MEPS HC-033C: 1999 Other Medical Expenses
May 2002
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
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 Source and Naming Conventions
2.4.1 Variable-Source Crosswalk
2.4.2
Expenditure and Sources of Payment Variables
2.5
File 1 Contents
2.5.1
Survey Administration and ID Variables
2.5.1.1
Person Identifiers (DUID, PID, DUPERSID)
2.5.1.2
Record Identifiers (EVNTIDX, FFEEIDX)
2.5.2
Type of Other Medical Expenses (OMTYPEX, OMTYPE, OMOTHOX,
OMOTHOX, OMOTHOS)
2.5.3
Flat Fee Variables
2.5.3.1
Definition of Flat Fee Payments
2.5.3.2
Flat Fee Variable Descriptions
2.5.3.2.1
Flat Fee ID (FFEEIDX)
2.5.3.2.2
Flat Fee Type (FFOMTYPE)
2.5.3.2.3
Counts of Flat Fee Events that Cross Years (FFBEF99,
FFTOT00)
2.5.3.3
Caveats of Flat Fee Groups
2.5.4
Expenditure Data
2.5.4.1
Definition of Expenditures
2.5.4.2
Data Editing and Imputation Methodologies of Expenditure
Variables
2.5.4.2.1
General Data Editing Methodology
2.5.4.2.2
General Hot-Deck Imputation
2.5.4.2.3
Other Medical Expenses Data Editing and Imputation
2.5.4.3
Capitation Imputation
2.5.4.4
Imputation Flag Variable (IMPFLAG)
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 Expenses Variables (OMSF99X-OMTC99X)
2.5.4.9
Rounding
3.0
Sample Weight (PERWT99F)
3.1
Overview
3.2
Details on Person Weights Construction
3.2.1
MEPS Panel 3 Weight
3.2.2
MEPS Panel 4 Weight
3.2.3
The Final Weight for 1999
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 this Event File
4.6
Variance Estimation
5.0
Merging/Linking MEPS Data Files
5.1
Merging a Person-Level File to the Other Medical Expenses
File
5.2
Linking the MEPS 1999 Other Medical Expenses File to the
MEPS 1999 Medical Conditions File and/or the MEPS 1999
Prescribed Medicines File
5.2.1
Limitations/Caveats of RXLK (the Prescribed Medicine Link
File)
5.2.2
Limitations/Caveats of CLNK (the Medical Conditions File)
Reference
Attachment 1
D. Variable-Source Crosswalk
A. Data Use Agreement
Individual identifiers
have been removed from the microdata contained in the files
on this CD-ROM. Nevertheless, under sections 308 (d) and 903
(c) of the Public Health Service Act (42 U.S.C. 242m and 42
U.S.C. 299 a-1), data collected by the Agency for Healthcare
Research and Quality (AHRQ) and/or the National Center for
Health Statistics (NCHS) may not be used for any purpose
other than for the purpose for which they were supplied; any
effort to determine the identity of any reported cases, is
prohibited by law.
Therefore in
accordance with the above referenced Federal statute, it is
understood that:
1. No one is to
use the data in this data set in any way except for
statistical reporting and analysis.
2. If the identity
of any person or establishment should be discovered
inadvertently, then (a) no use will be made of this
knowledge, (b) the Director, Office of Management, AHRQ
will be advised of this incident, (c) the information
that would identify any individual or establishment will
be safeguarded or destroyed, as requested by AHRQ, and
(d) no one else will be informed of the discovered
identity.
3. No one will
attempt to link this data set with individually
identifiable records from any data sets other than the
Medical Expenditure Panel Survey or the National Health
Interview Survey.
By using these data
you signify your agreement to comply with the above-stated
statutorily based requirements, with the knowledge that
deliberately making a false statement in any matter within
the jurisdiction of any department or agency of the Federal
Government violates 18 U.S.C. 1001 and is punishable by a
fine of up to $10,000 or up to 5 years in prison.
The Agency for
Healthcare Research and Quality requests that users cite
AHRQ and the Medical Expenditure Panel Survey as the data
source in any publications or research based upon these
data.
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Background
The Medical
Expenditure Panel Survey (MEPS) provides nationally
representative estimates of health care use, expenditures,
sources of payment, and insurance coverage for the U.S.
civilian noninstitutionalized population. MEPS is
cosponsored by the Agency for Healthcare Research and
Quality (AHRQ) and the National Center for Health Statistics
(NCHS).
MEPS is a family of
three surveys. The Household Component (HC) is the core
survey and forms the basis for the Medical Provider
Component (MPC) and part of the Insurance Component (IC).
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) was
conducted in 1977, and the National Medical Expenditure
Survey (NMES) was conducted in 1987. Since 1996, MEPS has
continued 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 advance these goals, MEPS includes linkage
with the National Health Interview Survey (NHIS)a survey
conducted by NCHS from which the sample for the MEPS HC is
drawn--and enhanced 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 2 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. 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/or replaces 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 home health
agencies and pharmacies reported by HC respondents.
Office-based physicians, hospitals, and hospital physicians
are also included in the MPC but may be subsampled at
various rates, depending on burden and resources, in certain
years.
Data are collected on
medical and financial characteristics of medical and
pharmacy events reported by HC respondents. The MPC is
conducted through telephone interviews and record
abstraction.
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3.0 Insurance Component
The MEPS IC collects
data on health insurance plans obtained through private and
public-sector employers. 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, and employer
characteristics.
Establishments
participating in the MEPS IC are selected through three
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
the Bureau of the Census.
To provide an
integrated picture of health insurance, data collected from
the first sampling frame (employers and other insurance
providers identified by MEPS HC respondents) are linked back
to data provided by those respondents. Data collected from
the two Census Bureau sampling frames are used to produce
annual national and State estimates of the supply and cost
of private health insurance available to American workers
and to evaluate policy issues pertaining to health
insurance. National estimates of employer contributions to
group health insurance from the MEPS IC are used in the
computation of Gross Domestic Product (GDP) by the Bureau of
Economic Analysis.
The MEPS IC is an
annual panel survey. Data are collected from the selected
organizations through a prescreening telephone interview, a
mailed questionnaire, and a telephone follow-up for
nonrespondents.
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4.0 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, microdata files, and compendiums of tables. Data
are also released through MEPSnet, an online interactive
tool developed to give users the ability to statistically
analyze MEPS data in real time. Summary reports and
compendiums of tables are released as printed documents and
electronic files. Microdata files are released on CD-ROM
and/or as electronic files.
Printed documents and
selected public use file data on 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 through 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
1999 Medical Expenditure Panel Survey (MEPS) Household
Component (HC). Released as an ASCII data file and a SAS
transport file, the 1999 Other Medical Expenses (OME) public
use event file provides information on the purchases 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. Data from the OME event file can be used
to make estimates of the utilization and expenditures
associated with medical items for calendar year 1999. As
illustrated below, this file consists of MEPS survey data
obtained in the 1999 portion of Round 3 (Round 2 for some
cases), and Rounds 4 and 5 for Panel 3, as well as Rounds 1,
2, and the 1999 portion of Round 3 for Panel 4 (i.e., the
rounds for the MEPS panels covering calendar year 1999).
301 Moved Permanently
301 Moved Permanently
Note:
Typically for MEPS panels, MEPSRound 2 data collection ends in the first year of a
panel and Round 3 data collection begins in the first
year of the panel and crosses the year boundary into
the second year of the panel. The crosshatched area in
the above figure signifies that Round 2 data
collection for approximately one quarter of the Panel
3 households began in 1998, the first year of the
panel, but ended in 1999. For those households, all of
the Round 3 data collection occurred in 1999. For the
other three quarters of Panel 3 households, Round 2
data collection followed the typical pattern and began
and ended in 1998. For those households, Panel 3 Round
3 data collection took place during both the first and
second years of the panel, as is typically done for
Round 3.
Note: The gray
shaded area in the above figure indicates the portion of Panel 4 Round 3 data
collection that extended into January 2000.
The OME event 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 3
and Rounds 1, 2 and 3 of Panel 4. Therefore, for these
items, 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 Rounds 5 (Panel 3) and 3 (Panel 4); for
these items, the reference period is the entire year.
The purchase of
medical equipment, supplies, and other medical items are
based entirely on household reports. They were not included
in the Medical Provider Component (MPC); therefore, all
expenditure and payment data on the OME event file are
reported by the household.
Data from this event
file can be merged with other 1999 MEPS HC data files for
the purpose of appending person-level data, such as
demographic characteristics or health insurance coverage, to
each OME record.
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 is provided on the
MEPS 1999 Full Year Person Level Expenditure File where each
record represents a MEPS sampled person.
Data users/analysts
should be aware of the limitations of the OME event file.
These limitations include the following:
a) A record can
represent one or more purchases of an item or service
during a reference period. For example, 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 were spent for ambulance
services, it is not known if the respondent used an
ambulance once or more than once in 1999;
b) Although data
users/analysts can link conditions to the current file
using DUPSERID, the specific condition requiring the
purchase of medical items or services, cannot be
identified. For example, if a person reported having
asthma, a head injury, and a heart attack, and also
reported requiring the purchase of ambulance service, 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 1999 Prescribed
Medicines File. All records for insulin and diabetic
supplies on this file have value of -1 INAPPLICABLE for
all expenditure (i.e., charge and payment) variables.
This documentation
offers an overview of the types and levels of data provided
and the content and structure of the files and the codebook.
It contains the following sections:
Data File Information
Sample Weights and Variance Estimation Variables
Strategies for Estimation
Merging/Linking MEPS Data Files
References
Definitions
Variable - Source Crosswalk
For more information
on MEPS HC survey design, see S. Cohen, 1997; J. Cohen,
1997; and S. Cohen, 1996. A copy of the MEPS HC survey
instrument used to collect the information on the OME event
file is available in the Survey Instrument section of
the MEPS web site at the following address: http://www.meps.ahrq.gov.
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2.0 Data File
Information
The 1999 OME public
use data set consists of one event level data file. The file
contains characteristics associated with the OME event and
imputed expenditure data. For data users/analysts wanting to
impute expenditures, pre-imputed data are available through
the CCFS Data Center. Please visit the CCFS Data Center
website for details: http://www.meps.ahrq.gov/mepsweb/data_stats/onsite_datacenter.jsp.
The data user/analyst is forewarned that the imputation of
expenditures will necessitate a sizable commitment of
resources: financial; staff; and time.
The OME public use
data set contains 6,079 other medical expenditure records;
of these records, 5,963 are associated with persons having a
positive person-level weight (PERWT99F). 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 1999. 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
1999 have no records on this file. These data were collected
during the 1999 portion of Round 3 (Round 2 for some cases),
and Rounds 4 and 5 for Panel 3, as well as Rounds 1, 2, and
the 1999 portion of Round 3 for Panel 4 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 1999 eligibility (i.e., persons with a
positive 1999 full-year person-level sampling weight
(PERWT99F > 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 1999 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 1999 eligibility, and at least one
family member had a positive 1999 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 1999 full-year family-level weight
(WTFAM99 >0)).
Please refer to
Attachment 1 for definitions of keyness, in-scope, and
eligibility.
Each record 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.
Data from this file
can be merged with the MEPS 1999 Full Year Population
Characteristics File using the unique person identifier,
DUPERSID, to append person level information, such as
demographic or health insurance characteristics, to each
record. See Section 5.0, "Merging/Linking MEPS Data
Files" or the MEPS 1999 Appendix File for
details on how to merge/link MEPS data files. Although
conditions can be linked to the OME event file, data
users/analysts 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 3 cases
(PANEL99=3 on the MEPS 1999 Full Year Population
Characteristics File) can also be linked back to the 1999
MEPS HC public use data files. However, data users/analysts
should be aware that, at this time, no weight is being
provided to facilitate two-year analysis of Panel 3 data.
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2.1 Codebook
Structure
For each variable on
the OME event file, both weighted and unweighted frequencies
are provided in the codebook (file H32CCB.PDF), located on
the MEPS web site: <http://www.meps.ahrq.gov>. The
codebook and data file sequence list variables in the
following order:
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
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2.2 Reserved Code
he 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 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>).
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2.3 Codebook Format
The OME 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 |
Definition |
Name |
Variable name
(maximum of 8 characters) |
Description |
Variable
descriptor (maximum of 40 characters) |
Format |
Number of bytes |
Type |
Type of data:
numeric (indicated by NUM) or character (indicated
by CHAR) |
Start |
Beginning column
position of variable in record |
End |
Ending column
position of variable in record |
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2.4 Variable Source
and Naming Conventions
In general, variable
names reflect the content of the variable, with an
8-character limitation.
All imputed/edited
variables end with an "X."
2.4.1
Variable-Source Crosswalk
Variables were derived
from the HC survey questionnaire. The source of each
variable is identified in Section D, "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,"
respectively;
(2) variables which come from one or
more specific questions have those questionnaire sections
and question numbers indicated in the "Source"
column; questionnaire sections are identified as
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.
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2.4.2 Expenditure and
Sources of Payment Variables
The expenditure and
sources of payment variable names follow a standard naming
convention. They are 7 characters in length with the last
one being an "X" indicating they are fully edited
and imputed.
The total sum of
payments variables, 12 source of payment variables, and the
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
event |
DV - dental visit |
OM - other
medical equipment |
RX - prescribed
medicine |
In the case of the
source of payment variables, the third and fourth characters
indicate:
SF - self or
family |
OF - other
Federal Government |
MR - Medicare |
SL - State/local
government |
MD - Medicaid |
WC - Workers
Compensation |
PV - private
insurance |
OT - other
insurance |
VA Veterans
Administration |
OR - other
private |
CH - CHAMPUS/CHAMPVA |
OU - other public |
XP - sum of
payments |
|
The fifth and sixth
characters indicate the year (99).
The seventh character
indicates whether or not the variable was edited/imputed
(ends with "X").
Example: OMSF99X is
the edited/imputed amount paid by self or family for 1999
other medical equipment and expenditures.
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Contents
2.5 File 1 Contents
2.5.1 Survey
Administration and ID Variables
2.5.1.1 Person
Identifiers (DUID, PID, DUPERSID)
The dwelling unit ID (DUID)
is a 5-digit random number assigned after the case was
sampled for MEPS. The 3-digit person number (PID) uniquely
identifies each person within the dwelling unit. The
8-character variable DUPERSID uniquely identifies each
person represented on the file and is the combination of the
variables DUID and PID. For detailed information on dwelling
units and families, please refer to the documentation for
the 1999 Full Year Population Characteristics File or to
definitions listed in Attachment 1.
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2.5.1.2 Record Identifiers (EVNTIDX,
FFEEIDX)
EVNTIDX uniquely
identifies each other medical expense event (i.e. each
record on the OME file) and is the variable required to link
other medical expenditures to data files containing details
on conditions and/or prescribed medicines (MEPS 1999 Medical
Condition File and MEPS 1999 Prescribed Medicines File,
respectively). For details on linking, see Section 5.0,
"Merging/Linking MEPS Data Files" or the MEPS 1999
Appendix File.
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 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 would be in different files (Outpatient Visits
and Other Medical Expenses) but 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
all MEPS event files (excluding prescribed medicines) in
order to determine the full set of events that are part of a
flat fee group.
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2.5.1.3 Round Indicators (EVENTRN)
EVENTRN indicates the
round in which the 6,079 other medical expenses were first
reported. For most types of other medical expenditures on
this file, data were collected only in Round 5 for Panel 3
and Round 3 for Panel 4; each record represents a summary of
expenditures for items purchased or otherwise obtained for
1999. There are two exceptions:
- Expenditure data for the purchase
of glasses and/or contact lenses were collected in
Rounds 3 (Round 2 for some cases),
4, and 5 for Panel 3 and Rounds 1, 2, and 3 for Panel
4. For vision items purchased in Round 3 for Panel 4
it could not be determined if the purchases occurred
in 1999 or 2000. Therefore, records with expenses
reported in Rounds 3 were only included if more than
half of the persons reference period for the round
was in 1999.
-
Respondents were
asked whether or not they obtained insulin or diabetic
supplies/equipment in Rounds 3 (Round 2 for some
cases), 4, and 5 for Panel 3 and Rounds 1, 2, and 3
for Panel 4. The reported purchases of these medical
items are included on this file while the actual
expenditures for insulin and diabetic
supplies/equipment are not included. Rather, these
expenditures are included on the 1999 Prescribed
Medicines file. All records for insulin and diabetic
supplies on this file have a value of 1
INAPPLICABLE for all each expenditure (i.e., charge
and payment) variable.
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2.5.2 Type of Other
Medical Expenses (OMTYPEX, OMTYPE, OMOTHOX, OMOTHOX, OMOTHOS)
Other medical
expenditures (OMTYPE) include glasses or contact
lenses, insulin, diabetic equipment/supplies, ambulance
services, orthopedic items, hearing devices, prosthesis,
bathroom aids, medical equipment, disposable supplies, and
alterations/modifications (to homes). When the
interviewer did not how to categorize types of medical item
expenditure, these items were specified in the variable
OMOTHOS (OMTYPE other specify). As a part of the editing
process, other medical expenditures identified in OMOTHOS
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 the OME file includes flat fee groups
where at least one of the health care events, as reported by
the HC respondent, occurred during 1999. By definition, a
flat fee group can span multiple years. Furthermore, a
single person can have multiple flat fee groups.
Fourteen (14)
variables on the OME file describe a flat fee payment
situation and the number of other medical events that are
part of a flat fee group.
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2.5.3.2 Flat Fee Variable
Descriptions
2.5.3.2.1 Flat Fee
ID (FFEEIDX)
As noted earlier in
the Section 2.5.1.2 "Record Identifiers," the
variable FFEEIDX can be used to uniquely identify all 1999
MEPS events (excluding the prescribed medicines file) that
are part of the same flat fee group because FFEEIDX is the
same value on all of the MEPS event files. 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 1 INAPPLICABLE.
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2.5.3.2.2 Flat
Fee Type (FFOMTYPE)
FFOMTYPE indicates
whether the 1999 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 expense
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. These
"leaf" records have their expenditure variables
set to zero.
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2.5.3.2.3 Counts
of Flat Fee Events that Cross Years (FFBEF99, FFTOT00)
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 the medical item was obtained in
1999 as part of a group of events, and some of the events
occurred before or after 1999, counts of the known events
are provided on the other medical expenditure record.
Variables that indicate events occurring before or after
1999 are the following:
FFBEF99
total number of pre-1999 events in the same flat fee
group as the medical item that was obtained in 1999.
This count would not include the medical item obtained
in 1999.
FFTOT00
indicates whether or not there are 2000 medical
events, including the purchase of the medical item, in
the same flat fee group as the medical item obtained
in 1999.
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2.5.3.3 Caveats of Flat Fee Groups
Data users/analysts
should note that flat fee payment situations are not common
on the OME file. There are only 14 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 1999, but the remaining
visits that were part of this flat fee group occurred in
2000. In this case, the 1999 flat fee group represented on
this file would consist of one event the "stem."
The 2000 "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 1998 but subsequent visits
occurred during 1999. In this case, the initial visit would
not be represented on the file. This 1999 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
Definition
of Expenditures
Expenditures on this
file 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, data user/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 and
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 follow.
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2.5.4.2.1 General
Data Editing Methodology
Logical edits were
used to resolve internal inconsistencies and other problems
in the HC survey-reported data. The edits were designed to
preserve partial payment data from households and providers,
and to identify actual and potential sources of payment for
each household-reported event. In general, these edits
accounted for outliers, copayments or charges reported as
total payments, and reimbursed amounts that were reported as
out of pocket payments. In addition, edits were implemented
to correct for misclassifications between Medicare and
Medicaid and between Medicare HMOs and private HMOs as
payment sources. These edits produced a complete vector of
expenditures for some events, and provided the starting
point for imputing missing expenditures in the remaining
events.
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2.5.4.2.2 General
Hot-Deck Imputation
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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2.5.4.2.3 Other
Medical Expenses Data Editing and 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 providers 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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2.5.4.3 Capitation Imputation
Health maintenance
organizations (HMOs) receive time-based (capitation)
payments to cover their members cost of health care.
Services provided by HMOs are referred to as "capitated
events" in the MEPS expenditure imputations. They are
singled out for special treatment because the payments
received by HMOs are not tied directly to individual events
and services. That is, per person per month payments to an
HMO, as opposed to fee-for-service reimbursement for health
care, pose a problem in the estimation of health care costs
because MEPS uses event-level payments for service as its
measure of expenditures. Capitated events are sent through
there own imputation procedure.
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2.5.4.4 Imputation Flag Variable (IMPFLAG)
Unlike prior data
releases, only one imputation flag was created for 1999
event files. This flag is a six-category variable that
indicates if the event contains complete Household Component
(HC) or Medical Provider Component (MPC) data, was fully or
partially imputed, or was imputed in the capitated
imputation process. Following is how the new imputation flag
is coded; the categories are mutually exclusive.
IMPFLAG=0 (not
eligible for imputation)
MPFLAG=1 (complete HHC data)
IMPFLAG=2 (complete MPC data)
IMPFLAG=3 (fully imputed)
IMPFLAG=4 (partially imputed)
IMPFLAG=5 (capitation imputation)
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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 1999, all of
the events that occurred in 1999 will have zero payments.
Conversely, if the first event in the flat fee group
occurred at the end of 1999, the total expenditure for the
entire flat fee group will be on that event, regardless of
the number of events it covered after 1999.
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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 (self) or family
2. Medicare
3. Medicaid
4. Private Insurance
5. Veterans 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. Workers Compensation
10. Other Unclassified Sources - includes sources such as
automobile, homeowners, 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, 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 persons who were not enrolled in
Medicaid, but were presumed eligible by a provider who
ultimately received payments from the program.
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2.5.4.8 Other Medical Expenses
Variables (OMSF99X-OMTC99X)
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. However, please note that expenditure data
for insulin and diabetic supplies are not included on this
file, but are included on the 1999 Prescribed Medicines
File. Missing expenditure data associated with these records
were not imputed. Charge and Payment variables in these
cases carry a value of 1 INAPPLICABLE.
OMSF99X - OMOT99X are
the 12 sources of payment, OMXP99X is the sum of the 12
sources of payment variables, and OMTC99X 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, Workmans Compensation, other private
insurance, other public insurance, and other insurance.
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2.5.4.9 Rounding
Expenditure variables
on this file have been rounded to the nearest penny. Person
level expenditure information released on the MEPS 1999
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 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 MEPS 1999 Appendix File for details on rounding
differences.
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3.0 Sample Weight
(PERWT99F)
3.1 Overview
There is a single full
year person-level weight (PERWT99F) 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 1999.
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.
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3.2 Details on Person
Weights Construction
The person-level
weight PERWT99F was developed in three stages. A person
level weight for Panel 4 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 3 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 1999 composite weight was formed from the Panel
3 and Panel 4 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 3
Weight
The person level
weight for MEPS Panel 3 was developed using the 1998 full
year weight for an individual as a "base" weight
for survey participants present in 1998. For key, in-scope
respondents who joined a RU some time in 1999 after being
out of scope in 1998, the 1998 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 1999. These control figures were derived by scaling
back the population totals obtained from the March 1999 CPS
to reflect the December, 1999 CPS estimated population
distribution across age and sex categories as of December,
1999. 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, 1999 is 273,003,778. Key, responding persons
not in-scope on December 31, 1999 but in-scope earlier in
the year retained, as their final Panel 3 weight, the weight
after the nonresponse adjustment.
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3.2.2 MEPS Panel 4
Weight
The person level
weight for MEPS Panel 4 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 1999 portion of Round 3 as well as
poststratification to the same population control figures
for December 1999 used for the MEPS Panel 3 weights. The
same five variables employed for Panel 3 poststratification
(census region, MSA status, race/ethnicity, sex, and age)
were used for Panel 4 poststratification. Similarly, for
Panel 4, key, responding persons not in-scope on December
31, 1999 but in-scope earlier in the year retained, as their
final Panel 4 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 1999 CPS data base.
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3.2.3 The Final
Weight for 1999
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, 1999 is
273,003,778 (PERWT99F>0 and INSC1231=1). The inclusion of
key, in-scope persons who were not in-scope on December 31,
1999 brings the estimated total number of persons
represented by the MEPS respondents over the course of the
year up to 276,410,767 (PERWT99F>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
1999 full year file an additional poststratification was
done to population totals obtained from the 1998 Medicare
Current Beneficiary Survey (MCBS) for the number of deaths
among Medicare beneficiaries experienced in the 1999 MEPS.
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3.2.4 Coverage
The target population
for MEPS in this file is the 1999 U.S. civilian,
noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households
interviewed in 1998 (Panel 3) and 1999 (Panel 4). New
households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who
entered the target population after 1998 (Panel 3) or after
1999 (Panel 4) 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 1999.
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.
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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 (PERWT99F) contained on that
record.
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Example 1
For example, 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 1999 is
estimated as the sum of the weight (PERWT99F) across all
other medical expense event records with OMTYPEX=1. That is,
Sum of Wj
= 47,507,983 for all records with OMTYPEXj =
1 (1)
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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,
(Sum of WjXj)/(Sum
of Wj) = $132.35 (2)
where
Sum of Wj
= 46,695,641 and Xj = OMSF99Xj
for all records
with OMTYPEXj = 1 and OMXP99Xj >
0
This gives $132.35 as
the estimated mean amount of out-of-pocket payment of
expenditures associated with "GLASSES OR CONTACT
LENSES" events and 46,695,641 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 1999.
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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,
(Sum of Wj
Yj)/(Sum of Wj)
= 0.1607 (3)
where
Sum of Wj
= 46,695,641 and Yj = OMPV99Xj /
OMXP99Xj
for all
records with OMTYPEXj = 1 and OMXP99Xj >
0
This gives 0.1607 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 1999.
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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 1999, this event file must
be used. This would be estimated as
Sum of Wi Xi
across all unique persons i on this file (4)
where
Wi is
the sampling weight (PERWT99F) for person
i
and
Xi =
1 if OMTYPEXj = 4 for any other medical
expense record of person i.
= 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 Wi
Zi)/(Sum of Wi) across
all unique persons i on this file (5)
where
Wi
is the sampling weight (PERWT99F) for
person i
and
Zi
= Sum of OMXP99Xj across all other
medical 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 1999, 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 Wi
Zi)/(Sum of Wi) across
all unique persons i on the MEPS HC-0xx file (6)
where
Wi
is the sampling weight (PERWT99F) for
person i
and
Zi =
1 if OMTYPEXj = 4 for any other medical
expense record of person i.
= 0 otherwise.
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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.
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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 1999
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 VARSTR99 and VARPSU99, 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.
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Examples 2 and 3 from
Section 4.2
Using a Taylor Series
approach, specifying VARSTR99 and VARPSU99 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
estimates of $2.50 and 0.0075 for the estimated mean of
out-of-pocket payment and the estimated mean proportion of
total expenditures paid by private insurance respectively.
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5.0 Merging/Linking
MEPS Data Files
5.1 Merging a
Person-Level File to the Other Medical Expenses File
Data from the MEPS
1999 OME event file can be used alone or in conjunction with
other files. Merging characteristics of interest from other
MEPS files (e.g., 1999 Full Year Population Characteristics
File or 1999 Full Year Person Level Expenditure File)
expands the scope of potential estimates. For example, to
estimate the expenditures for medical equipment, visual
aids, etc. for persons with specific demographic
characteristics (such as age, race, and sex), population
characteristics from a person-level file need to be merged
onto the OME event file. This procedure is shown below. The
MEPS 1999 Appendix File provides examples of how to merge
other MEPS files.
- Create data set PERSX by sorting
the 1999 Full Year Population Characteristics File, by
the person identifier, DUPERSID. Keep only variables
to be merged onto the Other Medical Expenses file and
DUPERSID.
- Create data set OMEXP by sorting
the Other Medical Expenses file by person identifier,
DUPERSID.
- 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=1999 Full Year Population Characteristics File
(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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5.2 Linking the
MEPS 1999 Other Medical Expenses File to the MEPS 1999
Medical Conditions File and/or the MEPS 1999 Prescribed
Medicines File
Because of survey
design issues, data users/analysts must keep the limitations
and/or caveats in mind when linking different files. Those
limitations/caveats are listed below. For detailed linking
examples, including SAS code, data users/analysts should
refer to the MEPS 1999 Appendix File.
5.2.1
Limitations/Caveats of RXLK (the Prescribed Medicine Link
File)
The RXLK file provides
a link from the MEPS event files to the prescribed medicine
records on the 1999 Prescribed Medicine Event File. When
using RXLK, data users/analysts should keep in mind that one
other medical expense can link to more than one prescribed
medicine record. Conversely, a prescribed medicine event may
link to more than one other medical expense. When this
occurs, it is up to the data user/analyst to determine how
the prescribed medicine expenditures should be allocated
among those other medical expenses.
5.2.2
Limitations/Caveats of CLNK (the Medical Conditions File)
The CLNK provides a
link from the MEPS event files to the Medical Conditions
File. When using the CLNK, data users/analysts should keep
in mind that (1) conditions are self-reported and (2) there
may be multiple conditions associated with another medical
expense. Data users/analyst should also note that not all
other medical expenses link to the condition file.
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Reference
Cohen, S.B. (1997).
Sample Design of the 1996 Medical Expenditure Panel Survey
Household Component. Rockville (MD): Agency for Health Care
Policy and Research; 1997. MEPS Methodology Report, No.
2. AHCPR Pub. No. 97-0027.
Cohen, J.W. (1997).
Design and Methods of the Medical Expenditure Panel Survey
Household Component. Rockville (MD): Agency for Health Care
Policy and Research; 1997. MEPS Methodology Report, No.
1. AHCPR Pub. No. 97-0026.
Cohen, S.B. (1996).
The Redesign of the Medical Expenditure Panel Survey: A
Component of the DHHS Survey Integration Plan. Proceedings of the COPAFS Seminar on
Statistical Methodology in the Public Service.
Monheit, A.C., Wilson,
R., and Arnett, III, R.H. (Editors). Informing American
Health Care Policy. (1999). Jossey-Bass Inc., San Francisco.
Shah, B.V., Barnwell,
B.G., Bieler, G.S., Boyle, K.E., Folsom, R.E., Lavange, L.,
Wheeless, S.C., and Williams, R. (1996). Technical
Manual: Statistical Methods and Algorithms Used in SUDAAN
Release 7.0, Research Triangle Park, NC: Research
Triangle Institute.
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Attachment 1
Definitions
Dwelling Units, Reporting Units, Families,
and Persons - The definitions of Dwelling Units (DUs)
and Group Quarters in the MEPS Household Survey are generally consistent with
the definitions employed for the National Health Interview Survey. The dwelling
unit ID (DUID) is a five-digit random ID number assigned after the case was
sampled for MEPS. The person number (PID) uniquely identifies all persons within
the dwelling unit. The variable DUPERSID is the combination of the variables
DUID and PID.
A Reporting Unit (RU) is a person or a
group of persons in the sampled dwelling unit who is related by blood, marriage,
adoption or other family association, and who is 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, persons returning from an institution,
or persons 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 that was
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, co-payments 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, co-payments or charges reported
as total payments, and reimbursed amounts counted as out-of-pocket payments.
These data were used as the imputation source to account for missing HC data.
Imputation -
A method of estimating values for cases with missing data. Hot-deck imputation
creates a data set with complete data for all nonrespondent cases, by
substituting the data from a respondent case that resembles the nonrespondent on
certain known variables.
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Variable-Source
Crosswalk
Survey Administration and ID Variables
Variable |
Description |
Source |
DUID |
Dwelling unit ID |
Assigned in sampling |
PID |
Person number |
Assigned in sampling |
DUPERSID |
Sample person ID (DUID + PID) |
Assigned in sampling |
EVNTIDX |
Event ID |
Assigned in Sampling |
EVENTRN |
Event round number |
CAPI derived |
FFEEIDX |
Flat fee ID |
Constructed |
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OME 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 |
Flat Fee Variables
Variable |
Description |
Source |
FFOMTYPE |
Flat Fee Bundle |
Constructed |
FFBEF99 |
Total # of events in flat fee
before 1999 |
FF05 |
FFTOT00 |
Total # of events in flat fee
after 1999 |
FF10 |
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Imputed Expenditure Variables
Variable |
Description |
Source |
OMSF99X |
Amount paid, family (Imputed) |
CP11 (Edited/Imputed) |
OMMR99X |
Amount paid, Medicare
(Imputed) |
CPO7 (Edited/Imputed) |
OMMD99X |
Amount paid, Medicaid
(Imputed) |
CPO7 (Edited/Imputed) |
OMPV99X |
Amount paid, private
insurance(Imputed) |
CPO7 (Edited/Imputed) |
OMVA99X |
Amount paid, Veterans
(Imputed) |
CPO7 (Edited/Imputed) |
OMCH99X |
Amount paid, CHAMPUS/CHAMPVA
(Imputed) |
CPO7 (Edited/Imputed) |
OMOF99X |
Amount paid, other federal
(Imputed) |
CPO7 (Edited/Imputed) |
OMSL99X |
Amount paid, state and local
govt (Imputed) |
CPO7 (Edited/Imputed) |
OMWC99X |
Amount paid, workers comp
(Imputed) |
CPO7 (Edited/Imputed) |
OMOR99X |
Amount paid, other private
(Imputed) |
Constructed |
OMOU99X |
Amount paid, other public
(Imputed) |
Constructed |
OMOT99X |
Amount paid, other insurance
(Imputed) |
Constructed |
OMXP99X |
Sum of payments OMSF99XOMOT99X
(Imputed) |
Constructed |
OMTC99X |
Household reported total
charge (Imputed) |
CP09 (Edited/Imputed) |
IMPFLAG |
Imputation Status |
Constructed |
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Weights
Variable |
Description |
Source |
PERWT99F |
Final person level weight, 1999 |
Constructed |
VARSTR99 |
Variance estimation stratum,
1999 |
Constructed |
VARPSU99 |
Variance estimation PSU, 1999 |
Constructed |
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