovered inadvertently, then
(a) no use will be made of this knowledge, (b) the Director, Office of Management,
AHRQ will be advised of this incident, (c) the information that would identify any
individual or establishment will be safeguarded or destroyed, as requested by
AHRQ,
and (d) no one else will be informed of the discovered identity.
- No one will attempt to link this data set with individually identifiable records from any
data sets other than the Medical Expenditure Panel Survey or the National Health
Interview Survey.
By using these data you signify your agreement to comply with the above-stated statutorily based
requirements, with the knowledge that deliberately making a false statement in any matter within
the jurisdiction of any department or agency of the Federal Government violates 18 U.S.C. 1001
and is punishable by a fine of up to $10,000 or up to 5 years in prison.
The Agency for Healthcare Research and Quality requests that users cite AHRQ and the Medical
Expenditure Panel Survey as the data source in any publications or research based upon these
data.
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B. Background
This documentation describes one in a series of public use files from the Medical Expenditure
Panel Survey (MEPS). The survey provides 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 followup 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 information on the
purchase of and expenditures for visual aids, medical equipment, supplies and other medical items
for a nationally representative sample of the civilian noninstitutionalized population of the United
States and can be used to make estimates of the utilization and expenditures associated with
medical items 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 of the MEPS HC (i.e., the rounds for the MEPS panels covering calender year
1997).
This file contains one record for each type of medical item reported as being purchased or
otherwise obtained by the household respondent during the specified reference period. It should be
noted that reference periods for reporting expenditures varies by type of medical item obtained.
Expenditure data for visual aides, insulin, and diabetic supplies and equipment are collected
during Rounds 3, 4, and 5 of Panel 1 and Rounds 1, 2 and 3 of Panel 2. Therefore, each round is a
reference period. Expenditure data for other medical items, which include orthopedic items,
hearing devices, medical equipment, disposable supplies, ambulance services, bathroom aides,
and home alterations are collected only in round 3 and 5 and the reference period is the entire
year.
Data from this event file can be merged with other MEPS HC data files for the purpose of
appending person characteristics such as demographic or health insurance coverage to each record
on the current file.
The purchase of medical equipment, supplies, and other medical items are based entirely on
household reports. They were not included in the MPC, therefore all expenditure and payment
data are reported by the household.
Data users should be aware of the limitations of this file. These limitations include the following:
a) A record can represent one or more purchases of an item or service during a reference
period. If a respondent reported spending $400 for glasses and/or contact lenses in round
2, it is unknown if the person purchased one or more pair of glasses and/or contact lenses
during that round. Similarly, if $800 was spent for ambulance services, it is not known if
the respondent used an ambulance once or more than once in 1997;
b) Although analysts can link conditions to the current file using DUPSERID, the specific
condition requiring the purchase of medical items or services, such as an ambulance,
cannot be identified. For example, if a person reported having asthma, a head injury, and a
heart attack, it is not known which condition(s) required the use of an ambulance.
c) Expenditure data for insulin and diabetic supplies are not included on this file, but are
included on the 1997 Prescribed Medicines File (HC-016A). All records for insulin and
diabetic supplies on this file have value of -1 for all expenditure (i.e., charge and payment)
variables.
This file can be used to construct summary variables of expenditures, sources of payment, and
related aspects of the purchase of medical items. Aggregate annual person-level information on
expenditures for other medical equipment 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 codebook, and programming information. 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 the type of medical
equipment obtained and imputed expenditure data. File 2 contains pre-imputed expenditure data
from the Household Component for medical equipment identified on File 1. Please see Section
2.5.4 for definitions of imputed and pre-imputed expenditure variables.
File 1 public use data set contains 8,365 other medical expenditure records; of these 8,139 are
associated with persons having a positive person-level weight (WTDPER97). These files include
records for all household survey respondents who resided in eligible responding households and
reported purchasing or otherwise obtaining at least one type of medical item, such as medical
equipment, glasses, hearing devices, etc., during calendar year 1997. Some household respondents
may have reported obtaining more than one type of medical item and, therefore have several
records on this file. Likewise, respondents who did not report obtaining a medical item in 1997
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 (WTFAM97
>0)).
Please refer to Attachment 1 for definitions of key, non-key, in-scope and eligible.
Each record on this file includes the following: type of medical item obtained; flat fee
information; imputed sources of payment; total payment and total charge for the medical item;
and a full-year person-level weight.
File 2 has fewer records (N=7,140) than File 1 (N=8,365) because medical expenditure records
associated with insulin and diabetic equipment/supplies (OMTYPEX=2 or 3) are not included on
File 2. This file is intended for analysts who want to perform their own imputations to handle
missing data. The 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 was 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. See Section 5.0 for details on how
to link MEPS data files. Although conditions can be linked to the current file, data users should
note that specific conditions requiring the purchase of medical items or services, such as
ambulance service, cannot be identified for records on this file.
Panel 1 cases (PANEL97=1 on 1997 Person Level File)
can also be linked back to the 1996 MEPS HC public use data file. 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 other medical expenses identifiers
Other survey administration variables
Type of other medical expenses
Imputed expenditure variables
Weight and variance estimation variables
File 2
Unique person identifiers
Unique other medical expenses 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".
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 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..
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2.4.2 Expenditure and Sources of Payment Variables
Pre-imputed and imputed versions of the expenditure and sources of payment variables are
provided on 2 separate files. Variables on Files 1 and 2 follow a standard naming convention and
are 8 characters in length. Please note that pre-imputed means that a series of logical edits have
been performed on the variable but missing data remain. The imputed versions incorporate the
same edits but also have undergone an imputation process to account for missing data.
The pre-imputed expenditure variables on File 2 end with an "H" indicating that the data source
was the MEPS Household Component. All imputed variables on File 1 end with an "X"indicating
they are fully edited and imputed.
The total sum of payments, 12 source 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').
Example: OMSF97X is the edited/imputed amount paid by self or family for 1997 other medical
equipment and 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).
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 crutches following outpatient foot surgery is
typically covered in a flat fee arrangement where the visit and the medical equipment are covered
under one flat fee dollar amount. These events are in different files but 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 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 other medical expenses was reported. For most types
of medical expenditures on this file data were collected only in round 5 for panel 1 and round 3
for panel 2 and each record represents a summary of expenditures for items purchased or
otherwise obtained for 1997. There are two exceptions:
a) Expenditure data for the purchase of glasses and/or contact lenses were collected in
rounds 3, 4, and 5 for panel 1 and rounds 1, 2, and 3 for panel 2. For vision items
purchased in rounds 3 or 5, it could not be determined if the purchases occurred in 1997 or
1998. Therefore, records with expenses reported in rounds 3 or 5 were only included if
more than half of the person's reference period for the round was in 1997.
b) Respondents were asked whether or not they obtained insulin or diabetic
supplies/equipment in rounds 3, 4, and 5 for panel 1 and rounds 1, 2, and 3 for panel 2.
Expenditures for insulin and diabetic supplies/equipment are not included on this file, but
are included on the 1997 Prescribed Medicines file (HC-016A). All records for insulin
and diabetic supplies on this file have a value of -1 for all expenditure (i.e., charge and
payment) variables.
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2.5.2 Type of Other Medical Expenditure (OMTYPE - OMOTHOX)
Other medical expenditures (OMTYPE) include glasses/contacts, insulin, diabetic supplies,
orthopedic items, hearing devices, medical equipment, disposable supplies, bathroom aids, and
homes alterations. Other medical expenditures identified in OMOTHOS ( type of expenditure -
other specify) have been edited to appropriate OMTYPE categories. The edited (OMTYPEX,
OMOTHOX) and unedited (OMTYPE, OMOTHOS) versions of both of these variables are
included on this file.
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2.5.3 Flat Fee Variables
2.5.3.1 Definition of Flat Fee Payments
A flat fee is the fixed dollar amount a person is charged for a package of services provided during
a defined period of time. 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 other medical expenditures that are not part of a flat fee payment
situation, the flat fee variables described below are all set to inapplicable (-1).
2.5.3.3 Flat Fee Type
(FFOMTYPE)
FFOMTYPE indicates whether the 1997 other medical expenditure is the "stem" or "leaf" of a flat
fee group. A stem (records with FFOMTYPE = 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 FFOMTYPE = 2) are those medical events that are tied back to the
initial medical event (the stem) in the flat fee group.
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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 the medical item was obtained in 1997 as 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 other medical expenditure 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 medical
item that was obtained in 1997. This count would not include the medical item obtained
in 1997.
FFTOT98 indicates whether or not there are 1998 medical events, including the
purchase of the medical item, in the same flat fee group as the medical item obtained in
1997.
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2.5.3.5 Caveats of Flat Fee Groups
Data users should note that flat fee payment situations are not common on this file compared with
other medical expenditures. There are only 24 records 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 the medical item. More specifically,
expenditures in MEPS are defined as the sum of payments for each medical item that was
obtained, 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. Measuring expenditures as the sum of payments incorporates
discounts in the MEPS expenditure estimates. 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 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 other
medical expenses 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 Other Medical Expenditure Imputation
Expenditures on other medical equipment and services 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.
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 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 might 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. Whenever possible missing data were imputed from
donors with the same other medical expenditure type, age (<45 and 45 and older), and region.
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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
Some respondents reported obtaining medical items where the payments were zero. This could
occur for several reasons including (1) item or service was free, (2) bad debt was incurred, or (3)
the item was covered under a flat fee arrangement beginning in an earlier year.
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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 sources 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 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 Other Medical Expenditures (OMSF97X-OMTC97X)
Other medical expenditure data were obtained only through the Household Component Survey.
For cases with missing expenditure data, other medical expenses were imputed using the
procedures described above. OMSF97X - OMOT97X are the 12 sources of payment, OMXP97X
is the sum of the 12 sources of payment variables, and OMTC97X is the total charge for the
medical item. 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 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 that 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 rounding differences.
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2.5.4.10 Imputation Flags
The variables IMPOMSLF - IMPOMCHG identify records where the expenditures have been
imputed using the methodologies outlined in this document. Records identified as being the leaf
of a flat fee or OMTYPE=2 or 3, 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 HHSFFIDX which is the original flat fee identifier that was
derived during the household interview. This identifier should only be used if the analyst is
interested in performing their own expenditure imputation.
The user 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.
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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 both files 1 and 2. A
person-level weight was 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 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 other medical expenditures and to allow for estimates of number of persons who obtained
medical items in 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 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 other medical expense 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:
The total number of other medical expense events for "GLASSES OR CONTACT
LENSES"(OMTYPEX=1), for the civilian non-institutionalized population of the U.S. in 1997 is
estimated as the sum of the weight (WTDPER97) across all other medical expense event records
with OMTYPEX=1. That is,
Sum of Wj=41,874,003 (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 on "GLASSES OR CONTACT
LENSES" for those who had such expense greater than 0 should be calculated as the weighted
mean of amount paid by self/family. That is,
X bar =(Sum of WjXj) / (Sum of Wj)= $130.36,
where where Sum of Wj= 41,189,157
and Xj= OMSF97Xj
for all records with OMTYPEX=1 AND OMXP97Xj>0 (2)
This gives $130.36 as the estimated mean amount of out-of-pocket payment of expenditures
associated with "GLASSES OR CONTACT LENSES" events and 41,189,157 as an estimate of
the total number of such other medical expense events 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 (where event
expense is greater than 0) paid by private insurance per "GLASSES OR CONTACT LENSES"
event. This should be calculated as the weighted mean of the proportion of the total "GLASSES
OR CONTACT LENSES" expense paid by private insurance at the other medical expense event
level. That is,
Y bar =(Sum of WjYj) / (Sum of Wj)=0.1332, (3)
where where Sum of Wj=41,189,157
and Yj=OMPV97Xj/OMXP97Xj
for all records with OMTYPEX=1 and OMXP97Xj>0
This gives 0.1332 as the estimated mean proportion of total expenditures paid by private
insurance for "GLASSES OR CONTACT LENSES" events with expenditure 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 Other Medical Expense Events
When calculating an estimate of the total number of persons with other medical expense events,
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 medical expense for ambulance
service in 1997, 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 OMTYPEX=4 for any other medical expense record of person i
and Xi=0 otherwise
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4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with Other Medical
Expense Events
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 other
medical expense events 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 OMXP97Xj across all othermedical expense events 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 other medical expense event are represented on this data file.
In this case the 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 other
medical expense event for ambulance services received in 1997, 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,
(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 OMTYPEXj=4 for any event of person i on the other medical expense event-level file =0 otherwise for all remaining persons on the MEPS HC-020 file.
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4.5 Sampling Weights for Merging Previous Releases of MEPS Household
Data with the Current Data File
There have been several previous releases of MEPS Household Survey public use data. Unless a
variable name common to several tapes is provided, the sampling weights contained on these data
files are file-specific. The file-specific weights reflect minor adjustments to eligibility and
response indicators due to birth, death, or institutionalization among respondents.
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 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 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 an estimate of standard error of $2.23
for the estimated mean 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 an estimate of standard error of
0.0065 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 the other medical expenditure 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) expands the scope of potential estimates. For example, to estimate the
expenditures for medical equipment, visual aids, etc. for 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 examples of
how to merge other MEPS files.
1. Create data set PERSX by sorting the Full year Population Characteristics file
(HCXXX), by the person identifier, DUPERSID. Keep only variables to be
merged on to the other medical expenses file and DUPERSID.
2. Create data set OMEXP by sorting the other medical expenditures file by person
identifier, DUPERSID.
3. Create final data set NEWOME 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=OMEXP;
BY DUPERSID;
RUN;
DATA NEWOME;
MERGE OMEXP (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
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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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Contents
Attachment 1
Definitions
Dwelling Units, Reporting Units, Families, and Persons The definitions of Dwelling Units
(DUs) and Group Quarters in the MEPS Household Survey are generally consistent with the
definitions employed for the National Health Interview Survey. The dwelling unit ID (DUID) is a
five-digit random ID number assigned after the case was sampled for MEPS. The person number
(PID) uniquely identifies all persons within the dwelling unit. The variable DUPERSID is the
combination of the variables DUID and PID.
A Reporting Unit (RU) is a person or group of persons in the sampled dwelling unit who are
related by blood, marriage, adoption or other family association, and who are to be interviewed as
a group in MEPS. Thus, the RU serves chiefly as a family-based "survey operations" unit rather
than an analytic unit. Regardless of the legal status of their association, two persons living
together as a "family" unit were treated as a single reporting unit if they chose to be so identified.
Unmarried college students under 24 years of age who usually live in the sampled household, but
were living away from home and going to school at the time of the Round 1 MEPS interview,
were treated as a Reporting Unit separate from that of their parents for the purpose of data
collection. These variables can be found on MEPS person level files.
In-Scope A person was classified as in-scope (INSCOPE) if he or she was a member of the U.S.
civilian, non-institutionalized population at some time during the Round 1 interview. This
variable can be found on MEPS person level files.
Keyness The term "keyness" is related to an individual's chance of being included in MEPS. A
person is key if that person is appropriately linked to the set of 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 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-016C: 1997 OTHER MEDICAL EXPENSES
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 |
Round number |
CAPI derived |
FFEEIDX |
Flat fee ID |
Constructed |
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OM Event Characteristics
Variable |
Description |
Source |
OMTYPEX |
Other medical expense type -edited |
EV03 (edited) |
OMTYPE |
Other medical expense type |
EV03 |
OMOTHOX |
OMTYPE other specify - edited |
EV03A (edited) |
OMOTHOS |
OMTYPE other specify |
EV03A |
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Imputed Expenditure Variables
Variable |
Description |
Source |
FFOMTYPE |
Flat Fee Bundle |
Constructed |
FFBEF97 |
Total # of events in flat fee before 1997 |
FF05 |
FFTOT98 |
Total # of events in flat fee after 1997 |
FF10 |
OMSF97X |
Amount paid, family (Imputed) |
CP11 (Edited/Imputed) |
OMMR97X |
Amount paid, Medicare (Imputed) |
CPO7 (Edited/Imputed) |
OMMD97X |
Amount paid, Medicaid (Imputed) |
CPO7 (Edited/Imputed) |
OMPV97X |
Amount paid, private (Imputed) |
CPO7 (Edited/Imputed) |
OMVA97X |
Amount paid, Veterans (Imputed) |
CPO7 (Edited/Imputed) |
OMCH97X |
Amount paid, CHAMPUS/CHAMPVA (Imputed) |
CPO7 (Edited/Imputed) |
OMOF97X |
Amount paid, other federal (Imputed) |
CPO7 (Edited/Imputed) |
OMSL97X |
Amount paid, state and local govt (Imputed) |
CPO7 (Edited/Imputed) |
OMWC97X |
Amount paid, workers comp (Imputed) |
CPO7 (Edited/Imputed) |
OMOR97X |
Amount paid, other private (Imputed) |
Constructed |
OMOU97X |
Amount paid, other public (Imputed) |
Constructed |
OMOT97X |
Amount paid, other insurance (Imputed) |
Constructed |
OMXP97X |
Sum of payments OMSLF97X OMWC97X (Imputed) |
Constructed |
OMTC97X |
Household reported total charge (Imputed) |
CP09 (Edited/Imputed) |
IMPOMSLF |
Imputation flag for OMSLF97X |
Constructed |
IMPOMMCR |
Imputation flag for OMMCR97X |
Constructed |
IMPOMMCD |
Imputation flag for OMMCD97X |
Constructed |
IMPOMPRV |
Imputation flag for OMPRV97X |
Constructed |
IMPOMVA |
Imputation flag for OMVA97X |
Constructed |
IMPOMCHM |
Imputation flag for OMCHM97X |
Constructed |
IMPOMOFD |
Imputation flag for OMOFD97X |
Constructed |
IMPOMSTL |
Imputation flag for OMSTL97X |
Constructed |
IMPOMWCP |
Imputation flag for OMWCP97X |
Constructed |
IMPOMOPR |
Imputation flag for OMOR97X |
Constructed |
IMPOMOPU |
Imputation flag for OMOU97X |
Constructed |
IMPOMOTH |
Imputation flag for OMOT97X |
Constructed |
IMPOMCHG |
Imputation flag for OMTC97X |
Constructed |
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Weights
Variable |
Description |
Source |
WTDPERF97 |
Poverty/mortality adjusted person weight, 1997 |
Constructed |
VARSTR97 |
Variance estimation stratum, 1997 |
Constructed |
VARPSU97 |
Variance estimation PSU, 1997 |
Constructed |
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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 |
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Pre-imputed Expenditure Variables
Variable |
Description |
Source |
OMSF97H |
Household reported amt. paid, family (Pre-imputed) |
CP11 (Edited) |
OMMR97H |
Household reported amt. paid, Medicare (Pre-imputed) |
CPO9 (Edited) |
OMMD97H |
Household reported amt. paid, Medicaid
(Pre-imputed) |
CPO7 (Edited) |
OMPV97H |
Household (Pre-imputed) reported amt. paid, private insurance |
CPO7 (Edited) |
OMVA97H |
Household reported amt. paid, Veterans (Pre-imputed) |
CPO7 (Edited) |
OMCH97H |
Household reported amt. paid, CHAMPUS/CHAMPVA (Pre-imputed) |
CPO7 (Edited) |
OMOF97H |
Household reported amt.paid, other federal
(Pre-imputed) |
CPO7 (Edited) |
OMSL97H |
Household reported amt. paid, state and local govt (Pre-imputed) |
CPO7 (Edited) |
OMWC97H |
Household reported amt. paid, workers comp (Pre-imputed) |
CPO7 (Edited) |
OMOT97H |
Household reported amt. paid, other insurance (Pre-imputed) |
CPO7 (Edited) |
OMUC97H |
Household reported uncollected liability (Pre-imputed) |
CPO7 (Edited) |
OMTC97H |
Household reported total charge (Pre-imputed) |
CP09 (Edited) |
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Weights
Variable |
Description |
Source |
WTDPERF97 |
Poverty/mortality adjusted person weight, 1997 |
Constructed |
VARSTR97 |
Variance estimation stratum, 1997 |
Constructed |
VARPSU97 |
Variance estimation PSU, 1997 |
Constructed |
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