MEPS HC-085I: Appendix to MEPS 2004 Event Files HC-085A - HC-085H
November 2006
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406
TABLE OF CONTENTS
A. Data Use Agreement
B. Background
1.0 Household Component
2.0 Medical Provider Component
3.0 Insurance Component
4.0 Survey Management
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Using MEPS Data for Trend and Longitudinal Analysis
2.2 Codebook Format
2.3 Variable Naming and Source
2.4 Contents of File 1: Condition-Event Link File (CLNK)
2.5 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)
2.6 2004 Condition-Event Frequency Table
2.7 2004 Utilization and Expenditures Summary Table
3.0 Merging/Linking MEPS Data Files
3.1 Example A: Using the RXLK and CLNK Files with the Medical Conditions File (HC-087), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-085A and HC-085G)
3.2 Example B: Using the CLNK File with the Medical Conditions File (HC-087) and the Prescribed Medicines Event File (HC-085A)
3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-087) and Office-Based Medical Provider Visits Event File (HC-085G)
3.4 Example D: Using the RXLK File with the Other Medical Expenses Event File (HC-085C)
3.5 Limitations/Caveats of the CLNK File
3.6 Limitations/Caveats of the RXLK File
Attachment 1: Clinical Classification Code to ICD-9-CM Code Crosswalk (link to separate file)
Attachment 2: Sample SAS Jobs for Linking Examples
(link to separate file)
A. Data Use Agreement
Individual identifiers have been removed from the micro-data contained in these files. Nevertheless, under sections 308 (d) and 903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or the National Center for Health Statistics (NCHS) may not be used for any purpose other than for the purpose for which they were supplied; any effort to determine the identity of any reported cases is prohibited by law.
Therefore in accordance with the above referenced Federal Statute, it is understood that:
- No one is to use the data in this data set in any way except for statistical reporting and analysis; and
- If the identity of any person or establishment should be discovered inadvertently, then (a) no use will be made of this knowledge, (b) the Director Office of Management AHRQ will be advised of this incident, (c) the information that would identify any individual or establishment will be safeguarded or destroyed, as requested by AHRQ, and (d) no one else will be informed of the discovered identity; and
- No one will attempt to link this data set with individually identifiable records from any data sets other than the Medical Expenditure Panel Survey or the National Health Interview Survey.
By using these data you signify your agreement to comply with the above stated statutorily based requirements with the knowledge that deliberately making a false statement in any matter within the jurisdiction of any department or agency of the Federal Government violates Title 18 part 1 Chapter 47 Section 1001 and is punishable by a fine of up to $10,000 or up to 5 years in prison.
The Agency for Healthcare Research and Quality requests that users cite AHRQ and the Medical Expenditure Panel Survey as the data source in any publications or research based upon these data.
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B. Background
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.
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1.0 Household Component
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.
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2.0 Medical Provider Component
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.
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3.0 Insurance Component
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:
- A Bureau of the Census list frame of private sector business establishments.
- The Census of Governments from the Bureau of the Census.
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.
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4.0 Survey Management
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).
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C. Technical and Programming Information
1.0 General Information
This documentation describes the MEPS Public Use Release HC-085I, which is the Appendix to MEPS releases HC-085A through HC-085H. This release contains two data files, both of which are provided in ASCII (with related SAS and SPSS programming statements) and SAS versions: 1) the condition-event link file; and 2) the prescribed medicines-event link file. Also included in this release are two tables provided as both HTML and PDF files: 1) the condition-event frequency table and 2) the utilization and expenditures summary table.
This documentation offers a brief overview of the content and structure of the files and the codebooks (provided as files H85IF1CB.PDF and H85IF2CB.PDF). It contains the following sections:
Data File Information
Merging MEPS Data Files
Crosswalk of Clinical Classification Code to ICD-9-CM Code
Sample SAS Jobs for Linking
For more information on MEPS HC survey design see S. Cohen, 1997; J. Cohen, 1997; and S. Cohen, 1996. For information on the MEPS MPC design, see S. Cohen, 1998. Both reports, along with a copy of the survey instruments used to collect the information on this file, are available on the MEPS web site at the following address: http://www.meps.ahrq.gov.
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2.0 Data File Information
This public use data set consists of two data files containing variables for linkage of the MEPS 2004 event-level data files. File 1, the H85IF1 or CLNK file, is used for linking the MEPS condition file with the MEPS event files; File 2, the H85IF2 or RXLK file, is used for linking the MEPS prescribed medicines event file with other MEPS event files.
The CLNK file contains 5 variables and has a logical record length of 57 with an additional 2-byte carriage return/line feed at the end of each record. The RXLK file contains 5 variables and has a logical record length of 57 with an additional 2-byte carriage return/line feed at the end of each record.
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2.1 Using MEPS Data for Trend and Longitudinal Analysis
MEPS began in 1996 and several annual data files have been released. As more 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).
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2.2 Codebook Format
This codebook describes an ASCII data set and provides the following programming identifiers for each variable:
IDENTIFIER |
DESCRIPTION |
Name |
Variable name (maximum of 8 characters) |
Description |
Variable descriptor (maximum of 40 characters) |
Format |
Number of bytes |
Type |
Type of data: numeric (indicated by NUM) or character (indicated by CHAR) |
Start |
Beginning column position of variable in record |
End |
Ending column position of variable in record |
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2.3 Variable Naming and Source
In general, variable names reflect the content of the variable, with an 8 character limitation. All variables contained on Files 1 and 2 were derived from the CAPI.
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2.4 Contents of File 1: Condition-Event Link File (CLNK)
File 1 (H85IF1) or the CLNK file, contains the variables needed to link each record on the MEPS 2004 condition file, HC-087, with one or more records on the MEPS 2004 event files, HC-085A through HC-085H. Section 3.0 contains additional information on completing this linkage.
The 8-character variable DUPERSID uniquely identifies each person represented on the file. There may be more than one record on the CLNK file for a specific DUPERSID value.
CONDIDX is the ID that uniquely identifies each condition for a person and corresponds to a unique record on the MEPS 2004 Condition file, HC-087. There may be more than one record on the CLNK file for a specific CONDIDX value.
EVNTIDX is the 12-digit number that uniquely identifies each event for a person and corresponds to a unique record on one of the MEPS 2004 event files, HC-085B through HC-085H. (EVNTIDX is not included on the 2004 Prescription Medicines event file, HC-085A; rather, on this file the variable for linking with EVNTIDX on the CLNK file is LINKIDX.) There may be more than one record on the CLNK file for a specific EVNTIDX value.
CLNKIDX is the 24-digit number which uniquely identifies each record on the CLNK file and is the combination of CONDIDX + EVNTIDX. There is just one record on this file for each value of CLNKIDX, i.e., each unique combination of CONDIDX + EVNTIDX.
The variable EVENTYPE indicates the type of event record identified by EVNTIDX, and has the following values:
1 = MVIS – |
office-based medical provider visit event contained on MEPS
release HC-085G |
2 = OPAT – |
outpatient department visit event contained on MEPS release
HC-085F |
3 = EROM – |
emergency room visit event contained on MEPS release HC-085E |
4 = STAZ – |
inpatient hospital stay event contained on MEPS release
HC-085D |
7 = HVIS – |
home health visit event contained on MEPS release HC-085H |
8 = PMED – |
prescribed medicines event contained on MEPS release HC-085A |
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2.5 Contents of File 2: Prescribed Medicines-Event Link File (RXLK)
File 2 (H85IF2) or the RXLK file, contains the variables needed to link each record on the MEPS 2004 prescribed medicines file, HC-085A, with one or more records on the MEPS 2004 event files, HC-085B through HC-085H. Section 3.0 contains additional information on completing this linkage.
The 8-character variable DUPERSID uniquely identifies each person represented on the file. There may be more than one record on the RXLK file for a specific DUPERSID value.
EVNTIDX is the 12-digit number which uniquely identifies each event for a person and corresponds to a unique record on one of the MEPS 2004 event files, HC-085B through HC-085H. There may be more than one record on the RXLK file for a specific EVNTIDX value.
LINKIDX is the 12-digit number which identifies the record(s) on the prescribed medicines file, HC-085A which link to an event record. There may be more than one record on the RXLK file for a specific LINKIDX value, and there may be more than one record on the HC-085A file for a specific LINKIDX value.
RXLKIDX is the 24-digit number which uniquely identifies each record on the RXLK file, and is the combination of EVNTIDX + LINKIDX. There is just one record on this file for each value of RXLKIDX, i.e., each unique combination of EVNTIDX + LINKIDX.
The variable EVENTYPE indicates the type of event record identified by EVNTIDX, and has the following values:
1 = MVIS – |
office-based medical provider visit event
contained on MEPS release HC-085G |
2 = OPAT – |
outpatient department visit event contained on MEPS
release HC-085F |
3 = EROM – |
emergency room visit event contained on MEPS
release HC-085E |
4 = STAZ – |
inpatient hospital stay event contained on MEPS
release HC-085D |
5 = DVIS – |
dental visit event contained on MEPS release
HC-085B |
6 = OMED – |
other medical expense event contained on MEPS release HC-085C |
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2.6 2004 Condition-Event Frequency Table
The files H85IT1.HTM and H85IT1.PDF contain the MEPS 2004 Condition-Event Frequency table. This table contains unweighted and weighted counts of records on the MEPS 2004 event files, HC-085A through HC-085H, for each of the condition, procedure and clinical classification codes contained on the MEPS 2004 condition file, HC-087. Attachment 1 contains a crosswalk of the clinical classification codes to ICD-9-CM codes.
Note that, for conditions related to certain medical events, the ICD-9-CM codes on the Conditions 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. ICD-9-CM codes are collapsed into broader codes to ensure confidentiality. Because of this collapsing, it is possible for there to be duplicate ICD-9-CM condition or procedure codes linked to a single medical event when different fully-specified codes are collapsed into the same code. For more information on ICD-9-CM codes, see the HC-087 documentation.
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2.7 2004 Utilization and Expenditures Summary Table
The files H85IT2.HTM and H85IT2.PDF contain the MEPS 2004 Utilization and Expenditures Summary table. This table contains statistics for all of the utilization and expenditure variables contained on the MEPS 2004 Full Year Use and Expenditure Data file, HC-089. For each of these variables, the following statistics are provided from the HC-089 file, and from the corresponding event-level file(s) HC-085A through HC-085H:
Number of persons with positive person-level weight (PERWT04F) and with value GT 0 for that variable
Weighted sum of the variable
Weighted mean of the variable
The table also includes the technical specifications used to construct each of the person-level HC-082 variables from the event-level files.
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3.0 Merging/Linking MEPS Data Files
This section provides information on using each of the two HC-085I files, RXLK and CLNK, to link with the files contained in MEPS releases HC-087 and HC-085A through HC-085H. The linking procedure is described using several examples of deriving MEPS-based estimates. Also included in this section are several caveats related to using the RXLK and CLNK files.
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3.1 Example A: Using the RXLK and CLNK Files with the Medical Conditions File (HC-087), the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-085A and HC-085G)
This example calculates the total expenditures for prescribed medicines associated with office-based medical provider visits for asthma, using these files: the condition file (HC-087), the CLNK file (HC-085I1), the office-based medical provider visit event file (HC-085G), the RXLK file (HC-085I2), and the prescribed medicines event file (HC-085A). It includes the following major steps:
- From HC-087 file select only records with condition coded as asthma.
- Use the CLNK file to obtain unique record IDs of events which are linked to each of the selected asthma condition records.
- From the HC-085G file, select only records for non-telephone office-based medical provider visits for persons with a positive weight.
- Using the selected record IDs obtained from the CLNK file with the selected HC-085G records, identify only those visits which were for asthma.
- Use the RXLK file with the selected visit records which were for asthma, to obtain unique record IDs of prescribed medicine records from file HC-085A linked to those visits.
- Using these record IDs obtain the linked records from the HC-085A file and calculate the weighted mean of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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3.2 Example B: Using the CLNK File with the Medical Conditions File (HC-087) and the Prescribed Medicines Event File (HC-085A)
This example calculates the total expenditure for prescribed medicines associated with asthma, using the condition file (HC-087), the CLNK file and the prescribed medicines event file (HC-085A). It includes the following major steps:
- From HC-087 file select only records with condition coded as asthma.
- Use the CLNK file to obtain unique record IDs of events which are linked to each of the asthma condition records.
- Using these record IDs, obtain linked records from the HC-085A file and calculate the weighted mean of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-087) and Office-Based Medical Provider Visits Event File (HC-085G)
This example calculates the total expenditures for office-based medical provider visits associated with asthma, using the condition file (HC-087), the CLNK file and the office-based medical provider visits event file (HC-085G). It includes the following major steps:
- From HC-087 file select only records with condition coded as asthma.
- Use the CLNK file to obtain unique record IDs of events which are linked to each of the asthma condition records.
- From the HC-085G file, select only records for non-telephone office-based medical provider visits for persons with a positive weight.
- Using the selected record IDs obtained from the CLNK file, with the selected HC-085G records, identify only those visits which were for asthma and calculate the weighted mean of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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3.4 Example D: Using the RXLK File with the Other Medical Expenses Event File (HC-085C)
This example calculates the total prescription expenditures for other medical events reported by the household with type of other medical expense indicated as insulin (OMTYPEX=2), using the RXLK file and the other medical expenses event file (HC-085C). It includes the following major steps:
- From HC-085C file select only records for other medical expense type of insulin, for persons with a positive weight.
- Use the RXLK file to obtain unique record IDs of prescribed medicine events which are linked to each of the selected other medical expense records.
- Use the selected record IDs from the RXLK file to obtain the linked prescribed medicines event records from the HC-085A file, and calculate the weighted sum of the expenditure variable.
Attachment 2 contains a copy of the SAS job for this example.
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3.5 Limitations/Caveats of the CLNK File
When using the CLNK file, analysts should keep in mind that (1) conditions are self-reported and (2) there may be multiple conditions associated with an event. Users should also note that not all events link to the condition file.
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3.6 Limitations/Caveats of the RXLK File
When using RXLK, analysts should keep in mind that one event record can link to more than one prescribed medicine record. Conversely, a prescribed medicine record may link to more than one event record in the same event file and/or more than one event record in other event files. When this occurs, it is up to the analyst to determine how the prescribed medicine expenditures should be allocated among those medical events.
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Attachment 1: Clinical Classification Code to ICD-9-CM Code Crosswalk (link to separate file)
Attachment 2: Sample SAS Jobs for Linking Example (link to separate file)
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