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June 2015
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 Survey Management and Data Collection
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 Source of Payment Variables
2.5 File Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID, PID, DUPERSID)
2.5.1.2 Record Identifiers (EVNTIDX, FFEEIDX)
2.5.1.3 Round Indicator (EVENTRN)
2.5.1.4 Panel Indicator (PANEL)
2.5.2 Other Medical Type Variables (OMTYPEX, OMTYPE, OMOTHOX, OMOTHOS)
2.5.3 Flat Fee Variables (FFEEIDX, FFOMTYPE, FFBEF13, FFTOT14)
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 (FFBEF13, FFTOT14)
2.5.3.3 Caveats of Flat Fee Groups
2.5.4 Condition, Procedure, and Clinical Classification Codes
2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
2.5.5.2 Data Editing and Imputation Methodologies of Expenditure Variables
2.5.5.2.1 General Data Editing Methodology
2.5.5.2.2 Imputation Methodologies
2.5.5.2.3 Other Medical Expenses Data Editing and Imputation
2.5.5.3 Imputation Flag Variable (IMPFLAG)
2.5.5.4 Flat Fee Expenditures
2.5.5.5 Zero Expenditures
2.5.5.6 Sources of Payment
2.5.5.7 Other Medical Expenditure Variables (OMSF13X-OMTC13X)
2.5.5.8 Rounding
3.0 Sample Weight (PERWT13F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 17 Weight Development Process
3.2.2 MEPS Panel 18 Weight Development Process
3.2.3 The Final Weight for 2013
3.2.4 Coverage
3.3 Using MEPS Data for Trend Analysis
4.0 Strategies for Estimation
4.1 Basic Estimates of Utilization, Expenditures, and Sources of Payment
4.1.1 Type of Records on File (OMTYPEX)
4.2 Variables with Missing Values
4.3 Variance Estimation (VARPSU, VARSTR)
5.0 Merging/Linking MEPS Data Files
5.1 Linking to the Person-Level File
5.2 Linking to the Prescribed Medicines File
5.3 Linking to the Medical Conditions File
References
D. Variable-Source Crosswalk
Individual identifiers have been removed from the
micro-data contained in these files. 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; and
- 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; and
- 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 Title 18 part 1
Chapter 47 Section 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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The Medical Expenditure Panel Survey (MEPS) provides
nationally representative estimates of health care use, expenditures, sources of
payment, and health insurance coverage for the U.S. civilian
non-institutionalized population. The MEPS Household Component (HC) also
provides estimates of respondents’ health status, demographic and socio-economic
characteristics, employment, access to care, and satisfaction with health care.
Estimates can be produced for individuals, families, and selected population
subgroups. The panel design of the survey, which includes 5 Rounds of interviews
covering 2 full calendar years, provides data for examining person-level changes
in selected variables such as expenditures, health insurance coverage, and
health status. Using computer assisted personal interviewing (CAPI) technology,
information about each household member is collected, and the survey builds on
this information from interview to interview. All data for a sampled household
are reported by a single household respondent.
The MEPS-HC was initiated in 1996. Each year a new
panel of sample households is selected. Because the data collected are
comparable to those from earlier medical expenditure surveys conducted in 1977
and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample
size is about 15,000 households. Data can be analyzed at either the person or
event level. Data must be weighted to produce national
estimates.
The set of households selected for each panel of the
MEPS HC is a subsample of households participating in the previous year’s
National Health Interview Survey (NHIS) conducted by the National Center for
Health Statistics. The NHIS sampling frame provides a nationally representative
sample of the U.S. civilian non-institutionalized population and reflects an
oversample of Blacks and Hispanics. In 2006, the NHIS implemented a new sample
design, which included Asian persons in addition to households with Black and
Hispanic persons in the oversampling of minority populations. MEPS further
oversamples additional policy relevant sub-groups such as low income households. The linkage of the MEPS to the previous year’s NHIS provides additional data for longitudinal analytic
purposes.
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Upon completion of the household CAPI interview and
obtaining permission from the household survey respondents, a sample of medical
providers are contacted by telephone to obtain information that household
respondents can not accurately provide. This part of the MEPS is called the
Medical Provider Component (MPC) and information is collected on dates of visit,
diagnosis and procedure codes, charges and payments. The Pharmacy Component
(PC), a subcomponent of the MPC, does not collect charges or diagnosis and
procedure codes but does collect drug detail information, including National
Drug Code (NDC) and medicine name, as well as date filled and sources and
amounts of payment. The MPC is not designed to yield national estimates. It is
primarily used as an imputation source to supplement/replace household reported
expenditure information.
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MEPS HC and MPC data are collected under the authority
of the Public Health Service Act. Data are collected under contract with Westat,
Inc. (MEPS HC) and Research Triangle Institute (MEPS MPC). Data sets and summary
statistics are edited and published in accordance with the confidentiality
provisions of the Public Health Service Act and the Privacy Act. The National
Center for Health statistics (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, micro data files, and tables via the MEPS Web site:
meps.ahrq.gov.
Selected data can be analyzed through MEPSnet, an on-line interactive tool
designed to give data users the capability to statistically analyze MEPS data in
a menu-driven environment.
Additional information on MEPS is available from the
MEPS project manager or the MEPS public use data manager at the Center for
Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality,
540 Gaither Road, Rockville, MD 20850 (301-427-1406).
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This documentation describes one in a series of public
use event files from the 2013 Medical Expenditure Panel Survey (MEPS) Household
Component (HC). Released as an ASCII data file (with related SAS, SPSS, and
Stata programming statements) and a SAS transport file, the 2013 Other Medical
Expenses 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 Other
Medical event file can be used to make estimates of the Other Medical event
expenditures associated with medical items for calendar year 2013. The purchase
of medical equipment, supplies, and other medical items is based entirely on
household reports. They were not included in the Medical Provider Component
(MPC); therefore, all expenditure and payment data on the Other Medical event
file are reported by the household.
This file contains 32 variables and has a logical
record length of 224 with an additional 2-byte carriage return/line feed at the
end of each record. As illustrated below, this file consists of MEPS survey data
obtained in the 2013 portion of Round 3, and Rounds 4 and 5 for Panel 17, as
well as Rounds 1, 2, and the 2013 portion of Round 3 for Panel 18 (i.e., the
rounds for the MEPS panels covering calendar year 2013).
The Other Medical event file contains one record for
each type of medical item reported as being purchased or otherwise obtained by a
household member during the specified reference period. It should be noted that
reference periods for reporting expenditures vary by type of medical item
obtained. Expenditure data for visual aids are collected during Rounds 3, 4, and
5 of Panel 17 and Rounds 1, 2, and 3 of Panel 18. Therefore, each round is a
reference period for purchases of visual aids. Expenditure data for other
medical items, which include ambulance services, orthopedic items, hearing
devices, prostheses, bathroom aides, medical equipment, disposable supplies, and
home alterations, are collected only in Round 5 (Panel 17) and Round 3 (Panel
18); for these items, the reference period is the entire year. A record can
represent one or more purchases of an item or service during a reference period.
For example, expenditures for glasses and contact lenses are asked every round.
If a respondent reported an expense of $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 (which has a reference period of a year), it is not known if
the person used an ambulance once or more than once during the year.
Following is a summary of other medical expense
categories included in this file:
Other medical events in file collected every round
- Glasses and contact lenses
Other medical events in file collected once a year
- Ambulance services
- Orthopedic items (such as corrective shoes or inserts,
braces, crutches, canes, walkers, wheelchairs, and scooters)
- Hearing devices (such as hearing aids, amplifiers for a
telephone, adaptive speech equipment, and speech synthesizers)
- Prostheses (such as artificial limbs)
- Bathroom aids (such as portable commodes, raised toilet
seats, portable tub seats, and handrails)
- Medical equipment (such as hospital beds, lifts, monitors,
special chairs, oxygen, bed pans, adaptive feeding equipment,
vaporizers or nebulizers, and blood pressure monitors)
- Disposable supplies (such as ostomy supplies, bandages,
dressings, tape, diapers, catheters, syringes, and IV supplies)
- Home alterations and modifications (such as ramps,
handrails, elevators, and automobile modifications)
- Any other medical item
Records for purchases of insulin and diabetic supplies
in a round were included in the Other Medical Expenses event files for
1996-2004. Beginning with the 2005 file, it was decided to exclude these records
from the Other Medical Expenses event file since the expenditures have always
been included on the Prescribed Medicines file. The Prescribed Medicines file is
a more appropriate source for estimates of both utilization and expenditures for
insulin and diabetic supplies. As a consequence, there are no records on this
file where the variable OMTYPEX = 2 or 3 (the values used in 1996-2004 to
identify records for purchases of insulin and diabetic supplies, respectively).
Data from this event file can be merged with other
2013 MEPS HC data files for the purpose of appending person-level data, such as
demographic characteristics or health insurance coverage, to each other medical
record.
This file can also be used to construct summary
variables of expenditures, source 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 2013 Full-Year
Consolidated Data File where each record represents a MEPS sampled person. This
aggregate information is provided for vision aids only and not other types of
other medical equipment.
The following documentation offers a brief 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:
- Sample Weights
- Strategies for Estimation
- Merging/Linking MEPS Data Files
- References
- Variable - Source Crosswalk
For more information on MEPS HC survey design, see T.
Ezzati-Rice, et al. (1998-2007) and
S. Cohen, 1996. A copy of the MEPS HC survey instrument used to collect the
information on the dental file is available on the MEPS Web site at the
following address:
meps.ahrq.gov.
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The 2013 Other Medical Expenses public use data set
consists of one event-level data file. The file contains characteristics
associated with the Other Medical event and imputed expenditure data.
The 2013 Other Medical Expenses public use data set
contains 7,421 other medical (OM) expenditure records; of these records, 7,208
are associated with persons having a positive person-level weight (PERWT13F).
This file includes records for all household members who resided in eligible
responding households and were reported to have purchased or otherwise obtained
at least one type of medical item such as medical equipment, glasses, hearing
devices, etc. during calendar year 2013. Some persons may have been reported to
have obtained more than one type of medical item and, therefore, have several
records on this file. On the other hand, persons who were not reported to
have obtained a medical item in 2013 have no records on this file. These data
were collected during the 2013 portion of Round 3, and Rounds 4 and 5 for
Panel 17, as well as Rounds 1, 2, and the 2013 portion of Round 3 for Panel 18
of the MEPS HC. The persons represented on this file had to meet either (a) or
(b) below:
- Be classified as a key in-scope person who responded for his
or her entire period of 2013 eligibility (i.e., persons with a
positive 2013 full-year person-level weight (PERWT13F > 0)), or
- Be an eligible member of a family all of whose key in-scope
members have a positive person-level weight (PERWT13F > 0).
(Such a family consists of all persons with the same value for
FAMIDYR.) That is, the person must have a positive
full-year family-level weight (FAMWT13F > 0). Note that FAMIDYR
and FAMWT13F are variables on the 2013 Full Year Consolidated
Data File.
Persons with no other medical events for 2013 are not
included on this event-level OM file but are represented on the person-level
2013 Full-Year Population Characteristics file.
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.
To append person-level information such as demographic
or health insurance coverage to each event record, data from this file can be
merged with 2013 MEPS HC person-level data (e.g.
Full-Year Consolidated or Full-Year Population Characteristics files) using the
person identifier, DUPERSID. Please see Section 5.0 for details on how to merge
MEPS data files.
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For most variables on the Other Medical Expenses event
file, both weighted and unweighted frequencies are provided in the accompanying
codebook. The exceptions to this are weight variables and variance estimation
variables. Only unweighted frequencies of these variables are included in the
accompanying codebook file. See the Weights Variables list in section D,
Variable-Source Crosswalk.
The codebook and data file sequence list variables in
the following order:
- Unique person identifier
- Unique other medical expenses identifier
- Type of other medical expenses
- Imputed expenditure variables
- Weight and variance estimation variables
Note that the person identifier is unique within this
data year.
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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 for
non-expenditure variables 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:
meps.ahrq.gov/survey_comp/survey_questionnaires.jsp).
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The 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 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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In general, variable names reflect the content of the
variable, with an eight-character limitation. All imputed/edited variables end
with an “X”.
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Variables were derived from the HC survey
questionnaire or from the CAPI. The source of each variable is identified in
Section D “Variable - Source Crosswalk” in one of four ways:
- Variables derived from CAPI or assigned in sampling are so
indicated as “CAPI derived” or “Assigned in sampling,”
respectively;
- 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
- Variables constructed from multiple questions using complex
algorithms are labeled “Constructed” in the “Source” column; and
- Variables that have been edited or imputed are so indicated.
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The names of the expenditure and source of payment
variables follow a standard convention, are seven characters in length, and end
in an “X” indicating edited/imputed. Please note that imputed means that a
series of logical edits, as well as an imputation process to account for missing
data, have been performed on the variable.
The total sum of payments and 12 source of payment
variables are named in the following way:
The first two characters indicate the type of event:
- IP - inpatient stay
- ER - emergency room visit
- HH - home health visit
- OM - other medical equipment
- OB - office-based visit
- OP - outpatient visit
- DV - dental visit
- RX - prescribed medicine
In the case of the source of payment variables, the
third and fourth characters indicate:
- SF - self or family
- MR - Medicare
- MD - Medicaid
- PV - private insurance
- VA - Veterans Administration/CHAMPVA
- TR - TRICARE
- OF - other Federal Government
- SL - State/local government
- WC - Workers’ Compensation
- OT - other insurance
- OR - other private
- OU - other public
- XP - sum of payments
In addition, the total charge variable is indicated by
TC in the variable name.
The fifth and sixth characters indicate the year (13).
The seventh character, “X”, indicates whether the variable is edited/imputed.
For example, OMSF13X is the edited/imputed amount paid
by self or family for 2013 other medical equipment and expenditures.
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The dwelling unit ID (DUID) is a five-digit random
number assigned after the case was sampled for MEPS. The three-digit person
number (PID) uniquely identifies each person within the dwelling unit. The
eight-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 2013
Full-Year Population Characteristics File.
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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 events to data files containing details on prescribed medicines
(MEPS 2013 Prescribed Medicines File). For details on linking, see Section 5.0,
or the MEPS 2013 Appendix File, HC-160I.
FFEEIDX is a constructed variable that uniquely
identifies a flat fee group, that is, all events that were part of a flat fee
payment. FFEEIDX identifies a flat fee payment that was identified using
information from the Household Component.
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EVENTRN indicates the round in which the other medical
event was reported. For most types of other medical expenditures on this file,
data were collected only in Round 5 for Panel 17 and Round 3 for Panel 18; each
record represents a summary of expenditures for items purchased or otherwise
obtained for 2013. There is one exception:
Expenditure data for the purchase of glasses and/or
contact lenses were collected in Rounds 3, 4, and 5 for Panel 17 and Rounds 1,
2, and 3 for Panel 18. For vision items purchased in Panel 18 Round 3, it could
not be determined if the purchases occurred in 2013 or 2014. Therefore, records
with expenses reported in Round 3 were only included if the number of purchases
in 2013 was greater than or equal to the number of purchases in 2014.
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PANEL is a constructed variable used to specify the
panel number for the person. PANEL will indicate either Panel 17 or Panel 18 for
each person on the file. Panel 17 is the panel that started in 2012, and Panel
18 is the panel that started in 2013.
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Other medical expenditures (OMTYPE) include
glasses or contact lenses, ambulance services, orthopedic items, hearing
devices, prostheses, bathroom aids, medical equipment, disposable supplies, and
alterations/modifications (to homes). When the interviewer did not know
how to categorize types of medical item expenditures, 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.
Records for purchases of insulin and diabetic supplies
in a round were included in the Other Medical Expenses event files for
1996-2004. Beginning with the 2005 file, it was decided to exclude these records
from the Other Medical Expenses event file since the expenditures have always
been included on the Prescribed Medicines file. The Prescribed Medicines file is
a more appropriate source for estimates of both utilization and expenditures for
insulin and diabetic supplies. As a consequence, there are no records on this
file where the variable OMTYPEX = 2 or 3 (the values used in 1996-2004 to
identify records for purchases of insulin and diabetic supplies, respectively).
Other Medical Expenses Event File
1996- 2004 (OMTYPEX) |
Other Medical Expenses Event File
2005 and later (OMTYPEX) |
| 1 = Glasses or Contact Lenses |
1 = Glasses or Contact Lenses |
| 2 = Insulin |
2 = not used |
| 3 = Diabetic Equipment/Supplies |
3 = not used |
| 4 = Ambulance Services |
4 = Ambulance Services |
| 5 = Orthopedic Items |
5 = Orthopedic Items |
| 6 = Hearing Devices |
6 = Hearing Devices |
| 7 = Prosthesis |
7 = Prosthesis |
| 8 = Bathroom Aids |
8 = Bathroom Aids |
| 9 = Medical Equipment |
9 = Medical Equipment |
| 10 = Disposable Supplies |
10 = Disposable Supplies |
| 11 = Alterations/modifications |
11 = Alterations/modifications |
| 91 = Other |
91 = Other |
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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. The flat fee groups represented on the Other Medical Expenses
event file include flat fee groups where at least one of the other medical
events, as reported by the HC respondent, occurred during 2013. By definition, a
flat fee group can span multiple years. Furthermore, a single person can have
multiple flat fee groups.
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As noted earlier in Section 2.5.1.2 “Record
Identifiers,” the variable FFEEIDX uniquely identifies all events that are part
of the same flat fee group for a person. On any 2013 MEPS event file, every
event that is part of a specific flat fee group will have the same value for
FFEEIDX. Note that prescribed medicine and home health events are never included
in a flat fee group and none of the flat fee variables are on those event files.
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FFOMTYPE indicates whether the 2013 other medical
expenditure is the “stem” or “leaf” of a flat fee group. A stem (records with
FFOMTYPE = 1) is the initial other 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 other
medical events that are tied back to the initial event (the stem) in the flat
fee group. These “leaf” records have their expenditure variables set to zero.
For the other medical events that are not part of a flat fee payment, the
FFOMTYPE is set to -1, “INAPPLICABLE”.
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As described in Section 2.5.3.1, a flat fee payment
covers multiple events and the multiple events could span multiple years. For
situations where the medical item was obtained in 2013 as part of a group of
events, and some of the events occurred before or after 2013, counts of the
known events are provided on the other medical record.
Variables that indicate events occurring before or
after 2013 are the following:
FFBEF13 – indicates total number of 2012 events in the
same flat fee group as the medical item that was obtained in 2013. This count
would not include the medical item obtained in 2013.
FFTOT14 – indicates the number of 2014 medical events,
including the purchase of any additional medical items, expected to be in the
same flat fee group as the medical item obtained in 2013.
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Data users/analysts should note that flat fee payments
are not common on the Other Medical Expenses file. There are 22 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 2013, but the remaining
visits that were part of this flat fee group occurred in 2014. In this case, the
2013 flat fee group represented on this file would consist of one event (the
stem). The 2014 “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 2012 but subsequent visits
occurred during 2013. In this case, the initial visit would not be represented
on the file. This 2013 flat fee group would then only consist of one or more
leaf records and no stem. Please note that the crosswalk in this document lists
all possible flat fee variables.
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Conditions data are not collected for Other Medical
events; therefore, this file cannot be linked to the Conditions File.
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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 1990s due to the increasingly common practice of discounting. Although
measuring expenditures as the sum of payments incorporates discounts in the MEPS
expenditure estimates, these estimates do not incorporate any payment not
directly tied to specific medical care events, such as bonuses or retrospective
payment adjustments paid by third party payers. Another general change from the
two prior surveys is that charges associated with uncollected liability, bad
debt, and charitable care (unless provided by a public clinic or
hospital) are not counted as expenditures because there are no payments
associated with those classifications. While charge data are provided on this
file, data users/analysts should use caution when working with these 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, please refer to the following, “Informing American
Health Care Policy” (Monheit et al., 2000). AHRQ has developed factors to apply
to the 1987 NMES expenditure data to facilitate longitudinal analysis. These
factors can be accessed via the CFACT data center. For more information see the
Data Center section of the MEPS Web site at
meps.ahrq.gov/data_stats/onsite_datacenter.jsp.
If examining trends in MEPS expenditures, please refer to Section C, sub-Section
3.3 for more information.
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The general methodology used for editing and imputing
expenditure data is described below. The MPC did not include either the dental
events or other medical expenditures (such as glasses, contact lenses, and
hearing devices). 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. Please see below for details on the
differences between these editing/imputation methodologies. Separate imputations
were performed for flat fee and simple events, as well.
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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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The predicted mean matching imputation method was used
to impute missing expenditures. This procedure uses regression models (based on
events with completely reported expenditure data) to predict total expenses for
each event. Then, for each event with missing payment information, a donor event
with the closest predicted payment with the same pattern of expected payment
sources as the event with the missing payment was used to impute the missing
payment value. The imputations for the flat fee events were carried out
separately from the simple events.
A weighted sequential hot-deck procedure was used to
impute the missing total charges. This procedure uses survey data from
respondents to replace missing data, while taking into account the persons’
weighted distribution in the imputation process.
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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. One of the more important edits separated flat fee events from simple
events. This edit was necessary because groups of events covered by a flat fee
(i.e., a flat fee bundle) were edited and imputed separately from individual
events each covered by a single charge (i.e., simple events). Other medical
services were imputed as flat fee events if the charges covered a package of
health care services (e.g., optical), and all of the services were part of the
same event type (i.e., a pure bundle). If a bundle contained any OM events with
any other types of events, the services were treated as simple events in the
imputations (See Section 2.5.3 for more detail on the definition and imputation
of events in flat fee bundles.)
Logical edits were used to sort each event into a
specific category for the imputations. Events with complete expenditures were
flagged as potential donors for the predictive mean imputations, while events
with missing expenditure data were assigned to various recipient categories.
Each event with missing expenditure data was assigned to a recipient category
based on the extent of its missing charge and expenditure data. For example, an
event with a known total charge but no expenditure information was assigned to
one category, while an event with a known total charge and partial expenditure
information was assigned to a different category. Similarly, events without a
known total charge and no or partial expenditure information were assigned to
various recipient categories.
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. Medicaid
events were imputed separately because persons on Medicaid rarely know the
provider’s charge for services or the amount paid by the state Medicaid program.
As a result, the total charge for Medicaid-covered services was imputed and
discounted to reflect the amount that a state program might pay for the care.
Separate predictive mean imputations were used to
impute missing data in each of the 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 distribution of free events among
complete events (donors) is not represented among incomplete events
(recipients).
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IMPFLAG 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 (for OP and MV events only). The following list
identifies how the imputation flag is coded; the categories are mutually
exclusive.
IMPFLAG = 0 not eligible for imputation (includes
zeroed out and flat fee leaf events)
IMPFLAG = 1 complete HC data
IMPFLAG = 2 complete MPC data (not applicable to OM
events)
IMPFLAG = 3 fully imputed
IMPFLAG = 4 partially imputed
IMPFLAG = 5 complete MPC data through capitation
imputation (not applicable to OM events)
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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 2013, all of the events that occurred in 2013 will have
zero payments. Conversely, if the first event in the flat fee group occurred at
the end of 2013, the total expenditure for the entire flat fee group will be on
that event, regardless of the number of events it covered after 2013. See
Section 2.5.3 for details on the flat fee variables.
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Some respondents reported persons 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. If
all of the medical events for a person fell into one of these categories, then
the total annual expenditures for that person would be zero.
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In addition to total expenditures, variables are
provided which itemize expenditures according to major source of payment
categories. These categories are:
- Out-of-pocket by User (self) or Family,
- Medicare,
- Medicaid,
- Private Insurance,
- Veterans Administration/CHAMPVA, excluding TRICARE,
- TRICARE,
- Other Federal Sources - includes Indian Health Service,
military treatment facilities, and other care by the federal
government,
- Other State and Local Source - includes community and
neighborhood clinics, state and local health departments, and
state programs other than Medicaid,
- Workers’ Compensation, and
- Other Unclassified Sources - includes sources such as
automobile, homeowner’s, and liability insurances, and other
miscellaneous or unknown sources.
Two additional source of payment
variables were created to classify payments for events with
apparent inconsistencies between insurance coverage and sources
of payment based on data collected in the survey. These
variables include:
- 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
- Other Public - Medicare/Medicaid payments reported for
persons who were not reported to be enrolled in the
Medicare/Medicaid program at any time during the year.
Though relatively small in magnitude, data
users/analysts should exercise caution when interpreting the expenditures
associated with these two additional sources of payment. While these payments
stem from apparent inconsistent responses to health insurance and source of
payment questions in the survey, some of these inconsistencies may have logical
explanations. For example, private insurance coverage in MEPS is defined as
having a major medical plan covering hospital and physician services. If a MEPS
sampled person did not have such coverage but had a single service type
insurance plan (e.g., dental insurance) that paid for a particular episode of
care, those payments may be classified as “other private.” Some of the “other
public” payments may stem from confusion between Medicaid and other state and
local programs or may be from persons who were not enrolled in Medicaid, but
were presumed eligible by a provider who ultimately received payments from the
public payer.
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Other medical expenditure data were obtained only
through the Household Component Survey. For cases with missing expenditure data,
other medical expenditures were imputed using the procedures described above.
OMSF13X – OMOT13X are the 12 sources of payment.
OMTC13X is the total charge, and OMXP13X is the sum of the 12 sources of payment
for the other medical expenditures. The 12 sources of payment are: self/family
(OMSF13X), Medicare (OMMR13X), Medicaid (OMMD13X), private insurance (OMPV13X),
Veterans Administration/CHAMPVA (OMVA13X), TRICARE (OMTR13X), other federal
sources (OMOF13X), state and local (non-federal) government sources (OMSL13X), Workers’ Compensation (OMWC13X),
other private insurance (OMOR13X), other public insurance (OMOU13X), and other
insurance (OMOT13X).
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Expenditure variables on the 2013 Other Medical event
file have been rounded to the nearest penny. Person-level expenditure
information released on the MEPS 2013 Full Year Consolidated File will be
rounded to the nearest dollar. It should be noted that using the MEPS event
files to create person-level totals will yield slightly different totals than
those found on the consolidated 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.
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There is a single full-year person-level weight
(PERWT13F) 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 2013. A key person was either a member of a responding NHIS
household at the time of interview or joined a family associated with such a
household after being out-of-scope at the time of the NHIS (the latter
circumstance includes newborns as well as those returning from military service,
an institution, or residence in a foreign country). 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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The person-level weight PERWT13F was developed in
several stages. Person-level weights for Panel 17 and Panel 18 were created
separately. The weighting process for each panel included an adjustment for
nonresponse over time and calibration to independent population figures. The
calibration was initially accomplished separately for each panel by raking the
corresponding sample weights for those in-scope at the end of the calendar year
to Current Population Survey (CPS) population estimates based on five variables.
The five variables used in the establishment of the initial person-level control
figures were: census region (Northeast, Midwest, South, West); MSA status (MSA,
non-MSA); race/ethnicity (Hispanic; Black, non-Hispanic; Asian,
non-Hispanic; and other); sex; and age. A 2013
composite weight was then formed by multiplying each weight from Panel 17 by the
factor .506 and each weight from Panel 18 by the factor .494. Control totals were established using poverty status (five categories: 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) the other five variables previously used in the weight calibration, and a variable associated with number of hospital stays for those under the age of 65.
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The person-level weight for MEPS Panel 17 was
developed using the 2012 full-year weight for an individual as a “base” weight
for survey participants present in 2012. For key, in-scope members who joined an
RU some time in 2013 after being out-of-scope in 2012, the initially assigned
person-level weight was the corresponding 2012 family weight. The weighting
process included an adjustment for person-level nonresponse over Rounds 4 and 5
as well as raking to population control totals for December 2013 for key,
responding persons in-scope on
December 31, 2013. These control figures were derived by scaling back the
population distribution obtained from the March 2014 CPS to reflect the December
31, 2013 estimated population total (estimated based on Census projections for
January 1, 2014). Variables used for person-level raking included: census region
(Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity
(Hispanic, Black non-Hispanic, Asian non-Hispanic, and
other); sex; and age. (Poverty status is not included in this version of the
MEPS full year database because of the time required to process the income data
collected and then assign persons to a poverty status category). The final
weight for key, responding persons who were not in-scope on December 31, 2013
but were in-scope earlier in the year was the person weight after the
nonresponse adjustment.
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The person-level weight for MEPS Panel 18 was
developed using the 2013 MEPS Round 1 person-level weight as a “base” weight.
For key, in-scope members 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 the remaining data collection rounds in 2013 as well as
raking to the same population control figures for December 2013 used for the
MEPS Panel 17 weights for key, responding persons in-scope on December 31, 2013.
The same five variables employed for Panel 17 raking (census region, MSA status,
race/ethnicity, sex, and age) were used for Panel 18 raking. Again, the final
weight for key, responding persons who were not
in-scope on December 31, 2013 but were in-scope earlier in the year was the
person weight after the nonresponse adjustment.
Note that the MEPS Round 1 weights for both panels
incorporated the following components: a weight reflecting the original
household probability of selection for the NHIS and an adjustment for NHIS
nonresponse; a factor representing the proportion of the 16 NHIS panel-quarter
combinations eligible for MEPS; the oversampling of certain subgroups for MEPS
among the NHIS household respondents eligible for MEPS; ratio-adjustment to
NHIS-based national population estimates at the household (occupied DU) level;
adjustment for nonresponse at the DU level for Round 1; and poststratification
to U.S. civilian noninstitutionalized population estimates at the family and
person level obtained from the corresponding March CPS data bases.
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The final raking of those in-scope at the end of the
year has been described above. In addition, the composite weights of two groups
of persons who were out-of-scope on December 31, 2013 were poststratified.
Specifically, the weights of those who were in-scope some time during the year,
out-of-scope on December 31, and entered a nursing home during the year were
poststratified to a corresponding control total obtained from the 1996 MEPS
Nursing Home Component. Those who died while in-scope during 2013 were
poststratified to corresponding estimates derived using data obtained from the
Medicare Current Beneficiary Survey (MCBS) and Vital Statistics information
provided by the National Center for Health Statistics (NCHS). Separate decedent
control totals were developed for the “65 and older” and “under 65” civilian noninstitutionalized populations.
In developing the final person-level weight for 2013 (PERWT13F), an additional raking dimension was included to adjust the proportion of persons under age 65 with at least one inpatient discharge based on independent sources of data reviewed by AHRQ. The table below shows ratios of weighted numbers of non-elderly persons that resulted from including this additional raking dimension to that of corresponding estimates without the additional dimension.
Ratio of Adjusted to Unadjusted Weights
| Number of Inpatient Discharges (IPDIS13) |
Non-elderly (AGE13X < 65) |
| 0 |
0.98938 |
| 1+ |
1.21587 |
Overall, the weighted population estimate for the
civilian noninstitutionalized population for December 31, 2013 is 312,098,312
(PERWT13F>0 and INSC1231=1). The sum of person-level weights across all persons
assigned a positive person-level weight is 315,721,982.
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The target population for MEPS in this file is the
2013 U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2011 (Panel 17)
and 2012 (Panel 18). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2011 (Panel 17) or after 2012 (Panel 18) are not covered by
MEPS. Neither are previously out-of-scope persons who join an existing household
but are unrelated to the current household residents. Persons not covered by a
given MEPS panel thus include some members of the following groups: immigrants;
persons leaving the military; U.S. citizens returning from residence in another
country; and persons leaving institutions. The set of uncovered persons
constitutes only a small segment of the MEPS target population.
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MEPS began in 1996, and the utility of the survey for
analyzing health care trends expands with each additional year of data. However,
it is important to consider a variety of factors when examining trends over time
using MEPS. Statistical significance tests should be conducted to assess the
likelihood that observed trends may be attributable to sampling variation. The modification to the weight based on hospital stays potentially could affect some analyses of trends. The
length of time being analyzed should also be considered. In particular, large
shifts in survey estimates over short periods of time (e.g. from one year to the
next) that are statistically significant should be interpreted with caution,
unless they are attributable to known factors such as changes in public policy,
economic conditions, or MEPS survey methodology.
With respect to methodological considerations, in 2013
MEPS introduced an effort to obtain more complete information about health care
utilization from MEPS respondents with full implementation in early 2014 at the
start of the final rounds of data collection for 2013. This effort likely
resulted in improved data quality and a reduction in underreporting in 2013, but
could have some modest impact on analyses involving trends in utilization across
years.
There are also statistical factors to consider in
interpreting trend analyses. Looking at changes over longer periods of
time can provide a more complete picture of underlying trends. Analysts may wish
to consider using techniques to evaluate, smooth, or stabilize analyses of
trends using MEPS data such as comparing pooled time periods (e.g. 1996-97
versus 2012-13), working with moving averages, or using modeling techniques with
several consecutive years of MEPS data to test the fit of specified patterns
over time. Finally, researchers should be aware of the impact of multiple
comparisons on Type I error. Without making appropriate allowance for multiple
comparisons, undertaking numerous statistical significance tests of trends
increases the likelihood of concluding that a change has taken place when one
has not.
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This file is constructed for estimation of
utilization, expenditures, and sources of payment for other medical expenditures
and to allow for estimates for the number of persons who obtained medical items
in 2013.
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In contrast to the other types of event files, the
unit and/or period of time covered are not consistent across all records within
this file. More specifically, this file contains round-specific expenditure data
on purchases of eyeglasses or contact lenses and annual data on certain other
types of medical equipment, supplies, and services (see description below and
OMTYPEX variable in codebook for more details). Data are not collected on the
actual number of purchases of the items/services represented on this file, so it
is not possible to estimate the average expenditure per unit of service.
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Records for purchases of insulin and diabetic supplies
were included in the Other Medical Expenses event files for 1996-2004. Beginning
with the 2005 file, these records were excluded from the Other Medical Expenses
event file since the expenditures have always been included on the Prescribed
Medicines file. The Prescribed Medicines file is a more appropriate source for
estimates of both utilization and expenditures for insulin and diabetic
supplies. As a consequence, there are no records on this file where the variable
OMTYPEX = 2 or 3 (the values used in 1996-2004 to identify records for purchases
of insulin and diabetic supplies, respectively).
Eyeglasses and contact lenses: Each record on this
file where OMTYPEX = 1 contains information on total expenditures during a
specific round for eyeglasses and/or contact lenses
(a maximum of 3 records for a sample person). Variables for annual expenditure
data for eyeglasses/contact lenses (obtained by cumulating across round specific
data in this file) are included on the annual Full-Year Consolidated File.
Other medical equipment, supplies and services:
Each of the records in this file where OMTYPEX does not equal 1 contains
person-specific information on annual expenditures for a specific category of
medical equipment and supplies asked about in the survey. Estimates of the total
number of persons with expenditures for an item during the year are the sum of
the weight variable (PERWT13F) across relevant records (e.g., for ambulance
services, records where OMTYPEX = 4). Estimates of expenditure variables must be
weighted by PERWT13F to be nationally representative. For example, the estimate
for the total expenditures for ambulance services paid out of pocket is produced
by summing the product of the variables PERWT13F and OMSF13X across all the
events in the file where OMTYPEX = 4 as follows (the subscript ‘j’ identifies
each event and represents a numbering of events from 1 through the total number
of events in the file):
Σ Wj Xj,
where
Wj = PERWT13Fj (full-year weight
for the person associated with event j) and
Xj = OMSF13Xj (amount paid by
self/family for event j) where OMTYPEX = 4.
The estimate for the total annual expenditures for
ambulance services paid out of pocket per person with that type of expense is
produced as follows (the subscript ‘j’ identifies each event and represents a
numbering of events from 1 through the total number of events in the file):
Σ Wj Xj/Σ Wj, where
Wj = PERWT13Fj (full-year weight
for the person associated with event j) and
Xj = OMSF13Xj(amount
paid by self/family for event j) where OMTYPEX = 4.
This type of estimate and corresponding standard error
(SE) can be derived using an appropriate computer software package for complex
survey analysis such as SAS, Stata, SUDAAN or SPSS (meps.ahrq.gov/survey_comp/standard_errors.jsp).
Variables are contained on the full-year annual file for aggregate expenditures
across all of these types of services/items (OMTYPEX = 4-11 or 91), but it is
necessary to use this file to produce an annual estimate for a specific category
of service. Small sample sizes make it advisable to pool multiple years of MEPS
data to produce statistically reliable estimates for some of the items.
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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 negative 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., source of payment, flat fee, and zero expenditures)
are described in Section 2.5.5.2.
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The MEPS has a complex sample design. To obtain
estimates of variability (such as the standard error of sample estimates or
corresponding confidence intervals) for MEPS estimates, analysts need to take
into account the complex sample design of MEPS for both person-level and
family-level analyses. Several methodologies have been developed for estimating
standard errors for surveys with a complex sample design, including the
Taylor-series linearization method, balanced repeated replication, and jackknife
replication. Various software packages provide analysts with the capability of
implementing these methodologies. Replicate weights have not been developed for
the MEPS data. Instead, the variables needed to calculate appropriate standard
errors based on the Taylor-series linearization method are included on this file
as well as all other MEPS public use files. Software packages that permit the
use of the Taylor-series linearization method include SUDAAN, Stata, SAS
(version 8.2 and higher), and SPSS (version 12.0 and higher). For complete
information on the capabilities of each package, analysts should refer to the
corresponding software user documentation.
Using the Taylor-series linearization method, variance
estimation strata and the variance estimation PSUs within these strata must be
specified. The variables VARSTR and VARPSU on this MEPS data file serve to
identify the sampling strata and primary sampling units required by the variance
estimation programs. Specifying a “with replacement” design in one of the
previously mentioned computer software packages will provide estimated 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
number available. For variables of interest distributed throughout the country
(and thus the MEPS sample PSUs), one can generally expect to have at least 100
degrees of freedom associated with the estimated standard errors for national
estimates based on this MEPS database.
Prior to 2002, MEPS variance strata and PSUs were
developed independently from year to year, and the last two characters of the
strata and PSU variable names denoted the year. However, beginning with the 2002
Point-in-Time PUF, the variance strata and PSUs were developed to be compatible
with all future PUFs until the NHIS design changed. Thus, when pooling data
across years 2002 through the Panel 11 component of the 2007 files, the variance
strata and PSU variables provided can be used without modification for variance
estimation purposes for estimates covering multiple years of data. There were
203 variance estimation strata, each stratum with either two or three variance
estimation PSUs.
From Panel 12 of the 2007 files, a new set of variance
strata and PSUs were developed because of the introduction of a new NHIS design.
There are 165 variance strata with either two or three variance estimation PSUs
per stratum, starting from Panel 12. Therefore, there are a total of 368
(203+165) variance strata in the 2007 Full Year file as it consists of two
panels that were selected under two independent NHIS sample designs. Since both
MEPS panels in the Full Year 2008 file and beyond are based on the new NHIS
design, there are only 165 variance strata. These variance strata (VARSTR
values) have been numbered from 1001 to 1165 so that they can be readily
distinguished from those developed under the former NHIS sample design in the
event that data are pooled for several years.
If analyses call for pooling MEPS data across several
years, in order to ensure that variance strata are identified appropriately for
variance estimation purposes, one can proceed as follows:
- When pooling any year from 2002 or later, one can use the
variance strata numbering as is.
- When pooling any year from 1996 to 2001 with any year from
2002 or later, use the H36 file.
- A new H36 file will be constructed in the future to allow
pooling of 2007 and later years with 1996 to 2006.
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Data from this file can be used alone or in
conjunction with other files for different analytic purposes. This section
summarizes various scenarios for merging/linking MEPS event files. Each MEPS
panel can also be linked back to the previous years’ National Health Interview
Survey public use data files. For information on obtaining MEPS/NHIS link files
please see
meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
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Merging characteristics of interest from other MEPS
files (e.g., 2013 Full-Year Consolidated File or 2013 Prescribed Medicines)
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 Other
Medical Expenses event file. This procedure is shown below. The MEPS 2013
Appendix File, HC-160I, provides additional details on how to merge other MEPS
data files.
- Create data set PERSX by sorting the 2013 Full-Year
Consolidated File, by the person identifier, DUPERSID. Keep only
variables to be merged onto the other medical events file and
DUPERSID.
- Create data set OMEXP by sorting the other medical event
file by person identifier, DUPERSID.
- Create final data set NEWOME by merging these two files by
DUPERSID, keeping only records on the other medical event file.
The following is an example of SAS code which
completes these steps:
PROC SORT DATA=HCXXX (KEEP=DUPERSID AGE31X AGE42X
AGE53X SEX RACEV1X EDRECODE EDUYRDG)
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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The RXLK file provides a link from the MEPS event
files to the 2013 Prescribed Medicine Event File. When using RXLK, data
users/analysts should keep in mind that one other medical record can link to
more than one prescribed medicine record. Conversely, a prescribed medicine
event may link to more than one other medical record. When this occurs, it is up
to the data user/analyst to determine how the prescribed medicine expenditures
should be allocated among those medical events. For detailed linking examples,
including SAS code, data users/analysts should refer to the MEPS 2013 Appendix
File, HC-160I.
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Conditions data are not collected for Other Medical
events; therefore, this file cannot be linked to the Conditions File.
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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.
Ezzati-Rice, T.M., Rohde, F., Greenblatt, J., Sample
Design of the Medical Expenditure Panel Survey Household Component, 1998–2007.
Methodology Report No. 22. March 2008. Agency for Healthcare Research and
Quality, Rockville, MD
Monheit, A.C., Wilson, R., and Arnett, III, R.H.
(Editors) (1999). Informing American Health Care Policy. 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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VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-160C: 2013 OTHER MEDICAL EXPENSES
Survey Administration Variables
| Variable |
Description |
Source |
| DUID |
Dwelling unit ID |
Assigned in sampling |
| PID |
Person number |
Assigned in sampling |
| DUPERSID |
Person ID (DUID + PID) |
Assigned in sampling |
| EVNTIDX |
Event ID |
Assigned in Sampling |
| EVENTRN |
Event round number |
CAPI derived |
| FFEEIDX |
Flat fee ID |
CAPI derived |
| PANEL |
Panel number |
Constructed |
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Other Medical Events Variables
| 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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Flat Fee Variables
| Variable |
Description |
Source |
| FFOMTYPE |
Flat Fee Bundle |
Constructed |
| FFBEF13 |
Total # of visits in FF before 2013 |
FF05 |
| FFTOT14 |
Total # of visits in FF after 2013 |
FF10 |
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Imputed Expenditure Variables
| Variable |
Description |
Source |
| OMSF13X |
Amount paid, family (Imputed) |
CP Section (Edited) |
| OMMR13X |
Amount paid, Medicare (Imputed) |
CP Section (Edited) |
| OMMD13X |
Amount paid, Medicaid (Imputed) |
CP Section (Edited) |
| OMPV13X |
Amount paid, private insurance (Imputed) |
CP Section (Edited) |
| OMVA13X |
Amount paid, Veterans/CHAMPVA (Imputed) |
CP Section (Edited) |
| OMTR13X |
Amount paid, TRICARE (Imputed) |
CP Section (Edited) |
| OMOF13X |
Amount paid, other federal (Imputed) |
CP Section (Edited) |
| OMSL13X |
Amount paid, state & local government (Imputed) |
CP Section (Edited) |
| OMWC13X |
Amount paid, workers’ compensation (Imputed) |
CP Section (Edited) |
| OMOR13X |
Amount paid, other private insurance (Imputed) |
Constructed |
| OMOU13X |
Amount paid, other public insurance (Imputed) |
Constructed |
| OMOT13X |
Amount paid, other insurance (Imputed) |
CP Section (Edited) |
| OMXP13X |
Sum of OMSF13X–OMOT13X (Imputed) |
Constructed |
| OMTC13X |
Household reported
total charge (Imputed) |
CP Section (Edited) |
| IMPFLAG |
Imputation status |
Constructed |
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Weights
| Variable |
Description |
Source |
| PERWT13F |
Expenditure file person weight, 2013 |
Constructed |
| VARSTR |
Variance estimation stratum, 2013 |
Constructed |
| VARPSU |
Variance estimation PSU, 2013 |
Constructed |
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|
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