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December 2011
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 Naming
2.5 File Contents
2.5.1 Identifier Variables (DUID-CONDRN)
2.5.2 Medical Condition Variables (PRIOLIST-CCCODEX)
2.5.2.1 Priority Conditions and Injuries
2.5.2.2 Age Priority Condition Began/Date Accident Occurred
2.5.2.3 Follow-up Questions for Injuries and Priority Conditions
2.5.2.4 Considerations for Making Estimates Using the MEPS Conditions File
2.5.2.4.1 Conditions File vs. Priority Conditions
2.5.2.4.2 Sources for Conditions on the MEPS Conditions File
2.5.2.5 Treatment of Data from Rounds Not Occurring in 2009
2.5.2.6 Rounds in Which Conditions Were Reported/Selected (CRND1 – CRND5)
2.5.2.7 Disability Flag Variables
2.5.2.8 Diagnosis Condition and Procedure Codes
2.5.2.9 Clinical Classification Codes
2.5.3 Utilization Variables (OBNUM – RXNUM)
3.0 Survey Sample Information
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 13 Weight
3.2.2 MEPS Panel 14 Weight
3.2.3 The Final Weight for 2009
3.2.4 Coverage
3.2.5 Incentive Experiment in Panel 13
3.3 Using MEPS Data for Trend Analysis
4.0 Merging/Linking MEPS Data Files
4.1 National Health Interview Survey
4.2 Longitudinal Analysis
References
Appendix 1: Variable-Source Crosswalk
Appendix 2: Condition, Procedure and Clinical Classification Code Frequencies
Appendix 3: Clinical Classification Code to ICD-9-CM Code Crosswalk
Appendix 4: List of Priority Conditions
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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The Medical Expenditure Panel Survey (MEPS) provides
nationally representative estimates of health care use, expenditures, sources of
payment, and health insurance coverage for the U.S. civilian
non-institutionalized population. The MEPS Household Component (HC) also
provides estimates of respondents’ health status, demographic and socio-economic
characteristics, employment, access to care, and satisfaction with health care.
Estimates can be produced for individuals, families, and selected population
subgroups. The panel design of the survey, which includes 5 Rounds of interviews
covering 2 full calendar years, provides data for examining person level changes
in selected variables such as expenditures, health insurance coverage, and
health status. Using computer assisted personal interviewing (CAPI) technology,
information about each household member is collected, and the survey builds on
this information from interview to interview. All data for a sampled household
are reported by a single household respondent.
The MEPS-HC was initiated in 1996. Each year a new
panel of sample households is selected. Because the data collected are
comparable to those from earlier medical expenditure surveys conducted in 1977
and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample
size is about 15,000 households. Data can be analyzed at either the person or
event level. Data must be weighted to produce national
estimates.
The set of households selected for each panel of the
MEPS HC is a subsample of households participating in the previous year’s
National Health Interview Survey (NHIS) conducted by the National Center for
Health Statistics. The NHIS sampling frame provides a nationally representative
sample of the U.S. civilian non-institutionalized population and reflects an
oversample of blacks and Hispanics. In 2006, the NHIS implemented a new sample
design, which included Asian persons in addition to households with black and
Hispanic persons in the oversampling of minority populations. MEPS further
oversamples additional policy relevant sub-groups such as low income households.
The linkage of the MEPS to the previous year’s NHIS provides additional data for
longitudinal analytic purposes.
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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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MEPS HC and MPC data are collected under the authority
of the Public Health Service Act. Data are collected under contract with Westat,
Inc. (MEPS HC) and Research Triangle Institute (MEPS MPC). 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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This documentation describes the data contained in
MEPS Public Use Release HC-128, which is one in a series of public use data
files to be released from the 2009 Medical Expenditure Panel Survey Household
Component (MEPS HC).
Released in ASCII (with related SAS and SPSS
programming statements and data user information) and SAS formats, this public
use file provides information on household-reported medical conditions collected
on a nationally representative sample of the civilian noninstitutionalized
population of the United States for calendar year 2009 MEPS HC. The file
contains 36 variables and has a logical record length of 102 with an additional
2-byte carriage return/line feed at the end of each record.
This documentation offers a brief overview of the
types and levels of data provided and the content and structure of the files. It
contains the following sections:
Data File Information
Survey Sample Information
Merging/Linking MEPS Data Files
Appendices
Variable to Source Crosswalk
Detailed ICD-9-CM Condition, Procedure, and Clinical Classification Code Frequencies
Clinical Classification Code to ICD-9-CM Code Crosswalk
List of Priority Conditions
A codebook of all the variables included in the 2009
Medical Conditions File is provided in an accompanying file.
For more information on MEPS survey design, see T.
Ezzati-Rice, et al., 1998-2007 and S. Cohen, 1996. A copy of the survey
instrument used to collect the information on this file is available on the MEPS
Website: www.meps.ahrq.gov.
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This file contains 117,342 records. Each record
represents one medical condition reported for a household survey member who
resides in an eligible responding household and who has a positive person or
family weight.
The PE section asks a series of questions regarding
whether the person has ever been diagnosed with a specified priority condition
(e.g., diabetes). If the answer is yes, then CAPI automatically creates a
condition record that is flagged as a priority condition (PRIOLIST = 1).
Respondents may also report medical conditions in the Condition Enumeration
(CE), medical events, and Disability Days (DD) sections. Prior to Panel 12, the
interviewer manually identified whether a condition collected in the CE, events,
or DD sections was a priority condition based on a list provided in the help
text. In addition to changing the method of assigning priority condition status
from manual to automated, the list of priority conditions changed in Panel 12.
See Appendix 4 for details.
Beginning in Panel 12, round-specific questions
(SEEDREV#, STILTR#, OVRALL#, FURTCA#, FOLOCA#, SEEDREF#) and some
accident/injury follow-up questions (ACDNTLOC, INOUTHH, VEHICLE, WEAPON,
POISON, FIREBURN, DROWN, SPORTS, FALL, ACDNTOTH, RECOVER) were no longer
collected.
Records meeting one of the following criteria are
included on the file:
In Panel 14:
- Round 1 and Round 2 conditions that are not priority conditions;
- Round 1 and Round 2 priority condition records that are current. A
current condition is defined as a condition linked to a 2009 event or
disability day, or a condition the person is currently experiencing
(i.e., a condition selected in the CE section);
- Round 3 conditions that were linked to a 2009 event;
- Round 3 conditions that were due to an accident or injury and began
before 2009;
- Round 3 priority condition records where the age of diagnosis is
less than or equal to the person’s age as of 12/31/2009 or where the age
of diagnosis is refused, don’t know, or not ascertained, and the
condition is current; or
- Round 3 priority conditions where 50 percent or more of person’s
reference period occurred in 2009.
In Panel 13:
- Round 3, Round 4, and Round 5 condition records that are not
priority conditions;
- Round 3, Round 4, and Round 5 priority condition records that are
current. A current condition is defined as a condition linked to a 2009
event or disability day or a condition the person is currently
experiencing (i.e., a condition selected in the CE section); or
- Round 1 and Round 2 condition records that are linked to a 2009
event or disability day, or a condition the person is currently
experiencing in 2009 (i.e., a condition selected in the CE section).
Overlap Condition Records (in 2008 and 2009)
Application of the above selection rules indicates
that all Panel 13 Round 3 conditions delivered in the 2008 file will be included
on the 2009 file if the person has a positive person or family weight in 2009.
For each variable on the file, the codebook provides
both weighted and unweighted frequencies. Because the conditions identified in
this file are derived from self-reports, these data cannot be used to make
estimates of disease, prevalence of health conditions, or mortality/morbidity.
However, data users can make estimates of treated prevalence.
Data from this file can be merged with 2009 MEPS
person-level data to append person-level characteristics such as demographic or
health insurance characteristics to each record by using DUPERSID (see Section
4.0 for details). Since each record represents a single condition reported by a
household respondent, some household members may have multiple medical
conditions and thus will be represented on multiple records on this file. Other
household members may have had no reported medical conditions and thus will have
no records on this file. Still other household members may have had
reported a medical condition that did not meet the criteria above and thus will
have no records on this file. Data from this file also can be merged to 2009
MEPS Event Files (HC-126A through HC-126H) by using the link files provided in
HC-126I. (See HC-126I for details.)
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The codebook and data file list variables in the
following order:
Unique person identifiers
Unique condition identifiers
Medical condition variables
Utilization variables
Weight and variance estimation variables
Note that the person identifier is unique within this
data year.
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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 |
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This codebook describes an ASCII data set and provides
the following programming identifiers for each variable:
| Identifier |
Description |
| Name |
Variable name (maximum of 8 characters) |
| Description |
Variable descriptor (maximum 40 characters) |
| Format |
Number of bytes |
| Type |
Type of data: numeric (indicated by NUM) or character (indicated by CHAR) |
| Start |
Beginning column position of variable in record |
| End |
Ending column position of variable in record |
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In general, variable names reflect the content of the
variable, with an 8-character limitation. For questions asked in a specific
round, the end digit in the variable name reflects the round in which the
question was asked. Edited variables end in an "X" and are so noted in the
variable label. (CONDIDX, which is an encrypted identifier variable, also ends
in an "X".)
Variables contained in this delivery were derived
either from the questionnaire itself or from the CAPI. The source of each
variable is identified in Appendix 1 "Variable to Source Crosswalk." Sources for
each variable are indicated in one of three ways: (1) variables derived from
CAPI or assigned in sampling are so indicated; (2) variables collected at one or
more specific questions have those numbers and questionnaire sections indicated
in the "SOURCE" column; and (3) variables constructed from multiple questions
using complex algorithms are labeled "Constructed" in the "SOURCE" column.
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The definitions of Dwelling Units (DUs) in the MEPS HC
are generally consistent with the definitions employed for the National Health
Interview Survey (NHIS). The dwelling unit ID (DUID) is a 5-digit random number
assigned after the case was sampled for MEPS. The person number (PID) uniquely
identifies each person within the dwelling unit. The variable DUPERSID uniquely
identifies each person represented on the file and is the combination of the
variables DUID and PID. CONDN indicates the condition number as it was reported
during the interview for an individual person (e.g., condition number 1, 2, 3,
etc.) plus a control digit. The current range for CONDN is 11-451 and the
largest range of records for any person on the file is 1-41. Note that this
discrepancy is expected, as condition numbers are not sequentially assigned by
the CAPI. In other words, if CONDN is set to 10 for a person's first condition,
then CONDN might be set to 17 for the person's second condition. CONDIDX
uniquely identifies each condition (i.e., each record on the file) and is the
combination of DUPERSID and the condition number CONDN. For CONDIDX, the
condition number is padded with leading zeroes to ensure consistent length.
PANEL is a constructed variable used to specify the
panel number for the interview in which the condition was reported. PANEL will
indicate either Panel 13 or Panel 14.
CONDRN indicates the round in which the condition was
first reported. For a small number of cases, conditions that actually
began in an earlier round were not reported by respondents until subsequent
rounds of data collection. During file construction, editing was performed for
these cases in order to reconcile the round in which a condition began and the
round in which the condition was first reported.
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This file contains variables describing medical
conditions reported by respondents in several sections of the MEPS
questionnaire, including the Condition Enumeration section, all questionnaire
sections collecting information about health provider visits, prescription
medications, and disability days (see Variable-Source Crosswalk in Appendix 1
for details).
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Certain conditions were a priori designated as
"priority conditions" (PRIOLIST=1) due to their prevalence, expense, or
relevance to policy. Some of these were long-term, life-threatening conditions,
such as cancer, diabetes, emphysema, high cholesterol, hypertension, ischemic
heart disease, and stroke. Others were chronic manageable conditions, including
arthritis and asthma. The only mental health condition on the priority
conditions list is attention deficit hyperactivity disorder/attention deficit
disorder. For a complete listing of priority conditions for Panel 12 and beyond,
see Appendix 4.
Prior to Panel 12, priority conditions were identified
as such in the field by MEPS interviewers. Occasionally, priority conditions
were not identified as such due to interviewer misinterpretation. Consequently,
these records are missing the follow-up questions described below. Likewise,
some conditions were inaccurately identified as priority conditions. These
records do have follow-up questions even though they are not priority
conditions. Beginning in Panel 12, priority conditions were flagged as
such by CAPI, thus preventing inaccurate identification.
When a condition was first mentioned, respondents were
asked whether it was due to an accident or injury (INJURY=1). Only non-priority
conditions (i.e., conditions reported in a section other than PE) are eligible
to be injuries. The interviewer is prevented from selecting priority conditions
as injuries.
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The month and year a priority condition began
(CONDBEGM and CONDBEGY) were dropped from this file beginning in Panel 12. The
age of diagnosis (AGEDIAG) was collected for all priority conditions, except
joint pain. The day, month, and year an accident or injury occurred (ACCDENTD,
ACCDENTM, and ACCDENTY) were collected only for conditions that were reported as
due to accident or injury. If the respondent did not know the accident year, or
refused to provide it, or if the year was not ascertained (ACCDENTY in (-7, -8,
-9)), a follow-up question gathered whether the accident occurred before or
after January 1 of the reference year (ACCDNJAN). If the respondent replied that
the accident occurred after January 1 of the reference year (ACCDNJAN = 2), then
the reference year was used to set the accident year and ACCDNJAN was reset to
Inapplicable (-1).
To ensure confidentiality, the accident year was
bottom-coded to 1924 and age of diagnosis was top-coded to 85. This corresponds
with the date of birth bottom-coding and age top-coding in person-level PUFs.
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When a respondent reported that a condition resulted
from an accident or injury (INJURY=1), respondents were asked during the round
in which the injury was first reported whether the accident/injury occurred at
work (ACCDNWRK). This question was not asked about persons aged 15 and younger;
the condition had ACCDNWRK coded to inapplicable (-1) for those persons.
For cancer conditions collected in the PE section, a
follow-up question was asked when the cancer was first reported to determine
whether the cancer was in remission/under control (REMISSN).
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Priority conditions created in the Priority Condition
Enumeration (PE) section were asked in the context of "has person ever been told
by a doctor or other health care professional that they have (condition)?"
except joint pain and chronic bronchitis, which ask only about the last 12
months. If the response is Yes (1), then a condition record is generated. Note
that priority conditions are included in the Conditions PUF only if the
condition is current. A current condition is defined as a condition linked to an
event or disability day or a condition the person is currently experiencing
(i.e., a condition selected in the CE section).
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Conditions can be added to the MEPS conditions roster
in several ways. A condition can be reported in the Priority Condition
Enumeration (PE) section in which persons are asked if they have been diagnosed
with specific conditions. The condition can be identified as the reason reported
by the household respondent for a particular medical event (hospital stay,
outpatient visit, emergency room visit, home health episode, prescribed
medication purchase, or medical provider visit). The condition may be reported
as the reason for one or more episodes of disability days. Finally, the
condition may be reported by the household level respondent as a condition
"bothering" the person during the reference period (see question CE03).
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Prior to the 2008 file, priority conditions reported
during Rounds 1 and 2 of the second year panel were included on the file even if
the conditions were not related to an event or disability day or reported as a
serious condition occurring in the second year of the panel. Beginning in 2008,
conditions are included on the file only if they are current conditions. A
current condition is defined as a condition linked to an event or disability day
or a condition the person is currently experiencing (i.e., a condition selected
in the Condition Enumeration (CE) section). Conditions from Rounds 1 and 2 that
are not included in the 2009 file are available in the 2008 Medical Conditions
File. Note that, for some Rounds 1 and 2 records, data may not be available on
the previous year’s file. This situation can occur when a person does not have a
positive person or family weight in the first year but is assigned a positive
weight in the subsequent year. The situation can also occur if the condition is
a priority condition for which no events or disability days were reported in the
first year but are reported in the second year.
For 2009, 104 conditions from Panel 13 Rounds 1 and 2
are included on the 2009 Medical Conditions File for persons who did not appear
on the previous year’s file. Of these, one is because the person did not have a
positive family weight in 2008, and 103 are because the priority condition was
not current in 2008.
The variables PRIORFLG and INJURFLG were dropped in
2008. Note: Priority conditions are generally chronic conditions. Even though a
person may not have reported an event or disability day in 2009 due to the
condition, or reported generally experiencing the condition in 2009, analysts
should consider that the person is probably still experiencing the condition. If
a Panel 13 person reported a priority condition in Round 1 or 2 and did not have
an event or disability day for the condition in Round 3, 4, or 5, the condition
will not be included on the 2009 Medical Conditions File.
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A set of constructed variables indicates the round in
which the condition was first reported (CONDRN), and the subsequent round(s) in
which the condition was selected (CRND1 – CRND5). The condition may be reported
or selected when the person reports an event or disability day that occurred due
to the condition, or the condition may be selected as a serious condition that
is not linked to any events or disability days. For example, consider a
condition for which CRND1 = 0, CRND2 = 1, and CRND3 = 1. For non-priority
conditions, this sequence of CRND indicators on a condition record implies that
the condition was not present during Round 1 (CRND1 = 0), was first mentioned
during Round 2, and was selected during Round 3. For priority conditions, it is
necessary to look at CONDRN rather than CRND# to determine in which round the
condition was first reported. In addition to the scenario above, this sequence
of CRND indicators may imply for priority conditions that the condition was
reported in the PE section in Round 1 but was not connected with an event or
disability day, and not selected in the CE section as a current condition until
Rounds 2 and 3.
Due to age-related confidentiality concerns, pregnancy
conditions for women under 16 and over 44 where there is no CRND in the round in
which the condition was reported have CRND# updated to 1 for that round.
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This file contains three flag variables indicating
whether a condition is associated with a missed work day (MISSWORK), a missed
school day (MISSSCHL), or a day spent in bed (INBEDFLG). Due to the MEPS
instrument design, there is no link indicating the specific number of
disability days associated with a particular medical condition.
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The medical conditions and procedures reported by the
Household Component respondent were recorded by the interviewer as verbatim
text, which was then coded by professional coders to fully-specified ICD-9-CM
codes, including medical condition and V codes (see Health Care Financing
Administration, 1980). Although codes were verified and error rates did not
exceed 2.5 percent for any coder, 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 Iachan,
1987; Edwards, et al, 1994; and Johnson and Sanchez, 1993). Some condition
information is collected in the Medical Provider Component of MEPS. However,
since it is not available for everyone in the sample, it is not used to
supplement, replace, or verify household reported condition data.
Professional coders followed specific guidelines in
coding missing values to the ICD-9-CM diagnosis condition and procedure
variables. The ICD-9-CM diagnosis condition variable (ICD9CODX) was coded -9
where the verbatim text fell into one of three categories: (1) the text
indicated that the condition was unknown (e.g., DK); (2) the text indicated the
condition could not be diagnosed by a doctor (e.g., doctor doesn’t know); or (3)
the specified condition was not codeable and a procedure could not be discerned
from the text. ICD9CODX was coded -1 where the verbatim text strictly denoted a
procedure and not a condition. The ICD-9-CM procedure variable (ICD9PROX) was
coded -9 where the verbatim text strictly denoted a procedure, but the text was
not specific enough to assign a procedure code. ICD9PROX was set to -1 where the
text strictly specified a condition and not a procedure.
In order to preserve confidentiality, nearly all of
the diagnosis condition codes provided on this file have been collapsed from
fully-specified codes to 3-digit code categories. Table 1 in Appendix 2 provides
unweighted and weighted frequencies for all ICD-9-CM condition code values
reported on the file. In this table, values that reflect this collapsing have an
asterisk in the label indicating that the 3-digit category includes all the
subclassifications within that category. For example, the ICD9CODX value of 034
"Strep Throat/Scarlet Fev *" includes the fully-specified subclassifications
034.0 and 034.1; the value 296 "Affective Psychoses*" includes the
fully-specified subclassifications 296.0 through 296.99. Less than 1 percent of
the records on this file were edited further by collapsing two or more 3-digit
codes into one 3-digit code.
Similarly, most of the procedure codes were collapsed
from fully-specified codes to 2-digit category codes. Table 2 in Appendix 2
provides unweighted and weighted frequencies for ICD9PROX, and this type of
collapsing is identified by an asterisk in the variable label. For example, the
ICD9PROX value of 81 "Joint Repair*" includes subclassifications 81.0 through
81.99. Less than 1 percent of records were further edited to combine two or more
2-digit categories.
Note that, for conditions related to certain medical
events, the ICD-9-CM codes on this file are also released in the Prescribed
Medicines, Emergency Room Visits, Office-based Medical Provider Visits,
Outpatient Department Visits, and Inpatient Hospital Stays Event Files. Because
the ICD-9-CM codes have been collapsed, 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
information on merging data on this file with the 2009 MEPS Event Files (HC-126A
through HC-126H) refer to the link files provided in HC-126I, and see HC-126I
for details.
In a small number of cases, diagnosis condition and
procedure codes were further recoded to -9 if they denoted a pregnancy for a
person younger than 16 or older than 44. There were 14 records recoded in this
manner on the 2009 Medical Conditions File. The person’s age was determined by
linking the 2009 Medical Conditions File to the 2008 and 2009 Person-Level Use
PUFs. If the person’s age is under 16 or over 44 in the round in which the
condition or procedure was reported, the appropriate condition or procedure code
was recoded to -9.
Users should note that because of the design of the
survey, most deliveries (i.e., births) are coded as pregnancies. For more
accurate estimates for deliveries, analysts should use RSNINHOS "Reason Entered
Hospital" found on the Hospital Inpatient Stays Public Use File (HC-126D).
Conditions and procedures were reported in the same
sections of the HC questionnaire (see Variable-Source Crosswalk in Appendix 1).
Labels for all values of the variables ICD9CODX and ICD9PROX, as shown in Tables
1 and 2, are provided in the SAS programming statements included in this release
(see the H128SU.TXT file).
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ICD-9-CM condition codes have been aggregated into
clinically meaningful categories that group similar conditions (CCCODEX).
CCCODEX was generated using Clinical Classification Software (formerly known as
Clinical Classifications for Health Care Policy Research (CCHPR)), which
aggregates conditions and V-codes into mutually exclusive categories, most of
which are clinically homogeneous (Elixhauser, et al, 2000). Appendix 3 lists the
ICD-9-CM codes that have been aggregated for each clinical classification
category.
The reported ICD-9-CM condition code values were
mapped to the appropriate clinical classification category prior to being
collapsed to 3-digit ICD-9-CM condition codes. The result is that every record
which has an ICD-9-CM diagnosis code also has a clinical classification code.
For confidentiality purposes, ICD-9-CM codes are
recoded to broader codes by clinicians for conditions that occur fewer than four
times within a year’s conditions file. CCS codes are assigned to the original
fully-specified ICD-9-CM codes. When the original ICD-9-CM codes undergo
recoding, no changes are made to the assigned CCS codes.
As with ICD9CODX and ICD9PROX, professional coders
followed specific guidelines in setting CCCODEX to a missing value. CCCODEX was
coded -9 where the verbatim text fell into one of three categories: (1) the text
indicated that the condition was unknown (e.g., DK); (2) the text indicated the
condition could not be diagnosed by a doctor (e.g., doctor doesn’t know); or (3)
the specified condition was not codeable and a procedure could not be discerned
from the text. CCCODEX was coded -1 where the verbatim text strictly denotes a
procedure and not a condition.
A small number (less than 1 percent) of clinical
classification codes have been edited for confidentiality purposes. Table 3 in
Appendix 2 provides weighted and unweighted frequencies for CCCODEX. Labels for
all values of the variable CCCODEX, as shown in Table 3, are provided in the SAS
programming statements included in this release (see the H128SU.TXT file).
In a small number of cases, clinical classification
codes were further recoded to -9 if they denoted a pregnancy for a person
younger than 16 or older than 44. There were 14 records recoded in this manner
on the 2009 Medical Conditions File. The person’s age was determined by linking
the 2009 Medical Conditions File to the 2008 and 2009 Person-Level Use PUFs. If
the person’s age is under 16 or over 44 in the round in which the condition was
reported, the appropriate clinical classification code was recoded to -9.
Note that, prior to 2004, the range for the variable
CCCODEX was 001 through 260. In 2004, revisions to the coding of mental
disorders were implemented. The codes 650 through 663 replaced 065 through 075
in 2004. Beginning in 2007, the mental disorders codes were reorganized again.
Alcohol and substance abuse disorders were broken into separate categories, and
miscellaneous mental disorders was renumbered.
Analysts should use the clinical classification codes
listed in the Conditions PUF document (HC-128) and the Appendix to the Event
Files (HC-126I) 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) Website, if updates to these codes and/or labels are
made on the HCUP Website after the release of the 2009 MEPS PUFs, these updates
will not be reflected in the 2009 MEPS data.
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The variables OBNUM, OPNUM, HHNUM, IPNUM, ERNUM, and
RXNUM indicate the total number of 2009 events that can be linked to each
condition record on the current file, i.e., office-based, outpatient, home
health, inpatient hospital stays, emergency room visits, and prescribed
medicines, respectively.
These counts of events were derived from Expenditure
Event Public Use Files (HC-126G, HC-126F, HC-126H, HC-126D, HC-126E, and
HC-126A). Events associated with conditions include all utilization that
occurred between January 1, 2009 and December 31, 2009.
Because persons can be seen for more than one
condition per visit, these frequencies will not match the person or event-level
utilization counts. For example, if a person had one inpatient hospital stay and
was treated for a fractured hip, a fractured shoulder and a concussion, each of
these conditions has a unique record in this file and IPNUM=1 for each record.
By summing IPNUM for these records, the total inpatient hospital stays would be
three when actually there was only one inpatient hospital stay for that person
and three conditions were treated. These variables are useful for determining
the number of inpatient hospital stays for head injuries, hip fractures, etc.
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There is a single full year person-level weight
(PERWT09F) 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 2009. 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.
There has been an important change in the MEPS sample
design that is worth noting. A new NHIS sample design was implemented in 2006
with a new sample of PSUs and segments, independent of the sample design used
from 1995-2005. To the extent that the new NHIS design provides better coverage
of the civilian, non-institutionalized U.S. population in general and specific
subgroups in particular, differences between estimates based on the old and new
designs could arise in both NHIS and MEPS due to such improved coverage rather
than actual changes in the characteristics of the target population.
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The person-level weight PERWT09F was developed in
several stages. Person-level weights for Panels 13 and 14 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 2009
composite weight was then formed by multiplying each weight from Panel 13 by the
factor .52 and each weight from Panel 14 by the factor .48. 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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The person-level weight for MEPS Panel 13 was
developed using the 2008 full year weight for an individual as a "base" weight
for survey participants present in 2008. For key, in-scope RU members who joined
an RU some time in 2009 after being out-of-scope in 2008, the 2008 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 2009. These control
figures were derived by scaling back the population totals obtained from the
March 2009 CPS to correspond to a national estimate for the civilian
noninstitutionalized population provided by the Census Bureau for December 2009.
Variables used in the establishment of person-level control figures included:
census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA);
race/ethnicity (Hispanic, black but non-Hispanic, Asian but non-Hispanic,
and other); sex; and age. Key, responding persons not in-scope on
December 31, 2009 but in-scope earlier in the year retained, as their final
Panel 13 weight, the weight after the nonresponse adjustment.
3.2.2 MEPS Panel 14 Weight
The person-level weight for MEPS Panel 14 was
developed using the MEPS Round 1 person-level weight as a "base" weight. For
key, in-scope RU members 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 2009 portion of Round 3 as well as raking
to the same population control figures for December 2009 used for the MEPS Panel
13 weights. The same five variables employed for Panel 13 raking (census region,
MSA status, race/ethnicity, sex, and age) were used for Panel 14 raking.
Similarly, for Panel 14, key, responding persons not in-scope on December 31,
2009 but in-scope earlier in the year retained, as their final Panel 14 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., 2008 for Panel 13 and 2009 for Panel 14).
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The composite weights of two groups of persons who
were out-of-scope on December 31, 2009 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 2009 were poststratified to corresponding
estimates derived using data obtained from the Medicare Current Beneficiary
Survey (MCBS) and Vital Statistics information provided by the National Center
for Health Statistics (NCHS). Separate decedent control totals were developed
for the "65 and older" and "under 65" civilian noninstitutionalized populations.
Overall, the weighted population estimate for the
civilian noninstitutionalized population for December 31, 2009 is 302,964,200
(PERWT09F>0 and INSC1231=1). The sum of the person-level weights across all
persons assigned a positive person-level weight is 306,660,588.
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3.2.4 Coverage
The target population for MEPS in this file is the
2009 U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 2007 (Panel 13)
and 2008 (Panel 14). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 2007 (Panel 13) or after 2008 (Panel 14) 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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With the encouragement of the Office of Management and
Budget (OMB), an experiment was undertaken for MEPS Panel 13 (first fielded in
2008) to evaluate whether and how differential payments to household respondents
might affect survey participation, the level of effort required to obtain
participation, and the quality of the data collected. Each sampled household in
Panel 13 was randomly assigned to one of three different levels of payment—$30,
$50, or $70—with the experiment continuing through the panel’s five rounds of
data collection. Households receiving the $30 payment represent the control
group, since that amount had been offered to all households in the 2007 panel.
To learn more about this experiment, go to the Respondent
Payment Experiment – Results
from Panel 13. Agency for Healthcare Research and Quality, Rockville, MD.
Return To Table Of Contents
MEPS began in 1996, and the utility of the survey for
analyzing health care trends expands with each additional year of data. However,
it is important to consider a variety of factors when examining trends over time
using MEPS. Statistical significance tests should be conducted to assess the
likelihood that observed trends may be attributable to sampling variation. The
length of time being analyzed should also be considered. In particular, large
shifts in survey estimates over short periods of time (e.g. from one year to the
next) that are statistically significant should be interpreted with caution,
unless they are attributable to known factors such as changes in public policy,
economic conditions, or MEPS survey methodology. Looking at changes over longer
periods of time can provide a more complete picture of underlying trends.
Analysts may wish to consider using techniques to smooth or stabilize analyses
of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97
versus 2004-05), working with moving averages, or using modeling techniques with
several consecutive years of MEPS data to test the fit of specified patterns
over time. Finally, researchers should be aware of the impact of multiple
comparisons on Type I error. Without making appropriate allowance for multiple
comparisons, undertaking numerous statistical significance tests of trends
increases the likelihood of concluding that a change has taken place when one
has not.
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Data from the current file can be used alone or in
conjunction with other files. Merging characteristics of interest from
person-level files expands the scope of potential estimates. See HC-126I for
instructions on merging the Condition File to the Medical Event Files.
Person-level characteristics can be merged to this Conditions File using the
following procedure:
- Sort the person-level file by person identifier, DUPERSID. Keep only
DUPERSID and the variables to be merged onto the Conditions File.
- Sort the Conditions File by person identifier, DUPERSID.
- Merge both files by DUPERSID, and output all records in the Conditions
File.
- If PERS contains the person-level variables, and COND is the Conditions
File, the following code can be used to add person-level variables to the
person’s conditions in the condition-level file.
PROC SORT DATA=PERS(KEEP=DUPERSID AGE SEX EDUCLEVL)
OUT=PERSX; BY DUPERSID;
RUN;
PROC SORT DATA=COND; BY DUPERSID;
RUN;
DATA COND;
MERGE COND (IN=A) PERSX(IN=B); BY DUPERSID;
IF A;
RUN;
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Data from this file can be used alone or in
conjunction with other files for different analytic purposes. 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
www.meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.
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For Panels 1 through 8, panel-specific files (called
Longitudinal Weight Files) containing estimation variables to facilitate
longitudinal analysis are available for downloading in the data section of the
MEPS Web site. To create longitudinal files for these panels, it is necessary to
link data from two subsequent annual files that contain data for the first and
second years of the panel, respectively. Starting with Panel 9, it is not
necessary to link files for longitudinal analysis because Longitudinal Data
Files have been constructed and are available for downloading on the Web.
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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. 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.
Evaluation of National Health Interview Survey Diagnostic Reporting. National
Center for Health Statistics, Vital Health 2(120). 1994.
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 Healthcare Research and Quality; 2000.
AHCPR Pub. No. 98-0049.
Ezzati-Rice, T.M., Rohde, F., Greenblatt, J., Sample
Design of the Medical Expenditure Panel Survey Household Component, 1998–2007.
Methodology Report No. 22. March 2008. Agency for Healthcare Research and
Quality, Rockville, MD.
Health Care Financing Administration (1980).
International Classification of Diseases, 9th Revision, Clinical
Modification (ICD-CM). Vol. 1. (Department of Health and Human Services Pub. No
(PHS) 80-1260). Department of Health and Human Services: U.S. Public Health
Services.
Johnson, Ayah E., and Sanchez, Maria Elena. (1993),
"Household and Medical Reports on Medical Conditions: National Medical
Expenditure Survey." Journal of Economic and Social Measurement, 19,
199-223.
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Appendix 1. Variable-Source Crosswalk
Unique Identifier Variables
| Variable |
Label |
Source1 |
| DUID |
Dwelling Unit ID |
Assigned In Sampling |
| PID |
Person Number |
Assigned In Sampling |
| DUPERSID |
Person ID (DUID + PID) |
Assigned In Sampling |
| CONDN |
Condition Number |
CAPI Derived |
| CONDIDX |
Condition ID |
CAPI Derived |
| PANEL |
Panel Number |
Constructed |
| CONDRN |
Condition Round Number |
CAPI Derived |
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Medical Condition Variables
| Variable |
Label |
Source1 |
| PRIOLIST |
Is Condition On Priority List |
CN02 |
| AGEDIAG |
Age When Diagnosed |
PE section |
| REMISSN |
Is Cancer in Remission/Under Control |
PE25 |
| CRND1 |
Has Condition Information In Round 1 |
Constructed |
| CRND2 |
Has Condition Information In Round 2 |
Constructed |
| CRND3 |
Has Condition Information In Round 3 |
Constructed |
| CRND4 |
Has Condition Information In Round 4 |
Constructed |
| CRND5 |
Has Condition Information In Round 5 |
Constructed |
| INJURY |
Was Condition Due To Accident/Injury |
CN02 |
| ACCDENTD |
Date Of Accident -- Day |
CN06 |
| ACCDENTM |
Date Of Accident -- Month |
CN06 |
| ACCDENTY |
Date Of Accident -- Year |
CN06 |
| ACCDNJAN |
Accident/Injury Occur Before/After Jan 1 |
CN06A |
| ACCDNWRK |
Did Accident Occur At Work |
CN07 |
| MISSWORK |
Flag Associated With Missed Work Days |
DD03 |
| MISSSCHL |
Flag Associated With Missed School Days |
DD06 |
| INBEDFLG |
Flag Associated With Bed Days |
DD09 |
| ICD9CODX |
ICD-9-CM Code For Condition - Edited |
CE05, HS04, ER04,
OP09, MV09, HH05,
PM09 (Edited) |
| ICD9PROX |
ICD-9-CM Code For Procedure - Edited |
CE05, HS04, ER04,
OP09, MV09, HH05,
PM09 (Edited) |
| CCCODEX |
Clinical Classification Code - Edited |
Constructed/Edited |
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Utilization Variables
| Variable |
Label |
Source1 |
| HHNUM |
# Home Health Events Assoc. w/ Condition |
Constructed |
| IPNUM |
# Inpatient Events Assoc. w/ Condition |
Constructed |
| OPNUM |
# Outpatient Events Assoc. w/ Condition |
Constructed |
| OBNUM |
# Office-Based Events Assoc. w/ Condition |
Constructed |
| ERNUM |
# ER Events Assoc. w/ Condition |
Constructed |
| RXNUM |
# Prescribed Medicines Assoc. w/ Cond. |
Constructed |
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Weights and Variance Estimation Variables
| Variable |
Label |
Source1 |
| PERWT09F |
Expenditure File Person Weight, 2009 |
Constructed |
| VARSTR |
Variance Estimation Stratum, 2009 |
Constructed |
| VARPSU |
Variance Estimation PSU, 2009 |
Constructed |
1See the Household Component section under Survey Questionnaires
on the MEPS home page for information on the MEPS HC questionnaire sections shown in the Source column (e.g., CN, DD).
Return To Table Of Contents
Appendix 4. List of Priority Conditions
- Angina/Angina Pectoris
- Arthritis
- Asthma
- Attention Deficit Hyperactivity Disorder (ADHD)/Attention Deficit Disorder (ADD)
- Cancer/Malignancy
- Chronic Bronchitis
- Coronary Heart Disease
- Diabetes/Sugar Diabetes
- Emphysema
- Heart Attack/Myocardial Infarction (MI)
- High Cholesterol
- Hypertension/High Blood Pressure
- Joint Pain
- Other Heart Disease (not coronary heart disease, angina, or heart attack)
- Stroke/Transient Ischemic Attack (TIA)/Mini-stroke
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