MEPS HC-094D: 2005 Hospital Inpatient Stays
October 2007
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-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,
FFBEF05, FFTOT06)
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 (FFBEF05, FFTOT06)
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 (IPFSF05X-IPFOT05X, IPFXP05X, IPFTC05X)
2.5.5.10.2 Hospital Inpatient
Physician Expenditures (IPDSF05X - IPDOT05X, IPDTC05X, IPDXP05X)
2.5.5.10.3 Total Expenditures and
Charges for Hospital Inpatient Stays (IPXP05X, IPTC05X)
2.5.5.11 Rounding
3.0 Sample Weight (PERWT05F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 9 Weight
3.2.2 MEPS Panel 10 Weight
3.2.3 The Final Weight for 2005
3.2.4 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
5.4 Pooling Annual Files
5.5 Longitudinal Analysis
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. MEPS oversamples additional policy relevant sub-groups
such as Asians and 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 2005 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 2005 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 2005. The file contains 68
variables and has a logical record length of 377 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 2005 portion of Round 3 and Rounds 4
and 5 for Panel 9, as well as Rounds 1, 2 and the 2005 portion of Round 3 for
Panel 10 (i.e., the rounds for the MEPS panels covering calendar year 2005).
Hospital stay events reported in Panel 10 Round 3 and
known to have begun after December 31, 2005 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.
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 2005
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 2005 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 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:
www.meps.ahrq.gov.
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2.0 Data File Information
The 2005 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 2005 STAZ public use data set contains variable and
frequency distributions for a total of 3,341 hospital inpatient stay records
reported during the 2005 portion of Round 3 and Rounds 4 and 5 for Panel 9, as
well as Rounds 1, 2, and the 2005 portion of Round 3 for Panel 10 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, 2005 or after December 31, 2005 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 3,341 hospital inpatient stay
records, 3,212 are associated with persons having a positive person-level weight
(PERWT05F). 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 2005. Stays
that began prior to 2005 but ended during 2005 are included on this data file.
Stays that began in 2005 but ended during 2006 are excluded from this data
file and will be included in a subsequent 2006 IP data file. Persons with no
hospital inpatient stay events for 2005 are not included on this event-level
IP file but are represented on the person-level 2005 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 2005 eligibility (i.e., persons
with a positive 2005 full-year person-level sampling weight (PERWT05F >
0)), or
- Be an eligible member of a family all of
whose key in-scope members have a positive person-level weight
(PERWT05F > 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 (FAMWT05F > 0). Note that FAMIDYR and
FAMWT05F are variables on the 2005 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.
Data from this file can be merged with the MEPS 2005 Full
Year Population Characteristics File using the 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 2005 Medical Conditions File and the MEPS 2005 Prescribed
Medicines File. Please see Section 5.0 or the MEPS 2005 Appendix File, HC-094I,
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. See the section on pooling annual files, 5.4, for
details.
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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 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:
- 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 |
OR - other private |
TR - TRICARE/CHAMPVA |
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 (05). The eighth character, "X",
indicates whether the variable is edited/imputed.
For example, IPFSF05X is the edited/imputed amount paid by
self or family for the facility portion of the hospital inpatient stay
expenditure incurred in 2005.
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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 2005 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 2005 Medical Conditions File and
MEPS 2005 Prescribed Medicines File, respectively). For details on linking, see
Section 5.0 or the MEPS 2005 Appendix File, HC-094I.
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 2005 STAZ file, there are 540
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 9. Likewise, Rounds 1, 2,
and 3 are associated with data collected from Panel 10.
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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 9
or Panel 10 for each person on the file. Panel 9 is the panel that started in
2004, and Panel 10 is the panel that started in 2005.
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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 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 2004 and ending in 2005, 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 2.5.1.2).
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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).
With respect to RSNINHOS, please note that while there
were 473 cases where RSNINHOS = 4 (reason entered hospital – to give birth to a
baby), this does not mean that there were actually 472 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 2005 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 reconciled with the ICD-9-CM
condition codes, the procedure codes, or the CCC codes that are on the file;
thus, there is a general inconsistency between reported reason in hospital and
reported conditions.
VAPLACE is a constructed variable that indicates whether
the service was provided 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 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 2005 Medical Conditions File. Details on how to link the 2005 STAZ file to
the MEPS 2005 Medical Conditions File are provided in Section 5.2 and the MEPS
2005 Appendix File, HC-094I. 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 2005 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
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 2005 Medical Conditions File. For frequencies
of conditions by event type, please see the MEPS 2005 Appendix File, HC-094I.
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 263 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 HC-096 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 2005 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-096) and the Appendix to the Event
Files (HC-094I) 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 2005 MEPS PUFs, these updates
will not be reflected in the 2005 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, FFBEF05, FFTOT06)
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 2005. 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 2005 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 2005 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 (FFBEF05, FFTOT06)
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 2005 as a part of
a group of events, and some event occurred before or after 2005, counts of the
known events are provided on the STAZ record. Variables that indicate events
occurred before or after 2005 are as follows:
FFBEF05 - total number of pre-2005 events in the same
flat fee group as the 2005 hospital inpatient stay(s). This count would not
include 2005 hospital inpatient stay(s). Because there were no 2004 events
for any flat fee group, this variable was omitted from the 2005 IP file.
FFTOT06 - the number of 2006 hospital inpatient stays
expected to be in the same flat fee group as the hospital inpatient stay
that occurred in 2005. Because there were no 2006 events expected for any
flat fee group, this variable was omitted from the 2005 IP file.
If there are no 2004 events on the file, FFBEF05 will be
omitted. Likewise, if there are no 2006 events on the file, FFTOT06 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 4 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 2005, but the remaining
visits that were part of this flat fee group occurred in 2006. In this case, the
2005 flat fee group would consist of one event, the stem. The 2006 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 2004 but subsequent visits occurred during 2005. In this case, the
initial visit would not be represented on the file. This 2005 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
CFACT data center. For more information, see the Data Center section of the MEPS
Web site www.meps.ahrq.gov.
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 2005,
all of the events that occurred in 2005 will have zero payments. Conversely, if
the first event in the flat fee group occurred at the end of 2005, the total
expenditure for the entire flat fee group will be on that event, regardless of
the number of events it covered after 2005. 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 2005 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 2005
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, excluding TRICARE/CHAMPVA,
- TRICARE/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, 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 (IPFSF05X-IPFOT05X, IPFXP05X, IPFTC05X)
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.
IPFSF05X - IPFOT05X are the 12 sources of payment. The 12
sources of payment are: self/family (IPFSF05X), Medicare (IPFMR05X), Medicaid
(IPFMD05X), private insurance (IPFPV05X), Veterans Administration (IPFVA05X),
TRICARE/CHAMPVA (IPFTR05X), other Federal sources (IPFOF05X), State and Local
(non-federal) government sources (IPFSL05X), Worker’s Compensation (IPFWC05X),
other private insurance (IPFOR05X), other public insurance (IPFOU05X), and other
insurance (IPFOT05X). IPFXP05X is the sum of the 12 sources of payment for the
Hospital Facility expenditures, and IPFTC05X 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 (IPDSF05X - IPDOT05X, IPDTC05X, IPDXP05X)
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. IPDSF05X - IPDOT05X are the 12 sources of
payment; IPDXP05X is the sum of the 12 sources of payments; and IPDTC05X 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 (IPXP05X and
IPTC05X)
Data users/analysts interested in total expenditures
should use the variable IPXP05X, which includes both facility and physician
amounts. Those interested in total charges should use the variable IPTC05X,
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 2005
Person-Level Use and Expenditure File were rounded to the nearest dollar. It
should be noted that using the MEPS 2005 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 2005 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 2005 Appendix File, HC-094I, for details on such rounding differences.
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3.0 Sample Weight (PERWT05F)
3.1 Overview
There is a single full year person-level weight (PERWT05F)
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 2005. 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 PERWT05F was developed in several
stages. Person-level weights for Panels 9 and 10 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 2005 composite weight was then formed by multiplying
each weight from Panel 9 by the factor .5 and each weight from Panel 10 by the
factor .5. 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 9 Weight
The person-level weight for MEPS Panel 9 was developed
using the 2004 full year weight for an individual as a "base" weight for survey
participants present in 2004. For key, in-scope respondents who joined an RU
some time in 2005 after being out-of-scope in 2004, the 2004 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 2005. These control
figures were derived by scaling back the population totals obtained from the
March 2005 CPS to correspond to a national estimate for the civilian
noninstitutionalized population provided by the Census Bureau for December 2005.
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. Overall, the weighted population estimate for the civilian
noninstitutionalized population on December 31, 2005 is 292,372,718. Key,
responding persons not in-scope on December 31, 2005 but in-scope earlier in the
year retained, as their final Panel 9 weight, the weight after the nonresponse
adjustment.
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3.2.2 MEPS Panel 10 Weight
The person-level weight for MEPS Panel 10 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 2005 portion of Round 3 as well as raking to the same
population control figures for December 2005 used for the MEPS Panel 9 weights.
The same five variables employed for Panel 9 raking (census region, MSA status,
race/ethnicity, sex, and age) were used for Panel 10 raking. Similarly, for
Panel 10, key, responding persons not in-scope on December 31, 2005 but in-scope
earlier in the year retained, as their final Panel 10 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 2005 CPS data base.
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3.2.3 The Final Weight for 2005
Variables used in the establishment of person-level
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, non-Hispanic
with black as sole reported race, non-Hispanic with Asian as sole reported race,
and other); sex; and age. Overall, the weighted population estimate for the
civilian noninstitutionalized population for December 31, 2005 is 292,372,718
(PERWT05F>0 and INSC1231=1). The weights of some persons out-of-scope on
December 31, 2005 were also calibrated, this time using poststratification.
Specifically, the weights of persons out-of-scope on December 31, 2005 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 2005 were poststratified to corresponding estimates derived using data
obtained from the Medicare Current Beneficiary Survey (MCBS) and Vital
Statistics information provided by the National Center for Health Statistics (NCHS).
Separate control totals were developed for the "65 and older" and "under 65"
civilian noninstitutionalized populations. The sum of the person-level weights
across all persons assigned a positive person level weight is 292,372,718.
Return to Table of Contents
3.2.4 Coverage
The target population for MEPS in this file is the 2005
U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2003 (Panel 9)
and 2004 (Panel 10). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2003 (Panel 9) or after 2004 (Panel 10) 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.
Return to Table of Contents
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 inappropriately concluding that a change has taken
place.
Return to Table of Contents
4.0 Strategies for
Estimation
4.1 Developing Event-Level
Estimates
The data in this file can be used to develop national 2005
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
(PERWT04F) across relevant event records while estimates of other variables must
be weighted by PERWT04F 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 (SE)
Excluding 0's* |
Total number of inpatient hospital stays (in millions) |
PERWT05F |
29.5 (1.03) |
29.2 (1.02) |
Total number of nights in hospital
across all stays (in millions) |
NUMNIGHX |
160.6 (8.81) |
159.3 (8.78) |
Average number of nights per stay |
NUMNIGHX |
5.4 (0.21) |
5.5 (0.21) |
Hospital Expenditures
Estimate of Interest |
Variable
Name |
Estimate (SE) |
Estimate (SE)
Excluding 0's* |
Mean total payments per stay |
IPxp05x |
$10,725 ($372.9) |
$10,846 ($375.8) |
Mean out-of-pocket payment per stay |
IPDsf05x
+IPFSF05X |
$406 ($71.6) |
$411 ($72.5) |
Mean proportion of total expenditures
per stay paid by private insurance |
(IPDpv05x+
IPFPV05X)
/IPxp05x |
------- |
0.372 (0.0145) |
Mean total payments per night
(NUMNIGHX > 0) |
IPxp05x/
NUMNIGHX |
$3,200 ($103.4) |
$3,232 ($102.8) |
* 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.
Return to Table of Contents
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.
Return to Table of Contents
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 2005 full year data associated with the corresponding estimates
of variance.
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. Such
data can be pooled and the variance strata and PSU variables provided can be
used without modification for variance estimation purposes for estimates
covering multiple years of data. There are 203 variance estimation strata, each
stratum with either two or three variance estimation PSUs.
Note: A new NHIS sample design is being implemented
beginning in 2006. As a result, the MEPS variance estimation structure will be
modified for MEPS data collected in 2007 and beyond.
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. Each
MEPS panel can also be linked back to the previous years National Health
Interview Survey public use data files. For information on obtaining MEPS/NHIS
link files please see
Return to Table of Contents
5.1 Linking to the Person-Level File
Merging characteristics of interest from other MEPS files
(e.g., MEPS 2005 Full-Year Population Characteristics 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
2005 Appendix File, HC-094I, provides additional detail on how to merge MEPS
data files.
Create data set PERSX by sorting the MEPS 2005 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 STAZ (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
Return to Table of Contents
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 2005 Appendix File, HC-094I.
Return to Table of Contents
5.3 Linking to the Medical
Conditions File
The CLNK provides a link from MEPS event files to the 2005
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
5.4 Pooling Annual Files
To facilitate analysis of subpopulations and/or low
prevalence events, it may be desirable to pool together more than one year of
data to yield sample sizes large enough to generate reliable estimates.
For more details on pooling MEPS data files see
www.meps.ahrq.gov/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036.
Starting in Panel 9, values for DUPERSID from previous
panels will occasionally be re-used. Therefore, it is necessary to use the panel
variable (PANEL) in combination with DUPERSID to ensure unique person-level
identifiers across panels. Creating unique records in this manner is advised
when pooling MEPS data across multiple annual files that have one or more
identical values for DUPERSID.
Return to Table of Contents
5.5 Longitudinal Analysis
MEPS Panel Longitudinal Weight files containing estimation
variables to facilitate longitudinal analysis are available for downloading in
the data section of the MEPS Web site.
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. (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.
Return to Table of Contents
D. VARIABLE-SOURCE CROSSWALK
VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-094D: 2005 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 |
Return to Table of Contents
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 |
VAPLACE |
VA facility flag |
Constructed |
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 |
FFBEF05 |
Total # of visits in FF before 2005 |
FF05 |
FFTOT06 |
Total # of visits in FF after 2005 |
FF10 |
Return to Table of Contents
Imputed Total Expenditure Variables
Variable |
Description |
Source |
IPXP05X |
Total expenditure for event (IPFXP05X+IPDXP05X) |
Constructed |
IPTC05X |
Total charge for event (IPFTC05X+IPDTC05X) |
Constructed |
Return to Table of Contents
Imputed Facility Expenditure Variables
Variable |
Description |
Source |
IPFSF05X |
Facility amount paid, self/family (Imputed) |
CP Section (Edited) |
IPFMR05X |
Facility amount paid, Medicare (Imputed) |
CP Section (Edited) |
IPFMD05X |
Facility amount paid, Medicaid (Imputed) |
CP Section (Edited) |
IPFPV05X |
Facility amount paid, private insurance (Imputed) |
CP Section (Edited) |
IPFVA05X |
Facility amount paid, Veterans Administration (Imputed) |
CP Section (Edited) |
IPFTR05X |
Facility amount paid, TRICARE/CHAMPVA (Imputed) |
CP Section (Edited) |
IPFOF05X |
Facility amount paid, other federal (Imputed) |
CP Section (Edited) |
IPFSL05X |
Facility amount paid state & local
government (Imputed) |
CP Section (Edited) |
IPFWC05X |
Facility amount paid, workers’ compensation
(Imputed) |
CP Section (Edited) |
IPFOR05X |
Facility amount paid, other private (Imputed) |
Constructed |
IPFOU05X |
Facility amount paid, other pub (Imputed) |
Constructed |
IPFOT05X |
Facility amount paid, other insurance (Imputed) |
CP Section (Edited) |
IPFXP05X |
Facility sum payments IPFSF05X – IPFOT05X |
Constructed |
IPFTC05X |
Total facility charge (Imputed) |
CP Section (Edited) |
Return to Table of Contents
Imputed Separately Billing Physician
Expenditure Variables
Variable |
Description |
Source |
IPDSF05X |
Doctor amount paid, family (Imputed) |
Constructed |
IPDMR05X |
Doctor amount paid, Medicare (Imputed) |
Constructed |
IPDMD05X |
Doctor amount paid, Medicaid (Imputed) |
Constructed |
IPDPV05X |
Doctor amount paid, private insurance (Imputed) |
Constructed |
IPDVA05X |
Doctor amount paid, Veterans Administration (Imputed) |
Constructed |
IPDTR05X |
Doctor amount paid, TRICARE/CHAMPVA (Imputed) |
Constructed |
IPDOF05X |
Doctor amount paid, other federal (Imputed) |
Constructed |
IPDSL05X |
Doctor amount paid, state & local
government (Imputed) |
Constructed |
IPDWC05X |
Doctor amount paid, workers’ compensation
(Imputed) |
Constructed |
IPDOR05X |
Doctor amount paid, other private insurance (Imputed) |
Constructed |
IPDOU05X |
Doctor amount paid, other public insurance (Imputed) |
Constructed |
IPDOT05X |
Doctor amount paid, other insurance (Imputed) |
Constructed |
IPDXP05X |
Doctor sum payments IPDSF05X–IPDOT05X |
Constructed |
IPDTC05X |
Total doctor charge (Imputed) |
Constructed |
IMPFLAG |
Imputation status |
Constructed |
Return to Table of Contents
Weights
Variable |
Description |
Source |
PERWT05F |
Expenditure file person weight, 2005 |
Constructed |
VARSTR |
Variance estimation stratum, 2005 |
Constructed |
VARPSU |
Variance estimation PSU, 2005 |
Constructed |
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