| MEPS HC-096: 2005 Medical Conditions November 2007 Agency for Healthcare Research and Quality Center for Financing, Access, and Cost Trends 540 Gaither Road Rockville, MD 20850 (301) 427-1406 A. Data Use Agreement Individual identifiers have been removed from the micro-data contained in these files. Nevertheless, under sections 308 (d) and 903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or the National Center for Health Statistics (NCHS) may not be used for any purpose other than for the purpose for which they were supplied; any effort to determine the identity of any reported cases is prohibited by law. Therefore in accordance with the above referenced Federal Statute, it is understood that:
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 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 households is selected. Because the data collected are comparable to those from earlier medical expenditure surveys conducted in 1977 and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample size is about 15,000 households. Data can be analyzed at either the person or event level. Data must be weighted to produce national estimates. The set of households selected for each panel of the MEPS HC is a subsample of households participating in the previous year's National Health Interview Survey (NHIS) conducted by the National Center for Health Statistics. The NHIS sampling frame provides a nationally representative sample of the U.S. civilian non-institutionalized population and reflects an oversample of blacks and Hispanics. MEPS oversamples additional policy relevant sub-groups such as Asians and low income households. The linkage of the MEPS to the previous year's NHIS provides additional data for longitudinal analytic purposes. 2.0 Medical Provider Component Upon completion of the household CAPI interview and obtaining permission from the household survey respondents, a sample of medical providers are contacted by telephone to obtain information that household respondents can not accurately provide. This part of the MEPS is called the Medical Provider Component (MPC) and information is collected on dates of visit, diagnosis and procedure codes, charges and payments. The Pharmacy Component (PC), a subcomponent of the MPC, does not collect charges or diagnosis and procedure codes but does collect drug detail information, including National Drug Code (NDC) and medicine name, as well as date filled and sources and amounts of payment. The MPC is not designed to yield national estimates. It is primarily used as an imputation source to supplement/replace household reported expenditure information. 3.0 Survey Management and Data Collection MEPS HC and MPC data are collected under the authority of the Public Health Service Act. Data are collected under contract with Westat, Inc. Data sets and summary statistics are edited and published in accordance with the confidentiality provisions of the Public Health Service Act and the Privacy Act. The National Center for Health statistics (NCHS) provides consultation and technical assistance. As soon as data collection and editing are completed, the MEPS survey data are released to the public in staged releases of summary reports, micro data files, and tables via the MEPS Web site: www.meps.ahrq.gov. Selected data can be analyzed through MEPSnet, an on-line interactive tool designed to give data users the capability to statistically analyze MEPS data in a menu-driven environment. Additional information on MEPS is available from the MEPS project manager or the MEPS public use data manager at the Center for Financing Access and Cost Trends, Agency for Healthcare Research and Quality, 540 Gaither Road, Rockville, MD 20850 (301-427-1406). C. Technical and Programming Information This documentation describes the data contained in MEPS Public Use Release HC-096, which is one in a series of public use data files to be released from the 2005 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 2005 MEPS HC. The file contains 81 variables and has a logical record length of 195 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 A codebook of all the variables included in the 2005 Medical Conditions File is provided in a separate file (H96CB in PDF and HTML formats). 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: www.meps.ahrq.gov. This file contains 104,855 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: In Panel 10:
In Panel 9:
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 2005 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 2005 MEPS Event Files (HC-094A through HC-094H) by using the link files provided in HC-094I. (See HC-094I for details.) The codebook and data file sequence lists variables in the following order: Unique person identifiers Note that the person identifier is unique within this data year. See the section on pooling annual files, 4.1, for details. The following reserved code values are used:
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. 2.5.1 Identifier Variables (DUID-CONDRN) 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 - 610 and the largest range of records for any person on the file is 1 - 53. 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 9 or Panel 10. 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. 2.5.2 Medical Condition Variables (PRIOLIST-CCCODEX) 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).
2.5.2.1 Priority Conditions and Injuries 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). 2.5.2.2 Date Priority Condition Began/Accident Occurred 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. 2.5.2.3 Round-Specific Questions for Priority Conditions and Injuries 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:
Note that the variables WHOTYP1 – WHOTYP5 are no longer included in this public release. The corresponding questions were removed from the MEPS household component starting in 2005. 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:
Note that the variables WHOTYP1 – WHOTYP5 are no longer included in this public release. The corresponding questions were removed from the MEPS household component starting in 2005. 2.5.2.4 Considerations for Making Estimates Using the MEPS Conditions File 2.5.2.4.1 Conditions File vs. Priority Conditions It should be noted that priority conditions reported in the Priority Conditions (PC) section of the MEPS questionnaire do not directly relate to 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. Researchers should use their judgment in using this variable and related information, keeping in mind that the PRIOLIST flag is a manual process and due to human error some information may be missing or inaccurately reported. 2.5.2.4.2 Sources for Conditions on the MEPS Conditions File 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. 2.5.2.5 Treatment of Data from Rounds Not Occurring in 2005 For Panel 9, Rounds 1 and 2 occurred in 2004 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 2005 event. Note that if, in Rounds 3, 4, and 5 of Panel 9, 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 2005 file unless it is also a priority condition or is related to a 2005 event. For Panel 10, Rounds 4 and 5 occurred in 2006 and conditions reported during these rounds are not included on this file. Therefore, round-specific variables for Rounds 1 and 2 of Panel 9 are assigned an inapplicable code (-1) on all of the condition records for respondents in Panel 9, and round-specific variables for Rounds 4 and 5 of Panel 10 are assigned an inapplicable code (-1) on all of the condition records for respondents in Panel 10. Round-specific data for Rounds 4 and 5 pertain only to Panel 9; round-specific data for Rounds 1 and 2 pertain only to Panel 10, and both panels provide data from Round 3. (Note: Use PANEL to identify whether Round 3 variables were collected in Panel 9 or Panel 10.) Conditions in this 2005 file first reported in Rounds 1 or 2 of Panel 9 that are priority conditions OR conditions resulting from an injury have round-specific data for those rounds included on the 2004 Medical Conditions File (HC-087). The variables PRIORFLG and INJURFLG indicate if the condition is "Not a priority/injury condition" (0), if "Additional information is included on the 2004 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 7 conditions from Panel 9 Rounds 1 and 2, round-specific information cannot be located in the 2005 Medical Conditions File, and additional round-specific information is not included on the 2004 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, an event, a prescribed medicine, or a disability day in 2005 due to the condition, analysts should consider that the respondent is probably still experiencing the condition. If a Panel 9 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 2005 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 2004 Medical Conditions File. 2.5.2.6 Rounds in Which Conditions Were Reported/Selected (CRND1 – CRND5) 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. 2.5.2.7 Disability Flag Variables 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. 2.5.2.8 Diagnosis Condition and Procedure Codes 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 2005 MEPS Event Files (HC-094A through HC-094H) refer to the link files provided in HC-094I, and see HC-094I 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 32 records recoded in this manner on the 2005 Medical Conditions File. The person’s age was determined by linking the 2005 Medical Conditions File to the 2004 and 2005 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-094D). 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 H96SU.TXT file). 2.5.2.9 Clinical Classification Codes 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 H96SU.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 32 records recoded in this manner on the 2005 Medical Conditions File. The person’s age was determined by linking the 2005 Medical Conditions File to the 2004 and 2005 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 replace 065 through 075. Analysts should use the clinical classification codes listed in the Conditions PUF document (HC-096) and the Appendix to the Event Files (HC-094I) document when analyzing MEPS conditions data. Although there is a list of clinical classification codes and labels on the Healthcare Cost and Utilization Project (HCUP) Website, if updates to these codes and/or labels are made on the HCUP Website after the release of the 2005 MEPS PUFs, these updates will not be reflected in the 2005 MEPS data. 2.5.3 Utilization Variables (OBNUM – RXNUM) The variables OBNUM, OPNUM, HHNUM, IPNUM, ERNUM, and RXNUM indicate the total number of 2005 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-094G, HC-094F, HC-094H, HC-094D, HC-094E, and HC-094A). Events associated with conditions include all utilization that occurred between January 1, 2005 and December 31, 2005. 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 (PERWT05F) assigned to each record for each key, in-scope person who responded to MEPS for the full period of time that he or she was in-scope during 2005. A key person either was a member of an NHIS household at the time of the NHIS interview, or became a member of a family associated with such a household after being out-of-scope at the time of the NHIS (the latter circumstance includes newborns as well as persons returning from military service, an institution, or living outside the United States). A person is in-scope whenever he or she is a member of the civilian noninstitutionalized portion of the U.S. population. 3.2 Details on Person Weight Construction The person-level weight PERWT05F was developed in several stages. Person-level weights for Panels 9 and 10 were created separately. The weighting process for each panel included an adjustment for nonresponse over time and calibration to independent population figures. The calibration was initially accomplished separately for each panel by raking the corresponding sample weights to Current Population Survey (CPS) population estimates based on five variables. The five variables used in the establishment of the initial person-level control figures were: census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, non-Hispanic with black as sole reported race, non-Hispanic with Asian as sole reported race, and other); sex; and age. A 2005 composite weight was then formed by multiplying each weight from Panel 9 by the factor .5 and each weight from Panel 10 by the factor .5. The choice of factors reflected the relative sample sizes of the two panels, helping to limit the variance of estimates obtained from pooling the two samples. The composite weight was again raked to the same set of CPS-based control totals. When poverty status information derived from income variables became available, a final raking was undertaken on the previously established weight variable. Control totals were established using poverty status (five categories: below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty) as well as the original five variables used in the previous calibrations. The person-level weight for MEPS Panel 9 was developed using the 2004 full year weight for an individual as a "base" weight for survey participants present in 2004. For key, in-scope respondents who joined an RU some time in 2005 after being out-of-scope in 2004, the 2004 family weight associated with the family the person joined served as a "base" weight. The weighting process included an adjustment for nonresponse over Rounds 4 and 5 as well as raking to population control figures for December 2005. These control figures were derived by scaling back the population totals obtained from the March 2005 CPS to correspond to a national estimate for the civilian noninstitutionalized population provided by the Census Bureau for December 2005. Variables used in the establishment of person-level control figures included: census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, Asian but non-Hispanic, and other); sex; and age. Overall, the weighted population estimate for the civilian noninstitutionalized population on December 31, 2005 is 292,372,718. Key, responding persons not in-scope on December 31, 2005 but in-scope earlier in the year retained, as their final Panel 9 weight, the weight after the nonresponse adjustment. The person-level weight for MEPS Panel 10 was developed using the MEPS Round 1 person-level weight as a "base" weight. For key, in-scope respondents who joined an RU after Round 1, the Round 1 family weight served as a "base" weight. The weighting process included an adjustment for nonresponse over Round 2 and the 2005 portion of Round 3 as well as raking to the same population control figures for December 2005 used for the MEPS Panel 9 weights. The same five variables employed for Panel 9 raking (census region, MSA status, race/ethnicity, sex, and age) were used for Panel 10 raking. Similarly, for Panel 10, key, responding persons not in-scope on December 31, 2005 but in-scope earlier in the year retained, as their final Panel 10 weight, the weight after the nonresponse adjustment. Note that the MEPS Round 1 weights (for both panels with one exception as noted below) incorporated the following components: the original household probability of selection for the NHIS; ratio-adjustment to NHIS-based national population estimates at the household (occupied dwelling unit) level; adjustment for nonresponse at the dwelling unit level for Round 1; and poststratification to figures at the family and person level obtained from the March 2005 CPS data base. 3.2.3 The Final Weight for 2005 Variables used in the establishment of person-level control figures included: poverty status (below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty); census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, non-Hispanic with black as sole reported race, non-Hispanic with Asian as sole reported race, and other); sex; and age. Overall, the weighted population estimate for the civilian noninstitutionalized population for December 31, 2005 is 292,372,718 (PERWT05F>0 and INSC1231=1). The weights of some persons out-of-scope on December 31, 2005 were also calibrated, this time using poststratification. Specifically, the weights of persons out-of-scope on December 31, 2005 who were in-scope some time during the year and also entered a nursing home during the year were poststratified to a corresponding control total obtained from the 1996 MEPS Nursing Home Component. The weights of persons who died while in-scope during 2005 were poststratified to corresponding estimates derived using data obtained from the Medicare Current Beneficiary Survey (MCBS) and Vital Statistics information provided by the National Center for Health Statistics (NCHS). Separate control totals were developed for the "65 and older" and "under 65" civilian noninstitutionalized populations. The sum of the person-level weights across all persons assigned a positive person level weight is 292,372,718. The target population for MEPS in this file is the 2005 U.S. civilian noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 2003 (Panel 9) and 2004 (Panel 10). New households created after the NHIS interviews for the respective Panels and consisting exclusively of persons who entered the target population after 2003 (Panel 9) or after 2004 (Panel 10) are not covered by MEPS. Neither are previously out-of-scope persons who join an existing household but are unrelated to the current household residents. Persons not covered by a given MEPS panel thus include some members of the following groups: immigrants; persons leaving the military; U.S. citizens returning from residence in another country; and persons leaving institutions. The set of uncovered persons constitutes only a small segment of the MEPS target population. 3.3 Using MEPS Data for Trend Analysis MEPS began in 1996, and the utility of the survey for analyzing health care trends expands with each additional year of data. However, it is important to consider a variety of factors when examining trends over time using MEPS. Statistical significance tests should be conducted to assess the likelihood that observed trends may be attributable to sampling variation. The length of time being analyzed should also be considered. In particular, large shifts in survey estimates over short periods of time (e.g. from one year to the next) that are statistically significant should be interpreted with caution, unless they are attributable to known factors such as changes in public policy, economic conditions, or MEPS survey methodology. Looking at changes over longer periods of time can provide a more complete picture of underlying trends. Analysts may wish to consider using techniques to smooth or stabilize analyses of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97 versus 2004-05), working with moving averages, or using modeling techniques with several consecutive years of MEPS data to test the fit of specified patterns over time. Finally, researchers should be aware of the impact of multiple comparisons on Type I error. Without making appropriate allowance for multiple comparisons, undertaking numerous statistical significance tests of trends increases the likelihood of inappropriately concluding that a change has taken place. 4.0 Merging/Linking MEPS Data Files 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-094I 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:
PROC SORT DATA=PERS(KEEP=DUPERSID AGE SEX EDUCLEVL) PROC SORT DATA=COND; BY DUPERSID; DATA COND; 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 To facilitate analysis of subpopulations and/or low prevalence events, it may be desirable to pool together more than one year of data to yield sample sizes large enough to generate reliable estimates. For more details on pooling MEPS data files see www.meps.ahrq.gov/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036. Starting in Panel 9, values for DUPERSID from previous panels will occasionally be re-used. Therefore, it is necessary to use the panel variable (PANEL) in combination with DUPERSID to ensure unique person-level identifiers across panels. Creating unique records in this manner is advised when pooling MEPS data across multiple annual files that have one or more identical values for DUPERSID. MEPS Panel Longitudinal Weight files containing estimation variables to facilitate longitudinal analysis are available for downloading in the data section of the MEPS Web site. 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. (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. Appendix 1 Variable-Source Crosswalk Appendix 1 – Variable to Source Crosswalk UNIQUE IDENTIFIER VARIABLES
MEDICAL CONDITION VARIABLES
UTILIZATION VARIABLES
WEIGHTS AND VARIANCE ESTIMATION VARIABLES
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. 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 Appendix 4 – List of Priority Conditions A. LONG-TERM, LIFE THREATENING CONDITIONS: Cancer (of any body part)
Diabetes
Emphysema
High Cholesterol
HIV/AIDS
Hypertension
Ischemic Heart Disease
Stroke
B. CHRONIC, MANAGEABLE CONDITIONS: Arthritis
Asthma
Gall Bladder Disease
Stomach Ulcers
Back Problems of Any Kind
C. MENTAL HEALTH ISSUES: Alzheimer’s Disease and Other Dementias
Depression and Anxiety Disorders
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