MEPS HC-102G: 2006 Office-Based Medical Provider Visits
September 2008
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, FFEEIDX)
2.5.1.3 Round Indicator (EVENTRN)
2.5.1.4 Panel Indicator (PANEL)
2.5.2 MPC Indicator (MPCELIG, MPCDATA)
2.5.3 Office-Based Medical Provider Visit Variables
2.5.3.1 Date of Visit (OBDATEYR - OBDATEDD)
2.5.3.2 Visit Details (SEETLKPV-VSTRELCN)
2.5.3.3 Treatments, Procedures, Services, and Prescription Medicines (PHYSTH-MEDPRESC)
2.5.3.4 VA Facility (VAPLACE)
2.5.4 Condition and Procedure Codes (OBICD1X-OBICD4X, OBPRO1X – OBPRO3X), and Clinical Classification Codes (OBCCC1X-OBCCC4X)
2.5.5 Flat Fee Variables (FFEEIDX, FFOBTYPE, FFBEF06, FFTOT07)
2.5.5.1 Definition of Flat Fee Payments
2.5.5.2 Flat Fee Variable Descriptions
2.5.5.2.1 Flat Fee ID (FFEEIDX)
2.5.5.2.2 Flat Fee Type (FFOBTYPE)
2.5.5.2.3 Counts of Flat Fee Events that Cross Years (FFBEF06, FFTOT07)
2.5.5.3 Caveats of Flat Fee Groups
2.5.6 Expenditure Data
2.5.6.1 Definition of Expenditures
2.5.6.2 Data Editing and Imputation Methodologies of Expenditure Variables
2.5.6.2.1 General Data Editing Methodology
2.5.6.2.2 General Hot-Deck Imputation
2.5.6.2.3 Office-Based Provider Visit Data Editing and Imputation
2.5.6.3 Capitation Imputation
2.5.6.4 Imputation Flag (IMPFLAG)
2.5.6.5 Flat Fee Expenditures
2.5.6.6 Zero Expenditures
2.5.6.7 Discount Adjustment Factor
2.5.6.8 Sources of Payment
2.5.6.9 Office-Based Expenditure Variables (OBSF06X - OBTC06X)
2.5.7 Rounding
3.0 Sample Weight (PERWT06F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 10 Weight
3.2.2 MEPS Panel 11 Weight
3.2.3 The Final Weight for 2006
3.2.4 Coverage
3.3 Using MEPS Data for Trend and Longitudinal Analysis
4.0 Strategies for Estimation
4.1 Developing Event-Level Estimates
4.2 Person-Based Estimates for Office-Based Visits
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 2006 Medical Expenditure Panel Survey (MEPS) Household (HC)
and Medical Provider Components (MPC). Released as an ASCII data file (with
related SAS and SPSS programming statements) and a SAS transport file, the 2006
Office-Based Medical Provider Visits public use event file provides detailed
information on office-based provider visits for a nationally representative
sample of the civilian noninstitutionalized population of the United States.
Data from the office-based provider events file can be used to make estimates of
office-based provider utilization and expenditures for calendar year 2006. The
file contains 76 variables and has a logical record length of 276 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 2006 portion
of Round 3 and Rounds 4 and 5 for Panel 10, as well as Rounds 1, 2 and the 2006
portion of Round 3 for Panel 11 (i.e., the rounds for the MEPS panels covering
calendar year 2006).
Each record on this event file represents a unique
office-based provider event; that is, an office-based provider event reported by
the household respondent. Office-based events reported in Panel 11 Round 3 and
known to have occurred after December 31, 2006 are not included on this file.
Utilization counts of office-based provider visits are based entirely on
household reports. Information from the MPC is used to supplement expenditure
payment data on the office-based provider file, reported by the household,
and does not affect use estimates.
Data from this event file can be merged with other 2006
MEPS HC data files for purposes of appending person-level data such as
demographic characteristics or health insurance coverage to each office-based
provider visit record on the current file.
This file can also be used to construct summary variables
of expenditures, sources of payment, and related aspects of office-based
provider visits for calendar year 2006. Aggregate annual person-level
information on the use of office-based providers and other health services use
is provided on the MEPS 2006 Full Year Consolidated Data File, where each record
represents a MEPS sampled person.
This documentation offers a brief overview of the types
and levels of data provided, and the content and structure of the files and the
codebook. It contains the following sections:
Data File Information
Sample Weights
Strategies for Estimation
Merging/linking MEPS Data Files
References
Variable-Source Crosswalk
For more information on MEPS HC survey design, see S.
Cohen, 1997; J. Cohen, 1997; and S. Cohen, 1996. A copy of the MEPS HC survey
instruments used to collect the information on the office-based provider file is
available on the MEPS Web site at the following address:
www.meps.ahrq.gov.
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2.0 Data File Information
The 2006 Office-Based Medical Provider public use data set
consists of one event-level data file. The file contains characteristics
associated with the OB event and imputed expenditure data.
The Office-Based Provider public use data set contains
155,502 office-based provider event records; of these records, 152,116 are
associated with persons having a positive person-level weight (PERWT06F). This
file includes office-based provider event records for all household survey
respondents who resided in eligible responding households and reported at least
one office-based provider event.
Each record represents one household-reported office-based
provider event that occurred during calendar year 2006. Office-based provider
visits known to have occurred after December 31, 2006 are not included on this
file. Some household respondents may have multiple events and thus will be
represented in multiple records on this file. Other household respondents may
have reported no events and thus will have no records on this file. These data
were collected during the 2006 portion of Round 3, and Rounds 4 and 5 for Panel
10, as well as Rounds 1, 2, and the 2006 portion of Round 3 for Panel 11 of the
MEPS Household Component. The persons represented on this file had to meet
either (a) or (b):
Be classified as a key in-scope person who
responded for his or her entire period of 2006 eligibility (i.e.,
persons with a positive 2006 full-year person-level weight (PERWT06F >
0)), or - Be an eligible member of a family all of whose
key in-scope members have a positive person-level weight (PERWT06F >
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 (FAMWT06F >0). Note that FAMIDYR and FAMWT06F are
variables on the 2006 Population Characteristics file.
Persons with no office-based medical provider visit events
for 2006 are not included on this event-level OB file but are represented on the
person-level 2006 Full Year Population Characteristics file.
Each office-based medical provider visit event record
includes the following: date of the event; type of provider seen; type of care
received; types of treatments (i.e., physical therapy, occupational therapy,
speech therapy, chemotherapy, radiation therapy, etc.) received during the
event; type of services (i.e., lab test, sonogram or ultrasound, x-rays, etc.)
received, medicines prescribed during the event; flat fee information; imputed
sources of payment; total payment and total charge of the office-based event
expenditure; a full-year person-level weight; variance strata; and variance PSU.
Data from this file can be merged with the MEPS 2006 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. The office-based medical provider visit events
can also be linked to the MEPS 2006 Medical Conditions File and MEPS 2006
Prescribed Medicines File. Please see Section 5.0 for details on how to
merge MEPS data files.
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2.1 Codebook Structure
For each variable on the office-based provider file, both
weighted and unweighted frequencies are provided in the accompanying codebook.
The codebook and data file sequence list variables in the following order:
Unique person identifiers
Unique office-based medical provider visit event identifiers
Office-based medical provider visit characteristic 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, 5.3, 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, values of -1, -7, -8, and -9 for
non-expenditure variables have not been edited on this file. The values of -1
and -9 can be edited by the data users/analysts by following the skip patterns
in the HC survey questionnaire (located on the MEPS Web site:
www.meps.ahrq.gov/survey_comp/survey_questionnaires.jsp).
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2.3 Codebook Format
The office-based medical provider visits codebook
describes an ASCII data set (although the data are also being provided in a SAS
transport file). The following codebook items are provided for each variable:
| Identifier |
Description |
| Name |
Variable name (maximum of 8 characters) |
Description |
Variable descriptor (maximum of 40 characters) |
| Format |
Number of bytes |
| Type |
Type of data: numeric (indicated by NUM) or character (indicated by CHAR) |
| Start |
Beginning column position of variable in record |
| End |
Ending column position of variable in record |
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2.4 Variable Source and Naming Conventions
In general, variable names reflect the
content of the variable, with an 8-character limitation. All imputed/edited
variables end with an "X".
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2.4.1 General
Variables contained on this file were derived from the HC
survey questionnaire itself, derived from the MPC data collection instrument,
derived from CAPI, or assigned in sampling. The source of each variable is
identified in Section D "Variable - Source Crosswalk" in one of four ways:
-
Variables derived from CAPI or assigned in sampling
are indicated as "CAPI derived" or "Assigned in sampling," respectively;
-
Variables which come from one or more specific
questions have those questionnaire sections and question numbers indicated
in the "Source" column; questionnaire sections are
identified as:
- MV - Office-Based Medical Provider Visits 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 seven characters in length, and end
in an "X" indicating edited/imputed. Please note that imputed means that a
series of logical edits, as well as an imputation process to account for missing
data, have been performed on the variable.
The total sum of payments and the 12 sources of payment
are named in the following way:
The first two characters indicate the type of event:
| IP - inpatient stay |
OB - office-based visit |
| ER - emergency room visit |
OP - outpatient visit |
| HH - home health visit |
DV - dental visit |
OM - other medical equipment |
RX - prescribed medicine |
In the case of source of payment variables, the third and
fourth characters indicate:
| SF - self or family |
OF - other Federal Government |
| MR - Medicare |
SL - State/local government |
| MD - Medicaid |
WC - Workers’ Compensation |
| PV - private insurance |
OT - other insurance |
VA - Veterans |
OR - other private |
TR - TRICARE/CHAMPVA |
OU - other public |
| |
XP - sum of payments |
In addition, the total charge variable is indicated by TC
in the variable name.
The fifth and sixth characters indicate the year (06). The
seventh character, "X", indicates whether the variable is edited/imputed.
For example, OBSF06X is the edited/imputed amount paid by
self or family for an office-based medical provider visit expenditure incurred
in 2006.
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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 2006 Full
Year Population Characteristics.
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2.5.1.2 Record Identifiers (EVNTIDX, FFEEIDX)
EVNTIDX uniquely identifies each office-based medical
provider visit event (i.e., each record on the office-based medical provider
visits file) and is the variable required for linking office-based medical
provider visit events to data files containing details on conditions and/or
prescribed medicines (MEPS 2006 Medical Condition file and MEPS 2006 Prescribed
Medicine file, respectively). For details on linking see Section 5.0 or the MEPS
2006 Appendix File, HC-102I.
FFEEIDX is a constructed variable that uniquely identifies
a flat fee group, that is, all events that were part of a flat fee payment. For
example, pregnancy is typically covered in a flat fee arrangement where the
prenatal visits, the delivery, and the postpartum visits are all covered under
one flat fee dollar amount. These events (the prenatal visit, the delivery, and
the postpartum visits) would have the same value for FFEEIDX. FFEEIDX identifies
a flat fee payment that was identified using information from the Household
Component. A "mixed" flat fee group could contain both outpatient and
office-based visits. Only outpatient and office-based events are allowed in a
mixed bundle. Please note that FFEEIDX should be used to link up the outpatient
and office-based events in order to determine the full set of events that are
part of a flat fee group.
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2.5.1.3 Round Indicator (EVENTRN)
EVENTRN indicates the round in which the office-based
event was reported. Please note that Rounds 3, 4, and 5 are associated with MEPS
survey data collected from Panel 10. Likewise, Rounds 1, 2, and 3 are associated
with data collected from Panel 11.
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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 10 or
Panel 11 for each person on the file. Panel 10 is the panel that started in
2005, and Panel 11 is the panel that started in 2006.
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2.5.2 MPC Indicator (MPCELIG, MPCDATA)
MPCELIG is a constructed variable that indicates whether
the office-based provider visit was eligible for MPC data collection. MPCDATA is
a constructed variable that indicates whether or not MPC data was collected for
the office-based provider.
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2.5.3 Office-Based Medical Provider Visit Variables
The file contains variables describing
office-based medical provider visit events reported by respondents in the
Medical Provider Visits section of the MEPS HC survey questionnaire.
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2.5.3.1 Date of Visit (OBDATEYR - OBDATEDD)
There are three variables that, together, indicate the
day, month, and year an office-based provider visit occurred (OBDATEDD, OBDATEMM,
OBDATEYR, respectively). These variables have not been edited or imputed.
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2.5.3.2 Visit Details (SEETLKPV-VSTRELCN)
The questionnaire determines if, during the office-based
medical provider visit, the person actually saw the provider or talked to the
provider on the telephone (SEETLKPV). Also, the questionnaire establishes the
kind of place the person saw the medical provider (MVPLACE). One of the answer
categories for the variable MVPLACE is "Laboratory/X-Ray Facility". The
importance of laboratory and x-ray events in relation to the creation of
office-based medical provider events is discussed above in Section 2.0. The
questionnaire also establishes whether the person saw or spoke to a
medical doctor (SEEDOC). If during the medical visit the patient did not see a
specialty doctor (DRSPLTY), or, if the person did not see a physician (i.e., a
medical doctor), the respondent was asked to identify the type of medical person
seen (MEDPTYPE). Whether or not any medical doctors worked at the visit location
(DOCATLOC), the type of care the person received (VSTCTGRY), and whether or not
the visit or telephone call was related to a specific condition (VSTRELCN) were
also determined.
Note that, in 2002, four new categories were added to the
imputation process (13 categories in total) as opposed to nine categories in
2001. These new categories are for alternative care ("Acupuncture", "Massage
Therapist", "Homeopathic/Naturopathic/Herbalist", and "Other
Alternative/Complementary Care Pro"). In 2001, these alternative care
categories, as indicated by the variable MEDPTYPE, were not available for all
rounds; therefore, records that indicated the medical provider type was
"Acupuncture", "Massage Therapist", "Homeopathic/Naturopathic/Herbalist", or
"Other Alternative/Complementary Care Pro" were included in the "Other" category
in the 2001 imputation process.
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2.5.3.3 Treatments, Procedures, Services, and Prescription Medicines (PHYSTH-MEDPRESC)
Types of treatments received during the office-based
medical provider visit include physical therapy (PHYSTH), occupational therapy (OCCUPTH),
speech therapy (SPEECHTH), chemotherapy (CHEMOTH), radiation therapy (RADIATTH),
kidney dialysis (KIDNEYD), IV therapy (IVTHER), drug or alcohol treatment (DRUGTRT),
allergy shots (RCVSHOT), psychotherapy/counseling (PSYCHOTH), and shots other
than allergy (OTHSHOT). Services received during the visit included whether or
not the person received lab tests (LABTEST), a sonogram or ultrasound
(SONOGRAM), x-rays (XRAYS), a mammogram (MAMMOG), an MRI or a CAT scan (MRI), an
electrocardiogram (EKG), an electroencephalogram (EEG), a vaccination (RCVVAC),
anesthesia (ANESTH), or other diagnostic tests or exams (OTHSVCE). Minimal
editing was done across treatment, services, and procedures to ensure
consistency across "inapplicable," "not ascertained," "don't know," "refused,"
and "no services received" values. Whether or not a surgical procedure was
performed during the visit was asked (SURGPROC). Finally, the questionnaire
determined if a medicine was prescribed for the person during the visit (MEDPRESC).
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2.5.3.4 VA Facility (VAPLACE)
VAPLACE is a constructed variable that indicates whether
the 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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2.5.4 Condition and Procedure Codes (OBICD1X-OBICD4X, OBPRO1X – OBPRO3X), and
Clinical Classification Codes (OBCCC1X-OBCCC4X)
Information on household-reported medical conditions and
procedures associated with each office-based medical provider visit is provided
on this file. There are up to four condition and CCS codes (OBICD1X-OBICD4X,
OBCCC1X-OBCCC4X) and up to three procedure codes (OBPRO1X – OBPRO3X) listed for
each office-based medical provider visit. In order to obtain complete condition
information associated with an event, the analyst must link to the Medical
Conditions File. Details on how to link to the MEPS Medical Conditions File are
provided in Section 5.0. The user should note that due to
confidentiality restrictions, provider-reported condition information is not
publicly available.
The medical conditions and procedures reported by the
Household Component respondent were recorded by the interviewer as verbatim
text, which were then coded to fully-specified 2006 ICD-9-CM codes, including
medical condition and V codes (see Health Care Financing Administration, 1980),
by professional coders. Although codes were verified and error rates did not
exceed 2.5 percent for any coder, data users/analysts should not presume this
level of precision in the data; the ability of household respondents to report
condition data that can be coded accurately should not be assumed (see Cox and
Cohen, 1985; Cox and Iachan, 1987; Edwards, et al, 1994; and Johnson and
Sanchez, 1993). For detailed information on how conditions and procedures were
coded, please refer to the documentation on the MEPS 2006 Medical Conditions
File. For frequencies of conditions by event type, please see the MEPS 2006
Appendix File, HC-102I.
The ICD-9-CM conditions were aggregated into clinically
meaningful categories. These categories, included on the file as
OBCCC1X-OBCCC4X, were generated using Clinical Classification Software [formerly
known as Clinical Classifications for Health Care Policy Research (CCHPR), (Elixhauser,
et al., 1998)], which aggregates conditions and V-codes into 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 3-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-104 documentation.
The condition codes (and clinical classification codes)
and procedure codes linked to each office-based medical provider visit event are
sequenced in the order in which the conditions were reported by the household
respondent, which was in order of input into the database and
not in order of importance or severity. Data users/analysts who use the
Medical Conditions file in conjunction with this office-based medical provider
visits file should note that the order of conditions on this file is not
identical to that on the 2006 Medical Conditions file.
Analysts should use the clinical classification codes
listed in the Conditions PUF document (HC-104) and the Appendix to the Event
Files (HC-102I) 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 2006 MEPS PUFs, these updates
will not be reflected in the 2006 MEPS data.
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2.5.5 Flat Fee Variables (FFEEIDX, FFOBTYPE, FFBEF06, FFTOT07)
2.5.5.1 Definition of Flat Fee Payments
A flat fee is the fixed dollar amount a person is charged
for a package of services provided during a defined period of time. An example
would be an obstetrician’s fee covering a normal delivery, and the associated
pre- and post-natal care. A flat fee group is the set of medical services (i.e.,
events) that are covered under the same flat fee payment. The flat fee groups
represented on the office-based provider file include flat fee groups where at
least one of the health care events, as reported by the HC respondent, occurred
during 2006. By definition, a flat fee group can span multiple years and/or
event types (only outpatient department visits and physician office visits).
Furthermore, a single person can have multiple flat fee groups.
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2.5.5.2 Flat Fee Variable Descriptions
2.5.5.2.1 Flat Fee ID (FFEEIDX)
As noted earlier in Section 2.5.1.2 "Record Identifiers,"
the variable FFEEIDX uniquely identifies all events that are part of the same
flat fee group for a person. On any 2006 MEPS event file, every event that is
part of a specific flat fee group will have the same value for FFEEIDX. Note
that prescribed medicine and home health events are never included in a flat fee
group and FFEEIDX is not a variable on those event files.
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2.5.5.2.2 Flat Fee Type (FFOBTYPE)
FFOBTYPE indicates whether the 2006 office-based medical
provider visit event is the "stem" or "leaf" of a flat fee group. A stem
(records with FFOBTYPE = 1) is the initial medical service (event) which is
followed by other medical events that are covered under the same flat fee
payment. The leaves of the flat fee group (records with FFOBTYPE = 2) are those
medical events that are tied back to the initial medical event (the stem) in the
flat fee group. These "leaf" records have their expenditure variables set to
zero. For the office-based visits that are not part of a flat fee payment, the
FFOBTYPE is set to -1, "INAPPLICABLE."
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2.5.5.2.3 Counts of Flat Fee Events that Cross Years (FFBEF06, FFTOT07)
As described in Section 2.5.5.1, a flat fee payment covers
multiple events and the multiple events could span multiple years. For
situations where the office-based medical provider visit occurred in 2006 as a
part of a group of events, and some of the events occurred before 2006, counts
of the known events are provided on the office-based medical provider visit
event file record. Variables that indicate events occurred before or after 2006
are as follows:
FFBEF06 - total number of pre-2006 events in the same
flat fee group as the 2006 office-based medical provider visit. This count
would not include the 2006 office-based medical visit(s).
FFTOT07 - the number of 2007 office-based events
expected to be in the same flat fee group as the office-based medical
provider visit event(s) that occurred in 2006.
If there are no 2005 events on the file,
FFBEF06 will be omitted. Likewise, if there are no 2007 events on the file,
FFTOT07 will be omitted. If there are no flat fee data related to the records in
this file, FFEEIDX and FFOBTYPE will be omitted as well. Please note that the
crosswalk in this document lists all possible flat fee variables.
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2.5.5.3 Caveats of Flat Fee Groups
Data users/analysts should note that flat fee payments are
common on the office-based medical provider visits file. There are 3,420
office-based medical provider visit events that are identified as being part of
a flat fee payment group. In order to correctly identify all events that are
part of a flat fee group, the user should link all MEPS events, except those in
the prescribed medicine file, using the variable FFEEIDX. In general, every flat
fee group should have an initial visit (stem) and at least one subsequent visit
(leaf). There are some situations where this is not true. For some of these flat
fee groups, the initial visit reported occurred in 2006, but the remaining
visits that were part of this flat fee group occurred in 2007. In this case, the
2006 flat fee group represented on this file would consist of one event (the
stem). The 2007 leaf events that are part of this flat fee group are not
represented on this file. Similarly, the household respondent may have reported
a flat fee group where the initial visit began in 2005 but subsequent visits
occurred during 2006. In this case, the initial visit would not be represented
on the file. This 2006 flat fee group would then consist only of one or more
leaf records and no stem. Another reason for which a flat fee group would not
have a stem and at least one leaf record is that the stem or leaves could have
been reported as different event types. Outpatient and Office-based medical
provider visits are the only two event types allowed in a single flat fee group.
The stem may have been reported as an outpatient department visit and the leaves
may have been reported as office-based medical provider visits.
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2.5.6 Expenditure Data
2.5.6.1 Definition of Expenditures
Expenditures on this file refer to what is paid for health
care services. More specifically, expenditures in MEPS are defined as the sum of
payments for care received, including out-of-pocket payments and payments made
by private insurance, Medicaid, Medicare and other sources. The definition of
expenditures used in MEPS differs slightly from its predecessors: the 1987 NMES
and 1977 NMCES surveys where "charges" rather than sum of payments were used to
measure expenditures. This change was adopted because charges became a less
appropriate proxy for medical expenditures during the 1990s due to the
increasingly common practice of discounting. Although measuring expenditures as
the sum of payments incorporates discounts in the MEPS expenditure estimates,
the estimates do not incorporate any payment not directly tied to specific
medical care visits, such as bonuses or retrospective payment adjustments paid
by third party payers. Another general change from the two prior surveys is that
charges associated with uncollected liability, bad debt, and charitable care
(unless provided by a public clinic or hospital) are not counted as expenditures
because there are no payments associated with those classifications. While
charge data are provided on this file, data users/analysts should use caution
when working with this data because a charge does not typically represent actual
dollars exchanged for services or the resource costs of those services, nor is
it directly comparable to the resource costs of those services or the
expenditures defined in the 1987 NMES (for details on expenditure definitions,
see Monheit et al., 1999). AHRQ has developed factors to apply to the 1987 NMES
expenditure data to facilitate longitudinal analysis. These factors can be
assessed via the 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.
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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2.5.6.2 Data Editing and Imputation Methodologies of Expenditure Variables
The expenditure data included on this file were derived
from both the MEPS household (HC) and medical provider (MPC) components. The MPC
contacted medical providers identified by household respondents. The charge and
payment data from medical providers were used in the expenditure imputation
process to supplement missing household data. For all office-based medical
provider visits, MPC data were used if available; otherwise HC data were used.
Missing data for office-based medical provider visits where HC data were not
complete and MPC data were not collected, or MPC data were not complete, were
derived through the imputation process.
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2.5.6.2.1 General Data Editing
Methodology
Logical edits were used to resolve internal
inconsistencies and other problems in the HC and MPC survey-reported data. The
edits were designed to preserve partial payment data from households and
providers, and to identify actual and potential sources of payment for each
household-reported event. In general, these edits accounted for outliers,
co-payments or charges reported as total payments, and reimbursed amounts that
were reported as out-of-pocket payments. In addition, edits were implemented to
correct for mis-classifications between Medicare and Medicaid and between
Medicare HMOs and private HMOs as payment sources. These edits produced a
complete vector of expenditures for some events, and provided the starting point
for imputing missing expenditures in the remaining events.
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2.5.6.2.2 General Hot-Deck Imputation
A weighted sequential hot-deck procedure was used to
impute for missing expenditures as well as total charge. This procedure uses
survey data from respondents to replace missing data, while taking into account
the respondents’ weighted distribution in the imputation process.
Classification variables vary by event type in the hot-deck imputations,
but total charge and insurance coverage are key variables in all of the
imputations. Separate imputations were performed for nine categories of medical
provider care: inpatient hospital stays; outpatient hospital department visits;
emergency room visits; visits to physicians; visits to non-physician providers;
dental services; home health care by certified providers; home health care by
paid independents; and other medical expenses. Within each event type file,
separate imputations were performed for flat fee and simple events.
After the imputations were finished, visits to physician and
non-physician providers were combined into a single medical provider file. The
two categories of home care also were combined into a single home health file.
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2.5.6.2.3 Office-Based Provider Visit Data Editing and Imputation
Expenditures for office-based provider visits were
developed in a sequence of logical edits and imputations. "Household" edits were
applied to sources and amounts of payment for all events reported by HC
respondents. "MPC" edits were applied to provider-reported sources and amounts
of payment for records matched to household-reported events. Both sets of edits
were used to correct obvious errors (as described above) in the reporting of
expenditures. After the data from each source were edited, a decision was made
as to whether household- or MPC-reported information would be used in the final
editing and hot-deck imputations for missing expenditures. The general rule was
that MPC data would be used for events where a household-reported event
corresponded to an MPC-reported event (i.e., a matched event), since providers
usually have more complete and accurate data on sources and amounts of payment
than households.
One of the more important edits separated flat fee events
from simple events. This edit was necessary because groups of events covered by
a flat fee (i.e., a flat fee bundle) were edited and imputed separately from
individual events covered by a single charge (i.e., simple events). (See Section
2.5.5 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).
For office-based and outpatient events, the donor pool
also included events originally reported by providers as paid on a capitated
basis. To obtain the fee-for-service (FFS) equivalent payments for these
capitated events, a "capitation imputation" was implemented (see the next
section). Once imputed with the FFS equivalent payments, these events became
donors for all other incomplete events, particularly for events reported by the
household as services covered under managed care plans.
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2.5.6.3 Capitation Imputation
The imputation process was also used to estimate
expenditures at the event level for events that were paid on a per month per
person (capitated) basis. The capitation imputation procedure was designed as a
reasonable approach to complete event-level expenditures for respondents in
non-fee for service managed care plans. HMO events reported in the MPC as
covered by capitation arrangements were imputed using similar completed HMO
events paid on a fee-for-service, with total charge as a key variable. Then this
fully completed set of MPC events was used in the donor pool for the main
imputation process for cases in HMOs. By using this strategy, capitated
HMO events were imputed as if the provider were reimbursed from the HMO on a
discounted fee-for-service basis.
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2.5.6.4 Imputation Flag (IMPFLAG)
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
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2.5.6.5 Flat Fee Expenditures
The approach used to count expenditures for flat fees was
to place the expenditure on the first visit of the flat fee group. The remaining
visits have zero payments. Thus, if the first visit in the flat fee group
occurred prior to 2006, all of the events that occurred in 2006 will have zero
payments. Conversely, if the first event in the flat fee group occurred at the
end of 2006, the total expenditure for the entire flat fee group will be on that
event, regardless of the number of events it covered after 2006. See Section
2.5.5 for details on the flat fee variables.
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2.5.6.6 Zero Expenditures
There are some medical events reported by respondents
where the payments were zero. Zero payment events can occur in MEPS for the
following reasons: (1) the visit 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 visit, (3) the provider was never paid
directly for services provided by an individual, insurance plan, or other
source, (4) charges were included in another bill, or (5) event was paid through
government or privately funded research or clinical trials.
The file also contains a small number of events involving
a telephone call rather than a visit to the medical provider (SEETLKPV = 2). The
expenditure variables for telephone calls have a value of -1 "INAPPLICABLE".
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2.5.6.7 Discount Adjustment Factor
An adjustment was also applied to some HC-reported
expenditure data because an evaluation of matched HC/MPC data showed that
respondents who reported that charges and payments were equal were often unaware
that insurance payments for the care had been based on a discounted charge. To
compensate for this systematic reporting error, a weighted sequential hot-deck
imputation procedure was implemented to determine an adjustment factor for
HC-reported insurance payments when charges and payments were reported to be
equal. As for the other imputations, selected predictor variables were used to
form groups of donor and recipient events for the imputation process.
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2.5.6.8 Sources of Payment
In addition to total expenditures, variables are provided
which itemize expenditures according to major source of payment categories.
These categories are:
- Out-of-pocket by user (self) or family,
- Medicare,
- Medicaid,
- Private Insurance,
- Veterans Administration, excluding TRICARE/CHAMPVA,
- TRICARE/CHAMPVA,
- Other Federal sources - includes Indian Health
Service, Military Treatment Facilities, and other care by the Federal
government,
- Other State and Local Sources - includes community
and neighborhood clinics, State and local health departments, and State
programs other than Medicaid,
- Workers’ Compensation, 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 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 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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2.5.6.9 Office-Based Expenditure Variables (OBSF06X - OBTC06X)
OBSF06X - OBOT06X are the 12 sources of payment. The 12
sources of payment are: self/family (OBSF06X), Medicare (OBMR06X), Medicaid
(OBMD06X), private insurance (OBPV06X), Veterans Administration (OBVA06X),
TRICARE/CHAMPVA (OBTR06X), other Federal sources (OBOF06X), State and Local
(non-federal) government sources (OBSL06X), Workers’ Compensation (OBWC06X),
other private insurance (OBOR06X), other public insurance (OBOU06X), and other
insurance (OBOT06X). OBXP06X is the sum of the 12 sources of payment for the
Office Based expenditures, and OBTC06X is the total charge.
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2.5.7 Rounding
Expenditure variables have been rounded to the nearest
penny. Person-level expenditure information released on the MEPS 2006
Person-Level Expenditure File will be rounded to the nearest dollar. It should
be noted that using the MEPS 2006 event files to create person-level
totals will yield slightly different totals than that those found on the
person-level expenditure file. These differences are due to rounding only.
Moreover, in some instances, the number of persons having expenditures on the
event files for a particular source of payment may differ from the number of
persons with expenditures on the person-level expenditure file for that source
of payment. This difference is also an artifact of rounding only. Please see the
MEPS 2006 Appendix File, HC-102I, for details on such
rounding differences.
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3.0 Sample Weight (PERWT06F)
3.1 Overview
There is a single full year person-level weight (PERWT06F)
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 2006. 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 PERWT06F was developed in several
stages. Person-level weights for Panels 10 and 11 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 2006 composite weight was then formed by multiplying
each weight from Panel 10 by the factor .47 and each weight from Panel 11 by the
factor .53. 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 10 Weight
The person-level weight for MEPS Panel 10 was developed
using the 2005 full year weight for an individual as a "base" weight for survey
participants present in 2005. For key, in-scope respondents who joined an RU
some time in 2006 after being out-of-scope in 2005, the 2005 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 2006. These control
figures were derived by scaling back the population totals obtained from the
March 2007 CPS to correspond to a national estimate for the civilian
noninstitutionalized population provided by the Census Bureau for December 2006.
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, 2006 is 295,668,762. Key,
responding persons not in-scope on December 31, 2006 but in-scope earlier in the
year retained, as their final Panel 10 weight, the weight after the nonresponse
adjustment.
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3.2.2 MEPS Panel 11 Weight
The person-level weight for MEPS Panel 11 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 2006 portion of Round 3 as well as raking to the same
population control figures for December 2006 used for the MEPS Panel 10 weights.
The same five variables employed for Panel 10 raking (census region, MSA status,
race/ethnicity, sex, and age) were used for Panel 11 raking. Similarly, for
Panel 11, key, responding persons not in-scope on December 31, 2006 but in-scope
earlier in the year retained, as their final Panel 11 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., 2005 for Panel 10 and 2006 for Panel 11).
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3.2.3 The Final Weight for 2006
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, 2006 is 295,668,762
(PERWT06F>0 and INSC1231=1). In addition, the weights of two groups of persons
who were out-of-scope on December 31, 2006 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 2006 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 299,267,035.
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3.2.4 Coverage
The target population for MEPS in this file is the 2006
U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2004 (Panel 10)
and 2005 (Panel 11). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2004 (Panel 10) or after 2005 (Panel 11) 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 inappropriately concluding that a change has taken
place.
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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 2006
event level estimates for the U.S. civilian noninstitutionalized population on
office-based medical provider visits as well as expenditures, and sources of
payment for these visits. Estimates of total visits are the sum of the weight
variable (PERWT06F) across relevant event records while estimates of other
variables must be weighted by PERWT06F to be nationally representative. The
tables below contain event-level estimates for selected variables.
Selected Event Level Estimates
Office-Based Visits
Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate (SE)
Excluding $0’s** |
Total number of office-based
medical provider visits (including
phone call events*, in millions) |
PERWT06F |
1,531.4 (44.60) |
1,437.2 (41.74) |
Total number of office-based
medical provider visits in person
and not by telephone (SEETLKPV=1,
in millions) |
PERWT06F |
1,518.8 (44.32) |
1,437.0 (41.74) |
Total number of in-person visits to
doctor (SEETLKPV=1 & SEEDOC=1,
in millions) |
PERWT06F |
978.5 (26.64) |
938.9 (25.74) |
Proportion of office-based medical
provider visits with expenditures > 0** |
OBXP06X |
0.939 (0.0028) |
-------- |
Office-Based Expenditures (SEETLKPV = 1)
Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate (SE)
Excluding $0’s** |
Mean total payments per visit
(all sources) |
OBXP06X |
$161 ($2.9) |
$170 ($3.1) |
Mean out-of-pocket payment per visit |
OBSF06X |
$26 ($0.7) |
$28 ($0.8) |
Mean proportion of total expenditures
paid by private insurance per visit |
OBPV06X
/OBXP06X |
------- |
0.396 (0.0065) |
Office-Based Expenditures: Physician Visits (SEEDOC = 1 & SEETLKPV = 1)
Estimate of Interest |
Variable Name |
Estimate (SE) |
Estimate (SE)
Excluding $0’s** |
Mean total payments per visit
where person saw medical doctor |
OBXP06X |
$180 ($3.1) |
$188 ($3.3) |
Mean out-of-pocket payment per
visit where person saw medical doctor |
OBSF06X |
$26 ($0.9) |
$27 ($0.9) |
Mean proportion of total expenditures
per visit paid by private insurance
where person saw medical doctor |
OBPV06X
/OBXP06X |
------- |
0.396 (0.0065) |
*OBXP06X=-1 (inapplicable) for all phone
call events (SEETLKPV=2).
** Zero payment events can occur in MEPS
for the following reasons: (1) the visit 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 visit, (3) the
provider was never paid directly for services provided by an individual,
insurance plan, or other source, (4) charges were included in another bill, or
(5) event was paid through government or privately funded research or clinical
trials.
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4.2 Person-Based
Estimates for Office-Based Visits
To enhance analyses of office-based visits, analysts may
link information about office-based visits 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 5.0 below for more details). Both
this file and the full year consolidated file may be used to derive estimates
for persons with office-based 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
office-based 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 office-based care.
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4.3 Variables with Missing Values
It is essential that the analyst examine all variables for
the presence of negative values used to represent missing values. For continuous
or discrete variables, where means or totals may be taken, it may be necessary
to set minus values to values appropriate to the analytic needs. That is, the
analyst should either impute a value or set the value to one that will be
interpreted as missing by the computing language used. For categorical and
dichotomous variables, the analyst may want to consider whether to recode or
impute a value for cases with negative values or whether to exclude or include
such cases in the numerator and/or denominator when calculating proportions.
Methodologies used for the editing/imputation of
expenditure variables (e.g., sources of payment, flat fee, and zero
expenditures) are described in Section 2.5.6.
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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 2006 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.
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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.
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5.1 Linking to the Person-Level File
Merging characteristics of interest from person-level file
(e.g., MEPS 2006 Full Year Population Characteristics File) expands the scope of
potential estimates. For example, to estimate the total number of office-based
medical provider visits of persons with specific demographic characteristics
(such as age, race, sex, and education), population characteristics from a
person-level file need to be merged onto the office-based medical provider
visits file. This procedure is illustrated below. The MEPS 2006 Appendix File,
HC-102I, provides additional detail on how to merge MEPS data files.
Create data set PERSX by sorting the 2006 Full Year
Population Characteristics File by the person identifier, DUPERSID. Keep
only variables to be merged onto the office-based medical provider visits
file and DUPERSID. Create data set OBMP by sorting the office-based
medical provider visits file by person identifier, DUPERSID. - Create final data set NEWOBMP by merging these two
files by DUPERSID, keeping only records on the office-based medical
provider visits file.
The following is an example of SAS code,
which completes these steps:
PROC SORT DATA=HCXXX (KEEP=DUPERSID AGE31X AGE42X
AGE53X SEX RACEX EDUCYR)
OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA=OBMP;
BY DUPERSID;
RUN;
DATA NEWOBMP;
MERGE OBMP (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
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5.2 Linking 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 office-based visit can link to more than one prescribed
medicine record. Conversely, a prescribed medicine event may link to more than
one office-based 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 2006 Appendix
File, HC-102I.
Return To Table Of Contents
5.3 Linking to the Medical Conditions File
The CLNK provides a link from MEPS event files to the 2006
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 an office-based medical provider visit, and (3) a condition may
link to more than one office-based medical provider visit or any other type of
visit. Users should also note that not all office-based medical provider visits
link to the condition 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.
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5.5 Longitudinal Analysis
Panel-specific 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. (1997). Sample Design of the 1996 Medical
Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health
Care Policy and Research; 1997. MEPS Methodology Report, No. 2.
AHCPR Pub. No. 97-0027.
Cohen, S.B. (1996). The Redesign of the Medical
Expenditure Panel Survey: A Component of the DHHS Survey Integration Plan.
Proceedings of the COPAFS Seminar on Statistical
Methodology in the Public Service.
Cohen, J.W. (1997). Design and Methods of the Medical
Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health
Care Policy and Research; 1997. MEPS Methodology Report, No. 1.
AHCPR Pub. No. 97-0026.
Cox, B.G. and Cohen, S.B. (1985). Chapter 6: A Comparison
of Household and Provider Reports of Medical Conditions. In Methodological
Issues for Health Care Surveys. Marcel Dekker, New York.
Cox, B. and Iachan, R. (1987). A Comparison of Household
and Provider Reports of Medical Conditions. Journal of the American
Statistical Association 82(400):1013-18.
Edwards, W.S., Winn, D.M., Kurlantzick V., et al. (1994).
Evaluation of National Health Interview Survey Diagnostic Reporting. National
Center for Health Statistics, Vital Health 2(120).
Elixhauser A., Steiner C.A., Whittington C.A., and
McCarthy E. Clinical Classifications for Health Policy Research: Hospital
Inpatient Statistics, 1995. Healthcare Cost and Utilization Project, HCUP-3
Research Note. Rockville, MD: Agency for Health Care Policy and Research; 1998.
AHCPR Pub. No. 98-0049.
Health Care Financing Administration (1980). International
Classification of Diseases, 9th Revision, Clinical Modification (ICD-CM).
Vol. 1. (DHHS Pub. No. (PHS) 80-1260). DHHS: U.S. Public Health Services.
Johnson, A.E. and Sanchez, M.E. (1993). Household and
Medical Provider Reports on Medical Conditions: National Medical Expenditure
Survey, 1987. Journal of Economic and Social Measurement. Vol. 19,
199-233.
Monheit, A.C., Wilson, R., and Arnett, III, R.H.
(Editors). Informing American Health Care Policy. (1999). Jossey-Bass Inc, San
Francisco.
Shah, B.V., Barnwell, B.G., Bieler, G.S., Boyle, K.E.,
Folsom, R.E., Lavange, L., Wheeless, S.C., and Williams, R. (1996). Technical
Manual: Statistical Methods and Algorithms Used in SUDAAN Release 7.0,
Research Triangle Park, NC: Research Triangle Institute.
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D. Variable-Source Crosswalk
VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-102G: 2006 OFFICE-BASED MEDICAL PROVIDER VISITS
Survey Administration Variables
Variable |
Description |
Source |
DUID |
Dwelling unit ID |
Assigned in sampling |
PID |
Person number |
Assigned in sampling |
DUPERSID |
Person ID (DUID + PID) |
Assigned in sampling |
EVNTIDX |
Event ID |
Assigned in sampling |
EVENTRN |
Event round number |
CAPI derived |
PANEL |
Panel number |
Constructed |
FFEEIDX |
Flat fee ID |
CAPI derived |
MPCELIG |
MPC eligibility flag |
Constructed |
MPCDATA |
MPC data flag |
Constructed |
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Medical Provider Visits Variables
Variable |
Description |
Source |
OBDATEYR |
Event date – year |
CAPI derived |
OBDATEMM |
Event date – month |
CAPI derived |
OBDATEDD |
Event date – day |
CAPI derived |
SEETLKPV |
Did P visit prov in person or telephone |
MV01 |
MVPLACE |
Kind of place patient saw MV provider |
MV02A |
SEEDOC |
Did P talk to MD this visit/phone call |
MV03 |
DRSPLTY |
MVIS doctor’s specialty |
MV03A |
MEDPTYPE |
Type of med person P talked to on vst dt |
MV04 |
DOCATLOC |
Any MD work at location where P saw prov |
MV06 |
VSTCTGRY |
Best category for care P recv on vst dt |
MV07 |
VSTRELCN |
This vst/phone call related to spec cond |
MV08 |
PHYSTH |
This visit did P have physical therapy |
MV10 |
OCCUPTH |
This vis did P have occupational therapy |
MV10 |
SPEECHTH |
This visit did P have speech therapy |
MV10 |
CHEMOTH |
This visit did P have chemotherapy |
MV10 |
RADIATTH |
This visit did P have radiation therapy |
MV10 |
KIDNEYD |
This visit did P have kidney dialysis |
MV10 |
IVTHER |
This visit did P have IV therapy |
MV10 |
DRUGTRT |
This vis did P have trt for drug/alcohol |
MV10 |
RCVSHOT |
This visit did P receive an allergy shot |
MV10 |
PSYCHOTH |
Did P have psychotherapy/counseling |
MV10 |
OTHSHOT |
This visit did P have other shot |
MV10 |
LABTEST |
This visit did P have lab tests |
MV11 |
SONOGRAM |
This visit did P have sonogram or ultrsd |
MV11 |
XRAYS |
This visit did P have x-rays |
MV11 |
MAMMOG |
This visit did P have a mammogram |
MV11 |
MRI |
This visit did P have an MRI/Catscan |
MV11 |
EKG |
This visit did P have an EKG or ECG |
MV11 |
EEG |
This visit did P have an EEG |
MV11 |
RCVVAC |
This visit did P receive a vaccination |
MV11 |
ANESTH |
This visit did P receive anesthesia |
MV11 |
OTHSVCE |
This visit did P have oth diag test/exam |
MV11 |
SURGPROC |
Was surg proc performed on P this visit |
MV12 |
MEDPRESC |
Any medicines prescribed for P this visit |
MV14 |
VAPLACE |
VA Facility Flag |
Constructed |
OBICD1X |
3-digit ICD-9-CM condition code |
Edited |
OBICD2X |
3-digit ICD-9-CM condition code |
Edited |
OBICD3X |
3-digit ICD-9-CM condition code |
Edited |
OBICD4X |
3-digit ICD-9-CM condition code |
Edited |
OBPRO1X |
2-digit ICD-9-CM procedure code |
Edited |
OBPRO2X |
2-digit ICD-9-CM procedure code |
Edited |
OBPRO3X |
2-digit ICD-9-CM procedure code |
Edited |
OBCCC1X |
Modified Clinical Classification Code |
Constructed/Edited |
OBCCC2X |
Modified Clinical Classification Code |
Constructed/Edited |
OBCCC3X |
Modified Clinical Classification Code |
Constructed/Edited |
OBCCC4X |
Modified Clinical Classification Code |
Constructed/Edited |
Return To Table Of Contents
Flat Fee Variables
Variable |
Description |
Source |
FFOBTYPE |
Flat fee bundle |
Constructed |
FFBEF06 |
Total # of visits in FF before 2006 |
FF05 |
FFTOT07 |
Total # of visits in FF after 2006 |
FF10 |
Return To Table Of Contents
Imputed Expenditure Variables
Variable |
Description |
Source |
OBSF06X |
Amount paid, self/family (imputed) |
CP Section (Edited) |
OBMR06X |
Amount paid, Medicare (imputed) |
CP Section (Edited) |
OBMD06X |
Amount paid, Medicaid (imputed) |
CP Section (Edited) |
OBPV06X |
Amount paid, private insurance (imputed) |
CP Section (Edited) |
OBVA06X |
Amount paid, Veterans Administration (imputed) |
CP Section (Edited) |
OBTR06X |
Amount paid, TRICARE/CHAMPVA (imputed) |
CP Section (Edited) |
OBOF06X |
Amount paid, other federal (imputed) |
CP Section (Edited) |
OBSL06X |
Amount paid, state & local government (imputed) |
CP Section (Edited) |
OBWC06X |
Amount paid, workers’ compensation (imputed) |
CP Section (Edited) |
OBOR06X |
Amount paid, other private insurance (imputed) |
Constructed |
OBOU06X |
Amount paid, other public insurance (imputed) |
Constructed |
OBOT06X |
Amount paid, other insurance (imputed) |
CP Section (Edited) |
OBXP06X |
Sum of OBSF06X – OBOT06X (imputed) |
Constructed |
OBTC06X |
Household reported total charge (imputed) |
CP Section (Edited) |
IMPFLAG |
Imputation status |
Constructed |
Return To Table Of Contents
Weights
Variable |
Description |
Source |
PERWT06F |
Expenditure file person weight, 2006 |
Constructed |
VARSTR |
Variance estimation stratum, 2006 |
Constructed |
VARPSU |
Variance estimation PSU, 2006 |
Constructed |
Return To Table Of Contents
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