MEPS HC-051D: 2000 Hospital Inpatient Stays
April 2003
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406
Table of Contents
A. Data Use Agreement
B. Background
1.0 Household Component
2.0 Medical Provider Component
3.0 Insurance Component
4.0 Survey Management
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Codebook Structure
2.2 Reserved Codes
2.3 Codebook Format2.4 Variable Source and Naming Conventions
2.4.1 General
2.4.2 Expenditure and Source of Payment Variables
2.5 File Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID, PID, DUPERSID)
2.5.1.2 Record Identifiers EVNTIDX, ERHEVIDX, FFEEIDX)
2.5.1.3 Round Indicator (EVENTRN)
2.5.2 MPC Data Indicator (MPCDATA)
2.5.3 Hospital Inpatient Stay Event Variables
2.5.3.1 Start and End Dates of Event (IPBEGDD-IPENDYR)
2.5.3.2 Length of Stay (NUMNIGHX, NUMNIGHT)
2.5.3.3 Preceding ER Visits (EMERROOM)
2.5.3.4 Other Visit Detail (SPECCOND - VAPLACE)
2.5.3.5 Condition and Procedure Codes (IPICD1X-IPICD4X,
IPPRO1X, IPPRO2X), and Clinical Classification Codes
IPCCC1X-IPCCC4X)
2.5.3.6 Discharge Detail (DSCHPMED)
2.5.4 Flat Fee Variables (FFEEIDX, FFIPTYPE, FFBEF00, FFTOT01)
2.5.4.1 Definition of Flat Fee Payments
2.5.4.2 Flat Fee Variable Descriptions
2.5.4.2.1 Flat Fee ID (FFEEIDX)
2.5.4.2.2 Flat Fee Type (FFIPTYPE)
2.5.4.2.3 Counts of Flat Fee Events that Cross Years (FFBEF00, FFTOT01)
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 Data Editing and Imputation Methodologies of Expenditure Variables
2.5.5.2.1 General Data Editing Methodology
2.5.5.2.2 General Hot-Deck Imputation
2.5.5.2.3 Hospital Inpatient Stay Data Editing and Imputation
2.5.5.3 Imputation Flag (IMPFLAG)
2.5.5.4 Flat Fee Expenditures
2.5.5.5 Zero Expenditures
2.5.5.6 Discount Adjustment Factor
2.5.5.7 Mother/Newborn Expenditures
2.5.5.8 Hospital Inpatient Stay/Emergency Room Expenditures
2.5.5.9 Sources of Payment
2.5.5.10 Imputed Hospital Inpatient Stay Expenditure Variables
2.5.5.10.1 Hospital Inpatient Facility Expenditures
(IPFSF00X-IPFOT00X, IPFXP00X, IPFTC00X)
2.5.5.10.2 Hospital Inpatient Physician Expenditures
(IPDSF00X - IPDOT00X, IPDTC00X, IPDXP00X)
2.5.5.10.3 Total Expenditures and Charges for
Hospital Inpatient Stays (IPXP00X, IPTC00X)
2.5.5.11 Rounding
3.0 Sample Weight (PERWT00F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 4 Weight
3.2.2 MEPS Panel 5 Weight
3.2.3 The Final Weight for 2000
3.2.4 Coverage
4.0 Strategies for Estimation
4.1 Variables with Missing Values
4.2 Basic Estimates of Utilization, Expenditures, and Sources of
Payment
4.3 Estimates of the Number of Persons with Hospital Inpatient Stays
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio Estimates Relative to Persons with
Hospital Inpatient Use
4.4.2 Person-Based Ratio Estimates Relative to the Entire
Population
4.5 Sampling Weights for Merging Previous Releases of MEPS Household
Data with this Event File
4.6 Variance Estimation (VARSTR00, VARPSU00)
5.0 Merging/Linking MEPS Data Files
5.1 Merging a 2000 Person-Level File to the 2000 Hospital Inpatient
Stays File
5.2 Linking the 2000 Hospital Inpatient Stays File to the 2000
Medical Conditions File and/or the 2000 Prescribed Medicines File
5.2.1 Limitations/Caveats of RXLK (the Prescribed Medicine Link
File)
5.2.2 Limitations/Caveats of CLNK (the Medical Conditions Link
File)
References
D. Variable-Source Crosswalk
A. Data Use Agreement
Individual identifiers have been removed from the micro-data contained in
these files. Nevertheless, under sections 308 (d) and 903 (c) of the Public
Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the
Agency for Healthcare Research and Quality (AHRQ) and/or the National Center for
Health Statistics (NCHS) may not be used for any purpose other than for the
purpose for which they were supplied; any effort to determine the identity of
any reported cases is prohibited by law.
Therefore in accordance with the above referenced Federal Statute, it is
understood that:
- No one is to use the data in this data set in any way except for
statistical reporting and analysis; and
- If the identity of any person or establishment should be discovered
inadvertently, then (a) no use will be made of this knowledge, (b) the
Director, Office of Management, AHRQ will be advised of this incident,
(c) the information that would identify any individual or
establishment will be safeguarded or destroyed, as requested by AHRQ,
and (d) no one else will be informed of the discovered identity; and
- No one will attempt to link this data set with individually
identifiable records from any data sets other than the Medical
Expenditure Panel Survey or the National Health Interview Survey.
By using these data you signify your agreement to comply with the above
stated statutorily based requirements with the knowledge that deliberately
making a false statement in any matter within the jurisdiction of any department
or agency of the Federal Government violates Title 18 part 1 Chapter 47
Section 1001 and is punishable by a fine of up to $10,000 or up to 5
years in prison.
The Agency for Healthcare Research and Quality requests that users cite AHRQ
and the Medical Expenditure Panel Survey as the data source in any publications
or research based upon these data.
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B. Background
The Medical Expenditure Panel Survey (MEPS) provides nationally
representative estimates of health care use, expenditures, sources of payment,
and insurance coverage for the U.S. civilian noninstitutionalized population.
MEPS is cosponsored by the Agency for Healthcare Research and Quality (AHRQ) and
the National Center for Health Statistics (NCHS).
MEPS is a family of three surveys. The Household Component (HC) is the core
survey and forms the basis for the Medical Provider Component (MPC) and part of
the Insurance Component (IC). Together these surveys yield comprehensive data
that provide national estimates of the level and distribution of health care use
and expenditures, support health services research, and can be used to assess
health care policy implications.
MEPS is the third in a series of national probability surveys conducted by
AHRQ on the financing and use of medical care in the United States. The National
Medical Care Expenditure Survey (NMCES, also known as NMES-1) was conducted in
1977 and the National Medical Expenditure Survey (NMES-2) in 1987. Since 1996,
MEPS continues this series with design enhancements and efficiencies that
provide a more current data resource to capture the changing dynamics of the
health care delivery and insurance systems.
The design efficiencies incorporated into MEPS are in accordance with the
Department of Health and Human Services (DHHS) Survey Integration Plan of June
1995, which focused on consolidating DHHS surveys, achieving cost efficiencies,
reducing respondent burden, and enhancing analytical capacities. To advance
these goals, MEPS includes linkage with the National Health Interview Survey (NHIS)
- a survey conducted by NCHS from which the sample for the MEPS HC is drawn -
and enhanced longitudinal data collection for core survey components. The MEPS
HC augments NHIS by selecting a sample of NHIS respondents, collecting
additional data on their health care expenditures, and linking these data with
additional information collected from the respondents' medical providers,
employers, and insurance providers.
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1.0 Household Component
The MEPS HC, a nationally representative survey of the U.S. civilian
noninstitutionalized population, collects medical expenditure data at both the
person and household levels. The HC collects detailed data on demographic
characteristics, health conditions, health status, use of medical care services,
charges and payments, access to care, satisfaction with care, health insurance
coverage, income, and employment.
The HC uses an overlapping panel design in which data are collected through a
preliminary contact followed by a series of five rounds of interviews over a 2
½-year period. Using computer-assisted personal interviewing (CAPI) technology,
data on medical expenditures and use for two calendar years are collected from
each household. This series of data collection rounds is launched each
subsequent year on a new sample of households to provide overlapping panels of
survey data and, when combined with other ongoing panels, will provide
continuous and current estimates of health care expenditures.
The sampling frame for the MEPS HC is drawn from respondents to NHIS. NHIS
provides a nationally representative sample of the U.S. civilian
noninstitutionalized population, with oversampling of Hispanics and blacks.
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2.0 Medical Provider Component
The MEPS MPC supplements and/or replaces information on medical care events
reported in the MEPS HC by contacting medical providers and pharmacies
identified by household respondents. The MPC sample includes all home health
agencies and pharmacies reported by HC respondents. Office-based physicians,
hospitals, and hospital physicians are also included in the MPC but may be
subsampled at various rates, depending on burden and resources, in certain
years.
Data are collected on medical and financial characteristics of medical and
pharmacy events reported by HC respondents. The MPC is conducted through
telephone interviews and record abstraction.
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3.0 Insurance Component
The MEPS IC collects data on health insurance plans obtained through private
and public-sector employers. Data obtained in the IC include the number and
types of private insurance plans offered, benefits associated with these plans,
premiums, contributions by employers and employees, eligibility requirements,
and employer characteristics.
Establishments participating in the MEPS IC are selected through three
sampling frames:
- A list of employers or other insurance providers identified by MEPS HC
respondents who report having private health insurance at the Round 1 interview.
- A Bureau of the Census list frame of private sector business establishments.
- The Census of Governments from Bureau of the Census.
To provide an integrated picture of health insurance, data collected from the
first sampling frame (employers and insurance providers identified by MEPS HC
respondents) are linked back to data provided by those respondents. Data from
the two Census Bureau sampling frames are used to produce annual national and
state estimates of the supply and cost of private health insurance available to
American workers and to evaluate policy issues pertaining to health insurance.
National estimates of employer contributions to group insurance from the MEPS IC
are used in the computation of Gross Domestic Product (GDP) by the Bureau of
Economic Analysis.
The MEPS IC is an annual panel survey. Data are collected from the selected
organizations through a prescreening telephone interview, a mailed
questionnaire, and a telephone follow-up for nonrespondents.
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4.0 Survey Management
MEPS data are collected under the authority of the Public Health Service Act.
They are edited and published in accordance with the confidentiality provisions
of this act and the Privacy Act. NCHS provides consultation and technical
assistance.
As soon as data collection and editing are completed, the MEPS survey data
are released to the public in staged releases of summary reports, microdata
files and compendiums of tables. Data are released through MEPSnet, an online
interactive tool developed to give users the ability to statistically analyze
MEPS data in real time. Summary reports and compendiums of tables are released
as printed documents and electronic files. Microdata files are released as
electronic files.
Selected printed documents are available through the AHRQ Publications
Clearinghouse. Write or call:
AHRQ Publications Clearinghouse
Attn: (publication number)
P.O. Box 8547
Silver Spring, MD 20907
800-358-9295
410-381-3150 (callers outside the United States only)
888-586-6340 (toll-free TDD service; hearing impaired only)
Be sure to specify the AHRQ number of the document you are requesting.
Additional information on MEPS is available from the MEPS project manager or
the MEPS public use data manager at the Center for Cost and Financing Studies,
Agency for Healthcare Research and Quality.
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C. Technical and
Programming Information
1.0 General Information
This documentation describes one in a series of public use event files from
the 2000 Medical Expenditure Panel Survey (MEPS) Household Component (HC) and
Medical Provider Component (MPC). Released as an ASCII data file and SAS
transport file, the 2000 Hospital Inpatient Stays (STAZ) public use file
provides detailed information on hospital inpatient stays for a nationally
representative sample of the civilian noninstitutionalized population of the
United States. Data from the STAZ event file can be used to make estimates of
hospital inpatient stay utilization and expenditures for calendar year 2000. As
illustrated below, this file consists of MEPS survey data from the 2000 portion
of Round 3 and Rounds 4 and 5 for Panel 4, as well as Rounds 1, 2 and the 2000
portion of Round 3 for Panel 5 (i.e., the rounds for the MEPS panels covering
calendar year 2000).
301 Moved Permanently
301 Moved Permanently
Hospital stay events reported in Round 3, Panel 5 and known to have begun
after December 31, 2000 are not included on this file.
Each record on the inpatient hospital event file represents a unique hospital
inpatient stay, that is, a hospital inpatient stay reported by the household
respondent. In addition to expenditures related to the stay, each record
contains household-reported medical conditions and procedures associated with
the hospitalization and information on the length of stay.
Counts of hospital inpatient stay utilization are based entirely on household
reports. Information from the MEPS MPC was used to supplement expenditure and
payment data reported by the household.
Data from this event file can be merged with other 2000 MEPS HC data files
for purposes of appending person-level data such as demographic characteristics
or health insurance coverage to each hospital inpatient stay record.
This file can also be used to construct summary variables of expenditures,
sources of payment, and related aspects of hospital inpatient care. Aggregate
annual person-level information on the use of hospital inpatient stays and other
health services use is provided on the MEPS 2000 Full Year Consolidated Data
File, where each record represents a MEPS sampled person.
This documentation offers an overview of the types and levels of data
provided, and the content and structure of the files and the codebook. It
contains the following sections:
Data File Information
Sample Weights
Strategies for Estimation
Merging/Linking MEPS Data Files
References
Variable - Source Crosswalk
Any variable not found on this file but released on previous years' files
were excluded because they contained only missing data.
For more information on MEPS HC survey design see S. Cohen, 1997; J. Cohen,
1997; and S. Cohen, 1996. For information on the MEPS MPC design, see S. Cohen,
1999. Copies of the HC and the MPC survey instruments used to collect the
information on the STAZ file are available in the Survey Instruments section
on the MEPS web site at the following address: <http://www.meps.ahrq.gov>.
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2.0 Data File Information
The 2000 Hospital Inpatient Stays public use data set consists of one
event-level data file. The file contains characteristics associated with the
STAZ event and imputed expenditure data. For users wanting to impute
expenditures, pre-imputed data are available through the CCFS data center.
Please visit the CCFS data center website for details: <http://www.meps.ahrq.gov/mepsweb/data_stats/onsite_datacenter.jsp>.
The data user/analyst is forewarned that the imputation of expenditures will
necessitate a sizable commitment of resources: financial, staff, and time.
The 2000 STAZ public use data set contains variable and frequency
distributions for a total of 2,508 hospital inpatient stay records reported
during the 2000 portion of Round 3 and Rounds 4 and 5 for Panel 4, as well as
Rounds 1, 2, and the 2000 portion of Round 3 for Panel 5 of the MEPS Household
Component. This file includes hospital inpatient stay records for all household
survey respondents who resided in eligible responding households and reported at
least one hospital inpatient stay. Hospital inpatient stay records known to have
ended before January 1, 2000 and after December 31, 2000 are not included on
this file. Some household respondents may have multiple hospital inpatient stays
and, thus, will be represented in multiple records on this file. Other household
respondents may have reported no hospital inpatient stays and, thus, will have
no records on this file. Of the 2,508 hospital inpatient stay records, 2,407 are
associated with persons having a positive person-level weight (PERWT00F). The
persons represented on this file had to meet the following three criteria:
-
The hospital stay had to have been reported by a household survey
respondent as an inpatient hospital stay (regardless of a stay's
length). Thus, the file contains some hospitalizations that were
reported as not including an overnight stay.
-
The hospital stay had to have ended during 2000. Stays that began
prior to 2000 but ended during 2000 are included on this file. Stays
that began in 2000 but ended during 2001 are excluded from this file and
will be represented on a subsequent 2001 data file. Persons with no
hospital inpatient stay events for 2000 are not included on this file
but are represented on the 2000 MEPS person-level files. A codebook for
the data file is provided in files H51DCB.PDF and H51DCB.ASP.
-
The persons represented on this file also had to meet either 3a or
3b:
-
Be classified as a key in-scope person who responded for his
or her entire period of 2000 eligibility (i.e., persons with a
positive 2000 full-year person-level sampling weight (PERWT00F >
0)), or
-
Be an eligible member of a family all of whose key in-scope
members have a positive person-level weight (PERWT00F > 0). (Such
a family consists of all persons with the same value for FAMIDYR.)
That is, the person must have a positive full-year family-level
weight (FAMWT00F >0). Note that FAMIDYR and FAMWT00F are
variables on the 2000 Population Characteristics file.
One caveat that should be noted is that in the case of a newborn and the
hospital inpatient stay associated with the newborn's birth, a separate
hospital inpatient stay record exists on the file only if the newborn was
discharged after the mother. Thus, hospital stays associated with a normal birth
are generally represented on the file as a single record (i.e., the mother's
hospital inpatient stay record, covering expenditure data for both the mother
and baby). In situations where the newborn was discharged after the mother, the
birth event will be represented as two records: one record for the mother and
one record for the baby. For newborns re-admitted to the hospital during the
reference year, each subsequent re-admission will have a separate record.
Each inpatient record includes the following: start and end dates of the
hospital inpatient stay; number of nights in the hospital; reason entered the
hospital; main surgical procedure; condition(s) associated with the hospital
inpatient stay; medicines prescribed at discharge; flat fee information; imputed
sources of payment; total payment and total charge for both the facility and
physician portions of the hospital inpatient stay expenditure; and a full-year
person-level weight.
Data from this file can be merged with the MEPS 2000 Full Year Population
Characteristics File using the unique person identifier, DUPERSID, to append
person-level information, such as demographic or health insurance
characteristics, to each record. Hospital inpatient stay events can also be
linked to the MEPS 2000 Medical Conditions File and the MEPS 2000 Prescribed
Medicines File. Please see section 5.0 and the MEPS 2000 Appendix File, HC-051I,
for details on how to merge MEPS data files.
Panel 4 cases (PANEL00 = 4 on the 2000 Full Year Population Characteristics
File) can also be linked back to the 1999 MEPS HC public use data files.
However, data users/analysts should be aware that, at this time, no weight is
being provided to facilitate two-year analysis of Panel 4 data.
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2.1 Codebook Structure
For each variable on the Inpatient Events file, both weighted and unweighted
frequencies are provided in the codebook files (H51DCB.PDF and H51DCB.ASP). The
codebook and data file sequence list variables in the following order:
Unique person identifiers
Unique hospital inpatient stay identifiers
Hospital inpatient stay characteristics variables
ICD-9 condition and procedure codes
Clinical Classification Software (CCS) codes
Imputed expenditure variables
Weight and variance estimation variables
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2.2 Reserved Codes
The following reserved code values are used:
Value |
Definition |
-1 INAPPLICABLE |
Question was not asked due to skip pattern. |
-7 REFUSED |
Question was asked and respondent refused to answer question. |
-8 DK |
Question was asked and respondent did not know answer. |
-9 NOT ASCERTAINED |
Interviewer did not record the data. |
Generally, the values of -1, -7, -8, and -9 for non-expenditure variables
have not been edited on this file. The values of -1 and -9 can be edited by data
users/analysts by following the skip patterns in the HC survey questionnaire
(located on the MEPS web site: <http://www.meps.ahrq.gov/mepsweb/survey_comp/survey.jsp>).
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2.3 Codebook Format
The STAZ codebook describes an ASCII data set (although the data are also
being provided in a SAS transport file). The following codebook items are
provided for each variable:
Identifier |
Description |
Name |
Variable name (maximum of 8 characters) |
Description |
Variable descriptor (maximum of 40 characters) |
Format |
Number of bytes |
Type |
Type of data: numeric (indicated by NUM) or character (indicated by CHAR) |
Start |
Beginning column position of variable in record |
End |
Ending column position of variable in record |
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2.4 Variable Source and Naming Conventions
In general, variable names reflect the content of the variable, with an
eight-character limitation. All imputed/edited variables end with an
"X."
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2.4.1 General
Variables on this file were derived from the HC questionnaire itself, derived
from the MPC data collection instrument, derived from CAPI, or assigned in
sampling. The source of each variable is identified in Section D "Variable
- Source Crosswalk" in one of four ways:
-
Variables derived from CAPI or assigned in sampling are indicated as
"CAPI derived" or "Assigned in sampling," respectively;
-
Variables which come from one or more specific questions have those
questionnaire sections and question numbers indicated in the
"Source" column; questionnaire sections are identified as:
-
Variables constructed from multiple questions using complex
algorithms are labeled "Constructed" in the "Source"
column; and
-
Variables which have been edited or imputed are so indicated.
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2.4.2 Expenditure and Source of Payment Variables
The names of the expenditure and source of payment variables follow a
standard convention, are eight characters in length, and end in an "X"
indicating edited/imputed. Please note that imputed means that a series of
logical edits, as well as an imputation process to account for missing data,
have been performed on the variable.
The total sum of payments and 12 source of payment variables are named in the
following way:
The first two characters indicate the type of event:
IP - inpatient stay |
OB - office-based visit |
ER - emergency room visit |
OP - outpatient visit |
HH - home health visit |
DV - dental visit |
OM - other medical equipment |
RX - prescribed medicine |
For expenditure variables on these files, the third character indicates
whether the expenditure is associated with the facility (F) or the physician
(D).
In the case of the source of payment variables, the fourth and fifth
characters indicate:
SF - self or family |
OF - other Federal Government |
MR - Medicare |
SL - State/local government |
MD - Medicaid |
WC - Workers' Compensation |
PV - private insurance |
OT - other insurance |
VA - Veterans |
OR - other private |
TR - TRICARE |
OU - other public |
|
XP - sum of payments |
In addition, the total charge variable is indicated by TC in the variable
name.
The sixth and seventh characters indicate the year (00). The eighth character
of all imputed/edited variables is an "X."
For example, IPFSF00X is the edited/imputed amount paid by self or family for
the facility portion of the hospital inpatient stay expenditure incurred in
2000.
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2.5 File Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID, PID, DUPERSID)
The dwelling unit ID (DUID) is a five-digit random number assigned after the
case was sampled for MEPS. The three-digit person number (PID) uniquely
identifies each person within the dwelling unit. The eight-character variable
DUPERSID uniquely identifies each person represented on the file and is the
combination of the variables DUID and PID. For detailed information on dwelling
units and families, please refer to the documentation for the 2000 Full Year
Population Characteristics File.
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2.5.1.2 Record Identifiers (EVNTIDX, ERHEVIDX,
FFEEIDX)
EVNTIDX uniquely identifies each hospital inpatient stay/event (i.e., each
record on the STAZ file) and is the variable required to link hospital inpatient
stay events to data files containing details on conditions and/or prescribed
medicines (MEPS 2000 Medical Conditions File and MEPS 2000 Prescribed Medicines
File, respectively). For details on linking, see Section 5.0 or the MEPS 2000
Appendix File, HC-051I.
ERHEVIDX is a constructed variable identifying a STAZ record that includes
the facility expenditures for the preceding emergency room visit. This variable
was constructed by comparing date information for the reported hospital stay and
all emergency room visits for the same person. On the 2000 STAZ file, there are
284 hospital stays linked to a preceding emergency room visit, that is, there
are 284 records with a valid ERHEVIDX value. ERHEVIDX has not been reconciled
with the unedited variable EMERROOM. Please note that, the physician
expenditures associated with the emergency room visit remain on the emergency
room file.
FFEEIDX is a constructed variable which uniquely identifies a flat fee group,
that is, all events that were a part of a flat fee payment situation. For
example, dialysis treatments are typically covered in a flat fee arrangement
where all visits are covered under one flat fee dollar amount. These events
would have the same value for FFEEIDX.
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2.5.1.3 Round Indicator (EVENTRN)
EVENTRN indicates the round in which the hospital inpatient stay was first
reported. Please note that Rounds 3, 4, and 5 are associated with MEPS survey
data collected from Panel 4. Likewise, Rounds 1, 2, and 3 are associated with
data collected from Panel 5.
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2.5.2 MPC Data Indicator (MPCDATA)
MPCDATA is a constructed variable which indicates whether or not MPC data
were collected for the hospital inpatient stay. While all hospital inpatient
events are sampled into the Medical Provider Component, not all hospital
inpatient stay records have MPC data associated with them. This is dependent
upon the cooperation of the household respondent to provide permission forms to
contact the hospital as well as the cooperation of the hospital to participate
in the survey.
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2.5.3 Hospital Inpatient Stay Event Variables
This file contains variables describing hospital inpatient stays/events
reported by respondents in the Hospital Stays section of the MEPS HC
questionnaire. The questionnaire contains specific probes for determining
details about the hospital inpatient stay.
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2.5.3.1 Start and End Dates of Event (IPBEGDD-IPENDYR)
This file contains variables describing hospital inpatient stays reported by
household respondents in the Hospital Section of the MEPS HC questionnaire.
There are three variables which indicate the day, month and year a hospital stay
began (IPBEGDD, IPBEGMM, IPBEGYR, respectively). Similarly, there are three
variables which indicate the day, month and year a hospital stay ended (IPENDDD,
IPENDMM, IPENDYR, respectively). These variables have not been edited.
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2.5.3.2 Length of Stay (NUMNIGHX, NUMNIGHT)
NUMNIGHX denotes the length of a hospital inpatient stay. For stays beginning
in 1999 and ending in 2000, this variable would include the nights associated
with the entire visit. It was edited using the above mentioned begin and end
dates of the hospital inpatient stay (Section 2.5.2.1). If the dates were
unknown, then NUMNIGHX used the number from the unedited variable NUMNIGHT
(number of nights in the hospital). If both the dates and NUMNIGHT were missing
data, then NUMNIGHX was imputed. Users should note that NUMNIGHT was only asked
for events with missing date information. Hence, it contains large amounts of
missing data and cannot be used alone but rather in conjunction with date
information.
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2.5.3.3 Preceding ER Visits (EMERROOM)
The variable EMERROOM was derived directly from the Hospital Inpatient Stays
section of the HC survey instrument and is unedited. EMERROOM describes whether
or not the hospital inpatient stay began with an emergency room visit. Data
users/analysts should be aware that no attempt was made to reconcile EMERROOM
with information from the Emergency Room Visit File.
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2.5.3.4 Other Visit Detail (SPECCOND - VAPLACE)
Also provided are the following unedited variables: hospital inpatient stays
related to a medical condition (SPECCOND); the reason the person entered the
hospital (RSNINHOS); any operation or surgery performed while the respondent was
in the hospital (ANYOPER); and, if surgery was performed, what the main surgical
procedure was (MAINSURG).
With respect to RSNINHOS, please note that while there were 353 cases where
RSNINHOS = 4 (reason entered hospital - to give birth to a baby), this does
not mean that there were actually 353 new births. In fact, it may have
been reported that the mother went to the hospital for delivery (hence, the
interviewer would have assigned the event RSNINHOS = 4), but the mother could
have had, for example, false labor pains or a stillbirth. Thus, this unedited
self-reported variable, may be inconsistent with reported number of births (see
the 2000 Full Year Population Characteristics File, section 2.5.2
"Navigating the MEPS Data with Information on Person Disposition
Status").
VAPLACE is a constructed variable that indicates whether the provider worked
at a VA facility. This variable only has valid data for providers that were
sampled into the Medical Provider Component. All other providers are classified
as "No."
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2.5.3.5 Condition and Procedure Codes (IPICD1X-IPICD4X, IPPRO1X,
IPPRO2X), and Clinical Classification Codes (IPCCC1X-IPCCC4X)
Information on household reported medical conditions and procedures
associated with each hospital inpatient stay event are provided on this file.
There are up to four condition and CCC codes (IPICD1X-IPICD4X, IPCCC1X-IPCCC4X)
and up to two procedure codes (IPPRO1X and IPPRO2X) listed for each hospital
inpatient stay event. In order to obtain complete condition information
associated with an event, the data user/analyst must link to the MEPS 2000
Medical Conditions File. Details on how to link the 2000 STAZ file to the MEPS
2000 Medical Conditions File are provided in Section 5.2 and the MEPS 2000
Appendix File, HC-051I. The data user/analyst should note that because of
confidentiality restrictions, provider-reported condition information is not
publicly available.
The medical conditions and procedures reported by the Household Component
respondent were recorded by the interviewer as verbatim text, which were then
coded to fully-specified 2000 ICD-9-CM codes, including medical condition and V
codes (Health Care Financing Administration, 1980) by professional coders.
Although codes were verified and error rates did not exceed 3 percent for any
coder, data users/analysts should not presume this level of precision in the
data; the ability of household respondents to report condition data that can be
coded accurately should not be assumed (Cox and Cohen, 1985; Cox and Iachan,
1987; Edwards, et al., 1994; and Johnson and Sanchez, 1993). For detailed
information on how condition and procedures were coded, please refer to the
documentation on the MEPS 2000 Medical Conditions File. For frequencies of
conditions by event type, please see the MEPS 2000 Appendix File, HC-051I.
The ICD-9-CM condition codes were aggregated into clinically meaningful
categories. These categories, included on the file as IPCCC1X-IPCCC4X, were
generated using Clinical Classification Software [formerly known as Clinical
Classifications for Health Care Policy Research (CCHPR), (Elixhauser, et al.,
1998)] which aggregates conditions and V-codes into 260 mutually exclusive
categories, most of which are clinically homogeneous.
In order to preserve respondent confidentiality, nearly all of the condition
codes provided on this file have been collapsed from fully-specified codes to
three-digit code categories. The reported ICD-9-CM code values were mapped to
the appropriate clinical classification category prior to being collapsed to the
three-digit categories. Details on this procedure can be found in the 2000 MEPS
Medical Conditions File.
The condition (and clinical classification codes) and procedure codes linked
to each hospital inpatient stay event are sequenced in the order in which the
conditions were reported by the household respondent, which was in order of
input into the database and not in order of importance or severity. Data
users/analysts who use the MEPS 2000 Medical Conditions File in conjunction with
this hospital inpatient stay event file should note that the order of conditions
on this file is not identical to that on the Medical Conditions file.
The user should also note that because of the design of the HC survey
instrument, most hospital stays that are reported as being for a delivery (RSNINHOS=4)
link to condition codes that are for pregnancy rather than a delivery. In
addition, RSNINHOS has not been reconciled with the ICD-9 condition codes, the
procedure codes, or the CCC codes that are on the file.
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2.5.3.6 Discharge Detail (DSCHPMED)
DSCHPMED is derived directly from the Hospital Stays Section of the HC survey
instrument. DSCHPMED indicates whether or not any medicines were prescribed at
discharge.
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2.5.4 Flat Fee Variables (FFEEIDX, FFIPTYPE, FFBEF00, FFTOT01)
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
health care services provided during a defined period of time. Examples would
be: obstetrician's fee covering a normal delivery, as well as pre- and
post-natal care; or a surgeon's fee covering surgical procedure and
post-surgical care. A flat fee group is the set of medical services (i.e.,
events) that are covered under the same flat fee payment situation. The flat fee
groups represented on the STAZ file include flat fee groups where at least one
of the health care events, as reported by the HC respondent, occurred during
2000. By definition, a flat fee group can span multiple years. Furthermore, a
single person can have multiple flat fee groups.
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2.5.4.2 Flat Fee Variable Descriptions
2.5.4.2.1 Flat Fee ID (FFEEIDX)
As noted earlier in Section 2.5.1.2 "Record Identifiers," the
variable FFEEIDX uniquely identifies all events that are part of the same flat
fee group for a person. On any 2000 MEPS event file, every event that is part of
a specific flat fee group will have the same value for FFEEIDX. Note that
prescribed medicine and home health events are never included in a flat fee
group and FFEEIDX is not a variable on those event files.
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2.5.4.2.2 Flat Fee Type (FFIPTYPE)
FFIPTYPE indicates whether the 2000 hospital stay is the "stem" or
"leaf" of a flat fee group. A stem (records with FFIPTYPE = 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 FFIPTYPE = 2) are those medical events that are tied back to the
initial medical event (the stem) in the flat fee group. These "leaf"
records have their expenditure variables set to zero. For the hospital inpatient
stays that are not part of a flat fee payment situation, the FFIPTYPE is set to
-1, "INAPPLICABLE."
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2.5.4.2.3 Counts of Flat Fee Events that Cross Years (FFBEF00, FFTOT01)
As explained in Section 2.5.4.1, a flat fee payment situation covers multiple
events and the multiple events could span multiple years. For situations where
the hospital inpatient stay/event occurred in 2000 as a part of a group of
events, and some event occurred before or after 2000, counts of the known events
are provided on the STAZ record. Variables that indicate events occurred before
or after 2000 are as follows:
FFBEF00 - total number of pre-2000 events in the same flat fee group as
the 2000 hospital inpatient stay(s). This count would not include 2000
hospital inpatient stay(s).
FFTOT01 - indicates the number of 2001 hospital inpatient stays expected
to be in the same flat fee group as the hospital inpatient stay that
occurred in 2000.
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2.5.4.3 Caveats of Flat Fee Groups
There are 18 hospital inpatient stays/events that are identified as being
part of a flat fee payment group. In general, every flat fee group should have
an initial visit (stem) and at least one subsequent visit (leaf). There are some
situations where this is not true. For some of these flat fee groups, the
initial visit reported occurred in 2000, but the remaining visits that were part
of this flat fee group occurred in 2001. In this case, the 2000 flat fee group
would consist of one event, the stem. The 2001 events that are part of this flat
fee group are not represented on the file. Similarly, the household respondent
may have reported a flat fee group where the initial visit began in 1999 but
subsequent visits occurred during 2000. In this case, the initial visit would
not be represented on the file. This 2000 flat fee group would then only consist
of one or more leaf records and no stem.
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2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
Expenditure variables on this file refer to what is paid for health care
services. More specifically, expenditures in MEPS are defined as the sum of
payments for care received for each hospital stay, including out-of-pocket
payments and payments made by private insurance, Medicaid, Medicare and other
sources. The definition of expenditures used in MEPS differs slightly from its
predecessors: the 1987 NMES and 1977 NMCES surveys where "charges"
rather than sum of payments were used to measure expenditures. This change was
adopted because charges became a less appropriate proxy for medical expenditures
during the 1990s due to the increasingly common practice of discounting.
Although measuring expenditures as the sum of payments incorporates discounts in
the MEPS expenditure estimates, these estimates do not incorporate any payment
not directly tied to specific medical care 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
expenditures defined in the 1987 NMES. For details on expenditure definitions,
please reference the following, "Informing American Health Care
Policy" (Monheit, et al., 1999). AHRQ has developed factors to apply to the
1987 NMES expenditure data to facilitate longitudinal analysis. These factors
can be assessed via the CCFS data center. For more information, see the Data
Center section of the MEPS web site <http://www.meps.ahrq.gov>.
Expenditure data related to hospital inpatient events are broken out by
facility and separately billing doctor expenditures. This file contains five
categories of expenditure variables per stay: basic hospital facility expenses;
expenses for doctors who billed separately from the hospital for any inpatient
services provided during hospital stay; total expenses, which is the sum of the
facility and physician expenses; facility total charge; and physician total
charge.
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2.5.5.2 Data Editing and Imputation Methodologies of Expenditure
Variables
The expenditure data included on this file were derived from both the MEPS
Household (HC) and Medical Provider Components (MPC). The MPC contacted medical
providers identified by household respondents. The charge and payment data from
medical providers were used in the expenditure imputation process to supplement
missing household data. For all hospital inpatient stays, MPC data were used if
complete; otherwise, HC data were used if complete. Missing data for hospital
inpatient stays, where HC data were not complete and MPC data were not collected
or complete, were imputed during the imputation process.
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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, copayments or charges reported as
total payments, and reimbursed amounts that were reported as out-of-pocket
payments. In addition, edits were implemented to correct for misclassifications
between Medicare and Medicaid and between Medicare HMOs and private HMOs as
payment sources. These edits produced a complete vector of expenditures for some
events and provided the starting point for imputing missing expenditures in the
remaining events.
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2.5.5.2.2 General Hot-Deck Imputation
A weighted sequential hot-deck procedure was used to impute for missing
expenditures as well as total charge. This procedure uses survey data from
respondents to replace missing data while taking into account the respondents'
weighted distribution in the imputation process. Classification variables vary
by event type in the hot-deck imputations, but total charge and insurance
coverage are key variables in all of the imputations. Separate imputations were
performed for nine categories of medical provider care: inpatient hospital
stays, outpatient hospital department visits, emergency room visits, visits to
physicians, visits to non-physician providers, dental services, home health care
by certified providers, home health care by paid independents, and other medical
expenses. Within each event type file, separate imputations were performed for
flat fee and simple events. After the imputations were finished, visits to
physician and non-physician providers were combined into a single medical
provider file. The two categories of home care also were combined into a single
home health file.
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2.5.5.2.3 Hospital Inpatient Stay Data Editing and Imputation
Facility expenditures for hospital inpatient stays were developed in a
sequence of logical edits and imputations. "Household" edits were
applied to sources and amounts of payment for all events reported by HC
respondents. "MPC" edits were applied to provider-reported sources and
amounts of payment for records matched to household-reported events. Both sets
of edits were used to correct obvious errors (as described above) in the
reporting of expenditures. After the data from each source were edited, a
decision was made as to whether household- or MPC-reported information would be
used in the final editing and hot-deck imputations for missing expenditures. The
general rule was that MPC data would be used for events where a
household-reported event corresponded to a MPC-reported event (i.e., a matched
event), since providers usually have more complete and accurate data on sources
and amounts of payment than households.
Separate imputations were performed for flat fee and simple events. Most
hospital inpatient stays were imputed as simple events because facility charges
for an inpatient hospital stay are rarely grouped with other events. (See
Section 2.5.4 for more details on flat fee groups.)
Logical edits also were used to sort each event into a specific category for
the imputations. Events with complete expenditures were flagged as potential
donors for the hot-deck imputations, while events with missing expenditure data
were assigned to various recipient categories. Each event was assigned to a
recipient category based on the extent of its missing charge and expenditure
data. For example, an event with a known total charge but no expenditure
information was assigned to one category, while an event with a known total
charge and partial expenditure information was assigned to a different category.
Similarly, events without a known total charge and no or partial expenditure
information were assigned to various recipient categories.
The logical edits produced eight recipient categories in which all events had
a common extent of missing data. Separate hot-deck imputations were performed on
events in each recipient category, and the donor pool was restricted to events
with complete expenditures from the MPC. The donor pool restriction was used
even though some unmatched events had complete household-reported expenditures.
These events were not allowed to donate information to other events because the
MPC data were considered to be more reliable.
The donor pool included "free events" because, in some instances,
providers are not paid for their services. These events represent charity care,
bad debt, provider failure to bill, and third party payer restrictions on
reimbursement in certain circumstances. If free events were excluded from the
donor pool, total expenditures would be over-counted because the cost of free
care would be both implicitly included in paid events, and explicitly included
in events that should have been treated as free from provider.
Expenditures for services provided by separately billing doctors in hospital
settings were also edited and imputed. These expenditures are shown separately
from hospital facility charges for hospital inpatient, outpatient, and emergency
room care.
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2.5.5.3 Imputation Flag (IMPFLAG)
Only one imputation flag was created for 2000 event files. This flag, IMPFLAG,
is a six-category variable that indicates if the event contains complete
Household Component (HC) or Medical Provider Component (MPC) data, was fully or
partially imputed, or was imputed in the capitated imputation process (for OP
and MV events only). The following list identifies how the imputation flag is
coded; the categories are mutually exclusive.
IMPFLAG=0 not eligible for imputation (includes zeroed out and leaf events)
IMPFLAG=1 complete HC data
IMPFLAG=2 complete MPC data
IMPFLAG=3 fully imputed
IMPFLAG=4 partially imputed
IMPFLAG=5 complete MPC data through capitation imputation (not applicable
to IP events)
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2.5.5.4 Flat Fee Expenditures
The approach used to count expenditures for flat fees was to place the
expenditure on the first visit of the flat fee group. The remaining visits have
zero payments. Thus, if the first visit in the flat fee group occurred prior to
2000, all of the events that occurred in 2000 will have zero payments.
Conversely, if the first event in the flat fee group occurred at the end of
2000, the total expenditure for the entire flat fee group will be on that event,
regardless of the number of events it covered after 2000. See Section 2.5.4 for
details on the flat fee variables.
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2.5.5.5 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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2.5.5.6 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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2.5.5.7 Mother/Newborn Expenditures
Expenditure data for newborns were edited to exclude discharges after birth
when the newborn left the hospital before or on the same day as the mother. As a
result, inpatient expenditures reported for 2000 births were usually applied to
the mother and not treated as separate expenditures for the infant. However, if
a newborn was discharged at a later date than the mother's discharge date,
then the hospitalization was treated as a separate hospital stay for the
newborn.
This means that, in most cases, expenditure data for the newborn is included
on the mother's record. A separate record for the newborn only exists if the
newborn was discharged after the mother. In this case, the expenditure for the
newborn is on the newborn's record.
In addition, the user should note that for the purposes of the expenditure
imputation, deliveries were identified using the variable RSNINHOS which has not
been reconciled with pregnancy and delivery ICD-9 codes on this file as well as
on the Medical Conditions File. As mentioned previously, in most instances where
RSNINHOS = 4 (delivery), the ICD-9 code indicates a pregnancy rather than a
delivery.
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2.5.5.8 Hospital Inpatient Stay/Emergency Room Expenditures
Although a person may have indicated that there was an emergency room visit
that preceded this hospital stay (EMERROOM), there was no verification that, in
fact, the emergency room visit was actually recorded within the Emergency Room
Section of the questionnaire.
While it is true that all of the event files can be linked by DUPERSID, there
is no unique record link between hospital inpatient stays and emergency room
visits. That is, a person could have one hospital inpatient stay and three
emergency room visits during the calendar year. While the hospital inpatient
stay record may indicate that it was preceded by an emergency room visit, there
is no unique record link to the appropriate (of the three) emergency room visit.
However, wherever relationships could be identified (using MPC start and end
date of the events as well as other information from the provider), the facility
expenditure associated with the emergency room visit was moved to the hospital
facility expenditure. Hence, for some hospital stays, facility expenditures for
a preceding emergency room visit are included. In these situations, the
corresponding emergency room record on the MEPS 2000 Emergency Room Visit File
will have its facility expenditure information zeroed out to avoid
double-counting. The variable ERHEVIDX identifies these hospital stays whose
expenditures include the expenditures for the preceding emergency room visit
(see ERHEVIDX in Section 2.5.1.2). It should also be noted that for these cases,
there is only one hospital stay associated with the emergency room stay.
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2.5.5.9 Sources of Payment
In addition to total expenditures, variables are provided which itemize
expenditures according to major source of payment categories. These categories
are:
-
Out-of-pocket by user or family,
-
Medicare,
-
Medicaid,
-
Private Insurance,
-
Veterans Administration, excluding TRICARE,
-
TRICARE, formerly CHAMPUS/CHAMPVA,
-
Other Federal sources - includes Indian Health Service, Military
Treatment Facilities, and other care by the Federal government,
-
Other State and Local Source - includes community and neighborhood
clinics, State and local health departments, and State programs other
than Medicaid,
-
Workers' Compensation, and
-
Other Unclassified Sources - includes sources such as automobile,
homeowner's, liability, and other miscellaneous or unknown sources.
Two additional source of payment variables were created to classify payments
for events with apparent inconsistencies between insurance coverage and sources
of payment based on data collected in the survey. These variables include:
-
Other Private - any type of private insurance payments reported
for persons not reported to have any private health insurance coverage
during the year as defined in MEPS, and
-
Other Public - Medicare/Medicaid payments reported for persons
who were not reported to be enrolled in the Medicare/Medicaid program at
any time during the year.
Though these two sources are relatively small in magnitude, data
users/analysts should exercise caution when interpreting the expenditures
associated with these two additional sources of payment. While these payments
stem from apparent inconsistent responses to health insurance and source of
payment questions in the survey, some of these inconsistencies may have logical
explanations. For example, private insurance coverage in MEPS is defined as
having a major medical plan covering hospital and physician services. If a MEPS
sampled person did not have such coverage but had a single service type
insurance plan (e.g., dental insurance) that paid for a particular episode of
care, those payments may be classified as "other private." Some of the
"other public" payments may stem from confusion between Medicaid and
other state and local programs or may be from persons who were not enrolled in
Medicaid, but were presumed eligible by a provider who ultimately received
payments from the program.
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2.5.5.10 Imputed Hospital Inpatient Stay Expenditure Variables
This file contains two sets of imputed expenditure variables: facility
expenditures and physician expenditures.
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2.5.5.10.1 Hospital Inpatient Facility Expenditures (IPFSF00X-IPFOT00X,
IPFXP00X, IPFTC00X)
Hospital facility expenses include all expenses for direct hospital care,
including room and board, diagnostic and laboratory work, x-rays, and similar
charges, as well as any physician services included in the hospital charge.
Hospital Facility expenditures were obtained primarily through the MPC. If
the physician charges were included in the hospital bill, then this expenditure
is included in the facility expenditure variables. The imputed facility
expenditures are provided on this file. IPFSF00X - IPFOT00X are the 12 sources
of payment: self/family, Medicare, Medicaid, private insurance, Veterans
Administration, TRICARE, other federal, state/local governments, Workers'
Compensation, other private insurance, other public insurance and other
insurance. IPFXP00X is the sum of the 12 sources of payments for the facility
expenditure, and IPFTC00X is the total charge.
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2.5.5.10.2 Hospital Inpatient Physician Expenditures (IPDSF00X -
IPDOT00X, IPDTC00X, IPDXP00X)
Separately billing doctor (SBD) expenses typically cover services provided to
patients in hospital settings by providers like anesthesiologists, radiologists,
and pathologists, whose charges are often not included in hospital bills.
For medical doctors who bill separately (i.e., outside the hospital bill), a
separate data collection effort within the Medical Provider Component was
performed to obtain this same set of expenditure information from each
separately billing doctor. It should be noted that there could be several
separately billing doctors associated with a medical event. For example, a
hospital inpatient stay could have a radiologist, anesthesiologist, pathologist
and a surgeon associated with it. If their services are not included in the
hospital bill then this is one medical event with four separately billing
doctors. The imputed expenditure information associated with the separately
billing doctors for a hospital inpatient stay is combined (i.e., the
expenditures incurred by the radiologist + anesthesiologist + pathologist +
surgeon) and is provided on the file. IPDSF00X - IPDOT00X are the 12 sources of
payment; IPDXP00X is the sum of the 12 sources of payments. IPDTC00X is the
total charge.
Data users/analysts need to take into consideration whether to analyze
facility and SBD expenditures separately, combine them within service
categories, or collapse them across service categories (e.g., combine SBD
expenditures with expenditures for physician visits to offices and/or outpatient
departments).
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2.5.5.10.3 Total Expenditures and Charges for Hospital Inpatient Stays
(IPXP00X, IPTC00X)
Data users/analysts interested in total expenditures should use the variable
IPXP00X, which includes both facility and physician amounts. Those interested in
total charges should use the variable IPTC00X (see Section 2.5.4.1 for an
explanation of the "charge" concept).
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2.5.5.11 Rounding
Expenditure variables have been rounded to the nearest penny. Person-level
expenditure information released on the MEPS 2000 Person Level Use and
Expenditure File were rounded to the nearest dollar. It should be noted that
using the MEPS 2000 event files to create person-level totals will yield
slightly different totals than those found on the person-level expenditure file.
These differences are due to rounding only. Moreover, in some instances, the
number of persons having expenditures on the MEPS 2000 event files for a
particular source of payment may differ from the number of persons with
expenditures on the person-level expenditure file for that source of payment.
This difference is also an artifact of rounding only. Please see the MEPS 2000
Appendix File, HC-051I, for details on such rounding differences.
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3.0 Sample Weight (PERWT00F)
3.1 Overview
There is a single full year person-level weight (PERWT00F) assigned to each
record for each key, in-scope person who responded to MEPS for the full period
of time that he or she was in-scope during 2000. A key person either was a
member of an NHIS household at the time of the NHIS interview, or became a
member of such a household after being out-of-scope at the time of the NHIS
(examples of the latter situation include newborns and persons returning from
military service, an institution, or living outside the United States). A person
is in-scope whenever he or she is a member of the civilian noninstitutionalized
portion of the U.S. population.
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3.2 Details on Person Weight Construction
The person-level weight PERWT00F was developed in several stages.
Person-level weights for Panels 4 and 5 were created separately. The weighting
process for each panel included an adjustment for nonresponse over time and
poststratification. Poststratification was achieved by controlling to Current
Population Survey (CPS) population estimates based on five variables. Variables
used in the establishment of person-level poststratification control figures
included: census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA);
race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and age. A
2000 composite weight was then formed by multiplying each panel weight by .5 and
then poststratifying the resulting weight to the same set of CPS-based control
totals. When poverty status information derived from income variables became
available, a final poststratification was done on the resulting weight variable,
including poverty status (below poverty, from 100 to 125 percent of poverty,
from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least
400 percent of poverty) as well as the original five poststratification
variables in the establishment of control totals.
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3.2.1 MEPS Panel 4 Weight
The person-level weight for MEPS Panel 4 was developed using the 1999 full
year weight for an individual as a "base" weight for survey
participants present in 1999. For key, in-scope respondents who joined an RU
some time in 2000 after being out-of-scope in 1999, the 1999 family weight
associated with the family the person joined served as a "base"
weight. The weighting process included an adjustment for nonresponse over Rounds
4 and 5 as well as poststratification to population control figures for December
2000. These control figures were derived by scaling back the population totals
obtained from the March 2000 CPS to reflect the December 2000 CPS estimated
population distribution across age and sex categories as of December 2000.
Variables used in the establishment of person-level poststratification control
figures included: census region (Northeast, Midwest, South, West); MSA status (MSA,
non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and
age. Overall, the weighted population estimate for the civilian
noninstitutionalized population on December 31, 2000 is 275,158,755. Key,
responding persons not in-scope on December 31, 2000 but in-scope earlier in the
year retained, as their final Panel 4 weight, the weight after the nonresponse
adjustment.
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3.2.2 MEPS Panel 5 Weight
The person-level weight for MEPS Panel 5 was developed using the MEPS Round 1
person-level weight as a "base" weight. For key, in-scope respondents who
joined an RU after Round 1, the Round 1 family weight served as a
"base" weight. The weighting process included an adjustment for
nonresponse over Round 2 and the 2000 portion of Round 3 as well as
poststratification to the same population control figures for December 2000 used
for the MEPS Panel 4 weights. The same five variables employed for Panel 4
poststratification (census region, MSA status, race/ethnicity, sex, and age)
were used for Panel 5 poststratification. Similarly, for Panel 5, key,
responding persons not in-scope on December 31, 2000 but in-scope earlier in the
year retained, as their final Panel 5 weight, the weight after the nonresponse
adjustment.
Note that the MEPS Round 1 weights (for both panels with one exception as
noted below) incorporated the following components: the original household
probability of selection for the NHIS; ratio-adjustment to NHIS-based national
population estimates at the household (occupied dwelling unit) level; adjustment
for nonresponse at the dwelling unit level for Round 1; and poststratification
to figures at the family and person level obtained from the March 2000 CPS data
base.
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3.2.3 The Final Weight for 2000
Variables used in the establishment of person-level poststratification
control figures included: poverty status (below poverty, from 100 to 125 percent
of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of
poverty, at least 400 percent of poverty); census region (Northeast, Midwest,
South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, black but
non-Hispanic, and other); sex; and age. Overall, the weighted population
estimate for the civilian noninstitutionalized population for December 31, 2000
is 275,158,755 (PERWT00F>0 and INSC1231=1). The weights of some persons
out-of-scope on December 31, 2000 were also poststratified. Specifically, the
weights of persons out-of-scope on December 31, 2000 who were in-scope some time
during the year and also entered a nursing home during the year were
poststratified to a corresponding control total obtained from the 1996 MEPS
Nursing Home Component. The weights of persons who died while in-scope during
2000 were poststratified to corresponding estimates derived using data obtained
from the Medicare Current Beneficiary Survey (MCBS) and Vital Statistics
information provided by the National Center for Health Statistics (NCHS).
Separate control totals were developed for the "65 and older" and
"under 65" civilian noninstitutionalized populations.
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3.2.4 Coverage
The target population for MEPS in this file is the 2000 U.S. civilian
noninstitutionalized population. However, the MEPS sampled households are a
subsample of the NHIS households interviewed in 1998 (Panel 4) and 1999 (Panel
5). New households created after the NHIS interviews for the respective Panels
and consisting exclusively of persons who entered the target population after
1998 (Panel 4) or after 1999 (Panel 5) are not covered by MEPS. Neither are
previously out-of-scope persons who join an existing household but are unrelated
to the current household residents. Persons not covered by a given MEPS panel
thus include some members of the following groups: immigrants; persons leaving
the military; U.S. citizens returning from residence in another country; and
persons leaving institutions. The set of uncovered persons constitutes only a
small proportion of the MEPS target population.
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4.0 Strategies for Estimation
This file is constructed for efficient estimation of utilization,
expenditures, and sources of payment for hospital inpatient care and to allow
for estimates of number of persons with inpatient hospital utilization for 2000.
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4.1 Variables with Missing Values
It is essential that the data user/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 data
user/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 data user/analyst may want to consider whether to recode or impute a value for cases with negative
values or whether to exclude or include such cases in the numerator and/or
denominator when calculating proportions.
Methodologies used for the editing/imputation of expenditure variables (e.g.,
sources of payment, flat fee, and zero expenditure) are described in Section
2.5.4.
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4.2 Basic Estimates of Utilization, Expenditures, and Sources of
Payment
While the examples described below illustrate the use of event-level data in
constructing person-level total expenditures, these estimates can also be
derived from the person-level expenditure file unless the characteristic of
interest is event-specific.
In order to produce national estimates related to hospital inpatient stays,
expenditures and sources of payment, the value in each record contributing to
the estimates must be multiplied by the weight (PERWT00F) contained on that
record.
Example 1
For example, the total number of hospital inpatient stays, regardless of the
length of the hospital stay, for the civilian noninstitutionalized population of
the U.S. in 2000, is estimated as the sum of the weight (PERWT00F) across all
records. That is,
301 Moved Permanently
301 Moved Permanently
|
= 28,344,307 |
(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 at the hospital inpatient stay level (for those who had such expense
greater than 0), should be calculated as the weighted mean of the facility bill
and doctor's bill paid by self/family. That is,
301 Moved Permanently
301 Moved Permanently
|
= $182.87
|
(2) |
where Xj = IPFSF00Xj + IPDSF00Xj and
|
301 Moved Permanently
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|
= 27,678,086 |
for all records with IPXP00Xj > 0.
This gives $182.87as the estimated mean amount of out-of-pocket payment of
expenditures associated with hospital inpatient stays (discharges) and
27,678,086 as an estimate of the total number of hospital inpatient stays with
expenditures. Both of these estimates are for the civilian noninstitutionalized
population of the U.S. in 2000.
Example 3
Another example would be to estimate the mean proportion of total
expenditures paid by private insurance for hospital inpatient stays with
expenditures. This should be calculated as the weighted mean of the proportion
of total expenditures paid by private insurance at the event level. That is,
301 Moved Permanently
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|
= 0.4020
|
(3) |
where Yj = (IPFPV00Xj + IPDPV00Xj)/IPXP00Xj
and |
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301 Moved Permanently
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= 27,678,086 |
for all records with IPXP00Xj > 0.
This gives 0.4020 as the estimated mean proportion of total expenditures paid
by private insurance for hospital inpatient stays with expenditures for the
civilian noninstitutionalized population of the U.S. in 2000.
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4.3 Estimates of the Number of Persons with Hospital Inpatient Stays
When calculating an estimate of the total number of persons with hospital
inpatient stays, users can use a person-level file or this event file. However,
this event file must be used when the measure of interest is defined at the
event level. For example, to estimate the number of persons in the civilian
noninstitutionalized population of the U.S. discharged from a hospital in 2000
with at least one hospital stay of 10 or more nights, this event file must be
used. This would be estimated as,
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across all
unique persons i on this file
|
(4) |
where Wi is the sampling weight (PERWT00F) for
person i
and
Xi = 1 if NUMNIGHXj GE 10 for any stay 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 Hospital
Inpatient Use
This file may be used to derive person-based ratio estimates. However, when
calculating ratio estimates where the denominator is at the person level, care
should be taken to
properly define and estimate the unit of analysis as person-level. For
example, the mean expense for persons with hospital inpatient stays is estimated
as:
301 Moved Permanently
301 Moved Permanently
|
across all unique persons i on this file
|
(5) |
where
Wi is the sampling weight (PERWT00F) for
person i
and
|
Zi = |
301 Moved Permanently
301 Moved Permanently
|
IPXP00Xj
across all stays 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 hospital
inpatient stay are represented on this data file. In this case, the Full Year
Consolidated File, which has data for all sampled persons, must be used to
estimate the total number of persons (i.e., those with use and those without
use). For example, the proportion of the civilian noninstitutionalized
population of the U.S. with at least one hospital inpatient stay of four or more
days would be estimated as:
301 Moved Permanently
301 Moved Permanently
|
across all unique persons i on the person-level file
|
(6) |
where Wi is the sampling weight (PERWT00F) for
person i
and
Zi = 1 if NUMNIGHXj GE 4 for any stay of
person i
= 0 otherwise.
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4.5 Sampling Weights for Merging Previous Releases of MEPS Household
Data with this Event File
There have been several previous releases of MEPS Household Survey public use
data. Unless a variable name common to several files is provided, the sampling
weights contained on these data files are file-specific. The file-specific
weights reflect minor adjustments to eligibility and response indicators due to
birth, death, or institutionalization among respondents.
For estimates from a MEPS data file that do not require merging with
variables from other MEPS data files, the sampling weight(s) provided on that
data file are the appropriate weight(s). When merging a MEPS Household data file
with another, the major analytical variable (i.e., the dependent variable)
determines the correct sampling weight to use.
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4.6 Variance Estimation (VARSTR00, VARPSU00)
To obtain estimates of variability (such as the standard error of sample
estimates or corresponding confidence intervals) for estimates based on MEPS
survey data, one needs to take into account the complex sample design of MEPS.
Various approaches can be used to develop such estimates of variance including
use of the Taylor Series or various replication methodologies. Replicate weights
have not been developed for the MEPS 2000 data. Variables needed to implement a
Taylor Series estimation approach are provided in the file and are described in
the paragraph below.
Using a Taylor Series approach, variance estimation strata and the variance
estimation PSUs within these strata must be specified. The corresponding
variables on the MEPS full year utilization database are VARSTR00 and VARPSU00,
respectively. Specifying a "with replacement" design in a computer
software package such as SUDAAN (Shah, et al, 1996) should provide standard
errors appropriate for assessing the variability of MEPS survey estimates. It
should be noted that the number of degrees of freedom associated with estimates
of variability indicated by such a package may not appropriately reflect the
actual number available. For MEPS sample estimates for characteristics generally
distributed throughout the country (and thus the sample PSUs), there are over
100 degrees of freedom associated with the corresponding estimates of variance.
The following illustrates these concepts using two examples from section 4.2.
Examples 2 and 3 from Section 4.2
Using a Taylor Series approach, specifying VARSTR00 and VARPSU00 as the
variance estimation strata and PSUs (within these strata), respectively, and
specifying a "with replacement" design in a computer software package
(i.e., SUDAAN) will yield standard error estimates of $16.29 and 0.0154 for the
estimated mean out-of-pocket payment and the estimated mean proportion of total
expenditures paid by private insurance, respectively.
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5.0 Merging/Linking MEPS Data Files
Data from the MEPS 2000 Hospital Inpatient Stays File can be used alone or in
conjunction with other files. This section provides instructions for linking the
hospital stays file with other MEPS public use files, namely, the person-level
file, the prescribed medicines file, and the medical conditions file.
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5.1 Merging a 2000 Person-Level File to the 2000 Hospital
Inpatient Stays File
Merging characteristics of interest from person-level files (e.g., MEPS 2000
Full-Year Population Characteristics File) expands the scope of potential
estimates. To estimate the total number of hospital inpatient stays for persons
with specific demographic characteristics (such as, age, race, and sex),
population characteristics from a person-level file need to be merged onto the
hospital inpatient stays file. This procedure is illustrated below. The MEPS
2000 Appendix File, HC-051I, provides additional detail on how to merge MEPS
data files.
-
Create data set PERSX by sorting the MEPS 2000 Full Year Population
Characteristics File by the person identifier, DUPERSID. Keep only
variables to be merged onto the hospital inpatient stays file, and
DUPERSID.
-
Create data set STAZ by sorting the hospital inpatient stays file by
person identifier, DUPERSID.
-
Create final data set NEWSTAZ by merging these two files by DUPERSID,
keeping only records on the hospital inpatient stays file.
The following is an example of SAS code which completes these steps:
PROC SORT DATA=HCXXX(KEEP= DUPERSID AGE31X AGE42X AGE53X SEX RACEX
EDUCYR)
OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA=STAZ;
BY DUPERSID;
RUN;
DATA NEWSTAZ;
MERGE STAYS (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
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5.2 Linking the 2000 Hospital Inpatient Stays File to the 2000
Medical Conditions File and/or the 2000 Prescribed Medicines File
Due to survey design issues, data users/analysts must keep limitations and
caveats in mind when linking the different files. Those limitations/caveats are
listed below. For detailed linking examples, including SAS code, data
users/analysts should refer to the MEPS 2000 Appendix File, HC-051I.
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5.2.1 Limitations/Caveats of RXLK (the Prescribed Medicine Link File)
The RXLK file provides a link from the MEPS event files to records on the
2000 Prescribed Medicine File. When using RXLK, data users/analysts should keep
in mind that one hospital inpatient stay could link to more than one prescribed
medicine record. Conversely, a prescribed medicine event may link to more than
one hospital inpatient stay or different types of events. When this occurs, it
is up to the data user/analyst to determine how the prescribed medicine
expenditures should be allocated among those medical events.
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5.2.2 Limitations/Caveats of CLNK (the Medical Conditions Link File)
The CLNK provides a link from MEPS event files to the 2000 Medical Conditions
File. When using the CLNK, data users/analysts should keep in mind that (1)
conditions are self-reported and (2) there may be multiple conditions associated
with a hospital inpatient stay. Data users/analysts should also note that not
all hospital inpatient stays link to the medical conditions file.
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References
Cohen, S.B. (1999). 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. 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: Health Inpatient Statistics, 1995.
Healthcare Cost and Utilization Project, HCUP-3 Research Note. Rockville, MD:
Agency for Health Care Policy and Research: 1998. AHCPR Pub. No. 98-0049.
Health Care Financing Administration (1980). International Classification of
Diseases, 9th Revision, Clinical Modification (ICD-CM). Vol. 1. (DHHS
Pub. No. (PHS) 80-1260). DHHS: U.S. Public Health Services.
Johnson, A.E. and Sanchez, M.E. (1993). Household and Medical Provider
Reports on Medical Conditions: National Medical Expenditure Survey, 1987. Journal
of Economic and Social Measurement. Vol. 19, 199-233.
Monheit, A.C., Wilson, R., and Arnett, III, R.H. (Editors). Informing
American Health Care Policy. (1999). Jossey-Bass Inc., San Francisco.
Shah, B.V., Barnwell, B.G., Bieler, G.S., Boyle, K.E., Folsom, R.E., Lavange,
L., Wheeless, S.C., and Williams, R. (1996). Technical Manual: Statistical
Methods and Algorithms Used in SUDAAN Release 7.0, Research Triangle Park,
NC: Research Triangle Institute.
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D. Variable-Source
Crosswalk
Variable-Source Crosswalk
For MEPS HC-051D: 2000 Hospital Inpatient Stays
Survey Administration Variables
Variable |
Description |
Source |
DUID |
Dwelling unit ID |
Assigned in sampling |
PID |
Person number |
Assigned in sampling |
DUPERSID |
Person ID (DUID + PID) |
Assigned in sampling |
EVNTIDX |
Event ID |
Assigned in Sampling |
EVENTRN |
Event Round number |
CAPI derived |
ERHEVIDX |
Event ID for corresponding emergency room visit |
Constructed |
FFEEIDX |
Flat fee ID |
CAPI derived |
MPCDATA |
MPC Data Flag |
Constructed |
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Characteristics of Hospital Inpatient Stays
Variable |
Description |
Source |
IPBEGYR |
Event start date - year |
CAPI derived |
IPBEGMM |
Event start date - month |
CAPI derived |
IPBEGDD |
Event start date - day |
CAPI derived |
IPENDYR |
Event end date - year |
CAPI derived |
IPENDMM |
Event end date - month |
CAPI derived |
IPENDDD |
Event end date - day |
CAPI derived |
NUMNIGHX |
# of nights in hospital - Edited/Imputed |
(Edited/Imputed) |
NUMNIGHT |
Number of nights stayed at provider |
HS01 |
EMERROOM |
Did stay begin with emergency room visit |
HS02 |
SPECCOND |
Hospital stay related to condition |
HS03 |
RSNINHOS |
Reason entered hospital |
HS05 |
ANYOPER |
Any operations or surgeries performed |
HS06 |
MAINSURG |
Main surgical procedure |
HS07 |
VAPLACE |
VA facility flag |
Constructed |
IPICD1X |
3 digit ICD-9 condition code |
Edited |
IPICD2X |
3 digit ICD-9 condition code |
Edited |
IPICD3X |
3 digit ICD-9 condition code |
Edited |
IPICD4X |
3 digit ICD-9 condition code |
Edited |
IPPRO1X |
2 digit ICD-9 procedure code |
Edited |
IPPRO2X |
2 digit ICD-9 procedure code |
Edited |
IPCCC1X |
Modified Clinical Classification Code |
Constructed/Edited |
IPCCC2X |
Modified Clinical Classification Code |
Constructed/Edited |
IPCCC3X |
Modified Clinical Classification Code |
Constructed/Edited |
IPCCC4X |
Modified Clinical Classification Code |
Constructed/Edited |
DSCHPMED |
Medicines prescribed at discharge |
HS08 |
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Flat Fee Variables
Variable |
Description |
Source |
FFIPTYPE |
Flat Fee Bundle |
Constructed |
FFBEF00 |
Total # of visits in FF before 2000 |
FF05 |
FFTOT01 |
Total # of visits in FF after 2000 |
FF10 |
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Imputed Total Expenditure Variables
Variable |
Description |
Source |
IPXP00X |
Total expenditure for event (IPFXP00X+IPDXP00X) |
Constructed |
IPTC00X |
Total charge for event (IPFTC00X+IPDTC00X) |
Constructed |
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Imputed Facility Expenditure Variables
Variable |
Description |
Source |
IPFSF00X |
Facility amount paid, self/family (Imputed) |
CP Section (Edited) |
IPFMR00X |
Facility amount paid, Medicare (Imputed) |
CP Section (Edited) |
IPFMD00X |
Facility amount paid, Medicaid (Imputed) |
CP Section (Edited) |
IPFPV00X |
Facility amount paid, private insurance (Imputed) |
CP Section (Edited) |
IPFVA00X |
Facility amount paid, Veterans Administration (Imputed) |
CP Section (Edited) |
IPFTR00X |
Facility amount paid, TRICARE (Imputed) |
CP Section (Edited) |
IPFOF00X |
Facility amount paid, other federal (Imputed) |
CP Section (Edited) |
IPFSL00X |
Facility amount paid state & local government (Imputed) |
CP Section (Edited) |
IPFWC00X |
Facility amount paid, workers' compensation (Imputed) |
CP Section (Edited) |
IPFOR00X |
Facility amount paid, other private (Imputed) |
Constructed |
IPFOU00X |
Facility amount paid, other pub (Imputed) |
Constructed |
IPFOT00X |
Facility amount paid, other insurance (Imputed) |
CP Section (Edited) |
IPFXP00X |
Facility sum payments IPFSF00X - IPFOT00X |
Constructed |
IPFTC00X |
Total facility charge (Imputed) |
CP Section (Edited) |
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Imputed Separately Billing Physician Expenditure Variables
Variable |
Description |
Source |
IPDSF00X |
Doctor amount paid, family (Imputed) |
Constructed |
IPDMR00X |
Doctor amount paid, Medicare (Imputed) |
Constructed |
IPDMD00X |
Doctor amount paid, Medicaid (Imputed) |
Constructed |
IPDPV00X |
Doctor amount paid, private insurance (Imputed) |
Constructed |
IPDVA00X |
Doctor amount paid, Veterans Administration (Imputed) |
Constructed |
IPDTR00X |
Doctor amount paid, TRICARE (Imputed) |
Constructed |
IPDOF00X |
Doctor amount paid, other federal (Imputed) |
Constructed |
IPDSL00X |
Doctor amount paid, state & local government (Imputed) |
Constructed |
IPDWC00X |
Doctor amount paid, workers' compensation (Imputed) |
Constructed |
IPDOR00X |
Doctor amount paid, other private insurance (Imputed) |
Constructed |
IPDOU00X |
Doctor amount paid, other public insurance (Imputed) |
Constructed |
IPDOT00X |
Doctor amount paid, other insurance (Imputed) |
Constructed |
IPDXP00X |
Doctor sum payments IPDSF00X-IPDOT00X |
Constructed |
IPDTC00X |
Total doctor charge (Imputed) |
Constructed |
IMPFLAG |
Imputation status |
Constructed |
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Weights
Variable |
Description |
Source |
PERWT00F |
Final person level weight, 2000 |
Constructed |
VARSTR00 |
Variance estimation stratum, 2000 |
Constructed |
VARPSU00 |
Variance estimation PSU, 2000 |
Constructed |
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