MEPS HC-087: 2004 Medical 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:

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.

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 noninstitutionalized population. MEPS is co-sponsored by the Agency for Healthcare Research and Quality (AHRQ) and the National Center for Health Statistics (NCHS), and has been conducted annually since 1996. The predecessor surveys to MEPS were the 1977 National Medical Care Expenditure Survey (NMCES, also known as NMES-1) and the 1987 National Medical Expenditure Survey (NMES-2).

MEPS is a family of three surveys. The Household Component (HC) is the core survey and also forms the basis for the Medical Provider Component (MPC). Together these two surveys yield comprehensive data that provide national estimates of the level and distribution of health care use and expenditures, support health services research, and can be used to assess health care policy implications. The third survey, the Insurance Component (IC), is a survey of private and public sector employers that provides national and state level estimates of employer-sponsored health insurance coverage and cost.

The MEPS HC, a nationally representative survey of the U.S. civilian noninstitutionalized population, collects medical expenditure data at both the person and household levels. Using computer-assisted personal interviewing (CAPI) technology, the HC collects detailed data on demographic characteristics, health conditions, health status, use of medical care services, charges and payments, access to care, satisfaction with care, health insurance coverage, income, and employment.

The HC is based on an overlapping panel design in which data covering a two year period are collected through a preliminary contact followed by a series of five rounds of interviews over a 2 ½-year period. Data on medical expenditures and use for two calendar years are collected from each household. This series of data collection rounds is launched each year on a new sample panel of households, and annual data are developed by combining data from the first year of the new panel with that from the second year of the previous panel.

Each year’s sample for the MEPS HC is drawn from respondents to the previous year’s National Health Interview Survey (NHIS). The NHIS provides a nationally representative sample of the U.S. civilian noninstitutionalized population, with an over-sampling of Hispanics and blacks that carries over to the MEPS sample. In addition, the MEPS sample design over-samples Asians and persons in low income families.

The MEPS MPC collects data from providers that are primarily used to supplement and/or replace information on medical care expenditures reported in the MEPS HC. The survey contacts medical providers and pharmacies identified by household respondents and for which signed Health Insurance Portability and Accountability Act of 1996 (HIPAA) compliant permission forms have been obtained from family members who received services from the medical providers and pharmacies.

The MPC sample includes all hospitals, emergency rooms, home health agencies, outpatient departments and pharmacies reported by HC respondents as well as all physician’s who provide services for patients in hospitals but bill separately from the hospital. Office based medical providers where the provider is either a doctor of medicine (MD) or Osteopathy (DO) or practices under the direct supervision of an MD or DO are included in the MPC as well.

Data are collected on medical and financial characteristics of medical and pharmacy events reported by HC respondents. These data include dates of visit, diagnosis and procedure codes, charges and payments. These data allow records to be matched with household events to facilitate expenditure imputation. The MPC was not designed as a stand alone survey to generate national estimates. The MPC data are collected from sampled providers through an initial screening telephone contact to verify provider eligibility, a mailed or faxed questionnaire, and a phone call to collect the data. Many providers prefer to send electronic, fax, or hard copies of records from which the necessary information can be abstracted. To supplement abstraction, telephone calls are placed to providers to clarify items, obtain critical information that may be missing, and follow-up on nonresponse.

The MEPS IC collects data on health insurance plans obtained through private and public-sector employers. Data obtained in the IC include the number and types of private insurance plans offered, benefits associated with these plans, premiums, contributions by employers and employees, eligibility requirements, and employer characteristics.

Establishments participating in the MEPS IC are selected through two sampling frames:

Data from these two Census Bureau sampling frames are used to produce annual national and state estimates of the supply and cost of private health insurance available to American workers and to evaluate policy issues pertaining to health insurance. National estimates of employer contributions to group insurance from the MEPS IC are used in the computation of Gross Domestic Product (GDP) by the Bureau of Economic Analysis.

The MEPS IC is an annual survey. Data are collected from the selected organizations through a prescreening telephone interview, a mailed questionnaire, and a telephone follow-up for non-respondents.

MEPS HC data are collected under the authority of the Public Health 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 this Act and the Privacy Act. NCHS provides consultation and technical assistance.

MEPS IC data are collected under the authority of the Public Health Service Act and under the authority provided in Title 13, United States Code (U.S.C.). The data are collected under an interagency agreement with the U.S. Census Bureau. Data sets and summary statistics are edited and published in accordance with the confidentiality provisions of this Act, Title 13 U.S.C., and the Privacy Act.

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. (MEPS IC micro data files are confidential and are only accessible for approved research projects at the Census Bureau’s Research Data Centers.) 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).

This documentation describes the data contained in MEPS Public Use Release HC-087, which is one in a series of public use data files to be released from the 2004 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 non-institutionalized population of the United States for calendar year 2004 MEPS HC. The file contains 86 variables and has a logical record length of 202 with an additional 2-byte carriage return/line feed at the end of each record.

The following 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:

A codebook of all the variables included in the 2004 Medical Conditions File is provided in a separate file (H87CB.PDF).

For more information on MEPS survey design, see Cohen 1997; Cohen 1997; and Cohen 1996. A copy of the survey instrument used to collect the information on this file is available on the MEPS website: http://www.meps.ahrq.gov.

This file contains 106,738 records. Each record represents one medical condition reported by a household survey respondent who resides in an eligible responding household and who has a positive person or family weight. Records meeting one of the following criteria are included on the file:

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 2004 MEPS person-level data using DUPERSID to append person-level characteristics such as demographic or health insurance characteristics to each record (see Section 4.0 for details). Since each record represents a single condition reported by a household respondent, some household respondents may have multiple medical conditions and thus will be represented on multiple records on this file. Other household respondents may have reported no medical conditions and thus will have no records on this file. Still other respondents may have 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 2004 MEPS Event Files (HC-085A through HC-085H) by using the link files provided in HC-085I, see HC-085I for details.

MEPS began in 1996 and several annual data files have been released. As additional years of data are produced, MEPS will become increasingly valuable for examining health care trends. 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 are attributable to sampling variation. MEPS expenditure estimates are especially sensitive to sampling variation due to the underlying skewed distribution of expenditures. For example, 1 percent of the population accounts for about one-quarter of all expenditures. The extent to which observations with extremely high expenditures are captured in the MEPS sample varies from year to year (especially for smaller population subgroups), which can produce substantial shifts in estimates of means or totals that are simply an artifact of the sample(s). 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 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 trend analyses of MEPS data such as pooling time periods for comparison (e.g. 1996-97 versus 1998-99), 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 because performing numerous statistical significance tests of trend increases the likelihood of inappropriately concluding a change is statistically significant.

The records on this file can be linked to all other 2004 MEPS-HC public use data sets by the sample person identifier (DUPERSID).

This codebook describes an ASCII data set and provides the following programming identifiers for each variable:

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 entitled "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.

The definitions of Dwelling Units (DUs) and Group Quarters 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 respondent (e.g., condition number 1, 2, 3, etc.) plus a control digit. The current range for CONDN is 10 - 578 and the largest range of records for any person on the file is 1 - 49. 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 last four digits of a person's CONDID.

PANEL04 is a constructed variable used to specify the panel number for the interview in which the condition was reported. PANEL04 will indicate either Panel 8 or Panel 9.

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.

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).

Certain conditions were a priori designated as "priority conditions" (PRIOLIST=1) due to their prevalence, expense, or relevance to policy. Some were long-term, life-threatening conditions, such as cancer, diabetes, emphysema, high cholesterol, HIV/AIDS, hypertension, ischemic heart disease, and stroke. Others were chronic manageable conditions, including arthritis, asthma, gall bladder disease, stomach ulcers, and back problems of any kind. In addition, Alzheimer’s disease or other dementias, as well as depression and anxiety disorders, were included in the priority list. For a complete listing of "priority conditions" see Appendix 4. 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 followup 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.

When a condition was first mentioned, respondents were asked whether it was due to an accident or injury (INJURY=1). Some injuries are also priority conditions (e.g., back pain).

The date a priority condition began (CONDBEGD, CONDBEGM, CONDBEGY) is collected only for conditions that appear on the priority list and are not accident/injury conditions. The date an accident or injury occurred (ACCDENTD, ACCDENTM, ACCDENTY) is collected only for accident/injury conditions, including accident/injury conditions that are also priority conditions.

When a respondent first reported a condition on the priority list (PRIOLIST=1) or a condition caused by an accident or injury (INJURY=1), the interviewer asked a series of questions regarding health care utilization for that condition and the effect of that condition on the person’s overall health. The names of these variables end in 1, 2, 3, 4, or 5 indicating the round in which they were asked. The following questions were asked in the round in which the respondent first reported a priority condition or a condition resulting from an injury:

When a respondent reported a condition that resulted from an accident or injury (INJURY=1), the following information was obtained from respondents during the round in which the injury was first reported:

For priority conditions only, additional information was obtained in rounds subsequent to the one in which the condition was first reported. This information was obtained only if the condition was experienced or there was an event, a prescribed medication, or a disability day associated with the condition in that round. If this occurred, the condition was "selected" for follow-up questions for the round.

For priority conditions selected in rounds after they were first reported, the following questions were asked in that round:

It should be noted that priority conditions reported in the Priority Conditions (PC) section of the MEPS questionnaire do not directly relate those listed as "priority conditions" on the Medical Conditions PUF. Unlike those on this file, the conditions identified in the PC section of the instrument were not added to the condition roster. Chronic conditions asked about in the PC section were asked in the context of "has person ever been told by a doctor or other health care professional that they have (condition)?", while the priority conditions on the Conditions PUF refer to those experienced by the respondent during a specific reference period. Some of those round-specific conditions were then determined to be a priority due to their prevalence, expense, or relevance to policy. There may be logical inconsistencies between items in the PC section and conditions on the Conditions PUF because they were asked in reference to different time periods.

Conditions can be added to the MEPS condition roster in one of several ways. Most directly, 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). Second, the condition may have been reported as the reason for one or more episodes of disability days. Finally, the condition may have been reported by the household level respondent as a condition "bothering" the person during the reference period (see question CE03).

Researchers need to be certain that they select the condition records appropriate for their analysis. There is no attempt made to reconcile the condition file and the responses to questions in the Priority Conditions section of the instrument. Two common ways of using condition information are 1) identifying persons through the PC section as "persons who reported ever having condition _____" or 2) identifying persons who had a specific condition named as a reason for one or more medical events (treated "prevalence"). Researchers are cautioned to use discretion in constructing other condition variables.

For Panel 8, Rounds 1 and 2 occurred in 2003 and conditions reported during these rounds are not included on this file unless the condition was identified as a priority condition (see the discussion of PRIORFLG below) or was related to a 2004 event. Note that if, in Rounds 3, 4, and 5 of Panel 8, the person "selects" a Round 1 or 2 condition as a serious condition experienced during the current round or the reason for a reported disability day, this condition does not appear on the 2004 file unless it is also a priority condition or is related to a 2004 event. For Panel 9, Rounds 4 and 5 occurred in 2005 and conditions reported during these rounds are not included on this file. Therefore, round-specific variables for Rounds 1 and 2 of Panel 8 are assigned an inapplicable code (-1) on all of the condition records for respondents in Panel 8, and round-specific variables for Rounds 4 and 5 of Panel 9 are assigned an inapplicable code (-1) on all of the condition records for respondents in Panel 9. Round-specific data for Rounds 4 and 5 pertain only to Panel 8; round-specific data for Rounds 1 and 2 pertain only to Panel 9, and both panels provide data from Round 3. (Note: Use PANEL04 to identify whether Round 3 variables were collected in Panel 8 or Panel 9.)

Conditions in this 2004 file first reported in Rounds 1 or 2 of Panel 8 that are priority conditions OR conditions resulting from an injury have round-specific data for those rounds included on the 2003 Medical Conditions File (HC-078). The variables PRIORFLG and INJURFLG indicate if the condition is "Not a priority/injury condition" (0), if "Additional information is included on the 2003 Medical Conditions File" (1), or if "All priority/injury information is included on the current file" (2). For a small number of records, additional round-specific data cannot be located on the file from the previous year. For 9 conditions from Panel 8 Rounds 1 and 2, round-specific information cannot be located in the 2004 Medical Conditions File, and additional round-specific information is not included on the 2003 Medical Conditions File. This situation occurs when a record is unweighted and therefore not included on the file in one year but is assigned a positive weight and included on the file in the subsequent year. The situation can also occur when a condition is incorrectly identified as not a priority condition in one year but is later updated to be a priority condition in the subsequent year.

Note: Priority conditions are generally chronic conditions. Even though a respondent may not have reported experiencing the condition with the round or an event, a prescribed medicine, or a disability day in 2004 due to the condition, analysts should consider that the respondent is probably still experiencing the condition. If a Panel 8 respondent reported a priority condition in Round 1 or 2 and did not have an event, a prescribed medicine, or a disability day for the condition in Round 3, 4, or 5, round-specific variables for Rounds 3, 4, and 5 are coded as –1. The only information provided on the current 2004 file for such conditions are the ICD9CODX, ICD9PROX, CCCODEX, and non-round-specific variables. These records are identified by PRIORFLG=1. Round-specific data from Rounds 1 and 2 for these records are available in the 2003 Medical Conditions File.

A set of constructed variables (CRND1 – CRND5) indicates the round in which the condition was first reported, and the subsequent round(s) in which the condition was selected. The condition may be reported or selected when the person reports an event, prescription medication, 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, prescription medications, or disability days. For example, consider a condition for which CRND1 = 0, CRND2 = 1, and CRND3 = 1. 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. CRND1 – CRND5 are not applicable for most pregnancies, prenatal visits, or deliveries due to the questionnaire design.

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.

The medical conditions and procedures reported by the Household Component respondent were recorded by the interviewer as verbatim text, which were 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 procedure was not specific enough to assign a code. ICD9PROX was set to -1 where the text strictly specified a condition and not a procedure.

In order to preserve respondent 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 2004 MEPS Event Files (HC-085A through HC-085H, refer to the link files provided in HC-085I) see HC-085I 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 40 records recoded in this manner on the 2004 Medical Conditions File.

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-085D).

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 H87SU.TXT file).

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 263 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. Note that 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.

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 H87SU.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 40 records recoded in this manner on the 2004 Medical Conditions File.

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 replace 065 through 075. In the accompanying codebook, the values of CCCODEX will be broken out into allowable ranges rather than provided in a minimum/maximum format.

The variables OBNUM, OPNUM, HHNUM, IPNUM, ERNUM, and RXNUM indicate the total number of 2004 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-085G, HC-085F, HC-085H, HC-085D, HC-085E, and HC-085A). Events associated with conditions include all utilization that occurred between January 1, 2004 and December 31, 2004.

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.

There is a single full year person-level weight (PERWT04F) 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 2004. 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.

The person-level weight PERWT04F was developed in several stages. Person-level weights for Panels 8 and 9 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 2004 composite weight was then formed by multiplying each weight from Panel 8 by the factor .49 and each weight from Panel 9 by the factor .51. 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.

The person-level weight for MEPS Panel 8 was developed using the 2003 full year weight for an individual as a "base" weight for survey participants present in 2003. For key, in-scope respondents who joined an RU some time in 2004 after being out-of-scope in 2003, the 2003 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 2004. These control figures were derived by scaling back the population totals obtained from the March 2004 CPS to correspond to a national estimate for the civilian noninstitutionalized population provided by the Census Bureau for December 2004. 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, 2004 is 289,659,890. Key, responding persons not in-scope on December 31, 2004 but in-scope earlier in the year retained, as their final Panel 8 weight, the weight after the nonresponse adjustment.

The person-level weight for MEPS Panel 9 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 2004 portion of Round 3 as well as raking to the same population control figures for December 2004 used for the MEPS Panel 8 weights. The same five variables employed for Panel 8 raking (census region, MSA status, race/ethnicity, sex, and age) were used for Panel 9 raking. Similarly, for Panel 9, key, responding persons not in-scope on December 31, 2004 but in-scope earlier in the year retained, as their final Panel 9 weight, the weight after the nonresponse adjustment.

Note that the MEPS Round 1 weights (for both panels with one exception as noted below) incorporated the following components: the original household probability of selection for the NHIS; ratio-adjustment to NHIS-based national population estimates at the household (occupied dwelling unit) level; adjustment for nonresponse at the dwelling unit level for Round 1; and poststratification to figures at the family and person level obtained from the March 2004 CPS data base.

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, 2004 is 289,659,890 (PERWT04F>0 and INSC1231=1). The weights of some persons out-of-scope on December 31, 2004 were also calibrated, this time using poststratification. Specifically, the weights of persons out-of-scope on December 31, 2004 who were in-scope some time during the year and also entered a nursing home during the year were poststratified to a corresponding control total obtained from the 1996 MEPS Nursing Home Component. The weights of persons who died while in-scope during 2004 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 293,527,003.

The target population for MEPS in this file is the 2004 U.S. civilian noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 2002 (Panel 8) and 2003 (Panel 9). New households created after the NHIS interviews for the respective Panels and consisting exclusively of persons who entered the target population after 2002 (Panel 8) or after 2003 (Panel 9) 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.

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-085I 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:

Cohen, S. B. (1997). A Sample Design of the 1996 Medical Expenditure Panel Survey Household Component, Rockville (MD): Agency for Healthcare Research and Quality; 1997. MEPS Methodology Report, No. 2. AHCPR Pub. No. 97-0027.

Cohen, J. W. (1997). A Design and Methods of the Medical Expenditure Panel Survey Household Component. Rockville (MD): Agency for Healthcare Research and Quality; 1997. MEPS Methodology Report, No.1. AHCPR Pub. No. 97-0026.

Cohen, S. B. (1996). The Redesign of the Medical Expenditure Panel Survey: A Component of the DHHS Survey Integration Plan. Proceedings of the COPAFS Seminar on Statistical Methodology in the Public Service.

Cox, B. 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.

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, 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.

VARIABLE	LABEL	SOURCE¹
PRIOLIST	Is Condition On Priority List	CN02
CONDBEGD	Date Condition Started -- Day	CN05
CONDBEGM	Date Condition Started -- Month	CN05
CONDBEGY	Date Condition Started -- Year	CN05
SEEDREV1	RD1: Ever Seen Dr For Cond	CN03, CN17
SEEDREV2	RD2: Ever Seen Dr For Cond	CN03, CN17
SEEDREV3	RD3: Ever Seen Dr For Cond	CN03, CN17
SEEDREV4	RD4: Ever Seen Dr For Cond	CN03, CN17
SEEDREV5	RD5: Ever Seen Dr For Cond	CN03, CN17
LSTSAW1	RD1: When Was Last Time Dr Was Seen	CN04
STILTR1	RD1: Is Pers Still Treated For Cond	CN11, CN18
STILTR2	RD2: Is Pers Still Treated For Cond	CN11, CN18
STILTR3	RD3: Is Pers Still Treated For Cond	CN11, CN18
STILTR4	RD4: Is Pers Still Treated For Cond	CN11, CN18
STILTR5	RD5: Is Pers Still Treated For Cond	CN11, CN18
OVRALL1	RD1: How Cond Affect Overall Health	CN13, CN19
OVRALL2	RD2: How Cond Affect Overall Health	CN13, CN19
OVRALL3	RD3: How Cond Affect Overall Health	CN13, CN19
OVRALL4	RD4: How Cond Affect Overall Health	CN13, CN19
OVRALL5	RD5: How Cond Affect Overall Health	CN13, CN19
WHOTYP1	RD1: Who Reported Condition Affect	CN13OV, CN19OV
WHOTYP2	RD2: Who Reported Condition Affect	CN13OV, CN19OV
WHOTYP3	RD3: Who Reported Condition Affect	CN13OV, CN19OV
WHOTYP4	RD4: Who Reported Condition Affect	CN13OV, CN19OV
WHOTYP5	RD5: Who Reported Condition Affect	CN13OV, CN19OV
FURTCA1	RD1: Further Treatment Recommended	CN14
FURTCA2	RD2: Further Treatment Recommended	CN14
FURTCA3	RD3: Further Treatment Recommended	CN14
FURTCA4	RD4: Further Treatment Recommended	CN14
FURTCA5	RD5: Further Treatment Recommended	CN14
FOLOCA1	RD1: Rcv FollowUp Care For Condition	CN15
FOLOCA2	RD2: Rcv FollowUp Care For Condition	CN15
FOLOCA3	RD3: Rcv FollowUp Care For Condition	CN15
FOLOCA4	RD4: Rcv FollowUp Care For Condition	CN15
FOLOCA5	RD5: Rcv FollowUp Care For Condition	CN15
SEEDREF1	RD1: Saw Dr In Reference Period	CN03, CN17
SEEDREF2	RD2: Saw Dr In Reference Period	CN03, CN17
SEEDREF3	RD3: Saw Dr In Reference Period	CN03, CN17
SEEDREF4	RD4: Saw Dr In Reference Period	CN03, CN17
SEEDREF5	RD5: Saw Dr In Reference Period	CN03, CN17
CRND1	Has Condition Information In Round	Constructed
CRND2	Has Condition Information In Round	Constructed
CRND3	Has Condition Information In Round	Constructed
CRND4	Has Condition Information In Round	Constructed
CRND5	Has Condition Information In Round	Constructed
PRIORFLG	Location Of Rnd Specific Priority Info	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
ACCDNWRK	Did Accident Occur At Work	CN07
ACDNTLOC	Where Did Accident Happen	CN08
INOUTHH	Was Accident Inside/Outside The House	CN09
VEHICLE	Was A Motor Vehicle Involved	CN10
GUN	Was A Gun Involved	CN10
WEAPON	Was Some Other Weapon Involved	CN10
POISON	Was Poison/Poisonous Substance Involved	CN10
FIREBURN	Was Fire/Burning Involved	CN10
DROWN	Was Drowning/Near-Drowning Involved	CN10
SPORTS	Was It A Sports Injury	CN10
FALL	Was It A Fall	CN10
ACDNTOTH	Was Something Else Involved	CN10
RECOVER	Fully Recovered From Condition	CN12
INJURFLG	Location Of Rnd Specific Injury Info	Constructed
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

1See the README file in the Survey Instruments section of the MEPS home page for information on the MEPS HC questionnaire sections (e.g., CN, DD) shown in the Source column.

Cancer (of any body part)
cancer
tumor
malignancy
malignant tumor
carcinoma
sarcoma
lymphoma
Hodgkin’s disease
leukemia
melanoma
metastasis
neuroma
adenoma

Diabetes
diabetes
diabetes mellitus
high blood sugar
juvenile diabetes (Type I diabetes)
adult-onset diabetes (Type II diabetes)
diabetic neuropathy

Emphysema
emphysema
chronic obstructive pulmonary disease (COPD)
chronic bronchitis (MUST use the word (“chronic”, only for adults)
chronic obstructive bronchitis (MUST use the word “chronic”, only for adults)
smoker’s cough

High Cholesterol
high cholesterol
high or elevated triglycerides
hyperlipidemia
hypercholesterolemia

Ischemic Heart Disease
ischemic heart disease (MUST use the word “ischemic”)
angina
angina pectoris
coronary artery disease blocked, obstructed, or occluded coronary arteries
arteriosclerosis
myocardial infarction
heart attack

Stroke
stroke
cerebral hemorrhage
cerebral aneurysm
transient ischemic accident
transient ischemic attack
apoplexy
carotid artery blockage
arterial thrombosis in brain
blood clot in brain

Arthritis
anything with the word “arthritis”
rheumatoid arthritis
degenerative arthritis
osteoarthritis
bursitis
rheumatism

Gall Bladder Disease
gall bladder disease, trouble, attacks, infection, or problems
gallstones

Stomach Ulcers
stomach ulcer
duodenal ulcer
peptic ulcer
bleeding ulcer
ulcerated stomach
perforated ulcer

Back Problems of Any Kind
back problems or pain of any kind (lower or upper back)
sore, hurt, injured, or stiff back backache
anything with the words ‘vertebra’, ‘vertebrae’, ‘lumbar’, ‘spine’, or ‘spinal’
sprained back
muscle spasms
back spasms
bad back
lumbago
sciatica or sciatic nerve problems
disc problems: herniated, ruptured, slipped, compressed, extruded, dislocated, deteriorated, or misaligned discs

Alzheimer’s Disease and Other Dementias
anything with the words ‘Alzheimer’s’ or ‘dementia’
organic brain syndrome

Depression and Anxiety Disorders
depression (including severe, chronic, or major depression)
dysthymia
dysthymic disorder
bipolar disorder
manic depression or manic depressive illness
anxiety attacks
panic attacks
anxiety
nerves
nervous condition
nervous breakdown

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