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MEPS HC-059F: 2001 Outpatient Department Visits
January 2004
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 Using MEPS Data for Trend and Longitudinal
Analysis
2.2 Codebook Structure
2.3 Reserved Codes
2.4 Codebook Format
2.5 Variable Source and Naming Conventions
2.5.1 General
2.5.2 Expenditure and Source of Payment Variables
2.6 File Contents
2.6.1 Survey Administration Variables
2.6.1.1 Person Identifiers (DUID, PID, DUPERSID)
2.6.1.2 Record Identifiers (EVNTIDX, FFEEIDX)
2.6.1.3 Round Indicator (EVENTRN)
2.6.2 MPC Data Indicator (MPCDATA)
2.6.3 Outpatient Visit Event Variables
2.6.3.1 Visit Details (OPDATEYR-VSTRELCN)
2.6.3.2 Treatment, Services, Procedures, and Prescription
Medicines (PHYSTH - MEDPRESC)
2.6.3.3 VA Facility (VAPLACE)
2.6.4 Conditions and Procedures Codes (OPICD1X-OPICD4X, OPPRO1X),
and Clinical Classification Codes (OPCCC1X-OPCCC4X)
2.6.5 Flat Fee Variables (FFEEIDX, FFOPTYPE, FFBEF01, FFTOT02)
2.6.5.1 Definition of Flat Fee Payments
2.6.5.2 Flat Fee Variable Descriptions
2.6.5.2.1 Flat Fee ID (FFEEIDX)
2.6.5.2.2 Flat Fee Type (FFOPTYPE)
2.6.5.2.3 Counts of Flat Fee Events that Cross Years
(FFBEF01, FFTOT02)
2.6.5.3 Caveats of Flat Fee Groups
2.6.6 Expenditure Data
2.6.6.1 Definition of Expenditures
2.6.6.2 Data Editing and Imputation Methodologies of
Expenditure Variables
2.6.6.2.1 General Data Editing
Methodology
2.6.6.2.2 General Hot-Deck Imputation
2.6.6.2.3 Outpatient Visit Data Editing and Imputation
2.6.6.3 Capitation Imputation
2.6.6.4 Imputation Flag (IMPFLAG)
2.6.6.5 Flat Fee Expenditures
2.6.6.6 Zero Expenditures
2.6.6.7 Discount Adjustment Factor
2.6.6.8 Sources of Payment
2.6.6.9 Imputed Outpatient Expenditure Variables
2.6.6.9.1 Outpatient Facility Expenditure Variables
(OPFSF01X-OPFOT01X, OPFTC01X, OPFXP01X)
2.6.6.9.2 Outpatient Physician Expenditures (OPDSF01X -
OPDOT01X, OPDTC01X, OPDXP01X)
2.6.6.9.3 Total Expenditures and
Charges for Outpatient Visits (OPXP01X, OPTC01X)
2.6.6.10 Rounding
3.0 Sample Weight (PERWT01F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 5 Weight
3.2.2 MEPS Panel 6 Weight
3.2.3 The Final Weight for 2001
3.2.4 Coverage
4.0 Strategies for Estimation
4.1 Variables with Missing Values
4.2 Basic Estimates of Utilization, Expenditures and Sources of
Payment
4.3 Estimates of the Number of Persons with Outpatient Visit Events
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with
Outpatient Visit 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 (VARSTR01, VARPSU01)
5.0 Merging/Linking MEPS Data Files
5.1 Linking a 2001 Person-Level File to the 2001 Outpatient Visit
File
5.2 Linking the 2001 Outpatient Visits File to the 2001 Medical
Conditions File and/or the 2001 Prescribed Medicines File
5.2.1 Limitations/Caveats of RXLK (the Prescribed Medicine Link
File)
5.2.2 Limitations/Caveats of CLNK (the Medical Conditions Link
File)
References
D. Variable-Source Crosswalk
A. Data Use Agreement
Individual identifiers have been removed from the microdata contained in the
files in this release. Nevertheless, under sections 308 (d) and 903 (c) of the
Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected
by the Agency for Healthcare Research and Quality (AHRQ) and/or the National
Center for Health Statistics (NCHS) may not be used for any purpose other than
for the purpose for which they were supplied; any effort to determine the
identity of any reported cases is prohibited by law.
Therefore in accordance with the above referenced Federal statute, it is
understood that:
- No one is to use the data in this data set in any way except for
statistical reporting and analysis.
- If the identity of any person or establishment should be discovered
inadvertently, then (a) no use will be made of this knowledge, (b) the
Director, Office of Management, AHRQ will be advised of this incident, (c)
the information that would identify any individual or establishment will
be safeguarded or destroyed, as requested by AHRQ, and (d) no one else
will be informed of the discovered identity.
- No one will attempt to link this data set with individually
identifiable records from any data sets other than the Medical Expenditure
Panel Survey or the National Health Interview Survey.
By using these data you signify your agreement to comply with the
above-stated statutorily based requirements, with the knowledge that
deliberately making a false statement in any matter within the jurisdiction of
any department or agency of the Federal Government violates
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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B. 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 systems.
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 2 ½
-year period. Using computer-assisted personal interviewing (CAPI) technology,
data on medical expenditures and use for two calendar years are collected from
each household. This series of data collection rounds is launched each
subsequent year on a new sample of households to provide overlapping panels of
survey data and, when combined with other ongoing panels, will provide
continuous and current estimates of health care expenditures.
The sampling frame for the MEPS HC is drawn from respondents to NHIS. 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 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.
Selected printed documents 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 you are requesting.
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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C. Technical and Programming Information
1.0 General Information
This documentation describes one in a series of public use event files from
the 2001 Medical Expenditure Panel Survey (MEPS) Household (HC) and Medical
Provider Components (MPC). Released as an ASCII data file and SAS transport
file, this public use file provides detailed information on outpatient visits
for a nationally representative sample of the civilian noninstitutionalized
population of the United States and can be used to make estimates of outpatient
utilization and expenditures for calendar year 2001. As illustrated below, this
file consists of MEPS survey data obtained in the 2001 portion of Round 3 and
Rounds 4 and 5 for Panel 5, as well as Rounds 1, 2 and the 2001 portion of Round
3 for Panel 6 (i.e., the rounds for the MEPS panels covering calendar year
2001).
301 Moved Permanently
301 Moved Permanently
Each record on this event file represents a unique outpatient department
event; that is, an outpatient event reported by the household respondent. In
addition to expenditures related to this event, each record contains
household-reported medical conditions and procedures associated with the
outpatient visit.
Annual counts of outpatient visits are based entirely on household reports.
Information from the MEPS MPC is used to supplement expenditure and payment data
reported by the household, and does not affect use estimates.
Data from this event file can be merged with other MEPS HC data files, for
purposes of appending person characteristics such as demographic or health
insurance characteristics to each outpatient visit record.
This file can also be used to construct summary variables of expenditures,
sources of payment, and related aspects of outpatient visits. Aggregate annual
person-level information on the use of outpatient departments and other health
services use is provided on the MEPS 2001 Full Year Consolidated Data File,
where each record represents a MEPS sampled person.
This documentation offers a brief overview of the types and levels of data
provided, and the content and structure of the files and the codebooks. It
contains the following sections:
Data File Information
Sample Weights
Strategies for Estimation
Merging/linking MEPS Data Files
References
Variable - Source Crosswalk
Any variables not found on this file but released on previous years' files
were excluded because they contained only missing data.
For more information on MEPS HC survey design see S. Cohen, 1997; J. Cohen,
1997; and S. Cohen, 1996. For information on the MEPS MPC design, see S. Cohen,
1998. Copies of the HC and the MPC survey instruments used to collect the
information on the Outpatient Department Visit file are 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 2001 Outpatient Department Visit public use data set consists of one
event-level data file. The file contains characteristics associated with the
outpatient event and imputed expenditure data. For users wanting to impute
expenditures, pre-imputed data are available through the Center for Financing,
Access and Cost Trends (CFACT) data center. Please visit the CFACT data center
web site 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 2001 outpatient public use data set contains 16,274 outpatient event
records; of these records, 15,937 are associated with persons having a positive
person-level weight (PERWT01F). This file includes outpatient event records for
all household survey respondents who resided in eligible responding households
and reported at least one outpatient event. Each record represents one
household-reported outpatient event that occurred during calendar year 2001.
Outpatient visits known to have occurred after December 31, 2001 are not
included on this file. Some household respondents may have multiple outpatient
events and thus will be represented in multiple records on this file. Other
household respondents may have reported no outpatient events and thus will have
no records on this file. These data were collected during the 2001 portion of
Round 3, and Rounds 4 and 5 for Panel 5, as well as Rounds 1, 2, and the 2001
portion of Round 3 for Panel 6 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 2001 eligibility (i.e., persons with a positive 2001
full-year person-level weight (PERWT01F > 0)), or
- Be an eligible member of a family all of whose key in-scope members
have a positive person-level weight (PERWT01F > 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 (FAMWT01F
>0). Note that FAMIDYR and FAMWT01F are variables on the 2001
Population Characteristics file.
Persons with no outpatient visit events for 2001 are not included on this
file but are represented on the 2001 MEPS person-level file. A codebook for the
data file is provided in files H55CB.PDF and H55CB.ASP.
Each outpatient visit record includes the following information: date of the
visit; whether or not the survey respondent saw the doctor; type of care
received; type of services (i.e., lab test, sonogram or ultrasound, x-rays, etc)
received; medicines prescribed during the visit; flat fee information; imputed
sources of payment; total payment and total charge; and a full-year person-level
weight.
Data from this file can be merged with the MEPS 2001 Full Year Population
Characteristics file using the unique person identifier, DUPERSID, to append
person characteristics, such as demographic or health insurance characteristics,
to each record. Outpatient visit events on this file can also be linked to the
MEPS 2001 Medical Conditions File and to the MEPS 2001 Prescribed Medicines
File. Please see Section 5.0 for details on how to merge MEPS data files.
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2.1 Using MEPS Data for Trend and Longitudinal Analysis
MEPS began in 1996 and several annual data files have been released. As more
years of data are produced, MEPS will become increasingly valuable for examining
health care trends. 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 are
attributable to sampling variation. MEPS expenditures estimates are especially
sensitive to sampling variation due to the underlying skewed distribution of
expenditures. For example, 1 percent of the population accounts for about
one-quarter of all expenditures. The extent to which observations with extremely
high expenditures are captured in the MEPS sample varies from year to year
(especially for smaller population subgroups), which can produce substantial
shifts in estimates of means or totals that are simply an artifact of the
sample(s). 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 or MEPS survey methodology. 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 smooth or stabilize trends
analyses of MEPS data such as pooling time periods for comparison (e.g. 1996-97
versus 1998-99), 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 because performing numerous statistical significance
tests of trends increases the likelihood of inappropriately concluding a change
is statistically significant.
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2.2 Codebook Structure
For each variable on the Outpatient Events file, both weighted and unweighted
frequencies are provided in the codebook (files H59FCB.HCB and H59FCB.ASP). The
codebook and data file sequence list variables in the following order:
Unique person identifiers
Unique outpatient visit identifiers
Outpatient characteristic variables
ICD-9-CM condition and procedure codes
Clinical Classification Software (CCS) codes
Imputed expenditure variables
Weight and variance estimation variables
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2.3 Reserved Codes
The following reserved code values are used:
| Value |
Definition |
| -1 INAPPLICABLE |
Question was not asked due to skip pattern. |
| -7 REFUSED |
Question was asked and respondent refused to answer question. |
| -8 DK |
Question was asked and respondent did not know answer. |
| -9 NOT ASCERTAINED |
Interviewer did not record the data. |
Generally, values of -1, -7, -8, and -9 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: <http://www.meps.ahrq.gov/mepsweb/survey_comp/survey.jsp>).
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2.4 Codebook Format
This codebook describes an ASCII data set (although the data are also being
provided in a SAS transport file). The following codebook items are provided for
each variable:
| Identifier |
Description |
| Name |
Variable name (maximum of 8 characters) |
| Description |
Variable descriptor (maximum 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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2.5 Variable Source and Naming Conventions
In general, variable names reflect the content of the variable, with an
eight-character limitation. All imputed/edited variables end with a "X".
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2.5.1 General
Variables on this file were derived from the HC questionnaire itself, the MPC
data collection instrument, derived from CAPI, or assigned in sampling. 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;
- FF- Flat Fee section
- CP- Charge Payment section
- OP - Outpatient Section
- Variables constructed from multiple questions using complex algorithms
are labeled "Constructed" in the "Source" column; and
- Variables which have been imputed are so indicated.
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2.5.2 Expenditure and Source of Payment
Variables
The names of the expenditure and source of payment variables follow a
standard convention, are eight 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 the 12 source of payment variables are named in
the following way:
The first two characters indicate the type of event:
| IP - inpatient stay |
OB - office-based visit |
| ER - emergency room visit |
OP - outpatient visit |
| HH - home health visit |
DV - dental visit |
| OM - other medical equipment |
RX - prescribed medicine |
For expenditure variables on these files, the third character indicates
whether the expenditure (or amount paid) is associated with the facility (F) or
the physician (D).
In the case of the source of payment variables, the fourth and fifth
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 |
OR - other private |
| TR - TRICARE |
OU - other public |
|
XP - sum of payments |
In addition, the total charge variable is indicated by TC in the variable
name.
The sixth and seventh characters indicate the year (01). The eighth
character, "X", indicates whether the variable is edited/imputed.
For example, OPFSF01X is the edited/imputed amount paid by self or family for
the facility portion of the expenditure associated with an outpatient visit.
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2.6 File Contents
2.6.1 Survey Administration Variables
2.6.1.1 Person Identifiers (DUID, PID,
DUPERSID)
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 2001 Full Year
Population Characteristics File.
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2.6.1.2 Record Identifiers (EVNTIDX, FFEEIDX)
EVNTIDX uniquely identifies each outpatient event (i.e., each record on the
outpatient file) and is the variable required to link outpatient events to data
files containing details on conditions and/or prescribed medicines (MEPS 2001
Medical Condition file and MEPS 2001 Prescribed Medicine file, respectively).
For details on linking see Section 5.0 or the MEPS 2001 Appendix File, HC-059I.
FFEEIDX is a constructed variable that uniquely identifies a flat fee group,
that is, all events that were part of a flat fee payment. For example, if a
patient receives stitches in an outpatient visit and comes back to have the
stitches removed ten days later in a follow-up outpatient visit, both visits are
covered under one flat fee dollar amount. These two events (the initial
outpatient visit and the subsequent outpatient visit) would have the same value
for FFEEIDX.
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2.6.1.3 Round Indicator (EVENTRN)
EVENTRN indicates the round in which the outpatient event was reported.
Please note: Rounds 3, 4, and 5 are associated with MEPS survey data collected
from Panel 5. Likewise, Round 1, 2, and 3 are associated with data collected
from Panel 6.
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2.6.2 MPC Data Indicator (MPCDATA)
MPCDATA is a constructed variable that indicates whether or not MPC data were
collected for the outpatient visit. While all outpatient events are sampled into
the Medical Provider Component, not all outpatient event records have MPC data
associated with them. This is dependent upon the cooperation of the household
respondent to provide permission forms to contact the outpatient facility as
well as the cooperation of the outpatient facility to participate in the survey.
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2.6.3 Outpatient Visit Event Variables
This file contains variables describing outpatient events reported by
respondents in the Outpatient Department section of the MEPS HC questionnaire.
The questionnaire contains specific probes for determining details about the
outpatient visit. These variables have not been edited.
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2.6.3.1 Visit Details (OPDATEYR-VSTRELCN)
When a person reported having had a visit to a hospital outpatient department
or special clinic, the date of the outpatient visit was reported (OPDATEYR,
OPDATEMM, OPDATEDD). Also reported is whether the person actually saw the
provider or talked to the provider on the telephone (SEETLKPV). Expenditures for
telephone calls (SEETLKPV=2, n=20) are set to -1. It also
establishes whether the person saw or spoke to a medical doctor
or not (SEEDOC). If the person did not see a physician (i.e., medical doctor),
the respondent was asked to identify the type of medical person that was seen (MEDPTYPE).
The type of care the person received (VSTCTGRY), and whether or not the visit or
telephone call was related to a specific condition (VSTRELCN) were also
determined.
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2.6.3.2 Treatment, Services, Procedures, and
Prescription Medicines (PHYSTH - MEDPRESC)
Types of treatment received during the outpatient visit include physical
therapy (PHYSTH), occupational therapy (OCCUPTH), speech therapy (SPEECHTH),
chemotherapy (CHEMOTH), radiation therapy (RADIATTH), kidney dialysis (KIDNEYD),
IV therapy (IVTHER), drug or alcohol treatment (DRUGTRT), allergy shots (RCVSHOT),
and psychotherapy/counseling (PSYCHOTH). Services received during the visit
included whether or not the person received lab tests (LABTEST), a sonogram or
ultrasound (SONOGRAM), x-rays (XRAYS), a mammogram (MAMMOG), an MRI or CAT scan
(MRI), an electrocardiogram (EKG), an electroencephalogram (EEG), a vaccination
(RCVVAC), anesthesia (ANESTH), or other diagnostic tests or exams (OTHSVCE).
Whether or not a surgical procedure was performed during the visit was asked (SURGPROC).
Finally, the questionnaire determined if a medicine was prescribed for the
person during the visit (MEDPRESC).
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2.6.3.3 VA Facility (VAPLACE)
VAPLACE is a constructed variable that indicates whether the outpatient
department or clinic was a VA facility. This variable only has valid data for
providers that were sampled into the Medical Provider Component. All other
providers are classified as "No".
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2.6.4 Conditions and Procedures Codes
(OPICD1X-OPICD4X, OPPRO1X), and Clinical Classification Codes
(OPCCC1X-OPCCC4X)
Information on household-reported medical conditions and procedures
associated with each outpatient visit is provided on this file. There are up to
four condition and CCS codes (OPICD1X-OPICD4X, OPCCC1X-OPCCC4X) and one
procedure code (OPPRO1X) listed for each outpatient visit. In order to obtain
complete information on conditions and procedures associated with an event, the
analyst must link to the Medical Conditions File. Please see Section 5.0 for
details on how to link this file to the Medical Conditions File. The user should
note that due to confidentiality restrictions, provider-reported condition
information is not publicly available.
The medical conditions reported by the Household Component respondent were
recorded by the interviewer as verbatim text, which were then coded to
fully-specified 2001 ICD-9-CM codes, including medical condition and V codes
(see Health Care Financing Administration, 1980), by professional coders.
Although codes were verified and error rates did not exceed 2.5 percent for any
coder, data users/analysts should not presume this level of precision in the
data; the ability of household respondents to report condition data that can be
coded accurately should not be assumed (see Cox and Cohen, 1985; Cox and Iachan,
1987; Edwards, et al, 1994; and Johnson and Sanchez, 1993). For detailed
information on conditions, please refer to the documentation on the Medical
Conditions File.
The ICD-9-CM conditions and procedures codes were aggregated into clinically
meaningful categories. These categories, included on the file as
OPCCC1X-OPCCC4X, were generated using Clinical Classification Software [formerly
known as Clinical Classifications for Health Care Policy Research (CCHPR)], (Elixhauser,
et al., 1998), which aggregates conditions and V-codes into 260 mutually
exclusive categories, most of which are clinically homogeneous.
In order to preserve respondent confidentiality, nearly all of the condition
codes provided on this file have been collapsed from fully-specified codes to
three-digit code categories. The reported ICD-9-CM code values were mapped to
the appropriate clinical classification category prior to being collapsed to the
three-digit categories.
The conditions and procedures codes (and clinical classification codes)
linked to each outpatient visit are sequenced in the order in which the
conditions were reported by the household respondent, which was in order of
input into database and not in order of importance or severity. Data
users/analysts who use the MEPS 2001 Medical Conditions file in conjunction with
this outpatient visit file should note that the order of conditions on this file
is not identical to that on the Medical Conditions file.
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2.6.5 Flat Fee Variables (FFEEIDX, FFOPTYPE, FFBEF01,
FFTOT02)
2.6.5.1 Definition of Flat Fee Payments
A flat fee is the fixed dollar amount a person is charged for a package of
health care services provided during a defined period of time. Examples would
be: an obstetrician's fee covering a normal delivery, as well as pre- and
post-natal care; or a surgeon's fee covering surgical procedure along with
post-surgical care. A flat fee group is the set of medical services (i.e.,
events) that are covered under the same flat fee payment. The flat fee groups
represented on this file include flat fee groups where at least one of the
health care events, as reported by the HC respondent, occurred during 2001. By
definition a flat fee group can span multiple years. Furthermore, a single
person can have multiple flat fee groups.
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2.6.5.2 Flat Fee Variable Descriptions
2.6.5.2.1 Flat Fee ID (FFEEIDX)
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 2001 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 FFEEIDX is not a variable on those event files.
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2.6.5.2.2 Flat Fee
Type (FFOPTYPE)
FFOPTYPE indicates whether the 2001 outpatient visit is the "stem" or "leaf"
of a flat fee group. A stem (records with FFOPTYPE = 1) is the initial medical
service (event) which is followed by other medical events that are covered under
the same flat fee payment. The leaves of the flat fee group (records with
FFOPTYPE = 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. For the outpatient visits that are not part
of a flat fee payment, the FFOPTYPE is set to -1, "INAPPLICABLE."
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2.6.5.2.3 Counts
of Flat Fee Events that Cross Years (FFBEF01, FFTOT02)
As described above, a flat fee payment covers multiple events and the
multiple events could span multiple years. For situations where the outpatient
visit occurred in 2001 as a part of a group of events, and some of the events
occurred before or after 2001, counts of
the known events are provided on the outpatient visit record. Variables
indicating events that occurred before or after 2001 are as follows:
FFBEF01 - total number of pre-2001 events in the same flat fee group as
the 2001 outpatient visit. This count would not include the 2001
outpatient visit(s).
FFTOT02 - the number of 2002 outpatient visits expected to be in the
same flat fee group as the outpatient visit record that occurred in 2001.
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2.6.5.3 Caveats of
Flat Fee Groups
There are 595 outpatient visits 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 2001 but the remaining visits that were part of this flat fee group
occurred in 2002. In this case, the 2001 flat fee group represented on this file
would consist of one event (the stem). The 2002 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
2000 but subsequent visits occurred during 2001. In this case, the initial visit
would not be represented on the file. This 2001 flat fee group would then only
consist of one or more leaf records and no stem. Another reason for which a flat
fee group would not have a stem and at least one leaf record is that the stem or
leaves could have been reported as different event types. Outpatient and
Office-based medical provider visits are the only two event types allowed in a
single flat fee group. The stem may have been reported as an outpatient
department visit and the leaves may have been reported as office-based medical
provider visits.
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2.6.6 Expenditure Data
2.6.6.1 Definition of Expenditures
Expenditures on this file refer to what is paid for outpatient services. More
specifically, expenditures in MEPS are defined as the sum of payments for care
received for each outpatient visit, 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, the estimates do not incorporate any payment not directly
tied to specific medical care visits, such as bonuses or retrospective payment
adjustments paid by third party payers. Another general change from the two
prior surveys is that charges associated with uncollected liability, bad debt,
and charitable care (unless provided by a public clinic or hospital) are not
counted as expenditures because there are no payments associated with those
classifications. For details on expenditure definitions, please reference the
following: "Informing American Health Care Policy" (Monheit, et al., 1999). AHRQ
has developed factors to apply to the 1987 NMES expenditure data to facilitate
longitudinal analysis. These factors can be assessed via the CFACT data center.
For more information, see the data center section of the MEPS web site <http://www.meps.ahrq.gov>.
Expenditure data related to outpatient visits are broken out by facility and
separately billing doctor expenditures. This file contains six categories of
expenditure variables per visit: basic hospital outpatient facility expenses;
expenses for doctors who billed separately from the outpatient facility for any
services provided during the outpatient visit; total expenses, which is the sum
of the facility and physician expenses; facility charge; physician charge, total
charges, which is the sum of the facility and physician charges. If examining
trends in MEPS expenditures or performing longitudinal analysis on MEPS
expenditures, please refer to section C, sub-section 2.1 for more information.
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2.6.6.2 Data Editing and Imputation Methodologies of Expenditure Variables
The expenditure data included on this file were derived from both the MEPS
Household (HC) and the Medical Provider Components (MPC). The MPC contacted
medical providers identified by household respondents. The charge and payment
data from medical providers were used in the expenditure imputation process to
supplement missing household data. For all outpatient visits, MPC data were used
if complete; otherwise, HC data were used if complete. Missing data for
outpatient visits where HC data were not complete and MPC data were not
collected or complete were derived through the imputation process.
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2.6.6.2.1 General Data Editing Methodology
Logical edits were used to resolve internal inconsistencies and other
problems in the HC and MPC survey-reported data. The edits were designed to
preserve partial payment data from households and providers, and to identify
actual and potential sources of payment for each household-reported event. In
general, these edits accounted for outliers, co-payments 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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2.6.6.2.2 General Hot-Deck Imputation
A weighted sequential hot-deck procedure was used to impute for missing
expenditures as well as total charge. This procedure uses survey data from
respondents to replace missing data, while taking into account 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. Within each event type file, separate imputations were performed for
flat fee and simple events. After the imputations were finished, visits to
physician and non-physician providers were combined into a single medical
provider file. The two categories of home care also were combined into a single
home health file.
Expenditures for services provided by separately billing doctors in hospital
settings were also edited and imputed. These expenditures are shown separately
from hospital facility charges for hospital inpatient, outpatient, and emergency
room care.
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2.6.6.2.3 Outpatient Visit Data Editing and
Imputation
Facility expenditures for outpatient services were developed in a sequence of
logical edits and imputations. "Household" edits were applied to sources and
amounts of payment for all events reported by HC respondents. "MPC" edits were
applied to provider-reported sources and amounts of payment for records matched
to household-reported events. Both sets of edits were used to correct obvious
errors in the reporting of expenditures. After the data from each source were
edited, a decision was made as to whether household- or MPC-reported information
would be used in the final editing and hot-deck imputations for missing
expenditures. The general rule was that MPC data would be used where a
household-reported event corresponded to an MPC-reported event (i.e., a matched
event), since providers usually have more complete and accurate data on sources
and amounts of payment than households.
One of the more important edits separated flat fee events from simple events.
This edit was necessary because groups of events covered by a flat fee (i.e., a
flat fee bundle) were edited and imputed separately from individual events
covered by a single charge (i.e., simple events). (See Section 2.6.5 for more
details on flat fee groups).
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 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 eight recipient categories in which all events had
a common extent of missing data. Separate hot-deck imputations were performed on
events in each recipient category, and the donor pool was restricted to events
with complete expenditures from the MPC. The donor pool restriction was used
even though some unmatched events had complete household-reported expenditures.
These events were not allowed to donate information to other events because the
MPC data were considered to be more reliable.
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 event among
complete events (donors) is not represented among incomplete events
(recipients).
Expenditures for services provided by separately billing doctors in hospital
settings were also edited and imputed. These expenditures are shown separately
from hospital facility charges for hospital inpatient, outpatient, and
outpatient care.
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2.6.6.3 Capitation Imputation
The imputation process was also used to make expenditure estimates at the
event level for events that were paid on a capitated basis. The capitation
imputation procedure was designed as a reasonable approach to complete
event-level expenditures for respondents in managed care plans. This procedure
was conducted in two stages. First, HMO events reported in the MPC as covered by
capitation arrangements were imputed using similar HMO events paid on a
fee-for-service, with total charge as a key variable. Then this completed set of
MPC events was used as the donor pool for unmatched household-reported events
for sample persons in HMOs. By using this strategy, capitated HMO events were
imputed as if the provider were reimbursed from the HMO on a discounted
fee-for-service basis.
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2.6.6.4 Imputation Flag (IMPFLAG)
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
IMPFLAG=3 fully imputed
IMPFLAG=4 partially imputed
IMPFLAG=5 complete MPC data through capitation imputation
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2.6.6.5 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 facility payments, physician's expenditures may be still present. Thus, if
the first visit in the flat fee group occurred prior to 2001, all of the events
that occurred in 2001 will have zero payments. Conversely, if the first event in
the flat fee group occurred at the end of 2001, the total expenditure for the
entire flat fee group will be on that event, regardless of the number of events
it covered after 2001. See Section 2.6.5 for details on the flat fee variables.
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2.6.6.6 Zero Expenditures
There are some outpatient events reported by respondents where the payments
were zero. This could occur for several reasons including (1) free care was
provided, (2) bad debt was incurred, (3) care was covered under a flat fee
arrangement beginning in an earlier year, or (4) follow-up visits were provided
without a separate charge (e.g., after a surgical procedure). If all of the
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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2.6.6.7 Discount Adjustment Factor
An adjustment was also applied to some HC-reported expenditure data because
an evaluation of matched HC/MPC data showed that respondents who reported that
charges and payments were equal were often unaware that insurance payments for
the care had been based on a discounted charge. To compensate for this
systematic reporting error, a weighted sequential hot-deck imputation procedure
was implemented to determine an adjustment factor for HC-reported insurance
payments when charges and payments were reported to be equal. As for the other
imputations, selected predictor variables were used to form groups of donor and
recipient events for the imputation process.
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2.6.6.8 Sources of Payment
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 or family,
- Medicare,
- Medicaid,
- Private Insurance,
- Veterans Administration, 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 insurance, 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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2.6.6.9 Imputed Outpatient Expenditure Variables
This file contains two sets of imputed expenditure variables: facility
expenditures and physician expenditures.
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2.6.6.9.1 Outpatient Facility Expenditure Variables
(OPFSF01X-OPFOT01X, OPFTC01X, OPFXP01X)
Outpatient visit expenses include all expenses for treatment, services,
tests, diagnostic and laboratory work, x-rays, and similar charges, as well as
any physician services included in the hospital outpatient visit charge.
OPFSF01X - OPFOT01X are the 12 sources of payment. OPFTC01X is the total
charge, and OPFXP01X is the sum of the 12 sources of payment for the Outpatient
Facility expenditures. The 12 sources of payment are: self/family (OPFSF01X),
Medicare (OPFMR01X), Medicaid (OPFMD01X), private insurance (OPFPV01X), Veterans
Administration (OPFVA01X), TRICARE (OPFTR01X), other Federal sources (OPFOF01X),
State and Local (non-federal) government sources (OPFSL01X), Worker's
Compensation (OPFWC01X), other private insurance (OPFOR01X), other public
insurance (OPFOU01X), and other insurance (OPFOT01X). Please note that where an
outpatient visit record is linked to a hospital inpatient stay record, OPFTC01X
has been zeroed out.
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2.6.6.9.2 Outpatient Physician Expenditures
(OPDSF01X - OPDOT01X, OPDTC01X, OPDXP01X)
Separately billing doctor (SBD) expenses typically cover services provided to
patients in hospital settings by providers like anesthesiologists, radiologists,
and pathologists, whose charges are often not included in the outpatient
facility bill.
For physicians who bill separately (i.e., outside the outpatient facility
bill), a separate data collection effort within the Medical Provider Component
was performed to obtain the same set of expenditure information from each
separately billing doctor. It should be noted that there could be several
separately billing doctors associated with a medical event. For example, an
outpatient visit could have a radiologist and a pathologist associated with it.
If their services are not included in the outpatient visit bill then this is one
medical event with 2 separately billing doctors. The imputed expenditure
information associated with the separately billing doctors was summed to the
event level and is provided on the file. OPDSF01X - OPDOT01X are the 12 sources
of payment, OPDXP01X is the sum of the 12 sources of payments, and OPDTC01X is
the physician(s) total charge.
Data users/analysts need to take into consideration whether to analyze
facility and SBD expenditures separately, combine them within service
categories, or collapse them across service categories (e.g., combine SBD
expenditures with expenditures for physician visits to offices and/or outpatient
departments).
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2.6.6.9.3 Total Expenditures and Charges for
Outpatient Visits (OPXP01X, OPTC01X)
Data users/analysts interested in total expenditures should use the variable
OPXP01X, which includes both facility and physician amounts. Those interested in
total charges should use the variable OPTC01X (see Section 2.5.6.2 for an
explanation of the "charge" concept).
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2.6.6.10 Rounding
Expenditure variables have been rounded to the nearest penny. Person-level
expenditure information released on the MEPS 2001 Person-Level and Expenditure
File were rounded to the nearest dollar. It should be noted that using the MEPS
2001 event files to create person-level totals will yield slightly
different totals than those found on the person-level expenditure file. These
differences are due to rounding only. Moreover, in some instances, the number of
persons having expenditures on the event files for a particular source of
payment may differ from the number of persons with expenditures on the
person-level expenditure file for that source of payment. This difference is
also an artifact of rounding only. Please see the MEPS 2001 Appendix File,
HC-059I, for details on such rounding differences.
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3.0 Sample Weight (PERWT01F)
3.1 Overview
There is a single full year person-level weight (PERWT01F) 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 2001. A key person either was a
member of an NHIS household at the time of the NHIS interview, or became a
member of a family associated with 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 Weight Construction
The person-level weight PERWT01F was developed in several stages.
Person-level weights for Panels 5 and 6 were created separately. The weighting
process for each panel included an adjustment for nonresponse over time and
poststratification. Poststratification was achieved initially by controlling to
Current Population Survey (CPS) population estimates based on five variables.
The five variables used in the establishment of the initial person-level
poststratification control figures were: census region (Northeast, Midwest,
South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, black but
non-Hispanic, and other); sex; and age. A 2001 composite weight was then formed
by multiplying each weight from Panel 5 by the factor (1/3) and each weight from
Panel 6 by the factor (2/3). The choice of factors reflected the relative sample
sizes of the two panels, helping to limit the variance of estimates obtained
from pooling the two samples. The composite weight was then poststratified to
the same set of CPS-based control totals. When poverty status information
derived from income variables became available, a final poststratification was
done on the previously established weight variable. Control totals were
established based on 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.
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3.2.1 MEPS Panel 5 Weight
The person-level weight for MEPS Panel 5 was developed using the 2000 full
year weight for an individual as a "base" weight for survey participants present
in 2000. For key, in-scope respondents who joined an RU some time in 2001 after
being out-of-scope in 2000, the 2000 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 2001. These control figures were derived
by scaling back the population totals obtained from the March 2001 CPS to
reflect the December 2001 CPS estimated population distribution across age and
sex categories as of December 2001. 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, 2001 is 280,791,812. Key, responding persons not in-scope on
December 31, 2001 but in-scope earlier in the year retained, as their final
Panel 5 weight, the weight after the nonresponse adjustment.
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3.2.2 MEPS Panel 6 Weight
The person-level weight for MEPS Panel 6 was developed using
the MEPS Round 1 person-level weight as a "base" weight. For key, in-scope
respondents who joined an RU after Round 1, the Round 1 family weight served as
a "base" weight. The weighting process included an adjustment for nonresponse
over Round 2 and the 2001 portion of Round 3 as well as poststratification to
the same population control figures for December 2001 used for the MEPS Panel 5
weights. The same five variables employed for Panel 5 poststratification (census
region, MSA status, race/ethnicity, sex, and age) were used for Panel 6
poststratification. Similarly, for Panel 6, key, responding persons not in-scope
on December 31, 2001 but in-scope earlier in the year retained, as their final
Panel 6 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 2001 CPS data
base.
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3.2.3 The Final Weight for 2001
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, 2001
is 280,791,812 (PERWT01F>0 and INSC1231=1). The weights of some persons
out-of-scope on December 31, 2001 were also poststratified. Specifically, the
weights of persons out-of-scope on December 31, 2001 who were in-scope some time
during the year and also entered a nursing home during the year were
poststratified to a corresponding control total obtained from the 1996 MEPS
Nursing Home Component. The weights of persons who died while in-scope during
2001 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 control totals were developed for the "65 and older" and "under 65"
civilian noninstitutionalized populations. The sum of the person-level weights
across all persons assigned a positive person level weight is 284,247,327.
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3.2.4 Coverage
The target population for MEPS in this file is the 2001 U.S. civilian
noninstitutionalized population. However, the MEPS sampled households are a
subsample of the NHIS households interviewed in 1999 (Panel 5) and 2000 (Panel
6). New households created after the NHIS interviews for the respective Panels
and consisting exclusively of persons who entered the target population after
1999 (Panel 5) or after 2000 (Panel 6) 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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4.0 Strategies for Estimation
This file is constructed for efficient estimation of utilization,
expenditures, and sources of payment for outpatient care and to allow for
estimates of the number of persons with outpatient visits during 2001.
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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 expenditure) are described in Section
2.5.6.
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4.2 Basic Estimates of Utilization,
Expenditures 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 outpatient visits,
expenditures and sources of payment, the value in each record contributing to
the estimates must be multiplied by the weight (PERWT01F) contained on that
record.
Example 1
For example, the total number of outpatient visits, for the civilian
noninstitutionalized population of the U.S. in 2001 is estimated as the sum of
the weight (PERWT01F) across all outpatient visit records. That is,
301 Moved Permanently
301 Moved Permanently
= 49,459,732. |
(1) |
Example 2
Subsetting to records based on characteristics of interest expands the scope
of potential estimates. For example, the estimate for the mean out-of-pocket
payment for outpatient visits (where the
visit has a total expense greater than 0) should be
calculated as the weighted mean of the facility bill and doctor's bill paid by
self/family. That is,
301 Moved Permanently
301 Moved Permanently
= $32.79 |
(2) |
where Xj = OPFSF01Xj + OPDSF01Xj
and
301 Moved Permanently
301 Moved Permanently
= 141,767,531
for all records with OPXP01Xj > 0.
This gives $32.79 as the estimated mean amount of out-of-pocket payment of
expenditures associated with outpatient visits and 141,767,531as an estimate of
the total number of such outpatient visits with expenditures. Both of these
estimates are for the civilian noninstitutionalized population of the U.S. in
2001.
Example 3
Another example would be to estimate the average proportion of total
expenditures paid by private insurance for outpatient visits with expenditure.
This should be calculated as the weighted mean of the proportion of total
expenditures paid by private insurance at the event level. That is,
301 Moved Permanently
301 Moved Permanently
= 0.4259 |
(3) |
where Yj = (OPFPV01Xj + OPDPV01Xj)/OPXP01Xj
and
301 Moved Permanently
301 Moved Permanently
= 141,767,531
for all outpatient visit records with OPXP01Xj > 0.
This gives 0.4259 as the estimated mean proportion of total expenditures paid
by private insurance for outpatient visits with expenditure for the civilian
noninstitutionalized population of the U.S. in 2001.
Return To Table Of Contents
4.3 Estimates of the Number of Persons with
Outpatient Visit Events
When calculating an estimate of the total number of persons with outpatient
visits, users can use a person-level file or this event file. However, this
event file must be used when the measure of interest is defined at the event
level. For example, to estimate the number of persons in the civilian
noninstitutionalized population of the U.S. with outpatient visits where the
patient sees a doctor, this event file must be used. This would be estimated as
301 Moved Permanently
301 Moved Permanently
across all
unique persons i on this file |
(4) |
where Wi is the sampling weight (PERWT01F)
for person i
and
Xi = 1 if SEEDOCi = 1 for any outpatient visit
record of person i
= 0 otherwise.
Return To Table Of Contents
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to
Persons with Outpatient Visit Events
This file may be used to derive person-based ratio estimates. However, when
calculating ratio estimates where the denominator is at the person level, care
should be taken to properly define and estimate the unit of analysis as
person-level. For example, the mean expense for persons with outpatient visits
is estimated as,
301 Moved Permanently
301 Moved Permanently
across all unique persons i on this file |
(5) |
where
Wi is the sampling weight (PERWT01F) for
person i
and
Zi =
301 Moved Permanently
301 Moved Permanently
OPXP01Xj
across all outpatient visits for person i.
Return To Table Of Contents
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 outpatient
visit are represented on this data file. In this case, the Full Year
Consolidated 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 the civilian
noninstitutionalized population of the U.S. with at least one outpatient visit
where the
person saw a doctor, 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,
301 Moved Permanently
301 Moved Permanently
across all unique persons i on the person-level file |
(6) |
where Wi is the sampling weight (PERWT01F)
for person i
and
Zi = 1 if SEEDOCj = 1 for any outpatient
visit of person i
= 0 otherwise.
Return To Table Of Contents
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
with another, the major analytical variable (i.e., the dependent variable)
determines the correct sampling weight to use.
Return To Table Of Contents
4.6 Variance Estimation (VARSTR01, VARPSU01)
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 2001 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 VARSTR01 and VARPSU01,
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.
Return To Table Of Contents
Examples 2 and 3 from Section 4.2
Using a Taylor Series approach, specifying VARSTR01 and VARPSU01 as the
variance estimation strata and PSUs (within these strata), respectively, and
specifying a "with replacement" design in a computer software package (i.e.,
SUDAAN) will yield standard error estimates of $2.69 and 0.0185 for the
estimated mean out-of-pocket payment and the estimated mean proportion of total
expenditures paid by private insurance, respectively.
Return To Table Of Contents
5.0 Merging/Linking MEPS Data Files
Data from the current file can be used alone or in conjunction with other
files. This section provides instructions for linking the outpatient visits file
with other MEPS public use files, including: the conditions file, the prescribed
medicines file, and a person-level file.
Return To Table Of Contents
5.1 Linking a 2001 Person-Level File to
the 2001 Outpatient Visit File
Merging characteristics of interest from other MEPS files (e.g., 2001
Population Characteristics File, or the 2001 Use and Expenditure File) expands
the scope of potential estimates. For example, to estimate the total number of
outpatient visits for persons with specific characteristics (e.g., age, race,
and sex), population characteristics from a person-level file need to be merged
onto the outpatient visit file. This procedure is illustrated below. The MEPS
2001 Appendix File, HC-059I, provides additional detail on how to merge MEPS
data files.
- Create data set PERSX by sorting the Full Year Population
Characteristics file by the person identifier, DUPERSID. Keep only
variables to be merged onto the outpatient visit file and DUPERSID.
- Create data set OPAT by sorting the outpatient visit file by person
identifier, DUPERSID.
- Create final data set NEWOPAT by merging these two files by DUPERSID,
keeping only records on the outpatient visit file.
The following is an example of SAS code which completes these steps:
PROC SORT DATA=2001 Full Year Population Characteristics file
(KEEP= DUPERSID AGE31X AGE42X AGE53X SEX RACEX EDUCYR)
OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA=OPAT;
BY DUPERSID;
RUN;
DATA NEWOPAT;
MERGE OPAT(IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
Return To Table Of Contents
5.2 Linking the 2001 Outpatient Visit File to the 2001 Medical
Conditions File and/or the 2001 Prescribed Medicines File
Due to survey design issues, there are limitations/caveats that data
users/analysts must keep in mind when linking the different files. Those
limitations/caveats are listed below. For detailed linking examples, including
SAS code, data users/analysts should refer to the MEPS 2001 Appendix File,
HC-059I.
Return To Table Of Contents
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 2001
Prescribed Medicine File. When using RXLK, data users/analysts should keep in
mind that one outpatient visit can link to more than one prescribed medicine
record. Conversely, a prescribed medicine event may link to more than one
outpatient visit or different types of events. When this occurs, it is up to the
data users/analysts to determine how the prescribed medicine expenditures should
be allocated among those medical events.
Return To Table Of Contents
5.2.2 Limitations/Caveats of CLNK (the Medical
Conditions Link File)
The CLNK provides a link from MEPS event files to the 2001 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 an outpatient visit. Users should also note that not all outpatient visits
link to the medical conditions file.
Return To Table Of Contents
References
Cohen, S.B. (1998). Sample Design of the 1996 Medical Expenditure Panel
Survey Medical Provider Component. Journal of Economic and Social Measurement.
Vol 24, 25-53.
Cohen, S.B. (1997). Sample Design of the 1996 Medical Expenditure Panel
Survey Household Component. Rockville (MD): Agency for Health Care Policy and
Research; 1997. MEPS Methodology Report, No. 2. AHCPR Pub. No.
97-0027.
Cohen, 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.
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.
Cox, B.G. and Cohen, S.B. (1985). Chapter 6: A Comparison of Household and
Provider Reports of Medical Conditions. In Methodological Issues for Health
Care Surveys. Marcel Dekker, New York.
Cox, B. and Iachan, R. (1987). A Comparison of Household and Provider Reports
of Medical Conditions. Journal of the American Statistical Association
82(400):1013-18.
Edwards, W.S., Winn, D.M., Kurlantzick V., et al. (1994). Evaluation of
National Health Interview Survey Diagnostic Reporting. National Center for
Health Statistics, Vital Health 2(120).
Elixhauser A., Steiner C.A., Whittington C.A., and McCarthy E. Clinical
Classifications for Health Policy Research: Hospital Inpatient Statistics, 1995.
Healthcare Cost and Utilization Project, HCUP-3 Research Note. Rockville, MD:
Agency for Health Care Policy and Research; 1998. AHCPR Pub. No. 98-0049.
Health Care Financing Administration (1980). International Classification of
Diseases, 9th Revision, Clinical Modification (ICD-CM). Vol. 1. (DHHS
Pub. No. (PHS) 80-1260). DHHS: U.S. Public Health Services.
Johnson, A.E. and Sanchez, M.E. (1993). Household and Medical Provider
Reports on Medical Conditions: National Medical Expenditure Survey, 1987.
Journal of Economic and Social Measurement. Vol. 19, 199-233.
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.
Return To Table Of Contents
D. Variable-Source Crosswalk
VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-059F: 2001 OUTPATIENT DEPARTMENT VISITS
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 |
MPCDATA |
MPC data flag |
Constructed |
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Outpatient Department Visit Variables
| Variable |
Description |
Source |
OPDATEYR |
Event date - year |
CAPI derived |
OPDATEMM |
Event date - month |
CAPI derived |
OPDATEDD |
Event date - day |
CAPI derived |
SEETLKPV |
Did person visit provider in person or telephone |
OP02 |
SEEDOC |
Did person talk to MD this visit/phone call |
OP04 |
MEDPTYPE |
Type of medical person person talked to on visit date |
OP05 |
VSTCTGRY |
Best category for care person received on visit date |
OP07 |
VSTRELCN |
This visit/phone call related to spec condition |
OP08 |
PHYSTH |
This visit did person have physical therapy |
OP10 |
OCCUPTH |
This visit did person have occupational therapy |
OP10 |
SPEECHTH |
This visit did person have speech therapy |
OP10 |
CHEMOTH |
This visit did person have chemotherapy |
OP10 |
RADIATTH |
This visit did person have radiation therapy |
OP10 |
KIDNEYD |
This visit did person have kidney dialysis |
OP10 |
IVTHER |
This visit did person have IV therapy |
OP10 |
DRUGTRT |
This visit did person have treatment for drug/alcohol |
OP10 |
RCVSHOT |
This visit did person receive an allergy shot |
OP10 |
PSYCHOTH |
This visit did person have psychotherapy/counseling |
OP10 |
LABTEST |
This visit did person have lab tests |
OP11 |
SONOGRAM |
This visit did person have sonogram or ultrasound |
OP11 |
XRAYS |
This visit did person have x-rays |
OP11 |
MAMMOG |
This visit did person have a mammogram |
OP11 |
MRI |
This visit did person have an MRI/Catscan |
OP11 |
EKG |
This visit did person have an EKG or ECG |
OP11 |
EEG |
This visit did person have an EEG |
OP11 |
RCVVAC |
This visit did person receive a vaccination |
OP11 |
ANESTH |
This visit did person receive anesthesia |
OP11 |
OTHSVCE |
This visit did person have other diagnostic tests or exams |
OP11 |
SURGPROC |
Was surgical procedure performed on person this visit |
OP12 |
MEDPRESC |
Any medicine prescribed for person during visit |
OP14 |
VAPLACE |
VA facility flag |
Constructed |
OPICD1X |
3-digit ICD-9-CM condition code |
Edited |
OPICD2X |
3-digit ICD-9-CM condition code |
Edited |
OPICD3X |
3-digit ICD-9-CM condition code |
Edited |
OPICD4X |
3-digit ICD-9-CM condition code |
Edited |
OPPRO1X |
2-digit ICD-9-CM procedure code |
Edited |
OPCCC1X |
Modified Clinical Classification Code |
Constructed/ Edited |
OPCCC2X |
Modified Clinical Classification Code |
Constructed/ Edited |
OPCCC3X |
Modified Clinical Classification Code |
Constructed/ Edited |
OPCCC4X |
Modified Clinical Classification Code |
Constructed/ Edited |
Return To Table Of Contents
Flat Fee Variables
| Variable |
Description |
Source |
FFOPTYPE |
Flat fee bundle |
Constructed |
FFBEF01 |
Total # of visits in FF before 2001 |
FF05 |
FFTOT02 |
Total # of visits in FF after 2001 |
FF10 |
Return To Table Of Contents
Imputed Expenditure Variables
| Variable |
Description |
Source |
OPXP01X |
Total expenditure for event (OPFXP01X+OPDXP01X) |
Constructed |
OPTC01X |
Total charge for event (OPFTC01X+OPDTC01X) |
Constructed |
OPFSF01X |
Facility amount paid, self/family (Imputed) |
CP Section (Edited) |
OPFMR01X |
Facility amount paid, Medicare (Imputed) |
CP Section (Edited) |
OPFMD01X |
Facility amount paid, Medicaid (Imputed) |
CP Section (Edited) |
OPFPV01X |
Facility amount paid, private insurance (Imputed) |
CP Section (Edited) |
OPFVA01X |
Facility amount paid, Veterans (Imputed) |
CP Section (Edited) |
OPFTR01X |
Facility amount paid, TRICARE (Imputed) |
CP Section (Edited) |
OPFOF01X |
Facility amount paid, other federal (Imputed) |
CP Section (Edited) |
OPFSL01X |
Facility amount paid, state & local government (Imputed) |
CP Section (Edited) |
OPFWC01X |
Facility amount paid, workers' compensation (Imputed) |
CP Section (Edited) |
OPFOR01X |
Facility amount paid, other private insurance (Imputed) |
Constructed |
OPFOU01X |
Facility amount paid, other public insurance (Imputed) |
Constructed |
OPFOT01X |
Facility amount paid, other insurance (Imputed) |
CP Section (Edited) |
OPFXP01X |
Facility sum payments OPFSF01X -OPFOT01X |
Constructed |
OPFTC01X |
Total facility charge (Imputed) |
CP Section (Edited) |
OPDSF01X |
Doctor amount paid, self/family (Imputed) |
Constructed |
OPDMR01X |
Doctor amount paid, Medicare (Imputed) |
Constructed |
OPDMD01X |
Doctor amount paid, Medicaid (Imputed) |
Constructed |
OPDPV01X |
Doctor amount paid, private insurance (Imputed) |
Constructed |
OPDVA01X |
Doctor amount paid, Veterans Administration (Imputed) |
Constructed |
OPDTR01X |
Doctor amount paid, TRICARE (Imputed) |
Constructed |
OPDOF01X |
Doctor amount paid, other federal (Imputed) |
Constructed |
OPDSL01X |
Doctor amount paid, state & local government (Imputed) |
Constructed |
OPDWC01X |
Doctor amount paid, workers' compensation (Imputed) |
Constructed |
OPDOR01X |
Doctor amount paid, other private insurance (Imputed) |
Constructed |
OPDOU01X |
Doctor amount paid, other public insurance (Imputed) |
Constructed |
OPDOT01X |
Doctor amount paid, other insurance (Imputed) |
Constructed |
OPDXP01X |
Doctor sum payments OPDSF01X -OPDOT01X |
Constructed |
OPDTC01X |
Total doctor charge (Imputed) |
Constructed |
IMPFLAG |
Imputation status |
Constructed |
Return To Table Of Contents
Weights
| Variable |
Description |
Source |
PERWT01F |
Final person level weight, 2001 |
Constructed |
VARSTR01 |
Variance estimation stratum, 2001 |
Constructed |
VARPSU01 |
Variance estimation PSU, 2001 |
Constructed |
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