MEPS HC-026G: 1998 Office-Based Medical Provider Visits
October 2001
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 Naming
2.4.1 General
2.4.2 Expenditure and Sources of Payment Variables
2.5 File 1 Contents
2.5.1 Survey Administration and ID Variables
2.5.1.1 Person Identifiers
(DUID- DUPERSID)
2.5.1.2 Record Identifiers
(EVNTIDX, FFEEIDX, EVENTRN)
2.5.2 Characteristics of Office-Based Medical Provider Visits
2.5.2.1 Date of Office-Based Medical Provider Visit
(OBDATEYR
- OBDATEDD)
2.5.2.2 Visit Details
(SEETLKPV-VSTRELCN)
2.5.2.3 Treatments, Procedures, Services, and Prescription
Medicines (PHYSTH-MEDPRESC)
2.5.2.4 Other Visit Details
(VAPLACE)
2.5.2.5 MPC Indicator
(MPCELIG, MPCDATA)
2.5.3 Condition and Procedure Codes (OBICD1X-OBICD4X, OBPRO1X) and
Clinical Classification Codes (OBCCC1X-OBCCC4X)
2.5.4 Flat Fee Variables
(FFOBTYPE, FFBEF98, FFTOT99)
2.5.4.1 Definition of Flat Fee Payments
2.5.4.3 Caveats of Flat Fee Groups
2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
2.5.5.2 Imputation and Data Editing Methodologies of
Expenditure Variables
2.5.5.2.1 General Data Editing Methodology
2.5.5.2.2 General Hot-Deck Imputation
2.5.5.3 Capitation Imputation
2.5.5.4 Imputation Methodology for Office-based Medical
Provider Events
2.5.5.5 Flat Fee Expenditures
2.5.5.6 Zero Expenditures
2.5.5.7 Discount Adjustment Factor
2.5.5.8 Sources of Payment
2.5.5.9 Office- Based Expenditure Variables (OBSF98X -
OBXP98X)
2.5.5.10 Rounding
2.5.5.11 Identifying Imputed Expenditures
2.6 File 2 Contents: Pre-imputed Expenditure Variables
3.0 Sample Weight (WTDPER98)
3.1 Overview
3.2 Details on Person Weights Construction
3.2.1 MEPS Panel 2 Weight
3.2.2 MEPS Panel 3 Weight
3.2.3 The Final Weight for 1998
3.2.4 Coverage
4.0 Strategies for Estimation
4.1 Variables with Missing Values
4.2 Basic Estimates of Utilization, Expenditure and Sources of
Payment
4.3 Estimates of the Number of Persons with Office-Based Medical
Provider Visits
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with
Office-Based Medical Provider Visits
4.4.2 Person-Based Ratio Estimates Relative to the Entire
Population
4.5 Sampling Weights for Merging Previous Releases of MEPS Household
Data with this Event File
4.6 Variance Estimation
5.0 Merging/Linking MEPS Data Files
5.1 Linking a Person-Level File to the Office-Based Medical Provider
Visit File
5.2 Linking the Office-Based Medical Provider Visit file to the MEPS
1998 Medical Conditions File and/or the MEPS 1998 Prescribed Medicines
File
5.3 Limitations/Caveats of RXLK (the Prescribed Medicine Link File)
5.4 Limitations/Caveats of CLNK (the Medical Conditions Link File)
References
Attachment 1
D. Variable Source Crosswalk
A. Data Use Agreement
Individual identifiers have been removed from the microdata
contained in the files on this CD-ROM. Nevertheless, under sections 308 (d) and
903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1),
data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or
the National Center for Health Statistics (NCHS) may not be used for any purpose
other than for the purpose for which they were supplied; any effort to determine
the identity of any reported cases, is prohibited by law.
Therefore in accordance with the above referenced Federal
statute, it is understood that:
-
No one is to use the data in this data set in any
way except for statistical reporting and analysis.
-
If the identity of any person or establishment
should be discovered inadvertently, then (a) no use will be made of this
knowledge, (b) the Director, Office of Management, AHRQ will be advised of
this incident, (c) the information that would identify any individual or
establishment will be safeguarded or destroyed, as requested by AHRQ, and
(d) no one else will be informed of the discovered identity.
-
No one will attempt to link this data set with individually identifiable
records from any data sets other than the Medical Expenditure Panel Survey
or the National Health Interview Survey.
By using these data you signify your agreement to comply with
the above-stated statutorily based requirements, with the knowledge that
deliberately making a false statement in any matter within the jurisdiction of
any department or agency of the Federal Government violates 18 U.S.C. 1001 and
is punishable by a fine of up to $10,000 or up to 5 years in prison.
The Agency for Healthcare Research and Quality requests that
users cite AHRQ and the Medical Expenditure Panel Survey as the data source in
any publications or research based upon these data.
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B. Background
This documentation describes one in a series of public use
files from the Medical Expenditure Panel Survey (MEPS). The survey provides an
extensive data set on the use of health services and health care in the United
States.
MEPS is conducted to provide nationally representative
estimates of health care use, expenditures, sources of payment, and insurance
coverage for the U.S. civilian noninstitutionalized population. MEPS also
includes a nationally representative survey of nursing homes and their
residents. MEPS is cosponsored by the Agency for Healthcare Research and Quality
(AHRQ) (formerly the Agency for Health Care Policy and Research (AHCPR)) and the
National Center for Health Statistics (NCHS).
MEPS comprises three component surveys: the Household
Component (HC), the Medical Provider Component (MPC), and the Insurance
Component (IC). The HC is the core survey, and it forms the basis for the MPC
sample and part of the IC sample. Together these surveys yield comprehensive
data that provide national estimates of the level and distribution of health
care use and expenditures, support health services research, and can be used to
assess health care policy implications.
MEPS is the third in a series of national probability surveys
conducted by AHRQ on the financing and use of medical care in the United States.
The National Medical Care Expenditure Survey (NMCES, also known as NMES-1) was
conducted in 1977. The National Medical Expenditure Survey (NMES-2) was
conducted in 1987. Beginning in 1996, MEPS continues this series with design
enhancements and efficiencies that provide a more current data resource to
capture the changing dynamics of the health care delivery and insurance system.
The design efficiencies incorporated into MEPS are in
accordance with the Department of Health and Human Services (DHHS) Survey
Integration Plan of June 1995, which focused on consolidating DHHS surveys,
achieving cost efficiencies, reducing respondent burden, and enhancing
analytical capacities. To accommodate these goals, new MEPS design features
include linkage with the National Health Interview Survey (NHIS), from which the
sampling frame for the MEPS HC is drawn, and continuous longitudinal data
collection for core survey components. The MEPS HC augments NHIS by selecting a
sample of NHIS respondents, collecting additional data on their health care
expenditures, and linking these data with additional information collected from
the respondents, medical providers, employers, and insurance providers.
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Contents
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 1/2 -year period. Using computer-assisted personal
interviewing (CAPI) technology, data on medical expenditures and use for two
calendar years are collected from each household. This series of data collection
rounds is launched each subsequent year on a new sample of households to provide
overlapping panels of survey data and, when combined with other ongoing panels,
will provide continuous and current estimates of health care expenditures.
The sampling frame for the MEPS HC is drawn from respondents
to NHIS, conducted by NCHS. NHIS provides a nationally representative sample of
the U.S. civilian noninstitutionalized population, with oversampling of
Hispanics and blacks.
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2.0 Medical Provider Component
The MEPS MPC supplements and validates information on medical
care events reported in the MEPS HC by contacting medical providers and
pharmacies identified by household respondents. The MPC sample includes all
hospitals, hospital physicians, home health agencies, and pharmacies reported in
the HC. Also included in the MPC are all office-based physicians who:
- were identified by the household respondent as providing care for HC
respondents receiving Medicaid.
- were selected through a 75-percent sample of HC households receiving care
through an HMO (health maintenance organization) or managed care plan.
- were selected through a 25-percent sample of the remaining HC households.
Data are collected on medical and financial characteristics
of medical and pharmacy events reported by HC respondents, including:
- Diagnoses coded according to ICD-9-CM (9th Revision, International
Classification of Diseases) and DSM-IV (Fourth Edition, Diagnostic and
Statistical Manual of Mental Disorders).
- Physician procedure codes classified by CPT-4 (Common Procedure
Terminology, Version 4).
- Inpatient stay codes classified by DRGs (diagnosis-related groups).
- Prescriptions coded by national drug code (NDC), medication name,
strength, and quantity dispensed.
- Charges, payments, and the reasons for any difference between charges and
payments.
The MPC is conducted through telephone interviews and mailed
survey materials. In some instances, providers sent medical and billing records
which were abstracted into the survey instruments.
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3.0 Insurance Component
The MEPS IC collects data on health insurance plans obtained
through employers, unions, and other sources of private health insurance. Data
obtained in the IC include the number and types of private insurance plans
offered, benefits associated with these plans, premiums, contributions by
employers and employees, eligibility requirements, and employer characteristics.
Establishments participating in the MEPS IC are selected
through four sampling frames:
- A list of employers or other insurance providers identified by MEPS HC
respondents who report having private health insurance at the Round 1
interview.
- A Bureau of the Census list frame of private-sector business
establishments.
- The Census of Governments from Bureau of the Census.
- An Internal Revenue Service list of the self-employed.
To provide an integrated picture of health insurance, data
collected from the first sampling frame (employers and insurance providers) are
linked back to data provided by the MEPS HC respondents. Data from the other
three sampling frames are collected to provide annual national and State
estimates of the supply of private health insurance available to American
workers and to evaluate policy issues pertaining to health insurance.
The MEPS IC is an annual survey. Data are collected from the
selected organizations through a prescreening telephone interview, a mailed
questionnaire, and a telephone 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 and microdata files. Summary reports are released as printed documents
and electronic files. Microdata files are released on CD-ROM and/or as
electronic files.
Printed documents and CD-ROMs are available through the AHRQ
Publications Clearinghouse. Write or call:
AHRQ Publications Clearinghouse
Attn: (publication number)
P.O. Box 8547
Silver Spring, MD 20907
800/358-9295
410/381-3150 (callers outside the United States only)
888/586-6340 (toll-free TDD service; hearing impaired only)
Be sure to specify the AHRQ number of the document or CD-ROM
you are requesting. Electronic files and accompanying documentation are
available from the Internet on the MEPS web site: <http://www.meps.ahrq.gov/>.
Additional information on MEPS is available from the MEPS
project manager or the MEPS public use data manager at the Center for Cost and
Financing Studies, Agency for Healthcare Research and Quality.
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Contents
C. Technical and Programming
Information
1.0 General Information
This documentation describes one in a series of public use
event files from the 1998 Medical Expenditure Panel Survey (MEPS) Household (HC)
and Medical Provider Components (MPC). Released as an ASCII data file and a SAS
transport file, the 1998 Office-Based Medical Provider 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 1998. As illustrated below, this file consists of MEPS survey data
obtained in the 1998 portion of Round 3 and Rounds 4 and 5 for Panel 2, as well
as Rounds 1,2 and the 1998 portion of Round 3 for Panel 3 of the MEPS HC (i.e.,
the rounds for the MEPS panels covering calendar year 1998).
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. Counts utilization of office-based provider visits are
based entirely on household reports. Office-based providers were sampled into
the MEPS MPC (see section B 2.0). Only those providers for whom the respondent
signed a permission form were included in the MPC. 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 1998 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 be also used to construct summary variables of
expenditures, sources of payment, and related aspects of office-based provider
visits for calendar year 1998. Aggregate annual person-level information on the
use of office-based providers and other health services use is provided on the
MEPS 1998 Full Year Person Level Expenditure file, where each record represents
a MEPS sampled person.
This documentation offers a brief overview of the types and
levels of data provided, the content and structure of the files and the
codebook. It contains the following sections:
Data File Information
Sample Weights and Variance Estimation Variables
Strategies for Estimation
Merging/linking MEPS Data Files
References
Attachment 1: Definitions
Codebooks
Variable to 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 office-based provider public use data set consists of two
event-level data files. File 1 contains characteristics associated with the
office-based provider event and imputed expenditure data. File 2 contains the
pre-imputed expenditure data from both the Household and Medical Provider
Components for all office-based provider visits on File 1. See Attachment 1 for
definitions of imputed, and pre-imputed expenditure variables.
Both File 1 and File 2 of the office-based provider public
use data set contain 104,740 office-based provider event records; of these
records, 102,898 are associated with persons having a positive person-level
weight (WTDPER98). 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 1998. Office-based provider visits known to have occurred after December
31, 1998 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 1998 portion of round
3 and rounds 4 and 5 for Panel 2, as well as rounds 1, 2, and the 1998 portion
of round 3 for Panel 3 of the MEPS HC. The persons represented on this file had
to meet either (a) or (b):
(a) Be classified as a key in-scope person who responded
for his or her entire period of 1998 eligibility (i.e., persons with a
positive 1998 full-year person-level sampling weight (WTDPER98>0)), or
(b) Be classified as either an eligible non-key person or
an eligible out-of-scope person who responded for his or her entire period
of 1998 eligibility, and belonged to a family (i.e., all persons with the
same value for FAMID) in which all eligible family members responded for
their entire period of 1998 eligibility, and at least one family member had
a positive 1998 full-year person weight (i.e., eligible non-key or eligible
out-of-scope persons who are members of a family all of whose members have a
positive 1998 full-year family-level weight (WTFAM98>0)).
Please refer to Attachment 1 for definitions of keyness,
in-scope and eligibility. Persons with no office-based medical provider visit
for 1998 are not included on this file (but are represented on MEPS person-level
files).
Each office-based medical provider event record on File 1
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.
File 2 of the office-based provider public use data set is
intended for data users/analysts who want to perform their own imputations to
handle missing data. This file contains one set of un-imputed expenditure
information from the Medical Provider Component (if office-based provider
sampled into MPC) as well as one set of pre-imputed expenditure information from
the Household Component. Both sets of expenditure data have been subject to
minimal logical editing that accounted for outliers, copayments or charges
reported as total payments, and reimbursed amounts that were reported as out of
pocket payments. In addition, edits were implemented to correct for
misclassifications between Medicare and Medicaid and between Medicare HMOs and
private HMOs as payment sources. However, missing data were not imputed.
Data from both Files 1 and 2 can be merged with the MEPS 1998
Full Year Population Characteristics file using the unique person identifier,
DUPERSID, to append person-level characteristics such as demographic or health
insurance characteristics to each record. The office-based medical provider
events can also be linked to the MEPS 1998 Medical Conditions File and MEPS 1998
Prescribed Medicines File. Please see the section 5.0 for details on how
to merge MEPS data files.
Panel 2 cases (PANEL98 = 2 on the MEPS1998 Full Year
Population Characteristics File) can also be linked back to the 1997 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
2 data.
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2.1 Codebook Structure
For each variable on the office-based provider files, both
weighted and unweighted frequencies are provided in the codebooks. The codebook
and data file sequence list variables in the following order:
File 1
Unique person identifiers
Unique office-based medical provider event identifier
Other survey administration variables
Office-based medical provider characteristic variables
ICD-9 codes
Clinical Classification Software codes
Imputed expenditure variables
Weight and variance estimation variables
File 2
Unique person identifiers
Unique office-based medical provider visit identifier
Pre-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, -1, -7, -8, and -9 have not been edited on this
file. The values of -1 and -9 can be edited by the data users/analysts by
following the skip patterns in the HC survey questionnaire (located on the MEPS
web site: <http://www.meps.ahrq.gov//survey_comp/survey.jsp>).
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2.3 Codebook Format
The office-based medical provider codebook describes an ASCII
data set (although the data are also being provided in a SAS transport file).
The following codebook items are provided for each variable:
| IDENTIFIER |
DESCRIPTION |
| Name |
Variable name (maximum of 8
characters) |
| Description |
Variable descriptor (maximum 40
characters) |
| Format |
Number of bytes |
| Type |
Type of data: numeric (indicated by
NUM) or character (indicated by CHAR) |
| Start |
Beginning column position of
variable in record |
| End |
Ending column position of variable
in record |
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2.4 Variable Naming
In general, variable names reflect the content of the
variable, with an 8-character limitation. All imputed/edited variables end with
an "X."
2.4.1 General
Variables contained on Files 1 and 2 were derived from the HC
survey questionnaire. The source of each variable is identified in Section D,
the "Variable - Source Crosswalk." Sources for each variable are
indicated in one of four ways:
- variables which are derived from CAPI or assigned in sampling are so indicated as "capi derived" or "assigned in sampling,";
variables which come from one or more specific questions have those
questionnaire sections and question numbers indicated in the
"Source" column
EV-Event Roster section
FF- Flat Fee section
CP- Charge Payment section;
-
variables constructed from multiple questions using complex algorithms are
labeled "Constructed" in the "Source" column; and
-
variables which have been edited or imputed are so indicated.
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2.4.2 Expenditure and Sources of Payment
Variables
Pre-imputed and imputed versions of the expenditure and
sources of payment variables are provided on two separate files. Variables on
Files 1 and 2 follow a standard naming convention and are 8 characters in
length. Please note that pre-imputed means that a series of logical edits have
been performed on the variable but missing data remains. The imputed versions
incorporate the same edits but have also undergone an imputation process to
account for missing data.
All imputed variables on File 1 end with an "X" indicating they are
fully edited and imputed.
The pre-imputed expenditure variables on File 2 end with an "H"
indicating that the data source was the MEPS Household Component.
The total sum of payments variables, 12 sources of payment variables, and the
total charge variables are named consistently in the following way:
The first two characters indicate the type of event:
IP - inpatient stay
OB - office-based
visit
ER - emergency room visit
OP - outpatient
visit
HH - home health 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
XP - sum
of payments
MR - Medicare
SL - State/local government
MD - Medicaid
WC - Worker's
Compensation
PV - private insurance
OT - other
insurance
VA - Veterans
OR - other private
CH - CHAMPUS/CHAMPVA
OU - other public
The fifth and sixth characters indicate the year (98). The
last character indicates whether it is edited/imputed (X) or came from household
(H) or MPC (M).
For example, OBSF98X is the edited/imputed amount paid by
self or family for an office-based medical provider expenditure incurred in
1998.
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2.5 File 1 Contents
2.5.1 Survey Administration and ID Variables
2.5.1.1 Person Identifiers (DUID- DUPERSID)
The dwelling unit ID (DUID) is a 5-digit random number
assigned after the case was sampled for MEPS. The 3-digit person number (PID)
uniquely identifies each person within the dwelling unit. The 8-character
variable DUPERSID uniquely identifies each person represented on the file and is
the combination of the variables DUID and PID. For detailed information on
dwelling units and families, please refer to the documentation for the 1998 Full
Year Population Characteristics File or to definitions listed in Attachment 1.
2.5.1.2 Record Identifiers (EVNTIDX, EVENTRN,
FFEEIDX)
EVNTIDX uniquely identifies each office-based medical
provider event (i.e. each record on the office-based medical provider file) and
is the variable required to linking office-based medical provider events to data
files containing details on conditions and/or prescribed medicines (MEPS 1998
Medical Condition file and MEPS 1998 Prescribed Medicine file; respectively).
For details on linking see Section 5.0 or the MEPS 1998 Appendix file.
EVENTRN indicates the round in which the office-based medical
provider visit were reported. Please note: Rounds 3, 4, and 5 are associated
with MEPS survey data collected from Panel 2. Likewise, Rounds 1, 2, and 3 are
associated with data collected from Panel 3.
FFEEIDX is a constructed variable which uniquely identifies a
flat fee group, that is, all events that were part of a flat fee payment
situation. For example, 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. Please note that FFEEIDX should be
used to link up all MEPS event files (excluding prescribed medicines) in order
to determine the full set of events that are part of a flat fee group.
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2.5.2 Characteristics of Office-Based Medical
Provider Visits
2.5.2.1 Date of Office-Based Medical Provider
Visit (OBDATEYR - OBDATEDD)
File 1 contains variables describing office-based medical
provider events reported by respondents in the Medical Provider Visits section
of the MEPS HC survey questionnaire. There are three variables which indicate
the day, month and year an office-based provider visit occurred (OBDATEYR,
OBDATEMM, and OBDATEDD, respectively). These variables have not been edited or
imputed.
2.5.2.2 Visit Details (SEETLKPV-VSTRELCN)
The questionnaire determines if during the office-based
medical provider visit whether 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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2.5.2.3 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 inapplicables, 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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2.5.2.4 Other Visit Details (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 unknown.
2.5.2.5 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 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 codes (OBICD1X-OBICD4X), one
procedure code (OBPRO1X), and up to four clinical classification codes
(OBCCC1X-OBCCC4X) 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 reported by the Household Component
respondent were recorded by the interviewer as verbatim text, which were then
coded to fully-specified 1998 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 1998 Medical
Conditions File. For frequencies of conditions by event type, please see: the
MEPS 1998 Appendix File.
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 3-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.
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 chronological order of occurrence 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 visit file should note
that the order of conditions on this file is not identical to that on the 1998
Medical Conditions file.
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2.5.4 Flat Fee Variables (FFOBTYPE, FFBEF98,
FFTOT99)
2.5.4.1 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, as well as 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, includes flat fee groups where at
least one of the health care events, as reported by the HC respondent, occurred
during 1998. By definition, a flat fee group can span multiple years and/or
event types (e.g., outpatient department visit, physician office visit).
Furthermore a single person can have multiple flat fee groups.
There are four variables on the office-based provider file that describe a
flat fee payment situation and the number of medical events that are part of a
flat fee group.
Flat Fee Variable Descriptions
Flat Fee ID (FFEEIDX)
As noted earlier in the Section 2.5.1.2 "Record
Identifiers," for a person, the variable FFEEIDX can be used to uniquely
identify all events that are part of the same flat fee group. It can identify
such events from all of the1998 MEPS event files (excluding the prescribed
medicine file) because FFEEIDX is the same value on all of the MEPS event files.
For the office-based medical provider events that are not part of a flat fee
payment situation, the flat fee variables described below are all set to -1
INAPPLICABLE.
Flat Fee Type (FFOBTYPE)
FFOBTYPE indicates whether the 1998 office-based medical
provider 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.
Counts of Flat Fee Events that Cross Years (FFBEF98 -
FFTOT99)
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 a 1998 office-based medical provider visit is part of a group
of events, and some of the events occurred before 1998, counts of the known
events are provided on the office-based medical provider event file record.
Indicator variables are provided if some of the events occurred before or after
1998. These variables are:
FFBEF98 -- total number of pre-1998 events in the
same flat fee group as the 1998 office-based medical provider event.
This count would not include 1998 office-based medical provider visit.
FFTOT99 -- indicates whether or not there are 1999
medical events in the same flat fee group as the 1998 office-based
medical provider event record.
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2.5.4.3 Caveats of Flat Fee Groups
Data users/analysts should note that flat fee payment
situations are common on the office-based medical provider file. There are 3,004
office-based medical provider 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 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 1998, but the remaining visits that were part of this flat fee group
occurred in 1999. In this case, the 1998 flat fee group represented on this file
would consist of one event (the stem). The 1999 "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 1997 but subsequent visits occurred during 1998. In this case, the
initial visit would not be represented on the file. This 1998 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 a leaf record is that the
stems or leaves could have been reported as different event types. In a small
number of cases, there are flat fee groups that span various event types (e.g.
office-based medical provider visit). The stem may have been reported as one
event type (e.g. outpatient department visit) and the leaves may have been
reported as another event type (e.g. office-based medical provider visit).
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2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
Expenditures on Files 1 and 2 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 are they directly comparable to the
resource costs of those services, nor are they directly comparable to the
expenditures defined in the 1987 NMES (for details on expenditure definitions
see Monheit et al, 1999). AHRQ has developed factors to apply to the 1987 NMES
expenditure data to facilitate longitudinal analysis. These factors can be
assessed via 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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2.5.5.2 Imputation and Data Editing
Methodologies of Expenditure Variables
The expenditure data included on this file were derived from
both the MEPS HC and MPC. 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. Specific methodologies
for editing and imputing office-based provides expenditures follows
2.5.5.2.1 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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2.5.5.2.2 General Hot-Deck Imputation
A weighted sequential hot-deck procedure was used to impute
for missing expenditures as well as total charge. The procedure uses survey data
from respondents to 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. 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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2.5.5.3 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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2.5.5.4 Imputation Methodology for Office-based
Medical Provider Events
Expenditures on visits of office-based medical providers 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 for matched events, 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. Many physician visits were imputed as flat fee events because the
charges covered a package of health care services. In some cases, all of the
services were provided in the physician's office. In other cases, the
physician provided services in multiple settings such as his or her office and a
hospital.
Logical edits also were used to sort each event into a
specific category for the imputations. Events with complete expenditures were
flagged as potential donors for the hot-deck imputations while events with
missing expenditure data were assigned to various recipient categories. Each
event was assigned to a recipient category based on its pattern of missing data.
For example, an event with a known total charge but no expenditure information
was assigned to one category, while an event with a known total charge and some
expenditure information was assigned to a different category. Similarly, events
without a known total charge were assigned to various recipient categories based
on the amount of missing data.
The logical edits produced eight recipient categories for
events with missing data. Expenditures were imputed through separate hot-deck
imputations for each of the eight recipient categories. The donor pool in these
imputations was restricted to events with complete expenditures from either the
HC or the MPC. For most MPC-eligible event types, unmatched household events
with complete data were not allowed to donate information to other events
because the MPC data were considered to be more reliable. However, this
restriction was relaxed in order to increase the size of the donor pool for
physician visits with missing expenditures and because household reported data
for physician visits was in general more reliable than for hospital-based
events.
The donor pool included "free events" because, in
some instances, providers are not paid for their services. These events
represent charity care, bad debt, provider failure to bill, and third party
payer restrictions on reimbursement in certain circumstances. If free events
were excluded from the donor pool, total expenditures would be over-counted
because the cost of free care would be implicitly included in paid events and
explicitly included in events that should have been treated as free from
provider.
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2.5.5.5 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 1998, all of the events that occurred in 1998 will have zero
payments. Conversely, if the first event in the flat fee group occurred at the
end of 1998, the total expenditure for the entire flat fee group will be on that
event, regardless of the number of events it covered after 1998.
2.5.5.6 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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2.5.5.7 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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2.5.5.8 Sources of Payment
In addition to total expenditures, variables are provided
which itemize expenditures according to major source of payment categories.
These categories are:
1. Out of pocket by user or family
2. Medicare
3. Medicaid
4. Private Insurance
5. Veteran's Administration, excluding CHAMPVA
6. CHAMPUS or CHAMPVA
7. Other Federal sources - includes Indian Health Service,
Military Treatment Facilities, and other care by the Federal government
8. Other State and Local Source - includes community and
neighborhood clinics, State and local health departments, and State programs
other than Medicaid.
9. Worker's Compensation
10. Other Unclassified Sources - includes sources such as
automobile, homeowner's, liability, and other miscellaneous or unknown
sources.
Two additional sources of payment variables were created to
classify payments for events with apparent inconsistencies between insurance
coverage and sources of payment based on data collected in the survey. These
variables include:
11. Other Private - any type of private insurance payments
reported for persons not reported to have any private health insurance coverage
during the year as defined in MEPS; and
12. Other Public - Medicaid payments reported for persons who
were not reported to be enrolled in the Medicaid program at any time during the
year.
Though relatively small in magnitude, data users/analysts
should exercise caution when interpreting the expenditures associated with these
two additional sources of payment. While these payments stem from apparent
inconsistent responses to health insurance and source of payment questions in
the survey, some of these inconsistencies may have logical explanations. For
example, private insurance coverage in MEPS is defined as having a major medical
plan covering hospital and physician services. If a MEPS sampled person did not
have such coverage but had a single service type insurance plan (e.g. dental
insurance) that paid for a particular episode of care, those payments may be
classified as "other private". Some of the "other public"
payments may stem from confusion between Medicaid and other state and local
programs or may be persons who were not enrolled in Medicaid, but were presumed
eligible by a provider who ultimately received payments from the program.
Data users/analysts should also note that the Other Public
and Other Private source of payment categories only exist on File 1 for imputed
expenditure data since they were created through the editing/imputation process.
File 2 reflects 10 sources of payment as they were collected through the survey
instrument.
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2.5.5.9 Office- Based Expenditure Variables
(OBSF98X - OBXP98X)
There are 13 expenditure variables included on this event
file. All of these expenditures have gone through an editing and imputation
process and have been rounded to the second decimal place. There is a sum of
payments variable (OBXP98X) which for each office-based medical provider visit
sums all the expenditures from the various source of payment. The 12 sources of
payment expenditure variables for each office-based medical provider visit are
the following: amount paid by self or family (OBSF98X), amount paid by Medicare
(OBMR98X), amount paid by Medicaid (OBMD98X), amount paid by private insurance
(OBPV98X), amount paid by Veterans Administration (OBVA98X), amount paid by
CHAMPUS/CHAMPVA (OBCH98X), amount paid other federal sources (OBOF98X), amount
paid by state and local (non-federal) government sources (OBSL98X), amount paid
by Worker's Compensation (OBWC98X), and amount paid by some other source of
insurance (OBOT98X). As mentioned previously, there are two additional
expenditure variables called OBOR98X and OBOU98X (other private and other public
respectively). These two expenditure variables were created to maintain
consistency between what the household reported as their private and public
insurance status for hospitalization and physician coverage.
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2.5.5.10 Rounding
Expenditure variables on File 1 have been rounded to the
nearest penny. Person-level expenditure information released on the MEPS 1998
Person Level Expenditure file will be rounded to the nearest dollar. It should
be noted that using the MEPS event files to create person-level totals
will yield slightly different totals than that those found on 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 1998
Appendix File for details on such rounding differences.
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2.5.5.11
Identifying Imputed Expenditures
If the data user/analyst desires to identify whether sources of payment and
total charge have been imputed, simply compare the expenditure variable of
interest from File 2 with the corresponding variable from File 1. An imputed
value would be one having a missing value on File 2 while the value on File 1
would be zero or greater. In a small number of cases, an imputed value on File 1
will have a corresponding value of zero rather than missing on File 2.
As explained in section 2.5.5.8 "Sources of Payment," there are 10
sources of payment variables in the pre-imputed expenditure data on File 2,
while the imputed expenditure data on File 1 contains 12 sources of payment
variables. The additional two sources of payment (which are not reported as
separate sources of payment through the data collection) are Other Private and
Other Public. These sources of payment categories were constructed to resolve
apparent inconsistencies between individuals' reported insurance coverage and
their sources of payment for specific events, such as where the insurance
variables indicated uninsured all year but the person reported private insurance
as a payor source.
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2.6 File 2 Contents: Pre-imputed Expenditure
Variables
Pre-imputed expenditure data are provided on File 2.
Pre-imputed means that only a series of logical edits were applied to the data
to correct for several problems including outliers, copayments or charges
reported as total payments, and reimbursed amounts counted as out of pocket
payments. Edits were also implemented to correct for misclassifications between
Medicare and Medicaid and between Medicare HMO's and private HMO's as
payment sources as well as a number of other data inconsistencies that could be
resolved through logical edits. This file contains no imputed data.
Included on File 2 is the variable HHSFFIDX, which is the
original flat fee identifier that was derived during the household interview.
This identifier should only be used if the data user/analyst is interested in
performing their own expenditure imputation.
The data user/analyst should note that there are 10 sources
of payment variables in the pre-imputed expenditure data, while the imputed
expenditure data on File 1 contains 12 sources of payment variables. The
additional two sources of payment (which are not reported as separate sources of
payment through the data collection) are Other Private and Other Public. These
source of payment categories were constructed to resolve apparent
inconsistencies between individual's reported insurance coverage and their
sources of payment for specific events. File 2 also includes a variable
indicating uncollected liability. Uncollected liability was not used in
imputation.
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3.0 Sample Weight
(WTDPER98)
3.1 Overview
There is a single full year person-level weight (WTDPER98) 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 1998. A key person either was a
member of an NHIS household at the time of the NHIS interview, or became a
member of such a household after being out-of-scope at the time of the NHIS
(examples of the latter situation include newborns and persons returning from
military service, an institution, or living outside the United States). A person
is in-scope whenever he or she is a member of the civilian noninstitutionalized
portion of the U.S. population.
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3.2 Details on
Person Weights Construction
The final person-level weight WTDPER98 was developed in three stages. A
person level weight for Panel 3 was created, including both an adjustment for
nonresponse over time and poststratification, controlling to Current Population
Survey (CPS) population estimates based on five variables. Variables used in the
establishment of person-level poststratification control figures included:
census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA);
race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and age. Then
a person level weight for Panel 2 was created, again including an adjustment for
nonresponse over time and poststratification, again controlling to CPS
population estimates based on the same five variables. When poverty status
information derived from income variables became available, a 1998 composite
weight was formed from the Panel 2 and Panel 3 weights by multiplying the Panel
weights by .5. Then a final poststratification was done on this composite weight
variable, including poverty status (below poverty, from 100 to 125 percent of
poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty,
at least 400 percent of poverty) as well as the original five poststratification
variables in the establishment of control totals.
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3.2.1 MEPS Panel 2
Weight
The person level weight for MEPS Panel 2 was developed using the 1997 full
year weight for an individual as a "base" weight for survey
participants present in 1997. For key, in-scope respondents who joined a RU some
time in 1998 after being out of scope in 1997, the 1997 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 1998.
These control figures were derived by scaling back the population totals
obtained from the March 1998 CPS to reflect the December, 1998 CPS estimated
population distribution across age and sex categories as of December, 1998.
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, 1998 is 270,114,457. Key,
responding persons not in-scope on December 31, 1998 but in-scope earlier in the
year retained, as their final Panel 2 weight, the weight after the nonresponse
adjustment.
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3.2.2 MEPS Panel 3
Weight
The person level weight for MEPS Panel 3 was developed using the MEPS Round 1
person-level weight as a 'base" weight. For key, in-scope respondents who
joined a RU after Round 1, the Round 1 family weight served as a
"base" weight. The weighting process included an adjustment for
nonresponse over Round 2 and the 1998 portion of Round 3 as well as
poststratification to the same population control figures for December 1998 used
for the MEPS Panel 2 weights. The same five variables employed for Panel 2
poststratification (census region, MSA status, race/ethnicity, sex, and age)
were used for Panel 3 poststratification. Similarly, for Panel 3, key,
responding persons not in-scope on December 31, 1998 but in-scope earlier in the
year retained, as their final Panel 3 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 1998 CPS data
base.
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3.2.3 The Final
Weight for 1998
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, 1998
is 270,114,457 (WTDPER98>0 and INSC1231=1). The inclusion of key, in-scope
persons who were not in-scope on December 31, 1998 brings the estimated total
number of persons represented by the MEPS respondents over the course of the
year up to 273,533,690 (WTDPER98>0). The weighting process included
poststratification to population totals obtained from the 1996 MEPS Nursing Home
Component for the number of individuals admitted to nursing homes. For the 1998
full year file an additional poststratification was done to population totals
obtained from the 1997 Medicare Current Beneficiary Survey (MCBS) for the number
of deaths among Medicare beneficiaries experienced in the 1998 MEPS.
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3.2.4 Coverage
The target population for MEPS in this file is the 1998 U.S. civilian,
noninstitutionalized population. However, the MEPS sampled households are a
subsample of the NHIS households interviewed in 1997 (Panel 2) and 1998 (Panel
3). New households created after the NHIS interviews for the respective Panels
and consisting exclusively of persons who entered the target population after
1997 (Panel 2) or after 1998 (Panel 3) are not covered by MEPS. These would
include families consisting solely of: immigrants; persons leaving the military;
U.S. citizens returning from residence in another country; and persons leaving
institutions. It should be noted that this set of uncovered persons constitutes
only a tiny proportion of the MEPS target population.
4.0 Strategies for Estimation
This file is constructed for efficient estimation of utilization,
expenditure, 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 1998.
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, Expenditure
and Sources of Payment
While the examples described below illustrate the use of event level data in
constructing person level total expenditures, these estimates can also be
derived from the person level expenditure file unless the characteristic of
interest is event specific.
In order to produce national estimates related to office-based medical
provider visits utilization, expenditure and sources of payment, the value in
each record contributing to the estimates must be multiplied by the weight
(WTDPER98) contained on that record.
Example 1
For example, the total number of office-based medical provider visits, for
the civilian non-institutionalized population of the U.S. in 1998, is estimated
as the sum of the weight (WTDPER98) across all office-based medical provider
records. That is,
Sum of Wj = 1,273,731,612
(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,
(Sum of Wj Xj)/(Sum
ofWj) = $18.30
(2)
where
Sum of Wj = 1,173,921,497 and Xj
= OBSF98Xj
for all records with OBXP98Xj > 0
This gives $18.30 as the estimated mean amount of out-of-pocket payment of
expenditures associated with office-based medical provider visits and
1,173,921,497 as an estimate of the total number of office-based medical
provider visits with expenditure. Both of these estimates are for the civilian
non-institutionalized population of the U.S. in 1998.
Example 3
Another example would be to estimate the average proportion of total
expenditures (where event expense is greater than 0) paid by private insurance
for office-based medical provider visits. This should be calculated as the
weighted mean of proportion of total expenditures paid by private insurance at
the provider visit level. That is
(Sum of Wj Yj)/(Sum
ofWj) = 0.4296
(3)
where
Sum of Wj = 1,173,921,497 and Yj
= OBPV98Xj / OBXP98Xj
for all office-based medical provider visits with OBXP98Xj>
0
This gives 0.4296 as the estimated mean proportion of total expenditures paid
by private insurance for office-based medical provider visits with expenditures
for the civilian non-institutionalized population of the U.S. in 1998.
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4.3 Estimates of the Number of Persons with
Office-Based Medical Provider Visits
When calculating an estimate of the total number of persons with office-based
medical provider visits, users can use a person-level file or this event 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,
Sum of Wi Xi across all
unique persons i on this file
(4)
where
Wi is the sampling weight (WTDPER98) 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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4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to
Persons with Office-Based Medical Provider Visits
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,
(Sum of Wi Zi)/(Sum
of Wi) across all unique persons i on this file
(5)
where
Wi is the sampling weight (WTDPER98) for
person i
and
Zi = Sum of OBXP98Xj
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 1998
person level 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 civilian
non-institutionalized 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 would be derived from data on the
person-level file. That is,
(Sum of Wi Zi)/(Sum
of Wi) across all unique persons i on the MEPS HC-person-level
file (6)
where
Wi is the sampling weight (WTDPER98) 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
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 1998 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 VARSTR98 and VARPSU98,
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 VARSTR98 and VARPSU98 as the
variance estimation strata and PSUs (within these strata) respectively and
specifying a Awith replacement@
design in a computer software package SUDAAN will yield standard error estimates
of $0.65 and 0.0079 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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Contents
5.0 Merging/Linking MEPS Data Files
Data from this office-based medical provider 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.
5.1 Linking a Person-Level File to the
Office-Based Medical Provider Visit File
Merging characteristics of interest from other MEPS files (e.g., 1998 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 file. This procedure is illustrated
below. The 1998 Appendix File provides examples of on how to merge MEPS other
data files.
- Create data set PERSX by sorting the 1998 Full Year Population
Characteristics File, by the person identifier, DUPERSID. Keep only
variables to be merged onto the office-based medical provider visit file
and DUPERSID.
- Create data set OBMP by sorting the office-based medical provider visit
file by person identifier, DUPERSID.
- Create final date set NEWOBMP by merging these two files by DUPERSID,
keeping only records on the office-based medical provider visit file.
The following is an example of SAS code, which completes these steps:
PROC SORT DATA=1998 Full Year Population Characteristics file (KEEP=DUPERSID
AGE 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 Office-Based Medical Provider
Visit file to the MEPS 1998 Medical Conditions File and/or the MEPS 1998
Prescribed Medicines File
Due to survey design issues, there are limitations/caveats that data
users/analyst must keep in mind when linking the different files. This
limitations/caveats are listed below. For detailed linking examples, including
SAS code, data users/analyst should refer to the 1998 Appendix File.
5.3 Limitations/Caveats of RXLK (the Prescribed
Medicine Link File)
The RXLK file provides a link from the prescribed medicine records to the
other event files. 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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5.4 Limitations/Caveats of CLNK (the Medical
Conditions Link File)
The CLNK provides a link from MEPS event files to the Medical Conditions
File. When using the CLNK, data users/analysts should keep in mind that (1)
conditions are self-reported and (2) there may be multiple conditions associated
with a 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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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, J.W. (1997). Design and Methods of the Medical Expenditure Panel
Survey Household Component. Rockville (MD): Agency for Health Care Policy and
Research; 1997. MEPS Methodology Report, No. 1. AHCPR Pub. No.
97-0026.
Cohen, S.B. (1996). The Redesign of the Medical Expenditure Panel Survey: A
Component of the DHHS Survey Integration Plan. Proceedings of the COPAFS
Seminar on Statistical Methodology in the Public Service.
Cox, B.G. and Cohen, S.B. (1985). Chapter 6: A Comparison of Household and
Provider Reports of Medical Conditions. In Methodological Issues for Health
Care Surveys. Marcel Dekker, New York.
Cox, B.G. and Cohen, S.B. (1985). Chapter 8: Imputation Procedures to
Compensate for Missing Responses to Data Items. In Methodological Issues for
Health Care Surveys. Marcel Dekker, New York.
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.
Moeller J.F., Stagnitti, M., Horan, E., et al. Data Collection and Editing
Procedures for Prescribed Medicines in the 1996 Medical Expenditure Panel Survey
Household Component. Rockville (MD): Agency for Healthcare Research and Quality;
2000. MEPS Methodology Report (forthcoming).
Monheit, A.C., Wilson, R., and Arnett, III, R.H. (Editors). Informing
American Health Care Policy. (1999). Jossey-Bass Inc, San Francisco.
Shah, B.V., Barnwell, B.G., Bieler, G.S., Boyle, K.E., Folsom, R.E., Lavange,
L., Wheeless, S.C., and Williams, R. (1996). Technical Manual: Statistical
Methods and Algorithms Used in SUDAAN Release 7.0, Research Triangle Park,
NC: Research Triangle Institute.
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Contents
Attachment 1
Definitions
Dwelling Units, Reporting Units, Families, and Persons - The definitions
of Dwelling Units (DUs) and Group Quarters in the MEPS Household Survey are
generally consistent with the definitions employed for the National Health
Interview Survey. The dwelling unit ID (DUID) is a five-digit random ID number
assigned after the case was sampled for MEPS. The person number (PID) uniquely
identifies all persons within the dwelling unit. The variable DUPERSID is the
combination of the variables DUID and PID.
A Reporting Unit (RU) is a person or a group of persons in the sampled
dwelling unit who is related by blood, marriage, adoption or other family
association, and who is to be interviewed as a group in MEPS. Thus, the RU
serves chiefly as a family-based "survey operations" unit rather than
an analytic unit. Regardless of the legal status of their association, two
persons living together as a "family" unit were treated as a single
reporting unit if they chose to be so identified.
Unmarried college students under 24 years of age, who usually live in the
sampled household but were living away from home and going to school at the time
of the Round 1 MEPS interview, were treated as a Reporting Unit separate from
that of their parents for the purpose of data collection. These variables can be
found on MEPS person-level files.
In-Scope - A person was classified as in-scope (IN-SCOPE) if he or she was
a member of the U.S. civilian, non-institutionalized population at some time
during the Round 1 interview. This variable can be found on MEPS person-level
files.
Keyness - The term "keyness" is related to an individual's
chance of being included in MEPS. A person is key if that person is
appropriately linked to the set of NHIS sampled households designated for
inclusion in MEPS. Specifically, a key person either was a member of an NHIS
household at the time of the NHIS interview or became a member of such a
household after being out-of-scope prior to joining that household (examples of
the latter situation include newborns and persons returning from military
service, persons returning from an institution, or persons living outside the
United States).
A non-key person is one whose chance of selection for the NHIS (and MEPS) was
associated with a household that was eligible but not sampled for the NHIS, who
happened to have become a member of a MEPS reporting unit by the time of the
MEPS Round 1 interview. MEPS data, (e.g., utilization and income) were collected
for the period of time a non-key person was part of the sampled unit to permit
family level analyses. However, non-key persons who leave a sample household
would not be recontacted for subsequent interviews. Non-key individuals are not
part of the target sample used to obtain person-level national estimates.
It should be pointed out that a person may be key even though not part of the
civilian, non-institutionalized portion of the U.S population. For example, a
person in the military may be living with his or her civilian spouse and
children in a household sampled for the NHIS. The person in the military would
be considered a key person for MEPS. However, such a person would not receive a
person-level sample weight so long as he or she was in the military. All key
persons who participated in the first round of a MEPS Panel received a
person-level sample weight except those who were in the military. The variable
indicating "keyness" is KEYNESS. This variable can be found on MEPS
person-level files.
Eligibility - The eligibility of a person for MEPS pertains to whether or
not data were to be collected for that person. All key, in-scope persons of a
sampled RU were eligible for data collection. The only non-key persons eligible
for data collection were those who happened to be living in the same RU as one
or more key persons, and their eligibility continued only for the time that they
were living with a key person. The only out-of-scope persons eligible for data
collection were those who were living with key in-scope persons, again only for
the time they were living with a key person. Only military persons meet this
description. A person was considered eligible if they were eligible at any time
during Round 1. The variable indicating "eligibility" is ELIGRND1,
where 1 is coded for persons eligible for data collection for at least a portion
of the Round 1 reference period, and 2 is coded for persons not eligible for
data collection at any time during the first round reference period. This
variable can be found on MEPS person-level files.
Pre-imputed - This means that only a series of logical edits were applied
to the HC data to correct for several problems including outliers, co-payments
or charges reported as total payments, and reimbursed amounts counted as
out-of-pocket payments. Missing data remains.
Unimputed - This means that only a series of logical edits were applied
to the MPC data to correct for several problems including outliers, co-payments
or charges reported as total payments, and reimbursed amounts counted as
out-of-pocket payments. These data were used as the imputation source to account
for missing HC data.
Imputation - A method of estimating values for cases with missing data.
Hot-deck imputation creates a data set with complete data for all nonrespondent
cases, by substituting the data from a respondent case that resembles the
nonrespondent on certain known variables.
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D. Variable Source Crosswalk
File 1:
Survey Administration Variables
| Variable |
Description |
Source |
|
DUID |
Dwelling unit ID (encrypted) |
Assigned in sampling |
|
PID |
Person number (encrypted) |
Assigned in sampling |
|
DUPERSID |
Sample person ID (DUID + PID) |
Assigned in sampling |
|
EVNTIDX |
Event ID |
Assigned in Sampling |
|
EVENTRN |
Event round number |
CAPI derived |
|
FFEEIDX |
Flat fee ID |
CAPI derived |
|
MPCELIG |
MPC eligibility flag |
CAPI derived |
|
MPCDATA |
MPC data flag |
CAPI derived |
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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 P visit provider in person or telephone |
MV01 |
|
REFERDBY |
P referred for this visit another physician |
MV02 |
|
SEEDOC |
Did P talk to MD this visit/phone call |
MV03 |
|
MEDPTYPE |
Type of medical person P talked to on visit date |
MV04 |
|
TIMESPNT |
Time spent with doctor/medical person |
MV05 |
|
DOCATLOC |
Any MDs work at location where P saw provider |
MV06 |
|
VSTCTGRY |
Best category for care P received on visit date |
MV07 |
|
VSTRELCN |
This visit/phone call related to specific condition |
MV08 |
|
PHYSTH |
This visit did P have physical therapy |
MV10 |
|
OCCUPTH |
This visit did P have occupational therapy |
MV10 |
|
SPEECHTH |
This visit did P have speech therapy |
MV10 |
|
CHEMOTH |
This visit did P have chemotherapy |
MV10 |
|
RADIATTH |
This visit did P have radiation therapy |
MV10 |
|
KIDNEYD |
This visit did P have kidney dialysis |
MV10 |
|
IVTHER |
This visit did P have IV therapy |
MV10 |
|
DRUGTRT |
This visit did P have treatment for drug or alcohol |
MV10 |
|
RCVSHOT |
This visit did P receive an allergy shot |
MV10 |
|
PSYCHOTH |
Did P have psychotherapy/counseling |
MV10 |
|
LABTEST |
This visit did P have lab tests |
MV11 |
|
SONOGRAM |
This visit did P have sonogram or ultrasound |
MV11 |
|
XRAYS |
This visit did P have x-rays |
MV11 |
|
MAMMOG |
This visit did P have a mammogram |
MV11 |
|
MRI |
This visit did P have MRI |
MV11 |
|
EKG |
This visit did P have EKG or ECG |
MV11 |
|
EEG |
During this visit did P have a EEG |
MV11 |
|
RCVVAC |
This visit did P receive a vaccination |
MV11 |
|
ANESTH |
During this visit did P receive anesthesia |
MV11 |
|
OTHSVCE |
This visit did P have other diagnostic tests/exams |
MV11 |
|
SURGPROC |
Was surgical procedure performed on P this visit |
MV12 |
|
SURGNAME |
Surgical procedure name in categories |
MV13 |
|
MEDPRESC |
Any medicines prescribed for P 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 |
Constructed/Edited |
|
OBCCC2X |
Modified Clinical Classification Code |
Constructed/Edited |
|
OBCCC3X |
Modified Clinical Classification Code |
Constructed/Edited |
|
OBCCC4X |
Modified Clinical Classification Code |
Constructed/Edited |
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Flat Fee Variables
| Variable |
Description |
Source |
|
FFOBTYPE |
Edited Flat Bundle |
FF01,FF02 (Edited) |
|
FFBEF98 |
Total # visits in flat fee before 1998 |
FF05 |
|
FFTOT99 |
Number of visits in flat fee after 1998 |
FF10 |
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Imputed Expenditure Variables
| Variable |
Description |
Source |
|
OBSF98X |
Amount paid, family (imputed) |
CP11 (Edited/Imputed) |
|
OBMR98X |
Amount paid, Medicare (imputed) |
CP09 (Edited/Imputed) |
|
OBMD98X |
Amount paid, Medicaid (imputed) |
CP07 (Edited/Imputed) |
|
OBPV98X |
Amount paid, Private Insurance (imputed) |
CP07 (Edited/Imputed) |
|
OBVA98X |
Amount paid, Veterans (imputed) |
CP07 (Edited/Imputed) |
|
OBCH98X |
Amount paid, CHAMP/CHAMPVA (imputed) |
CP07 (Edited/Imputed) |
|
OBOF98X |
Amount paid, other federal (imputed) |
CP07 (Edited/Imputed) |
|
OBSL98X |
Amount paid, state/local govt. (imputed) |
CP07 (Edited/Imputed) |
|
OBWC98X |
Amount paid, Worker's Comp (imputed) |
CP07 (Edited/Imputed) |
|
OBOR98X |
Amount paid, other private (imputed) |
Constructed |
|
OBOU98X |
Amount paid, other public (imputed) |
Constructed |
|
OBOT98X |
Amount paid, other insurance (imputed) |
CP07 (Edited/Imputed) |
|
OBXP98X |
Sum of payments OBSF98X - OBOT98X |
Constructed |
|
OBTC98X |
Total charge (imputed) |
CP09 (Edited/Imputed) |
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Weights
| Variable |
Description |
Source |
|
WTDPER98 |
Poverty/mortality/NH adjusted person level weight,
1998 |
Constructed |
|
VARPSU98 |
Variance estimation PSU 1998 |
Constructed |
|
VARSTR98 |
Variance estimation stratum |
Constructed |
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File 2:
Survey Administration Variables
| Variable |
Description |
Source |
|
DUID |
Dwelling unit ID |
Assigned in sampling |
|
PID |
Person number |
Assigned in sampling |
|
DUPERSID |
Sample person ID (DUID + PID) |
Assigned in sampling |
|
EVNTIDX |
Event ID |
Assigned in Sampling |
|
HHSFFIDX |
Household reported flat fee ID |
CAPI derived |
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Pre-imputed Expenditure Variables
| Variable |
Description |
Source |
|
OBSF98H |
Household reported amount paid, family (pre-imputed) |
CP11 (Edited/Imputed) |
|
OBMR98H |
Household reported amount paid, Medicare (pre-imputed) |
CP09 (Edited/Imputed) |
|
OBMD98H |
Household reported amount paid, Medicaid (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBPV98H |
Household reported amount paid, Private Insurance (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBVA98H |
Household reported amount paid, Veterans (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBCH98H |
Household reported amount paid, CHAMP/CHAMPVA (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBOF98H |
Household reported amount paid, other federal (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBSL98H |
Household reported amount paid, state/local govt. (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBWC98H |
Household reported amount paid, Worker's Comp (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBOT98H |
Household reported amount paid, other insurance (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBUC98H |
Household reported amount paid, uncollected liability (pre-imputed) |
CP07 (Edited/Imputed) |
|
OBTC98H |
Household reported total charge (pre-imputed) |
CP09 (Edited/Imputed) |
|
OBSF98M |
MPC reported amount paid, family (unimputed) |
HEF8a |
|
OBMR98M |
MPC reported amount paid, Medicare (unimputed) |
HEF8b |
|
OBMD98M |
MPC reported amount paid, Medicaid (unimputed) |
HEF8c |
|
OBPV98M |
MPC reported amount paid, Private Insurance (unimputed) |
HEF8d |
|
OBVA98M |
MPC reported amount paid, Veterans (unimputed) |
HEF8e |
|
OBCH98M |
MPC reported amount paid, CHAMP/CHAMPVA (unimputed) |
HEF8f |
|
OBOF98M |
MPC reported amount paid, other federal (unimputed) |
HEF8g |
|
OBSL98M |
MPC reported amount paid, state/local govt. (unimputed) |
HEF8g |
|
OBWC98M |
MPC reported amount paid, Worker's Comp (unimputed) |
HEF8g |
|
OBOT98M |
MPC reported amount paid, other insurance (unimputed) |
HEF8g |
|
OBTC98M |
MPC reported total charge (unimputed) |
HEF9 |
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Weights
| Variable |
Description |
Source |
|
WTDPER98 |
Poverty/mortality/NH adjusted person level weight,
1998 |
Constructed |
|
VARPSU98 |
Variance estimation PSU 1998 |
Constructed |
|
VARSTR98 |
Variance estimation stratum |
Constructed |
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