MEPS HC-118D: 2008 Hospital Inpatient Stays
September 2010
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406
Table of Contents
A. Data Use Agreement
B. Background
1.0 Household Component
2.0 Medical Provider Component
3.0 Survey Management and Data Collection
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Codebook Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Source and Naming Conventions
2.4.1 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)
2.5.1.4 Panel Indicator (PANEL)
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-IPENDYY)
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 - ANYOPER)
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, FFBEF08, FFTOT09)
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 (FFBEF08, FFTOT09)
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 (IPFSF08X-IPFOT08X, IPFXP08X, IPFTC08X)
2.5.5.10.2 Hospital Inpatient Physician Expenditures (IPDSF08X - IPDOT08X, IPDTC08X, IPDXP08X)
2.5.5.10.3 Total Expenditures and Charges for Hospital Inpatient Stays (IPXP08X and IPTC08X)
2.5.5.11 Rounding
3.0 Sample Weight (PERWT08F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 12 Weight
3.2.2 MEPS Panel 13 Weight
3.2.3 The Final Weight for 2008
3.2.4 Additional Adjustment to 2008 Person Weights for Persons Age 65 and Over
3.2.5 Coverage
3.3 Using MEPS Data for Trend Analysis
4.0 Strategies for Estimation
4.1 Developing Event-Level Estimates
4.2 Person-Based Estimates for Hospital Inpatient Stays
4.3 Variables with Missing Values
4.4 Variance Estimation (VARSTR, VARPSU)
5.0 Merging/Linking MEPS Data Files
5.1 Linking to the Person-Level File
5.2 Linking to the Prescribed Medicines File
5.3 Linking to the Medical Conditions File
_._ References
D. Variable-Source Crosswalk
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
1.0 Household Component
The Medical Expenditure Panel Survey (MEPS) provides
nationally representative estimates of health care use, expenditures, sources of
payment, and health insurance coverage for the U.S. civilian
non-institutionalized population. The MEPS Household Component (HC) also
provides estimates of respondents’ health status, demographic and socio-economic
characteristics, employment, access to care, and satisfaction with health care.
Estimates can be produced for individuals, families, and selected population
subgroups. The panel design of the survey, which includes 5 Rounds of interviews
covering 2 full calendar years, provides data for examining person level changes
in selected variables such as expenditures, health insurance coverage, and
health status. Using computer assisted personal interviewing (CAPI) technology,
information about each household member is collected, and the survey builds on
this information from interview to interview. All data for a sampled household
are reported by a single household respondent.
The MEPS-HC was initiated in 1996. Each year a new
panel of sample households is selected. Because the data collected are
comparable to those from earlier medical expenditure surveys conducted in 1977
and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample
size is about 15,000 households. Data can be analyzed at either the person or
event level. Data must be weighted to produce national
estimates.
The set of households selected for each panel of the
MEPS HC is a subsample of households participating in the previous year’s
National Health Interview Survey (NHIS) conducted by the National Center for
Health Statistics. The NHIS sampling frame provides a nationally representative
sample of the U.S. civilian non-institutionalized population and reflects an
oversample of blacks and Hispanics. In 2006, the NHIS implemented a new sample
design, which included Asian persons in addition to households with black and
Hispanic persons in the oversampling of minority populations. MEPS further
oversamples additional policy relevant sub-groups such as low income households.
The linkage of the MEPS to the previous year’s NHIS provides additional data for
longitudinal analytic purposes.
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2.0 Medical Provider Component
Upon completion of the household CAPI interview and
obtaining permission from the household survey respondents, a sample of medical
providers are contacted by telephone to obtain information that household
respondents can not accurately provide. This part of the MEPS is called the
Medical Provider Component (MPC) and information is collected on dates of visit,
diagnosis and procedure codes, charges and payments. The Pharmacy Component
(PC), a subcomponent of the MPC, does not collect charges or diagnosis and
procedure codes but does collect drug detail information, including National
Drug Code (NDC) and medicine name, as well as date filled and sources and
amounts of payment. The MPC is not designed to yield national estimates. It is
primarily used as an imputation source to supplement/replace household reported
expenditure information.
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3.0 Survey Management and Data Collection
MEPS HC and MPC data are collected under the authority
of the Public Health Service Act. Data are collected under contract with Westat,
Inc. Data sets and summary statistics are edited and published in accordance
with the confidentiality provisions of the Public Health Service Act and the
Privacy Act. The National Center for Health statistics (NCHS) provides
consultation and technical assistance.
As soon as data collection and editing are completed,
the MEPS survey data are released to the public in staged releases of summary
reports, micro data files, and tables via the MEPS Web site:
www.meps.ahrq.gov.
Selected data can be analyzed through MEPSnet, an on-line interactive tool
designed to give data users the capability to statistically analyze MEPS data in
a menu-driven environment.
Additional information on MEPS is available from the
MEPS project manager or the MEPS public use data manager at the Center for
Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality,
540 Gaither Road, Rockville, MD 20850 (301-427-1406).
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C. Technical and Programming Information
1.0 General Information
This documentation describes one in a series of public
use event files from the 2008 Medical Expenditure Panel Survey (MEPS) Household
Component (HC) and Medical Provider Component (MPC). Released as an ASCII data
file (with related SAS and SPSS programming statements) and SAS transport
file, the 2008 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 2008. The file contains 69
variables and has a logical record length of 382 with an additional 2-byte
carriage return/line feed at the end of each record. As illustrated below, this
file consists of MEPS survey data from the 2008 portion of Round 3 and Rounds 4
and 5 for Panel 12, as well as Rounds 1, 2 and the 2008 portion of Round 3 for
Panel 13 (i.e., the rounds for the MEPS panels covering calendar year 2008).
Incentive Experiment in Panel 13
With the encouragement of the Office of Management and
Budget (OMB), an experiment was undertaken for MEPS Panel 13 (first fielded
in
2008) to evaluate whether and how differential payments to household respondents
might affect survey participation, the level of effort required to obtain
participation, and the quality of the data collected. Each sampled household
in Panel 13 was randomly assigned to one of three different levels of payment--$30,
$50, or $70—with the experiment continuing through the panel’s five
rounds of data collection. Households receiving the $30 payment represent the
control
group, since that amount had been offered to all households in the 2007 panel.
To learn more about this experiment, refer to the Household
Annual Contractor Methodology Report (located in the Household – Survey
Basics section). Agency for Healthcare Research and Quality, Rockville, MD.
Hospital stay events reported in Panel 13 Round 3 and
known to have begun after December 31, 2008 are not included on this file.
Each record on the inpatient hospital event file
represents a unique 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.
Annual counts of hospital inpatient stay utilization
are based entirely on household reports. Information from the MEPS MPC is used
to supplement expenditure and payment data reported by the household and does
not affect use estimates.
Data from this event file can be merged with other
2008 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 2008 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 variables not found on this file but released on
previous years’ files were excluded because they contained only missing data.
For more information on MEPS HC survey design, see T.
Ezzati-Rice, et al. (1998-2007) 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:
www.meps.ahrq.gov.
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2.0 Data File Information
The 2008 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.
The 2008 STAZ public use data set contains variable
and frequency distributions for a total of 2,821 hospital inpatient stay records
reported during the 2008 portion of Round 3 and Rounds 4 and 5 for Panel 12, as
well as Rounds 1, 2, and the 2008 portion of Round 3 for Panel 13 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, 2008 or after December 31, 2008 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 2,821 hospital inpatient stay
records, 2,690 are associated with persons having a positive person-level weight
(PERWT08F). 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 2008. Stays that began prior
to 2008 but ended during 2008 are included on this data file. Stays that
began in 2008 but ended during 2009 are excluded from this data file and
will be included in a subsequent 2009 IP data file. Persons with no hospital
inpatient stay events for 2008 are not included on this event-level IP file
but are represented on the person-level 2008 Full Year Population
Characteristics file.
- 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 2008 eligibility (i.e., persons with a positive 2008
full-year person-level sampling weight (PERWT08F > 0)), or
- Be an eligible member of a family all of whose key in-scope members
have a positive person-level weight (PERWT08F > 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 (FAMWT08F >
0). Note that FAMIDYR and FAMWT08F are variables on the 2008 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; 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; a full-year person-level
weight; variance strata; and variance PSU.
To append person-level information such as demographic
or health insurance coverage to each event record, data from this file can be
merged with 2008 MEPS HC person-level data (e.g. Full Year Consolidated or Full
Year Population Characteristics files) using the person identifier, DUPERSID.
Hospital inpatient stay events can also be linked to the MEPS 2008 Medical
Conditions File and the MEPS 2008 Prescribed Medicines File. Please see Section
5.0 or the MEPS 2008 Appendix File, HC-118I, for details on how to merge MEPS
data files.
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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 accompanying codebook
file. 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-CM condition and procedure codes
- Clinical Classification Software (CCS) codes
- Imputed expenditure variables
- Weight and variance estimation variables
Note that the person identifier is unique within this
data year.
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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:
www.meps.ahrq.gov/survey_comp/survey_questionnaires.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 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:
- HS – Hospital Stays 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 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 sources 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 the IP file, 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 Administration/CHAMPVA |
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
(08). The eighth character, "X", indicates whether the variable is
edited/imputed.
For example, IPFSF08X is the edited/imputed amount
paid by self or family for the facility portion of the hospital inpatient stay
expenditure incurred in 2008.
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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 2008 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 2008 Medical Conditions File and MEPS 2008 Prescribed Medicines File, respectively). For details on linking, see
Section 5.0 or the MEPS 2008 Appendix File, HC-118I.
ERHEVIDX is a constructed variable identifying a STAZ
record that includes the facility expenditures for the preceding emergency room
visit. This variable is derived from provider-reported information on linked
emergency room and inpatient stay events that matched to corresponding events
reported by the household. The variable ERHEVIDX contains the EVNTIDX of the
linked event. On the 2008 STAZ file, there are 440 hospital stays linked to a
preceding emergency room visit, that is, there are 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. 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 12. Likewise, Rounds 1, 2,
and 3 are associated with data collected from Panel 13.
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2.5.1.4 Panel Indicator (PANEL)
PANEL is a constructed variable used to specify the
panel number for the person. PANEL will indicate either Panel 12 or Panel 13 for
each person on the file. Panel 12 is the panel that started in 2007, and Panel
13 is the panel that started in 2008.
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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 household 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 Stays section of the MEPS HC questionnaire.
There are three variables which indicate the day, month, and year a hospital
stay began (IPBEGDD, IPBEGMM, and IPBEGYR, respectively). Similarly, there
are three variables which indicate the day, month, and year a hospital stay
ended (IPENDDD, IPENDMM, and 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 2007 and ending in 2008, 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
2.5.3.1). 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.
Furthermore, no attempt has been made to reconcile the unedited EMERROOM
variable with the edited ERHEVIDX variable (see section 2.5.1.2).
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2.5.3.4 Other Visit Detail (SPECCOND - ANYOPER)
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). Starting in 2008, Vaginal or
Caesarean delivery (DLVRTYPE) and Receive an epidural or spinal for pain
(EPIDURAL) were added to this file. "Pregnancy-Related Complications" will be
included as a separate category for RSNINHOS in the 2008 version of this file.
With respect to RSNINHOS, please note that while there
were 460 cases where RSNINHOS = 4 (reason entered hospital – to give birth to a
baby), this does not mean that there were actually 460 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 2008 Full Year Population Characteristics File,
Section 2.5.2 "Navigating the MEPS Data with Information on Person Disposition
Status"). In addition, RSNINHOS has not been edited to ensure alignment with the
ICD-9-CM condition codes, the procedure codes, or the CCC codes associated with
an event.
VAPLACE, a constructed variable that indicates whether
the service was provided at a VA facility, was dropped from this file for
confidentiality purposes beginning in 2007.
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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 is 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 2008 Medical Conditions File. Details on how to link the 2008 STAZ file to
the MEPS 2008 Medical Conditions File are provided in Section 5.2 and the MEPS
2008 Appendix File, HC-118I. The data user/analyst should note that
provider-reported condition information is not publicly available because of
confidentiality restrictions.
The medical conditions and procedures reported by the
Household Component respondent were recorded by the interviewer as verbatim
text, which was then coded by professional coders to fully-specified 2008
ICD-9-CM codes, including medical condition and V codes (Health Care Financing
Administration, 1980). 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 (Cox and
Cohen, 1985; Cox and Iachan, 1987; Edwards, et al., 1994; and Johnson and
Sanchez, 1993). For detailed information on how conditions and procedures were
coded, please refer to the documentation on the MEPS 2008 Medical Conditions
File. For frequencies of conditions by event type, please see the MEPS 2008
Appendix File, HC-118I.
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
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. Similarly, the procedure codes
have been collapsed from fully-specified codes to two-digit code categories.
Because of this collapsing, it
is possible for there to be duplicate ICD-9-CM condition or procedure codes
linked to a single medical event when different fully-specified codes are
collapsed into the same code. For more information on ICD-9-CM codes, see the
MEPS 2008 Medical Conditions File documentation.
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 2008 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-CM
condition codes, the procedure codes, or the CCC codes that are on the file.
Analysts should use the clinical classification codes
listed in the Conditions PUF document (HC-120) and the Appendix to the Event
Files (HC-118I) document when analyzing MEPS conditions data. Although there is
a list of clinical classification codes and labels on the Healthcare Cost and
Utilization Project (HCUP) Web site, if updates to these codes and/or labels are
made on the HCUP Web site after the release of the 2008 MEPS PUFs, these updates
will not be reflected in the 2008 MEPS data.
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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, FFBEF08, FFTOT09)
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. 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 2008. 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 2008 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 2008 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, the FFIPTYPE is set to –1,
"INAPPLICABLE."
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2.5.4.2.3 Counts of Flat Fee Events that Cross Years (FFBEF08, FFTOT09)
As explained in Section 2.5.4.1, a flat fee payment
covers multiple events and the multiple events could span multiple years. For
situations where the hospital inpatient stay/event occurred in 2008 as a part of
a group of events, and some event occurred before or after 2008, counts of the
known events are provided on the STAZ record. Variables that indicate events
occurred before or after 2008 are as follows:
FFBEF08 - total number of pre-2008 events in the same
flat fee group as the 2008 hospital inpatient stay(s). This count would not
include 2008 hospital inpatient stay(s). Because there were no 2007 events for
any flat fee group, this variable was omitted from this file.
FFTOT09 - the number of 2009 hospital inpatient stays
expected to be in the same flat fee group as the hospital inpatient stay that
occurred in 2008. Because there were no 2009 events expected for any flat fee
group, this variable was omitted from this file.
If there are no 2007 events on the file, FFBEF08 will
be omitted. Likewise, if there are no 2009 events on the file, FFTOT09 will be
omitted. If there are no flat fee data related to the records in this file,
FFEEIDX and FFIPTYPE will be omitted as well. Please note that the crosswalk in
this document lists all possible flat fee variables.
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2.5.4.3 Caveats of Flat Fee Groups
There are 6 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 2008, but the remaining
visits that were part of this flat fee group occurred in 2009. In this case, the
2008 flat fee group would consist of one event, the stem. The 2009 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 2007 but subsequent visits occurred during 2008. In this case, the
initial visit would not be represented on the file. This 2008 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 accessed via the CFACT data center. For more information, see the
Data Center section of the MEPS Web site
www.meps.ahrq.gov/data_stats/onsite_datacenter.jsp.
Expenditure data related to hospital inpatient events
are broken out by facility and separately billing doctor expenditures. This file
contains six 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 charge; physician
charge; and total charges, which is the sum of the facility and physician
charges. If examining trends in MEPS expenditures or performing longitudinal
analysis on MEPS expenditures, please refer to Section C, sub-Section 3.3 for
more information.
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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 available; otherwise, HC data were used.
Missing data for hospital inpatient stays where HC data were not complete and
MPC data were not collected, or MPC data were not 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 with missing expenditure data was assigned to a recipient category based
on the extent of its missing charge and expenditure data. For example, an event
with a known total charge but no expenditure information was assigned to one
category, while an event with a known total charge and partial expenditure
information was assigned to a different category. Similarly, events without a
known total charge and no or partial expenditure information were assigned to
various recipient categories.
The logical edits produced eight recipient categories
in which all events had a common extent of missing data. Separate hot-deck
imputations were performed on events in each recipient category. For hospital
inpatient and emergency room events, the donor pool was restricted to events
with complete expenditures from the MPC. Due to the low ratio of donors to
recipients for hospital outpatient and office-based events, there were no donor
pool restrictions.
The donor pool included "free events" because, in some
instances, providers are not paid for their services. These events represent
charity care, bad debt, provider failure to bill, and third party payer
restrictions on reimbursement in certain circumstances. If free events were
excluded from the donor pool, total expenditures would be over-counted because
the distribution of free events among complete events (donors) would not be
represented among incomplete events (recipients).
Expenditures for services provided by separately
billing doctors in hospital settings were also edited and imputed. These
expenditures are shown separately from hospital facility charges for hospital
inpatient, outpatient, and emergency room care.
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2.5.5.3 Imputation Flag (IMPFLAG)
IMPFLAG is a six-category variable that indicates if
the event contains complete Household Component (HC) or Medical Provider
Component (MPC) data, was fully or partially imputed, or was imputed in the
capitated imputation process (for OP and MV events only). The following list
identifies how the imputation flag is coded; the categories are mutually
exclusive.
IMPFLAG = 0 not eligible for imputation (includes
zeroed out and flat fee leaf events)
IMPFLAG = 1 complete HC data
IMPFLAG = 2 complete MPC data
IMPFLAG = 3 fully imputed
IMPFLAG = 4 partially imputed
IMPFLAG = 5 complete MPC data through capitation
imputation (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 facility payments, while physician’s expenditures may
be still present. Thus, if the first visit in the flat fee group occurred prior
to 2008, all of the events that occurred in 2008 will have zero payments.
Conversely, if the first event in the flat fee group occurred at the end of
2008, the total expenditure for the entire flat fee group will be on that event,
regardless of the number of events it covered after 2008. 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. Zero payment events can occur in MEPS for the
following reasons: (1) the stay was covered under a flat fee arrangement (flat
fee payments are included only on the first event covered by the arrangement),
(2) there was no charge for a follow-up stay, (3) the provider was never paid by
an individual, insurance plan, or other source for services provided, (4)
charges were included in another bill, or (5) the event was paid for through
government or privately-funded research or clinical trials.
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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 2008 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.
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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 the 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 2008
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 facility 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/CHAMPVA,
- TRICARE,
- Other Federal sources - includes Indian Health Service, Military
Treatment Facilities, and other care by the Federal government,
- Other State and Local Source - includes community and neighborhood
clinics, State and local health departments, and State programs other than
Medicaid,
- Workers’ Compensation, and
- Other Unclassified Sources - includes sources such as automobile,
homeowner’s, and liability insurance, and other miscellaneous or unknown
sources.
Two additional source of payment variables were
created to classify payments for events with apparent inconsistencies
between health 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
public payer.
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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
(IPFSF08X-IPFOT08X, IPFXP08X, IPFTC08X)
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.
IPFSF08X - IPFOT08X are the 12 sources of payment. The
12 sources of payment are: self/family (IPFSF08X), Medicare (IPFMR08X), Medicaid
(IPFMD08X), private insurance (IPFPV08X), Veterans Administration/CHAMPVA
(IPFVA08X), TRICARE (IPFTR08X), other Federal sources (IPFOF08X), State and
Local (non-federal) government sources (IPFSL08X), Workers’ Compensation
(IPFWC08X), other private insurance (IPFOR08X), other public insurance
(IPFOU08X), and other insurance (IPFOT08X). IPFXP08X is the sum of the 12
sources of payment for the Hospital Facility expenditures, and IPFTC08X is the
total charge.
Wherever an emergency room visit record is linked to a
hospital inpatient stays record (identified by the variable ERHEVIDX, see
Section 2.5.1.2), the facility source of payment variables on the emergency room
visit record were zeroed out because the emergency room expenditures were
already included in the hospital facility source of payment variables.
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2.5.5.10.2 Hospital Inpatient Physician Expenditures
(IPDSF08X - IPDOT08X, IPDTC08X, IPDXP08X)
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. IPDSF08X - IPDOT08X are the 12 sources of
payment; IPDXP08X is the sum of the 12 sources of payments; and IPDTC08X is the
physician’s total charge.
Data users/analysts need to take into consideration
whether to analyze facility and SBD expenditures separately, combine them within
service categories, or collapse them across service categories (e.g., combine
SBD expenditures with expenditures for physician visits to offices and/or
outpatient departments).
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2.5.5.10.3 Total Expenditures and Charges for Hospital
Inpatient Stays (IPXP08X and IPTC08X)
Data users/analysts interested in total expenditures
should use the variable IPXP08X, which includes both facility and physician
amounts. Those interested in total charges should use the variable IPTC08X,
which includes both facility and physician charges (see Section 2.5.5.1 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 2008
Person-Level Use and Expenditure File were rounded to the nearest dollar. It
should be noted that using the MEPS 2008 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 2008 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 2008 Appendix File, HC-118I, for details on such rounding differences.
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3.0 Sample Weight (PERWT08F)
3.1 Overview
There is a single full year person-level weight
(PERWT08F) 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 2008. A
key person either was a member of an NHIS household at the time of the NHIS
interview, or became a member of a family associated with such a household after
being out-of-scope at the time of the NHIS (the latter circumstance includes
newborns as well as 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 PERWT08F was developed in
several stages. Person-level weights for Panels 12 and 13 were created
separately. The weighting process for each panel included an adjustment for
nonresponse over time and calibration to independent population figures. The
calibration was initially accomplished separately for each panel by raking the
corresponding sample weights to Current Population Survey (CPS) population
estimates based on five variables. The five variables used in the establishment
of the initial person-level control figures were: census region (Northeast,
Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic,
non-Hispanic with black as sole reported race, non-Hispanic with Asian as sole
reported race, and other); sex; and age. A 2008
composite weight was then formed by multiplying each weight from Panel 12 by the
factor .39 and each weight from Panel 13 by the factor .61. The choice of
factors reflected the relative sample sizes of the two panels, helping to limit
the variance of estimates obtained from pooling the two samples. The composite
weight was again raked to the same set of CPS-based control totals. When poverty
status information derived from income variables became available, a final
raking was undertaken on the previously established weight variable. Control
totals were established using poverty status (five categories: below poverty,
from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200
to 400 percent of poverty, at least 400 percent of poverty) as well as the
original five variables used in the previous calibrations.
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3.2.1 MEPS Panel 12 Weight
The person-level weight for MEPS Panel 12 was
developed using the 2007 full year weight for an individual as a "base" weight
for survey participants present in 2007. For key, in-scope respondents who
joined an RU some time in 2008 after being out-of-scope in 2007, the 2007 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 raking to population control figures for December 2008. These control
figures were derived by scaling back the population totals obtained from the
March 2009 CPS to correspond to a national estimate for the civilian
noninstitutionalized population provided by the Census Bureau for December 2008.
Variables used in the establishment of person-level control figures included:
census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA);
race/ethnicity (Hispanic, black but non-Hispanic, Asian but non-Hispanic,
and other); sex; and age. Key, responding persons not in-scope on
December 31, 2008 but in-scope earlier in the year retained, as their final
Panel 12 weight, the weight after the nonresponse adjustment.
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3.2.2 MEPS Panel 13 Weight
The person-level weight for MEPS Panel 13 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 2008 portion of Round 3 as well as raking
to the same population control figures for December 2008 used for the MEPS Panel
12 weights. The same five variables employed for Panel 12 raking (census region,
MSA status, race/ethnicity, sex, and age) were used for Panel 13 raking.
Similarly, for Panel 13, key, responding persons not in-scope on December 31,
2008 but in-scope earlier in the year retained, as their final Panel 13 weight,
the weight after the nonresponse adjustment.
Note that the MEPS Round 1 weights 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 CPS data base of the corresponding year
(i.e., 2007 for Panel 12 and 2008 for Panel 13).
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3.2.3 The Final Weight for 2008
The composite weights of two groups of persons who
were out-of-scope on December 31, 2008 were poststratified. Specifically, the
weights of those who were in-scope some time during the year, out-of-scope on
December 31, and entered a nursing home during the year were poststratified to a
corresponding control total obtained from the 1996 MEPS Nursing Home Component.
Those who died while in-scope during 2008 were poststratified to corresponding
estimates derived using data obtained from the Medicare Current Beneficiary
Survey (MCBS) and Vital Statistics information provided by the National Center
for Health Statistics (NCHS). Separate decedent control totals were developed
for the "65 and older" and "under 65" civilian noninstitutionalized populations.
The sum of the person-level weights across all persons assigned a positive
person level weight is 304,375,942.
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3.2.4 Additional Adjustment to 2008 Person Weights for
Persons Age 65 and Over
In developing the final 2008 person-level weights
(PERWT08F), an adjustment was made at the end of the process to mitigate a
noticeable decline in the proportion of elderly persons with at least one
hospital stay based on the weight derived using the traditional MEPS weighting
methodology. This decline is inconsistent with trends in MEPS and other data
sources and the underlying explanation is under investigation. A ratio
adjustment strategy was applied only to weights for persons age 65 and over
(3,493 persons) and therefore it did not affect the weights for persons under
age 65 (29,573 persons). Moreover, the adjustments were carried out by MSA
status based on a logistic regression analysis that showed inconsistent changes
from 2007 to 2008 in the likelihood of hospitalization for MSA residents versus
non-MSA residents. The table below shows the derivations of the adjustment
factors that were applied (total of 4 factors) to the previously described final
weights.
Ratio Adjustment Factors Applied to Analytic Weight
Variable for Persons Age 65 and older
# of Hospital Stays (IPDIS08) |
MSA Resident |
Non-MSA Resident |
0 |
.808/.845 = 0.9562 |
.808/.780 = 1.0359 |
1 or more |
.192/.155 = 1.2387 |
.192/.220 = 0.8727 |
Within each of the 2 MSA subgroups, separate factors
were developed for persons with no hospital stays and for persons with at least
one stay. The numerators are based on MEPS annual averages of the proportion of
elderly persons with at least one hospital stay for the preceding 3 year period
(2005-07) and can be regarded as control proportions. The denominators of the
factors reflect estimated proportions based on the traditional final weight. For
MSA residents, applying these factors to the weights had the joint effect of
inflating the estimated proportion of elderly persons with at least one hospital
stay while proportionately deflating the proportion with no stays. For non-MSA
residents, applying these factors to the weights had the joint effect of
deflating the estimated proportion of elderly persons with at least one hospital
stay while proportionately inflating the proportion with no stays.
Finally, the weights for the elderly were adjusted by
a constant factor to compensate for the negligible impact of rounding on the
aggregate weights that resulted from applying the factors in the table above.
This factor was derived as the ratio of the sum of weights prior to applying the
factors to the sum after applying the factors (39,742,176 / 39,737,780).
Overall, the weighted population estimate for the
civilian noninstitutionalized population for December 31, 2008 is 300,257,026
(PERWT08F>0 and INSC1231=1). The sum of the person-level weights across all
persons assigned a positive weight is 304,375,942.
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3.2.5 Coverage
The target population for MEPS in this file is the
2008 U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2006 (Panel 12)
and 2007 (Panel 13). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2006 (Panel 12) or after 2007 (Panel 13) are not covered by
MEPS. Neither are previously out-of-scope persons who join an existing household
but are unrelated to the current household residents. Persons not covered by a
given MEPS panel thus include some members of the following groups: immigrants;
persons leaving the military; U.S. citizens returning from residence in another
country; and persons leaving institutions. The set of uncovered persons
constitutes only a small segment of the MEPS target population.
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3.3 Using MEPS Data for Trend Analysis
MEPS began in 1996, and the utility of the survey for
analyzing health care trends expands with each additional year of data. However,
it is important to consider a variety of factors when examining trends over time
using MEPS. Statistical significance tests should be conducted to assess the
likelihood that observed trends may be attributable to sampling variation. The
length of time being analyzed should also be considered. In particular, large
shifts in survey estimates over short periods of time (e.g. from one year to the
next) that are statistically significant should be interpreted with caution,
unless they are attributable to known factors such as changes in public policy,
economic conditions, or MEPS survey methodology. Looking at changes over longer
periods of time can provide a more complete picture of underlying trends.
Analysts may wish to consider using techniques to smooth or stabilize analyses
of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97
versus 2004-05), working with moving averages, or using modeling techniques with
several consecutive years of MEPS data to test the fit of specified patterns
over time. Finally, researchers should be aware of the impact of multiple
comparisons on Type I error. Without making appropriate allowance for multiple
comparisons, undertaking numerous statistical significance tests of trends
increases the likelihood of concluding that a change has taken place when one
has not.
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4.0 Strategies for Estimation
4.1 Developing Event-Level Estimates
The data in this file can be used to develop national
2008 event level estimates for the U.S. civilian noninstitutionalized population
on inpatient hospital stays as well as expenditures, and sources of payment for
these stays. Estimates of total stays are the sum of the weight variable
(PERWT08F) across relevant event records while estimates of other variables must
be weighted by PERWT08F to be nationally representative. The tables below
contain event-level estimates for selected variables.
Selected Event Level Estimates
Hospital Stays
Estimate of Interest |
Variable
Name |
Estimate
(SE) |
Estimate
Excluding Zero
Payment Events
(SE)* |
Total number of inpatient
hospital stays (in millions) |
PERWT08F |
29.1 (1.17) |
28.5 (1.17) |
Total number of nights in hospital
across all stays (in millions) |
NUMNIGHX |
151.8 (8.47) |
148.8 (8.33) |
Average number of nights per stay |
NUMNIGHX |
5.2 (0.21) |
5.2 (0.21) |
Average number of nights per stay
(NUMNIGHX > 0) |
NUMNIGHX |
5.4 (0.21) |
5.4 (0.21) |
Hospital Expenditures
Estimate of Interest |
Variable
Name |
Estimate
(SE) |
Estimate
Excluding Zero
Payment Events
(SE)* |
Mean total payments per stay |
IPXP08X |
$11,349 ($427.4) |
$11,576 ($431.9) |
Mean out-of-pocket payment
per stay |
IPDSF08X
+IPFSF08X |
$313 ($22.1) |
$319 ($22.6) |
Mean proportion of total
expenditures per stay paid by
private insurance |
(IPDPV08X+
IPFPV08X)
/IPXP08X |
---------- |
0.356 (0.0144) |
Mean total payments per night
(NUMNIGHX > 0) |
IPXP08X/
NUMNIGHX |
$3,510 ($122.3) |
$3,577 ($122.1) |
* Zero payment events can occur in MEPS for the
following reasons: (1) the stay was covered under a flat fee arrangement (flat
fee payments are included only on the first event covered by the arrangement),
(2) there was no charge for a follow-up stay, (3) the provider was never paid by
an individual, insurance plan, or other source for services provided, (4)
charges were included in another bill, or (5) the event was paid for through
government or privately-funded research or clinical trials.
Return To Table Of Contents
4.2 Person-Based Estimates for Hospital Inpatient Stays
To enhance analyses of hospital inpatient stays,
analysts may link information about inpatient stays by sample persons in this
file to the annual full year consolidated file (which has data for all MEPS
sample persons), or conversely, link person-level information from the full year
consolidated file to this event level file (see Section 5 below for more
details). Both this file and the full year consolidated file may be used to
derive estimates for persons with hospital inpatient care and annual estimates
of total expenditures. However, if the estimate relates to the entire
population, this file cannot be used to calculate the denominator, as only those
persons with at least one inpatient event are represented on this data file.
Therefore, the full year consolidated file must be used for person-level
analyses that include both persons with and without inpatient care.
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4.3 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 2.5.5.
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4.4 Variance Estimation (VARSTR, VARPSU)
MEPS has a complex sample design. To obtain estimates
of variability (such as the standard error of sample estimates or corresponding
confidence intervals) for MEPS estimates, analysts need to take into account the
complex sample design of MEPS for both person-level and family-level analyses.
Several methodologies have been developed for estimating standard errors for
surveys with a complex sample design, including the Taylor-series linearization
method, balanced repeated replication, and jackknife replication. Various
software packages provide analysts with the capability of implementing these
methodologies. Replicate weights have not been developed for the MEPS data.
Instead, the variables needed to calculate appropriate standard errors based on
the Taylor-series linearization method are included on this file as well as all
other MEPS public use files. Software packages that permit the use of the
Taylor-series linearization method include SUDAAN, Stata, SAS (version 8.2 and
higher), and SPSS (version 12.0 and higher). For complete information on the
capabilities of each package, analysts should refer to the corresponding
software user documentation.
Using the Taylor-series linearization method, variance
estimation strata and the variance estimation PSUs within these strata must be
specified. The variance strata variable is named VARSTR, while the variance PSU
variable is named VARPSU. Specifying a "with replacement" design in a computer
software package, such as SUDAAN, provides 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), one can expect at least 100 degrees of
freedom for the 2008 full year data associated with the corresponding estimates
of variance and usually substantially more.
Prior to 2002, MEPS variance strata and PSUs were
developed independently from year to year, and the last two characters of the
strata and PSU variable names denoted the year. However, beginning with the 2002
Point-in-Time PUF, the variance strata and PSUs were developed to be compatible
with MEPS data associated with the NHIS sample design used through 2005.
As a result of the change in the NHIS sample design in
2006, a new set of variance strata and PSUs have been established for variance
estimation purposes for use with MEPS Panel 12 and subsequent MEPS panels. There
were 165 variance strata associated with both MEPS Panel 12 and Panel 13,
providing a substantial number of degrees of freedom for subgroups as well as
the nation as a whole. Each variance stratum contains either two or three
variance estimation PSUs.
Return To Table Of Contents
5.0 Merging/Linking MEPS Data Files
Data from this file can be used alone or in
conjunction with other files for different analytic purposes. This section
summarizes various scenarios for merging/linking MEPS event files. The set of
households selected for MEPS is a subsample of those participating in the
National Health Interview Survey (NHIS), thus, each MEPS panel can also be
linked back to the previous year’s NHIS public use data files. For information
on obtaining MEPS/NHIS link files please see
www.meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
Return To Table Of Contents
5.1 Linking to the Person-Level File
Merging characteristics of interest from other MEPS
files (e.g., MEPS 2008 Full-Year Consolidated File) expands the scope of
potential estimates. For example, to estimate the total number of hospital
inpatient stays for persons with specific demographic characteristics (such as,
age, race, sex, and education), population characteristics from a person-level
file need to be merged onto the hospital inpatient stays file. This procedure is
illustrated below. The MEPS 2008 Appendix File, HC-118I, provides additional
detail on how to merge MEPS data files.
- Create data set PERSX by sorting the MEPS 2008 Full Year Consolidated
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 STAZ (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
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5.2 Linking to the Prescribed Medicines File
The RXLK file provides a link from the MEPS event
files to the Prescribed Medicine Event File. When using RXLK, data
users/analysts should keep in mind that one inpatient stay can link to more than
one prescribed medicine record. Conversely, a prescribed medicine event may link
to more than one inpatient stay visit 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. For
detailed linking examples, including SAS code, data users/analysts should refer
to the MEPS 2008 Appendix File, HC-118I.
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5.3 Linking to the Medical Conditions File
The CLNK provides a link from MEPS event files to the
2008 Medical Conditions File. When using the CLNK, data users/analysts should
keep in mind that (1) conditions are self-reported, (2) there may be multiple
conditions associated with a hospital inpatient stay, and (3) a condition may
link to more than one hospital inpatient stay or any other type of visit. Data
users/analysts should also note that not all hospital inpatient stays link to
the medical conditions file.
Return To Table Of Contents
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. (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).
Ezzati-Rice, T.M., Rohde, F., Greenblatt, J., Sample
Design of the Medical Expenditure Panel Survey Household Component, 1998–2007.
Methodology Report No. 22. March 2008. Agency for Healthcare Research and
Quality, Rockville, MD.
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.
Ezzati-Rice, T.M., Rohde, F., Greenblatt, J., Sample
Design of the Medical Expenditure Panel Survey Household Component, 1998–2007.
Methodology Report No. 22. March 2008. Agency for Healthcare Research and Quality,
Rockville, MD.
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-118D: 2008 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 |
PANEL |
Panel Number |
Constructed |
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 |
DLVRTYPE |
Vaginal or Caesarean delivery |
HS06A |
EPIDURAL |
Receive an epidural or spinal for pain |
HS06B |
ANYOPER |
Any operations or surgeries performed |
HS06 |
IPICD1X |
3 digit ICD-9-CM condition code |
Edited |
IPICD2X |
3 digit ICD-9-CM condition code |
Edited |
IPICD3X |
3 digit ICD-9-CM condition code |
Edited |
IPICD4X |
3 digit ICD-9-CM condition code |
Edited |
IPPRO1X |
2 digit ICD-9-CM procedure code |
Edited |
IPPRO2X |
2 digit ICD-9-CM 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 |
Return To Table Of Contents
Flat Fee Variables
Variable |
Description |
Source |
FFIPTYPE |
Flat Fee Bundle |
Constructed |
FFBEF08 |
Total # of visits in FF before 2008 |
FF05 |
FFTOT09 |
Total # of visits in FF after 2008 |
FF10 |
Return To Table Of Contents
Imputed Total Expenditure Variables
Variable |
Description |
Source |
IPXP08X |
Total expenditure for event (IPFXP08X+IPDXP08X) |
Constructed |
IPTC08X |
Total charge for event (IPFTC08X+IPDTC08X) |
Constructed |
Return To Table Of Contents
Imputed Facility Expenditure Variables
Variable |
Description |
Source |
IPFSF08X |
Facility amount paid, self/family (Imputed) |
CP Section (Edited) |
IPFMR08X |
Facility amount paid, Medicare (Imputed) |
CP Section (Edited) |
IPFMD08X |
Facility amount paid, Medicaid (Imputed) |
CP Section (Edited) |
IPFPV08X |
Facility amount paid, private insurance (Imputed) |
CP Section (Edited) |
IPFVA08X |
Facility amount paid, Veterans/CHAMPVA (Imputed) |
CP Section (Edited) |
IPFTR08X |
Facility amount paid, TRICARE (Imputed) |
CP Section (Edited) |
IPFOF08X |
Facility amount paid, other federal (Imputed) |
CP Section (Edited) |
IPFSL08X |
Facility amount paid state & local government (Imputed) |
CP Section (Edited) |
IPFWC08X |
Facility amount paid, workers’ compensation (Imputed) |
CP Section (Edited) |
IPFOR08X |
Facility amount paid, other private (Imputed) |
Constructed |
IPFOU08X |
Facility amount paid, other pub (Imputed) |
Constructed |
IPFOT08X |
Facility amount paid, other insurance (Imputed) |
CP Section (Edited) |
IPFXP08X |
Facility sum payments IPFSF08X – IPFOT08X |
Constructed |
IPFTC08X |
Total facility charge (Imputed) |
CP Section (Edited) |
Return To Table Of Contents
Imputed Separately Billing Physician Expenditure Variables
Variable |
Description |
Source |
IPDSF08X |
Doctor amount paid, family (Imputed) |
Constructed |
IPDMR08X |
Doctor amount paid, Medicare (Imputed) |
Constructed |
IPDMD08X |
Doctor amount paid, Medicaid (Imputed) |
Constructed |
IPDPV08X |
Doctor amount paid, private insurance (Imputed) |
Constructed |
IPDVA08X |
Doctor amount paid, Veterans/CHAMPVA (Imputed) |
Constructed |
IPDTR08X |
Doctor amount paid, TRICARE (Imputed) |
Constructed |
IPDOF08X |
Doctor amount paid, other federal (Imputed) |
Constructed |
IPDSL087X |
Doctor amount paid, state & local government (Imputed) |
Constructed |
IPDWC08X |
Doctor amount paid, workers’ compensation (Imputed) |
Constructed |
IPDOR08X |
Doctor amount paid, other private insurance (Imputed) |
Constructed |
IPDOU08X |
Doctor amount paid, other public insurance (Imputed) |
Constructed |
IPDOT08X |
Doctor amount paid, other insurance (Imputed) |
Constructed |
IPDXP08X |
Doctor sum payments IPDSF08X–IPDOT08X |
Constructed |
IPDTC08X |
Total doctor charge (Imputed) |
Constructed |
IMPFLAG |
Imputation status |
Constructed |
Return To Table Of Contents
Weights
Variable |
Description |
Source |
PERWT08F |
Expenditure file person weight, 2008 |
Constructed |
VARSTR |
Variance estimation stratum, 2008 |
Constructed |
VARPSU |
Variance estimation PSU, 2008 |
Constructed |
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