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MEPS HC-051G: 2000 Office-Based Medical Provider Visits
March 2003
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406
Table of Contents
A. Data Use Agreement
B. Background
1.0 Household Component
2.0 Medical Provider Component
3.0 Insurance Component
4.0 Survey Management
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Codebook Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Source and Naming Conventions
2.4.1 General
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 Record Indicator (EVENTRN)
2.5.2 MPC Indicator (MPCELIG, MPCDATA)
2.5.3 Office-Based Medical Provider Visit
Variables
2.5.3.1 Date of Visit (OBDATEYR -
OBDATEDD)
2.5.3.2 Visit Details
(SEETLKPV-VSTRELCN)
2.5.3.3 Treatments, Procedures,
Services, and Prescription Medicines (PHYSTH-MEDPRESC)
2.5.3.4 VA Facility (VAPLACE)
2.5.4 Condition and Procedure Codes
(OBICD1X-OBICD4X, OBPRO1X), and Clinical Classification Codes
(OBCCC1X-BCCC4X)
2.5.5 Flat Fee Variables (FFEEIDX,
FFOBTYPE, FFBEF00, FFTOT01)
2.5.5.1 Definition of Flat Fee Payments
2.5.5.2 Flat Fee Variable Descriptions
2.5.5.2.1 Flat Fee ID (FFEEIDX)
2.5.5.2.2 Flat Fee Type (FFOBTYPE)
2.5.5.2.3 Counts of Flat Fee
Events that Cross Years (FFBEF00, FFTOT01)
2.5.5.3 Caveats of Flat Fee Groups
2.5.6 Expenditure Data
2.5.6.1 Definition of Expenditures
2.5.6.2 Data Editing and Imputation
Methodologies of Expenditure Variables
2.5.6.2.1 General Data Editing
Methodology
2.5.6.2.2 General Hot-Deck
Imputation
2.5.6.2.3 Office-Based Provider
Visit Data Editing and Imputation
2.5.6.3 Capitation Imputation
2.5.6.4 Imputation Flag
(IMPFLAG)
2.5.6.5 Flat Fee Expenditures
2.5.6.6 Zero Expenditures
2.5.6.7 Discount Adjustment Factor
2.5.6.8 Sources of Payment
2.5.6.9 Office-Based Expenditure
Variables (OBSF00X - OBTC00X)
2.5.7 Rounding
3.0 Sample Weight (PERWT00F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 4 Weight
3.2.2 MEPS Panel 5 Weight
3.2.3 The Final Weight for 2000
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
Office-Based Medical Provider Visit Events
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates
Relative to Persons with Office-Based Medical Provider 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 (VARSTR00, VARPSU00)
5.0 Merging/Linking MEPS Data Files
5.1 Linking a 2000 Person-Level File to the
2000 Office-Based Medical Provider Visits File
5.2 Linking the MEPS 2000 Office-Based Medical
Provider Visits File to the MEPS 2000 Medical Conditions File and/or
the MEPS 2000 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
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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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, also known as
NMES-1) was conducted in 1977 and the National Medical Expenditure Survey
(NMES-2) in 1987. Since 1996, MEPS continues this series with design
enhancements and efficiencies that provide a more current data resource to
capture the changing dynamics of the health care delivery and insurance system.
The design efficiencies incorporated into MEPS are in
accordance with the Department of Health and Human Services (DHHS) Survey
Integration Plan of June 1995, which focused on consolidating DHHS surveys,
achieving cost efficiencies, reducing respondent burden, and enhancing
analytical capacities. To 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,
eligibility requirements, 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 Bureau of the Census.
To provide an integrated picture of health insurance, data
collected from the first sampling frame (employers and insurance providers
identified by MEPS HC respondents) are linked back to data provided by those
respondents. Data 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
insurance from the MEPS IC are used in the computation of Gross Domestic Product
(GDP) by the Bureau of Economic Analysis.
The MEPS IC is an annual panel survey. Data are collected
from the selected organizations through a prescreening telephone interview, a
mailed questionnaire, and a telephone follow-up for nonrespondents.
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4.0 Survey
Management
MEPS data are collected under the authority of the Public
Health Service Act. They are edited and published in accordance with the
confidentiality provisions of this act and the Privacy Act. NCHS provides
consultation and technical assistance.
As soon as data collection and editing are completed, the
MEPS survey data are released to the public in staged releases of summary
reports, microdata files and compendiums of tables. Data are 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 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 Cost and
Financing Studies, Agency for Healthcare Research and Quality.
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C. Technical
and Programming Information
1.0 General
Information
This documentation describes one in a series of public use
event files from the 2000 Medical Expenditure Panel Survey (MEPS) Household (HC)
and Medical Provider Components (MPC). Released as an ASCII data file and a SAS
transport file, the 2000 Office-Based Medical Provider Visits public use event
file provides detailed information on office-based provider visits for a
nationally representative sample of the civilian noninstitutionalized population
of the United States. Data from the office-based provider events file can be
used to make estimates of office-based provider utilization and expenditures for
calendar year 2000. As illustrated below, this file consists of MEPS survey data
from the 2000 portion of Round 3 and Rounds 4 and 5 for Panel 4, as well as
Rounds 1, 2 and the 2000 portion of Round 3 for Panel 5 (i.e., the rounds for
the MEPS panels covering calendar year 2000).
301 Moved Permanently
301 Moved Permanently
Each record on this event file represents a unique
office-based provider event; that is, an office-based provider event reported by
the household respondent. Utilization counts of office-based provider visits are
based entirely on household reports. Information from the MPC was used to
supplement expenditure payment data, on the office-based provider file, reported
by the household.
Data from this event file can be merged with other 2000
MEPS HC data files for purposes of appending person-level data such as
demographic characteristics or health insurance coverage to each office-based
provider visit record on the current file.
This file can also be used to construct summary variables
of expenditures, sources of payment, and related aspects of office-based
provider visits for calendar year 2000. Aggregate annual person-level
information on the use of office-based providers and other health services use
is provided on the MEPS 2000 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
codebook. It contains the following sections:
Data File Information
Sample Weights
Strategies for Estimation
Merging/linking MEPS Data Files
References
Variable-Source Crosswalk
For more information on MEPS HC survey design, see S.
Cohen, 1997; J. Cohen, 1997; and S. Cohen, 1996. A copy of the MEPS HC survey
instruments used to collect the information on the office-based provider file is
available on the MEPS web site at the following address: <http://www.meps.ahrq.gov>.
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2.0 Data File
Information
The 2000 Office-Based Medical Provider
public use data set consists of one event-level data file. The file contains
characteristics associated with the OB event and imputed expenditure data. For
users wanting to impute expenditures, pre-imputed data are available through the
CCFS data center. Please visit the CCFS Data Denter website for details:
<http://www.meps.ahrq.gov/mepsweb/data_stats/onsite_datacenter.jsp>. The data user/analyst is
forewarned that the imputation of expenditures will necessitate a sizable
commitment of resources: financial, staff, and time.
The Office-Based Provider public use data set contains
102,530 office-based provider event records; of these records, 99,939 are
associated with persons having a positive person-level weight (PERWT00F). This
file includes office-based provider event records for all household survey
respondents who resided in eligible responding households and reported at least
one office-based provider event. Each record represents one household-reported
office-based provider event that occurred during calendar year 2000.
Office-based provider visits known to have occurred after December 31, 2000 are
not included on this file. Some household respondents may have multiple events
and thus will be represented in multiple records on this file. Other household
respondents may have reported no events and thus will have no records on this
file. These data were collected during the 2000 portion of Round 3, and Rounds 4
and 5 for Panel 4, as well as Rounds 1, 2, and the 2000 portion of Round 3 for Panel 5 of the
MEPS Household Component. The persons represented on this file had to meet
either (a) or (b):
-
Be classified as a key in-scope
person who responded for his or her entire period of 2000 eligibility
(i.e., persons with a positive 2000 full-year person-level weight
(PERWT00F > 0)), or
-
Be an eligible member of a family all of whose
key in-scope members have a positive person-level weight (PERWT00F
> 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 (FAMWT00F >0). Note that FAMIDYR and FAMWT00F
are variables on the 2000 Population Characteristics file.
Persons with no office-based medical provider visit events
for 2000 are not included on this file but are represented on the 2000 MEPS
person-level files. A codebook for the data file is provided in files H51GCB.PDF
and H51GCB.ASP.
Each office-based medical provider visit event record
includes the following: date of the event; type of provider seen; time spent
with the provider; type of care received; types of treatments (i.e., physical
therapy, occupational therapy, speech therapy, chemotherapy, radiation therapy,
etc.) received during the event; type of services (i.e., lab test, sonogram or
ultrasound, x-rays, etc.) received, medicines prescribed during the event; flat
fee information, imputed sources of payment, total payment and total charge of
the office-based event expenditure; and a full-year person-level weight.
Data from the this file can be merged with the MEPS 2000
Full Year Population Characteristics file using the unique person identifier,
DUPERSID, to append person-level information, such as demographic or health
insurance characteristics, to each record. The office-based medical provider
visit events can also be linked to the MEPS 2000 Medical Conditions File and
MEPS 2000 Prescribed Medicines File. Please see section 5.0 for details
on how to merge MEPS data files.
Panel 4 cases (PANEL00 = 4 on the MEPS 2000 Full Year
Population Characteristics File) can also be linked back to the 1999 MEPS HC
public use data files. However, data users/analysts should be aware that, at
this time, no weight is being provided to facilitate two-year analysis of Panel
4 data.
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2.1 Codebook Structure
For each variable on the office-based provider file, both
weighted and unweighted frequencies are provided in the codebook (files
H51GCB.PDF and H51GCB.ASP). The codebook and data file sequence list variables
in the following order:
Unique person identifiers
Unique office-based medical provider visit event
identifier
Office-based medical provider visit characteristic
variables
ICD-9 condition and procedure codes
Clinical Classification Software (CCS) codes
Imputed expenditure variables
Weight and variance estimation variables
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2.2 Reserved
Codes
The following reserved code values are used:
| Value |
Definition |
| -1 INAPPLICABLE |
Question was not asked due to skip pattern. |
| -7 REFUSED |
Question was asked and respondent refused to answer question. |
| -8 DK |
Question was asked and respondent did not know answer. |
| -9 NOT ASCERTAINED |
Interviewer did not record the data. |
Generally, values of -1, -7, -8, and -9
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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2.3 Codebook Format
The office-based medical provider visits 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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2.4 Variable
Source and Naming Conventions
In general, variable names reflect the content of the
variable, with an 8-character limitation. All imputed/edited variables end with
an "X."
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2.4.1 General
Variables contained on this file were derived from the HC
survey questionnaire itself, derived from 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 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:
- 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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2.4.2 Expenditure and Source of
Payment Variables
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 the 12 source of payment 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 |
In the case of source of payment variables, the third and
fourth characters indicate:
| SF - self or family |
OF - other Federal Government |
| MR - Medicare |
SL - State/local government |
| MD - Medicaid |
WC - Workers' Compensation |
| PV - private insurance |
OT - other insurance |
| VA - Veterans |
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 fifth and sixth characters indicate the year (00). The
last character indicates whether the variable is edited/imputed (X).
For example, OBSF00X is the edited/imputed amount paid by
self or family for an office-based medical provider visit expenditure incurred
in 2000.
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2.5 File
Contents
2.5.1 Survey
Administration Variables
2.5.1.1 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 2000 Full
Year Population Characteristics.
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2.5.1.2 Record Identifiers
(EVNTIDX, FFEEIDX)
EVNTIDX uniquely identifies each office-based medical
provider visit event (i.e., each record on the office-based medical provider
visits file) and is the variable required for linking office-based medical
provider visit events to data files containing details on conditions and/or
prescribed medicines (MEPS 2000 Medical Condition file and MEPS 2000 Prescribed
Medicine file, respectively). For details on linking see Section 5.0 or the MEPS
2000 Appendix File, HC-051I.
FFEEIDX is a constructed variable that uniquely identifies
a flat fee group, that is, all events that were part of a flat fee payment
situation. For example, pregnancy is typically covered in a flat fee arrangement
where the prenatal visits, the delivery, and the postpartum visits are all
covered under one flat fee dollar amount. These events (the prenatal visit, the
delivery, and the postpartum visits) would have the same value for FFEEIDX.
FFEEIDX identifies a flat fee payment situation that was identified using
information from the Household Component. A "mixed" flat fee group
could contain both outpatient and office-based visits. Only outpatient and
office-based events are allowed in a mixed bundle. Please note that FFEEIDX
should be used to link up the outpatient and office-based events in order to
determine the full set of events that are part of a flat fee group.
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2.5.1.3 Record Indicator
(EVENTRN)
EVENTRN indicates the round in which the outpatient event
was reported. Please note that Rounds 3, 4, and 5 are associated with MEPS
survey data collected from Panel 4. Likewise, Rounds 1, 2, and 3 are associated
with data collected from Panel 5.
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2.5.2 MPC Indicator (MPCELIG,
MPCDATA)
MPCELIG is a constructed variable that indicates whether
the office-based provider visit was eligible for MPC data collection. MPCDATA is
a constructed variable that indicates whether or not MPC data was collected for
the office-based provider.
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2.5.3
Office-Based Medical Provider Visit Variables
The file contains variables describing
office-based medical provider visit events reported by respondents in the
Medical Provider Visits section of the MEPS HC survey questionnaire.
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2.5.3.1 Date of Visit (OBDATEYR
- OBDATEDD)
There are three variables that, together, indicate the
day, month and year an office-based provider visit occurred (OBDATEDD, OBDATEMM,
OBDATEYR, respectively). These variables have not been edited or imputed.
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2.5.3.2 Visit Details
(SEETLKPV-VSTRELCN)
The questionnaire determines if during the
office-based medical provider visit the person actually saw the provider or
talked to the provider on the telephone (SEETLKPV). It also establishes if the
person was referred by another physician or medical provider (REFERDBY), and
whether the person saw or spoke to a medical doctor or not (SEEDOC). If the
person did not see a physician (i.e., a medical doctor), the respondent was
asked to identify the type of medical person seen (MEDPTYPE). The respondent was
also asked how much time was spent with the medical provider (TIMESPNT). Whether
or not any medical doctors worked at the visit location (DOCATLOC), 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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2.5.3.3 Treatments,
Procedures, Services, and Prescription Medicines
(PHYSTH-MEDPRESC)
Types of treatments received during the office-based
medical provider 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 a CAT scan (MRI), an electrocardiogram (EKG), an electroencephalogram
(EEG), a vaccination (RCVVAC), anesthesia (ANESTH), or other diagnostic tests or
exams (OTHSVCE). Minimal editing was done across treatment, services, and
procedures to ensure consistency across "inapplicable," "not
ascertained," "don't know," "refused," and "no
services received" values. Whether or not a surgical procedure was
performed during the visit was asked (SURGPROC) and, if so, the procedure name (SURGNAME).
Finally, the questionnaire determined if a medicine was prescribed for the
person during the visit (MEDPRESC).
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2.5.3.4 VA Facility (VAPLACE)
VAPLACE is a constructed variable that indicates whether
the provider worked at 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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2.5.4
Condition and Procedure Codes (OBICD1X-OBICD4X, OBPRO1X), and Clinical
Classification Codes (OBCCC1X-OBCCC4X)
Information on household-reported medical conditions and
procedures associated with each office-based medical provider visit are provided
on this file. There are up to four condition and CCS codes (OBICD1X-OBICD4X,
OBCCC1X-OBCCC4X) and one procedure code (OBPRO1X) listed for each office-based
medical provider visit. In order to obtain complete condition information
associated with an event, the analyst must link to the Medical Conditions File.
Details on how to link to the MEPS Medical Conditions File are provided in
Section 5.0. The user should note that due to confidentiality restrictions,
provider-reported condition information is not publicly available.
The medical conditions and procedures reported by the
Household Component respondent were recorded by the interviewer as verbatim
text, which were then coded to fully-specified 2000 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 3 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 how conditions and procedures were
coded, please refer to the documentation on the MEPS 2000 Medical Conditions
File. For frequencies of conditions by event type, please see the MEPS 2000
Appendix File, HC-051I.
The ICD-9-CM codes were aggregated into clinically
meaningful categories. These categories, included on the file as
OBCCC1X-OBCCC4X, 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 3-digit categories. Details on this procedure can be
found in the 2000 MEPS Medical Conditions File.
The condition codes (and clinical classification codes)
and procedure codes linked to each office-based medical provider visit event are
sequenced in the order in which the conditions were reported by the household
respondent, which was in order of input into the database and not
in order of importance or severity. Data user/analysts who use the Medical
Conditions file in conjunction with this office-based medical provider visits
file should note that the order of conditions on this file is not identical to
that on the 2000 Medical Conditions file.
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2.5.5 Flat
Fee Variables (FFEEIDX, FFOBTYPE, FFBEF00, FFTOT01)
2.5.5.1 Definition of Flat
Fee Payments
A flat fee is the fixed dollar amount a person is charged
for a package of services provided during a defined period of time. Examples
would be an obstetrician's fee covering a normal delivery, and the associated
pre- and post-natal care. A flat fee group is the set of medical services (i.e.,
events) that are covered under the same flat fee payment situation. The flat fee
groups represented on the office-based provider file include flat fee groups
where at least one of the health care events, as reported by the HC respondent,
occurred during 2000. By definition, a flat fee group can span multiple years
and/or event types (only outpatient department visits and physician office
visits). Furthermore, a single person can have multiple flat fee groups.
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2.5.5.2
Flat Fee Variable Descriptions
2.5.5.2.1 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 2000 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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2.5.5.2.2
Flat Fee Type (FFOBTYPE)
FFOBTYPE indicates whether the 2000 office-based medical
provider visit event is the "stem" or "leaf" of a flat fee
group. A stem (records with FFOBTYPE = 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 FFOBTYPE = 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 office-based visits that are not part of a flat
fee payment situation, the FFOBTYPE is set to -1, "INAPPLICABLE."
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2.5.5.2.3
Counts of Flat Fee Events that Cross Years (FFBEF00, FFTOT01)
As described in Section 2.5.4.1, a flat fee payment
situation covers multiple events and the multiple events could span multiple
years. For situations where the office-based medical provider visit occurred in
2000 as a part of a group of events, and some of the events occurred before
2000, counts of the known events are provided on the office-based medical
provider visit event file record. Variables indicating events that occurred
before or after 2000 as follows. These variables are:
FFBEF00 - total number of pre-2000 events in the same
flat fee group as the 2000 office-based medical provider visit. This count
would not include the 2000 office-based medical visit(s).
FFTOT01 - indicates the number of 2001 office-based
events expected to be in the same flat fee group as the office-based medical
provider visit event(s) that occurred in 2000.
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2.5.5.3 Caveats of Flat Fee
Groups
Data users/analysts should note that flat fee payment
situations are common on the office-based medical provider visits file. There
are 2,329 office-based medical provider visit events that are identified as
being part of a flat fee payment group. In order to correctly identify all
events that are part of a flat fee group, the user should link all MEPS events,
except those in the prescribed medicine file, using the variable FFEEIDX. 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 2000,
but the remaining visits that were part of this flat fee group occurred in 2001.
In this case, the 2000 flat fee group represented on this file would consist of
one event (the stem). The 2001 leaf events that are part of this flat fee group
are not represented on this file. Similarly, the household respondent may have
reported a flat fee group where the initial visit began in 1999 but subsequent
visits occurred during 2000. In this case, the initial visit would not be
represented on the file. This 2000 flat fee group would then consist only 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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2.5.6
Expenditure Data
2.5.6.1 Definition of
Expenditures
Expenditures on this file refer to what is paid for health
care services. More specifically, expenditures in MEPS are defined as the sum of
payments for care received, including out-of-pocket payments and payments made
by private insurance, Medicaid, Medicare and other sources. The definition of
expenditures used in MEPS differs slightly from its predecessors: the 1987 NMES
and 1977 NMCES surveys where "charges" rather than sum of payments
were used to measure expenditures. This change was adopted because charges
became a less appropriate proxy for medical expenditures during the 1990's due
to the increasingly common practice of discounting. Although measuring
expenditures as the sum of payments incorporates discounts in the MEPS
expenditure estimates, the estimates do not incorporate any payment not directly
tied to specific medical care visits, such as bonuses or retrospective payment
adjustments paid by third party payers. Another general change from the two
prior surveys is that charges associated with uncollected liability, bad debt,
and charitable care (unless provided by a public clinic or hospital) are not
counted as expenditures because there are no payments associated with those
classifications. While charge data are provided on this file, data
users/analysts should use caution when working with this data because a charge
does not typically represent actual dollars exchanged for services or the
resource costs of those services, nor is it directly comparable to the resource
costs of those services or the expenditures defined in the 1987 NMES (for
details on expenditure definitions, see Monheit et al., 1999). AHRQ has
developed factors to apply to the 1987 NMES expenditure data to facilitate
longitudinal analysis. These factors can be assessed via the CCFS data center.
For more information, see the Data Center section of the MEPS web site
<http://www.meps.ahrq.gov>.
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2.5.6.2 Data Editing and
Imputation Methodologies of Expenditure Variables
The expenditure data included on this file were derived
from both the MEPS household (HC) and medical provider (MPC) components. The MPC
contacted medical providers identified by household respondents. The charge and
payment data from medical providers was used in the expenditure imputation
process to supplement missing household data. For all office-based medical
provider visits, MPC data were used if complete; otherwise HC data were used if
complete. Missing data for office-based medical provider 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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2.5.6.2.1 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 mis-classifications between Medicare and Medicaid and between
Medicare HMOs and private HMOs as payment sources. These edits produced a
complete vector of expenditures for some events, and provided the starting point
for imputing missing expenditures in the remaining events.
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2.5.6.2.2 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.
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2.5.6.2.3 Office-Based
Provider Visit Data Editing and Imputation
Facility expenditures for office-based
provider visits 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 (as described above) 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 for events 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.
Separate imputations were performed for
flat fee and simple events.
Logical edits also were used to sort each
event into a specific category for the imputations. Events with complete
expenditures were flagged as potential donors for the hot-deck imputations,
while events with missing expenditure data were assigned to various recipient
categories. Each event was assigned to a recipient category based on 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 cost of free care would be both
implicitly included in paid events, and explicitly included in events that
should have been treated as free from provider.
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2.5.6.3 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. The
procedure was conducted in two stages. First, HMO events reported in the MPC as
covered by capitated arrangements were imputed using similar MPC HMO events that
were paid on a fee-for-service basis, 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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2.5.6.4 Imputation Flag
(IMPFLAG)
Only one imputation flag was created for 2000 event files.
This variable, 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 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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2.5.6.5 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 payments. Thus, if the first visit in the flat fee group
occurred prior to 2000, all of the events that occurred in 2000 will have zero
payments. Conversely, if the first event in the flat fee group occurred at the
end of 2000, the total expenditure for the entire flat fee group will be on that
event, regardless of the number of events it covered after 2000. See Section
2.5.3 for details on the flat fee variables.
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2.5.6.6 Zero Expenditures
There are some medical 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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2.5.6.7 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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2.5.6.8 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 (self) or family
- Medicare
- Medicaid
- Private Insurance
- Veterans Administration, excluding TRICARE
- TRICARE, formerly CHAMPUS/CHAMPVA,
- Other Federal sources - includes Indian Health
Service, Military Treatment Facilities, and other care by the Federal
government
- Other State and Local Sources - includes community
and neighborhood clinics, State and local health departments, and State
programs other than Medicaid.
- Workers' Compensation
- Other Unclassified Sources - includes sources such
as automobile, homeowner's, liability, and other miscellaneous or
unknown sources.
Two additional source of payment variables were created to
classify payments for 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 persons who were not enrolled in Medicaid, but were presumed
eligible by a provider who ultimately received payments from the program.
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2.5.6.9 Office-Based
Expenditure Variables (OBSF00X - OBTC00X)
OBSF00X - OBOT00X are the 12 sources of payment. OBTC00X
is the total charge, and OBXP00X is the sum of the 12 sources of payment for the
office-based provider visit expenditures. The 12 source of payment are: self/family (OBSF00X),
Medicare (OBMR00X), Medicaid (OBMD00X), private insurance (OBPV00X), Veterans
Administration (OBVA00X), TRICARE (OBTR00X), other Federal sources (OBOF00X),
State and Local (non-federal) government sources (OBSL00X), Worker's
Compensation (OBWC00X), other private insurance (OBOR00X), other public
insurance (OBOU00X), and other insurance (OBOT00X).
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2.5.7 Rounding
Expenditure variables have been rounded to the nearest
penny. Person-level expenditure information released on the MEPS 2000
Person-Level Expenditure File will be rounded to the nearest dollar. It should
be noted that using the MEPS 2000 event files to create person-level
totals will yield slightly different totals than that 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 2000 Appendix File, HC-051I, for details on such
rounding differences.
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3.0 Sample
Weight (PERWT00F)
3.1 Overview
There is a single full year person-level weight (PERWT00F)
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 2000. A key person
either was a member of an NHIS household at the time of the NHIS interview, or
became a member of such a household after being out-of-scope at the time of the
NHIS (examples of the latter situation include newborns and persons returning
from military service, an institution, or living outside the United States). A
person is in-scope whenever he or she is a member of the civilian
noninstitutionalized portion of the U.S. population.
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3.2 Details
on Person Weight Construction
The person-level weight PERWT00F was developed in several
stages. Person level weights for Panels 4 and 5 were created separately. The
weighting process for each panel included an adjustment for nonresponse over
time and poststratification. Poststratification was achieved by controlling to
Current Population Survey (CPS) population estimates based on five variables.
Variables used in the establishment of person-level poststratification control
figures included: census region (Northeast, Midwest, South, West); MSA status (MSA,
non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and
age. A 2000 composite weight was then formed by multiplying each panel weight by
.5 and then poststratifying the resulting weight 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 resulting weight
variable, including poverty status (below poverty, from 100 to 125 percent of
poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty,
at least 400 percent of poverty) as well as the original five poststratification
variables in the establishment of control totals.
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3.2.1 MEPS Panel 4 Weight
The person-level weight for MEPS Panel 4 was developed
using the 1999 full year weight for an individual as a "base" weight
for survey participants present in 1999. For key, in-scope respondents who
joined an RU some time in 2000 after being out-of-scope in 1999, the 1999 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
2000. These control figures were derived by scaling back the population totals
obtained from the March 2000 CPS to reflect the December 2000 CPS estimated
population distribution across age and sex categories as of December 2000.
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, 2000 is 275,158,755. Key,
responding persons not in-scope on December 31, 2000 but in-scope earlier in the
year retained, as their final Panel 4 weight, the weight after the nonresponse
adjustment.
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3.2.2 MEPS
Panel 5 Weight
The person-level weight for MEPS Panel 5 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 2000 portion of Round 3 as well
as poststratification to the same population control figures for December 2000
used for the MEPS Panel 4 weights. The same five variables employed for Panel 4
poststratification (census region, MSA status, race/ethnicity, sex, and age)
were used for Panel 5 poststratification. Similarly, for Panel 5, key,
responding persons not in-scope on December 31, 2000 but in-scope earlier in the
year retained, as their final Panel 5 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 2000 CPS data base.
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3.2.3 The
Final Weight for 2000
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, 2000 is 275,158,755 (PERWT00F>0 and
INSC1231=1). The weights of some persons out-of-scope on December 31, 2000 were
also poststratified. Specifically, the weights of persons out-of-scope on
December 31, 2000 who were inscope 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 inscope during 2000 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.
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3.2.4
Coverage
The target population for MEPS in this file is the 2000
U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 1998 (Panel 4)
and 1999 (Panel 5). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 1998 (Panel 4) or after 1999 (Panel 5) 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 proportion 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 office-based
medical provider visits and to allow for estimates of number of persons with
office-based medical provider visits in 2000.
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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 expenditures) are described in Section 2.5.5.
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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
office-based medical provider visits utilization, expenditures, and sources of
payment, the value in each record contributing to the estimates must be
multiplied by the weight (PERWT00F) contained on that record.
Example 1
For example, the total number of office-based medical
provider visits for the civilian noninstitutionalized population of the U.S. in
2000 is estimated as the sum of the weight (PERWT00F) across all office-based
medical provider visit records. That is,
301 Moved Permanently
301 Moved Permanently
|
= 1,236,897,482 |
(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 per office-based medical provider visit (for those who had
such expense greater than 0) should be calculated as the weighted mean of the
office-based provider's bill paid by self/family. That is,
301 Moved Permanently
301 Moved Permanently
|
= $19.58 |
(2) |
where
301 Moved Permanently
301 Moved Permanently
|
= 1,145,624,853 and Xj =
OBSF00Xj |
for all records with OBXP00Xj > 0.
This gives $19.58 as the estimated mean amount of
out-of-pocket payment of expenditures associated with office-based medical
provider visits and 1,145,624,853 as an estimate of the total number of
office-based medical provider visits with expenditure. Both of these estimates
are for the civilian noninstitutionalized population of the U.S. in 2000.
Example 3
Another example would be to estimate the mean proportion
of total expenditures (where event expense is greater than 0) paid by private
insurance for office-based medical provider visits. This should be calculated as
the weighted mean of the proportion of total expenditures paid by private
insurance at the provider visit level. That is
301 Moved Permanently
301 Moved Permanently
|
= 0.4373 |
(3) |
where
301 Moved Permanently
301 Moved Permanently
|
= 1,145,624,853 and Yj =
OBPV00Xj / OBXP00Xj |
for all office-based medical provider visits with
OBXP00Xj > 0.
This gives 0.4373 as the estimated mean proportion of
total expenditures paid by private insurance for office-based medical provider
visits with expenditures for the civilian noninstitutionalized population of the
U.S. in 2000.
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4.3 Estimates
of the Number of Persons with Office-Based Medical Provider Visit Events
When calculating an estimate of the total number of
persons with office-based medical provider visits, users can use a person-level
file or the current file. However, the current file must be used when the
measure of interest is defined at the event level. For example, to estimate the
number of office-based medical provider visits in person and not by telephone,
the current 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 (PERWT00F)for person i
and
Xi = 1 if SEETLKPVj = 1 for
any office-based medical provider visit of person i
= 0 otherwise.
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Contents
4.4
Person-Based Ratio Estimates
4.4.1
Person-Based Ratio Estimates Relative to Persons with Office-Based Medical
Provider Visit Events
This file may be used to derive person-based ratio
estimates. However, when calculating ratio estimates where the denominator is
persons, care should be taken to properly define and estimate the unit of
analysis up to person level. For example, the mean expense for persons with
office-based medical provider 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 (PERWT00F)for person i
and
| Zi = |
301 Moved Permanently
301 Moved Permanently
|
OBXP00Xj |
across all
office-based medical provider visits for person i. |
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4.4.2
Person-Based Ratio Estimates Relative to the Entire Population
If the ratio relates to the entire population, this file
cannot be used to calculate the denominator, as only those persons with at least
one office-based medical provider 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 visits and those without visits). For example, to estimate the
proportion of the civilian noninstitutionalized population of the U.S. with at
least one in-person office-based medical provider visit, the numerator would be
derived from data on the current file, and the denominator should 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 (PERWT00F) for person i
and
Zi = 1
if SEETLKPVj = 1
for any office-based medical provider visit of
person i.
= 0 otherwise.
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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 to another, the major analytical variable (i.e., the
dependent variable) determines the correct sampling weight to use.
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4.6 Variance
Estimation (VARSTR00, VARPSU00)
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 2000 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 VARSTR00
and VARPSU00, 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.
Examples 2 and 3 from Section 4.2
Using a Taylor Series approach, specifying VARSTR00 and
VARPSU00 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 $0.5677
and 0.0087 for the estimated mean of out-of-pocket payment and the estimated
mean proportion of total expenditures paid by private insurance, respectively.
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5.0
Merging/Linking MEPS Data Files
Data from this office-based medical provider visits file
can be used alone or in conjunction with other files. This section provides
instructions for linking the office-based medical provider visits with other
MEPS public use files, including the conditions file, the prescribed medicines
file, and a person-level file.
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Contents
5.1 Linking a
2000 Person-Level File to the 2000 Office-Based Medical Provider Visits
File
Merging characteristics of interest from person-level
files (e.g., MEPS 2000 Full Year Population Characteristics File) expands the
scope of potential estimates. For example, to estimate the total number of
office-based medical provider visits of persons with specific demographic
characteristics (such as age, race, and sex), population characteristics from a
person-level file need to be merged onto the office-based medical provider
visits file. This procedure is illustrated below. The MEPS 2000 Appendix File,
HC-051I provides additional detail on how to merge MEPS
data files.
- Create data set PERSX by sorting the 2000 Full Year
Population Characteristics File, by the person identifier, DUPERSID. Keep
only variables to be merged onto the office-based medical provider visits
file and DUPERSID.
- Create data set OBMP by sorting the office-based
medical provider visits file by person identifier, DUPERSID.
- Create final data set NEWOBMP by merging these two
files by DUPERSID, keeping only records on the office-based medical
provider visits file.
The following is an example of SAS code,
which completes these steps:
PROC SORT DATA=2000 Full Year
Population Characteristics file (KEEP=DUPERSID AGE31X AGE42X AGE53X SEX
RACEX)
OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA=OBMP;
BY DUPERSID;
RUN;
DATA NEWOBMP;
MERGE OBMP (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
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5.2 Linking the MEPS 2000 Office-Based Medical Provider Visits File to the MEPS 2000 Medical Conditions File and/or the MEPS 2000 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.
These limitations/caveats are listed below. For detailed linking examples,
including SAS code, data users/analysts should refer to the MEPS 2000 Appendix
File, HC-051I.
5.2.1
Limitations/Caveats of RXLK (the Prescribed Medicine Link File)
The RXLK file provides a link from MEPS event files to the
2000 Prescribed Medicine File. When using RXLK, data users/analysts should keep
in mind that one office-based medical visit can link to more than one prescribed
medicine record. Conversely, a prescribed medicine event may link to more than
one office-based medical visits or different types of events. When this occurs,
it is up to the analyst to determine how the prescribed medicine expenditures
should be allocated among those medical events.
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5.2.2
Limitations/Caveats of CLNK (the Medical Conditions Link File)
The CLNK provides a link from MEPS event files to the 2000
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 office-based medical provider visit. Users should
also note that not all office-based medical provider visits link to the
condition file.
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References
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.
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Contents
D.
Variable-Source Crosswalk
For MEPS HC-051G: 2000 Office-Based
Medical Provider 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 |
|
MPCELIG |
MPC eligibility flag |
Constructed |
|
MPCDATA |
MPC data flag |
Constructed |
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Contents
Medical Provider Visits Variables
| Variable |
Description |
Source |
|
OBDATEYR |
Event date - year |
CAPI derived |
|
OBDATEMM |
Event date - month |
CAPI derived |
|
OBDATEDD |
Event date - day |
CAPI derived |
|
SEETLKPV |
Did Person visit provider in person
or telephone |
MV01 |
|
REFERDBY |
This visit referred by another
physician |
MV02 |
|
SEEDOC |
Did Person talk to MD this
visit/phone call |
MV03 |
|
MEDPTYPE |
Type of medical person Person talked
to on visit date |
MV04 |
|
TIMESPNT |
Time Person spent with
doctor/medical person |
MV05 |
|
DOCATLOC |
Any MD work at location where Person
saw provider |
MV06 |
|
VSTCTGRY |
Best category for care Person
received on visit date |
MV07 |
|
VSTRELCN |
Was this visit/phone call related to
spec hlth cond |
MV08 |
|
PHYSTH |
This visit did Person have physical
therapy |
MV10 |
|
OCCUPTH |
This visit did Person have
occupational therapy |
MV10 |
|
SPEECHTH |
This visit did Person have speech
therapy |
MV10 |
|
CHEMOTH |
This visit did Person have
chemotherapy |
MV10 |
|
RADIATTH |
This visit did Person have radiation
therapy |
MV10 |
|
KIDNEYD |
This visit did Person have kidney
dialysis |
MV10 |
|
IVTHER |
This visit did Person have IV
therapy |
MV10 |
|
DRUGTRT |
This visit did Person have treatment
for drug/alcohol |
MV10 |
|
RCVSHOT |
This visit did Person receive an
allergy shot |
MV10 |
|
PSYCHOTH |
Did Person have
psychotherapy/counseling |
MV10 |
|
LABTEST |
This visit did Person have lab tests |
MV11 |
|
SONOGRAM |
This visit did Person have sonogram
or ultrasound |
MV11 |
|
XRAYS |
This visit did Person have x-rays |
MV11 |
|
MAMMOG |
This visit did Person have a
mammogram |
MV11 |
|
MRI |
This visit did Person have an MRI/Catscan |
MV11 |
|
EKG |
This visit did Person have an EKG or
ECG |
MV11 |
|
EEG |
This visit did Person have an EEG |
MV11 |
|
RCVVAC |
This visit did Person receive a
vaccination |
MV11 |
|
ANESTH |
This visit did Person receive
anesthesia |
MV11 |
|
OTHSVCE |
This visit did Person have other
diagnostic test/exam |
MV11 |
|
SURGPROC |
Was surgical procedure performed on
Person this visit |
MV12 |
|
SURGNAME |
Surgical procedure name in
categories |
MV13 |
|
MEDPRESC |
Any medicines prescribed for Person
this visit |
MV14 |
|
VAPLACE |
VA Facility Flag |
Constructed |
|
OBICD1X |
3-digit ICD-9 condition code |
Edited |
|
OBICD2X |
3-digit ICD-9 condition code |
Edited |
|
OBICD3X |
3-digit ICD-9 condition code |
Edited |
|
OBICD4X |
3-digit ICD-9 condition code |
Edited |
|
OBPRO1X |
2-digit ICD-9 procedure code |
Edited |
|
OBCCC1X |
Modified Clinical Classification
Code (CCS) |
Constructed/Edited |
|
OBCCC2X |
Modified Clinical Classification
Code (CCS) |
Constructed/Edited |
|
OBCCC3X |
Modified Clinical Classification
Code (CCS) |
Constructed/Edited |
|
OBCCC4X |
Modified Clinical Classification
Code (CCS) |
Constructed/Edited |
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Flat Fee Variables
| Variable |
Description |
Source |
|
FFOBTYPE |
Flat fee bundle |
Constructed |
|
FFBEF00 |
Total # of visits in FF before 2000 |
FF05 |
|
FFTOT01 |
Total # of visits in FF after 2000 |
FF10 |
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Contents
Imputed Expenditure Variables
| Variable |
Description |
Source |
|
OBSF00X |
Amount paid, self/family (imputed) |
CP Section (Edited) |
|
OBMR00X |
Amount paid, Medicare (imputed) |
CP Section (Edited) |
|
OBMD00X |
Amount paid, Medicaid (imputed) |
CP Section (Edited) |
|
OBPV00X |
Amount paid, private insurance
(imputed) |
CP Section (Edited) |
|
OBVA00X |
Amount paid, Veterans Administration
(imputed) |
CP Section (Edited) |
|
OBTR00X |
Amount paid, TRICARE (imputed) |
CP Section (Edited) |
|
OBOF00X |
Amount paid, other federal (imputed) |
CP Section (Edited) |
|
OBSL00X |
Amount paid, state & local
government (imputed) |
CP Section (Edited) |
|
OBWC00X |
Amount paid, workers' compensation
(imputed) |
CP Section (Edited) |
|
OBOR00X |
Amount paid, other private insurance
(imputed) |
Constructed |
|
OBOU00X |
Amount paid, other public insurance
(imputed) |
Constructed |
|
OBOT00X |
Amount paid, other insurance
(imputed) |
CP Section (Edited) |
|
OBXP00X |
Sum of OBSF00X - OBOT00X (imputed) |
Constructed |
|
OBTC00X |
Household reported total charge
(imputed) |
CP Section (Edited) |
|
IMPFLAG |
Imputation status |
Constructed |
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Contents
Weights
| Variable |
Description |
Source |
|
PERWT00F |
Final person level weight, 2000 |
Constructed |
|
VARSTR00 |
Variance estimation stratum, 2000 |
Constructed |
|
VARPSU00 |
Variance estimation PSU, 2000 |
Constructed |
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