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MEPSnet/HC Documentation for 1997 Full Year Data
December 2001
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406


The purpose of this documentation is to assist the user in identifying and utilizing MEPS public use variables through MEPSnet, an online interactive statistical tool. Users should note that the MEPSnet data file is a subset of public use file HC20: 1997 Full Year Consolidated Data File. The contents of the MEPSnet data file are limited to variables that can be used in descriptive analyses only. Hence, variables that require further data editing or are the building blocks for more analytic variables are not included in the MEPSnet data file. Analyses requiring such variables should be performed using the full HC20 public use data file. Similarly, this documentation focuses on the variables available in MEPSnet only. Detailed documentation is available for all 1997 public use variables in the codebook and documentation for HC20: 1997 Full Year Consolidated Data File.

Table of Contents

Background

Household Component
General Information
Codebook Structure
Reserved Codes
Codebook Format
Variable Naming Conventions
MEPSnet Data File Contents
Family Composition
Geographic Variables
Demographic Variables
Age
Sex
Race, Race/Ethnicity, Hispanic Ethnicity, and Hispanic Ethnicity Group
Marital Status
Student Status and Educational Attainment
Military Service and Service Era
Income Variables
Income Top-Coding
Poverty Status

Employment Variables

Health Insurance Variables

Health Status Variables

Utilization, Expenditures and Source of Payment Variables

Expenditure Definition
Data Sources on Expenditures
Imputation for Missing Expenditures and Data Adjustments
Methodology for Flat Fee Expenditures
Zero Expenditures
Source of Payment Categories
Charge Variables
Utilization and Expenditure Variables by Type of Medical Service
Medical Provider Visits (i.e., Office-Based Visits)
Hospital Events
Hospital Outpatient Visits
Hospital Emergency Room Visits

Hospital Inpatient Stays
Dental Visits
Home Health Care
Vision Aids
Other Medical Equipment and Services
Prescribed Medicines
Prescribed Medicines Data Collected
Prescribed Medicines Data Editing and Imputation
Variable Description Summary
Survey Administration Variables
Demographic Variables
Income Variables
Employment Variables
Health Insurance Variables
Health Status Variables

Background

This documentation describes public use data from the Medical Expenditure Panel Survey (MEPS). The survey provides a new and extensive data set on the use of health services and health care in the United States.

The Medical Expenditure Panel Survey (MEPS) is conducted to provide nationally representative estimates of health care use, expenditures, sources of payment, and insurance coverage for the U.S. civilian non-institutionalized population. MEPS also includes a nationally representative survey of nursing homes and their residents. MEPS is cosponsored by the Agency for Healthcare Research and Quality (AHRQ) and the National Center for Health Statistics (NCHS).

MEPS comprises three component surveys: the Household Component (HC), the Medical Provider Component (MPC) and the Insurance Component (IC), The HC is the core survey, and it forms the basis for the MPC sample and part of the IC sample. Together these 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.

MEPS is the third in a series of national probability surveys conducted by AHRQ on the financing and use of medical care in the United States. The National Medical Care Expenditure Survey (NMCES, also known as NMES-1) was conducted in 1977, the National Medical Expenditure Survey (NMES-2) in 1987. Beginning in 1996, MEPS continues this series with design enhancements and efficiencies that provide a more current data resource to capture the changing dynamics of the health care delivery and insurance system.

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Household Component

The MEPS HC, a nationally representative survey of the U.S. civilian non-institutionalized population, collects medical expenditure data at both the person and household levels. 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 uses an overlapping panel design in which data are collected through a preliminary contact followed by a series of five rounds of interviews over a 2 1/2 year period. Employing computer-assisted personal interviewing (CAPI) technology, 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 of households to provide overlapping panels of survey data and, when combined with other ongoing panels, will provide continuous and current estimates of health care expenditures.

The sample of households selected for the MEPS HC is drawn from among respondents to the NHIS, conducted by NCHS. The NHIS provides a nationally representative sample of the U.S. civilian non-institutionalized population, with oversampling of Hispanics and blacks.

MEPS data are collected under the authority of the Public Health Service Act. They are edited and published in accordance with the confidentiality provisions of this act and the Privacy Act. NCHS provides consultation and technical assistance.

General Information

This documentation describes 1997 full-year data from the Medical Expenditure Panel Survey Household Component (MEPS HC). This data file provides information collected on a nationally representative sample of the civilian non-institutionalized population of the United States for calendar year 1997.

This dataset contains variable and frequency distributions for a total of 34,551 persons who participated in the MEPS Household Component of the Medical Panel Expenditure Survey in 1997. This count includes all household survey respondents who resided in eligible responding households. The persons were part of one of the two MEPS panels that collected data about 1997: Rounds 3, 4, and 5 of Panel 1 or Rounds 1, 2, and 3 of Panel 2. Of these persons, 32,636 were assigned a positive person level weight. Both weighted and unweighted frequencies are provided for each variable. Using MEPSnet, data for these persons can be used to make national estimates for the civilian non-institutionalized U. S. population for 1997.

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Codebook Structure

The codebook and data file sequence lists variables in the following order:

  • Unique person identifiers
  • Geographic variables
  • Demographic variables
  • Income and Tax Filing variables
  • Employment variables
  • Health Insurance variables
  • Health Status variables
  • Utilization and Expenditure variables
  • Weight and variance estimation variables

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Reserved Codes

The following reserved code values are used:

VALUE DEFINITION
-1 INAPPLICABLE Question was not asked due to skip pattern
-7 REFUSED Question was asked and respondent refused to answer question.
-8 DK Question was asked and respondent did not know answer
-9 NOT ASCERTAINED     Interviewer did not record the data

Codebook Format

This codebook provides the following programming identifiers for each variable:

IDENTIFIER      DESCRIPTION
Name Variable name (maximum of 8 characters)
Description Variable descriptor (maximum 40 characters)
Format Number of bytes
Type Type of data: numeric (indicated by NUM) or character (indicated by CHAR)
Start Beginning column position of variable in record
End Ending column position of variable in record

Variable Naming Conventions

In general, variable names reflect the content of the variable, with an eight-character limitation. Edited variables end in an X, and are so noted in the variable label. The last two characters in round-specific variables denote the rounds of data collection, Round 3, 4, or 5 of Panel 1 and Round 1, 2, or 3 of Panel 2. Unless otherwise noted, variables that end in 97 represent status as of December 31, 1997.

Variables contained in this delivery were derived either from the questionnaire itself or from the CAPI. The source of each variable is identified in the section entitled "Appendix D. Variable-Source Crosswalk" of the full public use file documentation. Sources for each variable are indicated in one of four ways: (1) variables derived from CAPI or assigned in sampling are so indicated; (2) variables derived from complex algorithms associated with re-enumeration are labeled "RE Section"; (3) variables that are collected by one or more specific questions in the instrument have those question numbers listed in the Source column; (4) variables constructed from multiple questions using complex algorithms are labeled "Constructed."

Please note that variables names in MEPSnet may not always correspond to the variable names found on the corresponding public use file. Users are encouraged to read the documentation for detailed information on individual variables.

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MEPSnet Data File Contents

Family Composition

Many variables were constructed using data from specific rounds, if available. If data were missing from the target round, but were available in another round, data from that other round were used in the variable construction. If no valid data were available during any round of data collection, an appropriate reserved code was assigned.

Reporting Units and Families

A Reporting Unit (RU) is a person or group of persons in the sampled dwelling unit who are related by blood, marriage, adoption, foster care or other family association. Each RU was interviewed as a single entity for MEPS. Thus, the RU serves chiefly as a family-based "survey" operations unit rather than an analytic unit. Regardless of the legal status of their association, two persons living together as a "family" unit were treated as a single reporting unit if they chose to be so identified. Examples of different types of reporting units are:

1. A married daughter and her husband living with her parents in the same dwelling unit constitute a single reporting unit.

2. A husband and wife and their unmarried daughter, age 18, who is living away from home while at college constitute two reporting units.

3. Three unrelated persons living in the same dwelling unit would each constitute a distinct reporting unit (a total of three reporting units)

Unmarried college students (less than 24 years of age) who usually live in the sampled household, (but were living away from home and going to school at the time of the Round 3/1 MEPS interview) were treated as a reporting unit separate from that of their parents for the purpose of data collection. The end-of-year status variable RUSIZE97 indicates the number of persons in each RU, treating each student as a single RU separate from their parents. Thus, students are not included in the RUSIZE count of their parents RU. However, for many analytic objectives, the student reporting units would be combined with their parents' reporting unit, treating the combined entity as a single family. Family identifier and size variables are described below and include students with their parent’s reporting unit.

PANEL97 is a constructed variable used to specify the panel number for the interview. PANEL97 will indicate either Panel 1 or Panel 2 for each interview.

The end-of-year status variable FAMSZE97 indicates the number of persons associated with a single family unit (i.e., persons related to one another by blood, marriage, adoption, foster care, or self-identified as a single unit) after students are linked to their associated parent RUs for analytical purposes. FCSZ1231 indicates the number of persons associated with a single CPS-like family unit. Some of the distinctions between CPS and MEPS defined families are that MEPS families include and CPS families do not include: non-married partners, foster children, and in-laws. These persons are considered as members of separate families for CPS-like families. The reason CPS-like families are defined is so that a poverty status classification variable consistent with established definitions of poverty can be assigned to the CPS-like families and used for weight poststratification purposes.

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Geographic Variables

The variable REGION indicates the Census region for the RU for 1997. MSA indicates whether or not the RU is found in a metropolitan statistical area in 1997.

Demographic Variables

Demographic variables provide information about the demographic characteristics of each person from the MEPS-HC. The characteristics include age, sex, race, ethnicity, educational attainment, marital status, and military service.

The variables describing demographic status [i.e., related to marital status (MARRY), educational attainment (EDUCAT)], of the person for 1997 were developed using the following algorithm: data were taken from Round 5/3 counterpart if non-missing; else, if missing, data were taken from the Round 4/2 counterpart; else from the Round 3/1 counterpart. If no valid data was available during any of these Rounds of data collection, the same algorithm was followed to assign a missing value other than -1 (Inapplicable).

Age

Date of birth and age for each RU member were asked or verified during each MEPS interview.

If date of birth was available, age was calculated based on the difference between date of birth and date of interview (or the date of death, if the person died prior to the interview date). Inconsistencies between the calculated age and the age reported during the CAPI interview were reviewed and resolved. For purposes of confidentiality, the variables AGE was top coded at 90 years.

When date of birth was not provided but age was provided (either from the MEPS interviews or the 1995-1996 NHIS data), the month and year of birth were assigned randomly from among the possible valid options. For any cases still not accounted for, age was imputed using

  1. the mean age difference between MEPS participants with certain family relationships (where available) or
  2. the mean age value for MEPS participants.

For example, a mother’s age is imputed as the average age of her children plus 26, where 26 is the mean age difference between MEPS mothers and their children. Or a wife’s age is imputed as the husband’s age minus 3, where 3 is the mean age difference between MEPS wives and husbands.

AGE was constructed using the following algorithm: Age was taken from the Dec 31st variable if non-missing; else, if missing, age was taken from Round 5/3 counterpart if non-missing; else from the Round 4/2 counterpart; else from the Round 3/1 counterpart. If no valid data was available during any of these Rounds of data collection, the same algorithm was followed to assign a missing value other than -1 (Inapplicable).

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Sex

Data on the sex of each RU member (SEX) were initially determined from the 1995 NHIS for Panel 1 and from the 1996 NHIS for Panel 2. The SEX variable was verified and, if necessary, corrected during each MEPS interview. The data for new RU members (persons who were not members of the RU at the time of the NHIS interviews) was also obtained during each MEPS Round. When sex of the RU member was not available from the NHIS interviews and was not ascertained during one of the subsequent MEPS interviews, it was assigned in the following way. The person’s first name was used to assign sex, if obvious. If the person’s first name provided no indication of gender, then family relationships were reviewed. If neither of these approaches made it possible to determine the individual’s sex, sex was randomly assigned.

Race, Race/Ethnicity, Hispanic Ethnicity, and Hispanic Ethnicity Group

Race (RACEX) and Hispanic ethnicity (HISPANX) questions were initially asked for each RU member during the Round 1 MEPS interview. If this information was not obtained in Round 1, the questions were asked in subsequent Rounds. When race and/or ethnicity was not reported in the Rounds, values for these variables were obtained based on the following priority order. When available, they were obtained from the originally collected NHIS data (1995 or 1996, depending on the Panel). If not ascertained, the race, and/or ethnicity were assigned based on relationship to other members of the RU using a priority ordering that gave precedence to blood relatives in the immediate family. The variable RACETHNX indicating both race and ethnicity (e.g., with categories such as "Hispanic" and "black but not Hispanic") reflects the imputations done for RACEX and HISPANX. The specific Hispanic ethnicity group is given in the unedited variable HISPCAT.

Marital Status

Current marital status was collected and/or updated during every Round of the MEPS interview. This information was obtained in RE13 and RE97 and summarized as MARRY. Persons under the age of 16 were coded as 6 (under 16 – inapplicable). If marital status of a specified round differed from that of the previous Round, then the marital status of the specified Round was edited to reflect a change during the Round (e.g., married in Round, divorced in Round, separated in Round, or widowed in Round).

In instances where there were discrepancies between the marital status of two individuals within a family, other person-level variables were reviewed to determine the edited marital status for each individual. Thus, when one spouse was reported as married and the other spouse reported as widowed, the data were reviewed to determine if one partner should be coded as 8 (widowed in Round).

Four edits were performed to ensure minimal consistency across rounds. First, a person could not be coded as "Never Married" after previously being coded as any other marital status (e.g. "Widowed"). Second, a person could not be coded as "Under 16 – Inapplicable" after being previously coded as any other marital status. Third, a person could not be coded as "Married in Round" after being coded as "Married" in the Round immediately preceding. Fourth, a person could not be coded as an "in Round" code (e.g., "widowed in Round") in two subsequent Rounds. Because no other edits were performed, and since marital status can change across Rounds, unlikely sequences for marital status across the Round-specific variables do exist.

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Student Status and Educational Attainment

Completed years of education are summarized in the variable EDUCAT. Information was obtained from questions RE 103-105. Children who are 5 years of age or older and who never attended school were coded as 0; children under the age of 5 years were coded as -1 (Inapplicable) regardless of whether or not they attended school. However, among the cases coded as inapplicable, there is no distinction between those who were under the age of five and others who were inapplicable, such as persons who may be institutionalized for an entire round.

The user should note that the EDUCAT is an unedited variable and minimal data cleaning was performed on this variable.

Military Service and Service Era

The variable DIDSERVE is only collected during Round 1 of the MEPS interview. It indicates if the person ever served in the Armed Forces. Persons under the age of 16 were coded as 3 (Under 16 – Inapplicable). Individuals currently on active duty military service were coded as 4 (Now active duty). Those individuals entering a MEPS household after Round 1 have DIDSERVE set to –1 (Inapplicable).

Because DIDSERVE is only asked during Round 1, and because the 1997 FY file only contains data from Rounds 3, 4, and 5 of Panel 1, this variable would have been missing for persons in Panel 1. Consequently, an analyst would have had to go back to the 1996 full year file (MEPS HC-008) in order to determine the military service and veteran status values for those Panel 1 persons. Therefore, to provide a better estimation of military service for this 1997 data set, DIDSERVE from Panel 1, Round 1 (on the 1996 file) were brought forward onto the 1997 data set.  

Income Variables

Income related variables were constructed primarily from data collected in the Round 3 Income Section. Person-level income amounts have been edited and imputed for every record on the full-year file.

Logical editing or weighted, sequential hot-deck imputation was used to impute income amounts for missing values (both for item non-response and for persons in the full-year file who were not in Round 3). Reported income components were generally left unedited (with the few exceptions noted below). Thus, analysts using these data may wish to apply additional checks for outlier values that would appear to stem from mis-reporting.

Total person-level income (TTLP97X) is the sum of all income components: wages, salaries, bonuses, tips, commissions; business and farm gains and losses; unemployment and workman’s compensation; interest and dividends; alimony, child support, and other private cash transfers; private pensions, IRA withdrawals, social security, and veterans payments; supplemental security income and cash welfare payments from public assistance, Aid to Families with Dependent Children, and Aid to Dependent Children; gains or losses from estates, trusts, partnerships, S corporations, rent, and royalties; and a small amount of "other"income.

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Income Top-Coding

Total income was top-coded to preserve confidentiality. Top codes were applied to the top percentile of all cases (including negative amounts that exceeded income thresholds in absolute value). In cases where fewer than one percent of all persons received a particular income source, we top-coded all recipients. Top-coded income amounts were masked using a regression-based approach. The regressions relied on many of the same variables used in the hot-deck imputations, with the dependent variable in each case being the natural logarithm of the amount that the income component was in excess of its top-code threshold. Predicted values from this regression were reconverted from logarithms to levels using a smearing correction, and these predicted amounts were then added back to the top-code thresholds. This approach preserves the component-by-component weighted means (both overall and among top-coded cases), while also preserving much of the income distribution conditional on the variables contained in our regressions. At the same time, this approach ensures that every reported amount in excess of its respective threshold is altered on the public use file. The process of top-coding income amounts in this way inevitably introduces measurement error in cases where income amounts were reported correctly by respondents. Note, however, that top-coding can also help to reduce the impact of outliers that occur due to mis-reporting.

Poverty Status

POVCAT97 is a categorical variable for 1997 family income as a percentage of poverty This variable was constructed primarily from data collected in the Round 3 Income Section. Logical editing or weighted, sequential hot-deck imputation was used to impute income amounts for missing values (both for item non-response and or persons in the full-year file who were not in Round 3). Round-level data on employment status, hours worked, and wages were used to supplement earnings data collected in the Income Section. Family income was derived by constructing person-level total income comprising annual earnings from wages, salaries, bonuses, tips, commissions; business and farm gains and losses; unemployment and workman’s compensation; interest and dividends; alimony, child support, and other private cash transfers; private pensions, IRA withdrawals, social security, and veterans payments; supplemental security income and cash welfare payments from public assistance, Aid to Families with Dependent Children, and Aid to Dependent Children; gains or losses from estates, trusts, partnerships, S corporations, rent, and royalties; and a small amount of "other"income. Family income excluded tax refunds and capital gains. Person-level income totals were then summed over family members (as defined by the CPS) to yield the family-level total. POVCAT97 is constructed by dividing family income by the applicable poverty line (based on family size and composition), with the resulting percentages grouped into 5 categories; negative or poor (less than 100%), near poor (100 to less than 125%), low income (125 to less than 200%), middle income (200 to less than 400%), and high income (400%+). Persons who did not get assigned to a CPS family unit were treated as one-person families in constructing POVCAT97. Family income as well as the components of person level income have been subjected to internal editing patterns and derivation methods that are in accordance to specific definitions, and are not being released at this time.

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Employment Variables

Employment questions were asked of all persons 16 years and older at the time of the interview. Employment status was summarized using the following: data were taken from Round 5/3 counterpart if non-missing; else, if missing, data were taken from the Round 4/2 counterpart; else from the Round 3/1 counterpart. If no valid data was available during any of these Rounds of data collection, the same algorithm was followed to assign a missing value other than -1 (Inapplicable).

Health Insurance Variables

Question on health insurance coverage are asked during every round. One edit performed to the private insurance variables corrects for a problem concerning covered benefits which occurred when respondents reported a change in any of their private health insurance plan name. Additional edits address issues of missing data on the time period of coverage for both public and private coverage that was either reviewed or initially reported in a given round. For CHAMPUS/CHAMPVA coverage, respondents who were classified as active duty military or who were over age 65 had their reported CHAMPUS/CHAMPVA coverage overturned. Additional edits, described below, were performed on the Medicare and Medicaid variables to assign persons to coverage from these sources. Observations that contain edits assigning persons to Medicare or Medicaid coverage can be identified by comparing the edited and unedited versions of the Medicare and Medicaid variables.

Public sources include Medicare, CHAMPUS/CHAMPVA, Medicaid and other public hospital/physician coverage.

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1997 Summary Insurance Coverage Indicators (PRVEV97 - INSURCOV)

The variables PRVEV97-UNINS97 summarize health insurance coverage for the person in 1997 for the following types of insurance: private (PRVEV97); CHAMPUS/CHAMPVA (CHPEV97); Medicaid (MCDEV97); Medicare (MCREV97); other public A (OPAEV97); other public B (OPBEV97). Each variable was constructed based on the values of the corresponding 12 month to month health insurance variables described above. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered for a given type of insurance for all of 1997. The variable UNINS97 summarizes PRVEV97-OPBEV97. Where PRVEV97-OPBEV97 are all equal to 2, then UNINS97 equals 1; person was uninsured for all of 1997. Otherwise UNINS97 is set to 2, not uninsured for some portion of 1997.

For user convenience this file contains a constructed variable INSURCOV that summarizes health insurance coverage for the person in 1997, with the following values:

1 <65,  ANY PRIVATE (Person had any private insurance coverage (including Champus/VA) any time during 1997)
2 <65, ANY PUBLIC 

( Person had any public insurance coverage any time during 1997)

<65, UNINSURED

( Person was uninsured during all of 1997)

4 65+,  MEDICARE ONLY ( Person had only Medicare coverage during 1997)
5 65+,  MEDICARE AND PRIVATE  

( Person had private insurance coverage (including Champus/VA) and Medicare coverage during 1997)

65+,  MEDICARE AND OTHER PUBLIC

( Person had Medicare coverage and some other public coverage during 1997)

7 65+, UNINSURED

( Person was over 65 and uninsured during all of 1997)

8 65+, NO MEDICARE & OTHER INS ( Person was over 65 and had no Medicare or other insurance during all of 1997)

Please note this variable categorizes Champus as private coverage. If an analyst wishes to consider Champus public coverage, the variable can easily be reconstructed using the PRVEV97 and CHMPEV97 variables.

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Health Status Variables

HEALTH is a summary variable that describes general health status (excellent, good, fair, poor). It is asked of all sampled persons each round. Data were taken from Round 5/3 counterpart if non-missing; else, if missing, data were taken from the Round 4/2 counterpart; else from the Round 3/1 counterpart. If no valid data was available during any of these Rounds of data collection, the same algorithm was followed to assign a missing value other than -1 (Inapplicable).

Utilization, Expenditures and Source of Payment Variables (TOTTCH97-RXOSR97)

The MEPS Household Component (HC) collects data in each round on use and expenditures for office and hospital-based care, home health care, dental services, vision aids, and prescribed medicines. Data were collected for each sample person at the event level (e.g. doctor visit, hospital stay) and summed across rounds 1-3 (excluding 1997 events covered in round 3) to produce the annual utilization and expenditure data for 1997 in this file. In addition, the MEPS Medical Provider Component (MPC) is a follow-back survey that collected data from a sample of medical providers and pharmacies that were used by sample persons in 1997. Expenditure data collected in the MPC are generally regarded as more accurate than information collected in the HC and were used to improve the overall quality of MEPS expenditure data in this file (see below for description of methodology used to develop expenditure data).

This data set contains utilization and expenditure variables for several categories of health care services. In general, there is one utilization variable (based on HC responses only), 13 expenditure variables (derived from both HC and MPC responses), and 1 charge variable for each category of health care service. The utilization variable is typically a count of the number of medical events reported for the category. The 13 expenditure variables consist of an aggregate total payments variable, 10 main component source of payment category variables, and 2 additional source of payment category variables (see below for description of source of payment categories). Expenditure variables for all categories of health care combined are also provided.

Please see the full public use file documentation for a table in Appendix 3 which provides an overview of the utilization and expenditure variables included in this data set. For each health service category, the table lists the corresponding utilization variable(s) and provides a general key to the expenditure variable names (13 per service category). The first 3 characters of the expenditure variable names reflect the service category (except only 2 characters for prescription medicines) while the subsequent 3 characters (*** in table) reflect the naming convention for the source of payment categories described below (except only 2 characters for Veterans Administration). The last 2 positions of all utilization and expenditure variable names reflect the survey year (i.e. 97).

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Expenditures Definition

Expenditures on this file refer to what is paid for health care services. More specifically, expenditures in MEPS are defined as the sum of direct payments for care provided during the year, including out-of-pocket payments and payments by private insurance, Medicaid, Medicare, and other sources. Payments for over the counter drugs and for alternative care services are not included in MEPS total expenditures. Indirect payments not related to specific medical events, such as Medicaid Disproportionate Share and Medicare Direct Medical Education subsidies, are also not included.

The definition of expenditures used in MEPS is somewhat different from the 1987 NMES and 1977 NMCES surveys where ‘charges’ rather than ‘sum of payments’ were used to measure expenditures. This change was adopted because charges became a less appropriate proxy for medical expenditures during the 1990’s due to the increasingly common practice of discounting charges. Another change from the two prior surveys is that charges associated with uncollected liability, bad debt, and charitable care (unless provided by a public clinic or hospital) are not counted as expenditures because there are no payments associated with those classifications.

While the concept of expenditures in MEPS has been operationalized as payments for health care services, variables reflecting charges for services received are also provided on the file (see below). Analysts should use caution when working with the charge variables because they do not typically represent actual dollars exchanged for services or the resource costs of those services.

Data Sources on Expenditures

The expenditure data included on this file were derived from the MEPS Household and Medical Provider Components. Only HC data were collected for nonphysician visits, dental and vision services, other medical equipment and services, and home health care not provided by an agency while data on expenditures for care provided by home health agencies were only collected in the MPC. In addition to HC data, MPC data were collected for some office-based visits to physicians (or medical providers supervised by physicians), hospital-based events (e.g. inpatient stays, emergency room visits, and outpatient department visits), and prescribed medicines. For these types of events, MPC data were used if complete; otherwise HC data were used if complete. Missing data for events where HC data were not complete and MPC data were not collected or complete were derived through an imputation process (see below).

A series of logical edits were applied to both the HC and MPC data to correct for several problems including outliers, copayments or charges reported as total payments, and reimbursed amounts that were reported as out of pocket payments. In addition, edits were implemented to correct for misclassifications between Medicare and Medicaid and between Medicare HMO’s and private HMO’s as payment sources. Data were not edited to insure complete consistency between the health insurance and source of payment variables on the file.

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Imputation for Missing Expenditures and Data Adjustments

Expenditure data were imputed to 1) replace missing data, 2) provide estimates for care delivered under capitated reimbursement arrangements, and 3) to adjust household reported insurance payments because respondents were often unaware that their insurer paid a discounted amount to the provider. This section contains a general description of the approaches used for these three situations. A more detailed description of the editing and imputation procedures will be provided in the documentation for the forthcoming MEPS event level files.

Missing data on expenditures were imputed using a weighted sequential hot-deck procedure for most medical visits and services. In general, this procedure imputes data from events with complete information to events with missing information but similar characteristics. For each event type, selected predictor variables with known values (e.g., total charge, demographic characteristics, region, provider type, and characteristics of the event of care, such as whether it involved surgery) were used to form groups of donor events with known data on expenditures, as well as identical groups of recipient events with missing data. Within such groups, data were assigned from donors to recipients, taking into account the weights associated with the MEPS complex survey design. Only MPC data were used as donors for hospital-based events while data from both the HC and MPC were used as donors for office-based physician visits.

Because payments for medical care provided under capitated reimbursement arrangements and through public clinics and Veterans’ Hospitals are not tied to particular medical events, expenditures for events covered under those types of arrangements and settings were also imputed. Events covered under capitated arrangements were imputed from events covered under managed care arrangements that were paid based on a discounted fee-for-service method, while imputations for visits to public clinics and Veterans’ Hospitals were based on similar events that were paid on a fee-for-service basis. As for other events, selected predictor variables were used to form groups of donor and recipient events for the imputations.

An adjustment was also applied to some HC reported expenditure data because an evaluation of matched HC/MPC data showed that respondents who reported that charges and payments were equal were often unaware that insurance payments for the care had been based on a discounted charge. To compensate for this systematic reporting error, a weighted sequential hot-deck imputation procedure was implemented to determine an adjustment factor for HC reported insurance payments when charges and payments were reported to be equal. As for the other imputations, selected predictor variables were used to form groups of donor and recipient events for the imputation process.

Methodology for Flat Fee Expenditures

Most of the expenditures for medical care reported by MEPS participants are associated with single medical events. However, in some situations there is one charge that covers multiple contacts between a medical provider and patient (e.g. obstetrician services, orthodontia). In these situations (generally called flat or global fees), total payments for the flat or global fee were included if the initial service was provided in 1997. For example, all payments for an orthodontist’s fee that covered multiple visits over three years were included if the initial visit occurred in 1997. However, if a visit in 1997 to an orthodontist was part of a flat fee in which the initial visit occurred in 1996, then none of the payments for the flat fee were included.

The approach used to count expenditures for flat fees may create what appear to be inconsistencies between utilization and expenditure variables. For example, if several visits under a flat fee arrangement occurred in 1997 but the first visit occurred in 1995, then none of the expenditures were included, resulting in low expenditures relative to utilization for that person. Conversely, the flat fee methodology may result in high expenditures for some persons relative to their utilization. For example, all of the expenditures for an expensive flat fee were included even if only the first visit covered by the fee had occurred in 1997. On average, the methodology used for flat fees should result in a balance between overestimation and underestimation of expenditures in a particular year.

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Zero Expenditures

There are some medical events reported by respondents where the payments were zero. This could occur for several reasons including (1) free care was provided, (2) bad debt was incurred, (3) care was covered under a flat fee arrangement beginning in an earlier year, or (4) follow-up visits were provided without a separate charge (e.g. after a surgical procedure). In summary, these types of events have no impact on the person level expenditure variables contained in this file.

Source of Payment Categories

In addition to total expenditures, variables are provided which itemize expenditures according to the major source of payment categories. These categories are:

    1. Out of pocket by user or family (SLF);
    2. Medicare (MCR);
    3. Medicaid (MCD);
    4. Private Insurance (PRV);
    5. Veterans’ Administration, excluding CHAMPVA (VA);
    6. CHAMPUS (i.e. TRICARE) or CHAMPVA (CHM);
    7. Other Federal Sources--includes Indian Health Service, Military Treatment Facilities, and other care provided by the Federal government (OFD);
    8. Other State and Local Source--includes community and neighborhood clinics, State and local health departments, and State programs other than Medicaid (STL);
    9. Worker’s Compensation (WCP);
    10. Other Unclassified Sources--includes sources such as automobile, homeowner’s, liability, and other miscellaneous or unknown sources (OSR).
    11. Two additional source of payment variables were created to classify payments for particular persons that appear inconsistent due to differences between the survey questions on health insurance coverage and sources of payment for medical events. These variables include:

    12. Other Private (OPR): any type of private insurance payments reported for persons not reported to have any private health insurance coverage during the year as defined in MEPS (i.e. for hospital and physician services); and
    13. Other Public (OPU): Medicaid payments reported for persons who were not reported to be enrolled in the Medicaid program at any time during the year.

Though relatively small in magnitude, users should exercise caution when interpreting the expenditures associated with the OPR and OPU categories. While these payments stem from apparent inconsistent responses to the health insurance and source of payment questions in the survey, some of these inconsistencies may have logical explanations. For example, private insurance coverage in MEPS is defined as having a major medical plan covering hospital and physician services. If a MEPS sample person did not have such coverage but had a single service type insurance plan (e.g. dental insurance) that paid for a particular episode of care, those payments may be classified as ‘other private’. Some of the ‘other public’ payments may stem from confusion between Medicaid and other state and local programs or may be for persons who were not enrolled in Medicaid, but were presumed eligible by a provider who ultimately received payments from the program.

The naming conventions used for the source of payment expenditure variables are shown in parentheses in the list of categories above and in the key to the attached table in Appendix 3 of the 1997 Full Year Public Use File Documentation. In addition, total expenditure variables (EXP in key) based on the sum of the 12 source of payment variables above are provided.

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Charge Variables

In addition to the expenditure variables described above, a variable reflecting total charges is provided for each type of service category (except prescribed medicines). This variable represents the sum of all fully established charges for care received and usually does not reflect actual payments made for services, which can be substantially lower due to factors such as negotiated discounts, bad debt, and free care (see above). The naming convention used for the charge variables (TCH) is also included in the key Appendix 3 of the 1997 Full Year Public Use File Documentation. The total charge variable across services (TOTTCH97) excludes prescribed medicines.

Utilization and Expenditure Variables by Type of Medical Service

The following sections summarize definitional, conceptual and analytic considerations when using the utilization and expenditure variables in this file. Separate discussions are provided for each MEPS medical service category.

Medical Provider Visits (i.e., Office-Based Visits)

Medical provider visits consist of encounters that took place primarily in office-based settings and clinics. Care provided in other settings such as a hospital, nursing home, or a person=s home are not included in this category.

The total number of office based visits reported for 1997 (OBTOTV97) as well as the number of such visits to physicians (OBDRV97) and nonphysician providers (OBOTHV97) are contained in this file. For a small proportion of sample persons, the sum of the physician and nonphysician visit variables (OBDRV97+OBOTHV97) is less than the total number of office-based visits variable (OBTOTV97) because OBTOTV97 contains reported visits where the respondent did not know the type of provider.

Non-physician visits (OBOTHV97) include visits to the following types of providers: chiropractors, midwives, nurses and nurse practitioners, optometrists, podiatrists, physician’s assistants, physical therapists, occupational therapists, psychologists, social workers, technicians, receptionists/clerks/secretaries, or other medical providers. Separate utilization variables are included for selected types of more commonly seen non-physician providers including chiropractors (OBCHIR97), nurses/nurse practitioners (OBNURS97), optometrists (OBOPTO97), physician assistants (OBASST97), and physical or occupational therapists (OBTHER97).

Expenditure variables associated with all medical provider visits, physician visits, and non-physician visits in office-based settings can be identified in Appendix 3 of the 1997 Full Year Public Use File Documentation. As for the corresponding utilization variables, the sum of the physician and non-physician visit expenditure variables (e.g. OBDEXP97+OBOEXP97) is less than the total office-based expenditure variable (OBVEXP97) for a small proportion of sample persons. This can occur because OBVEXP97 includes visits where the respondent did not know the type of provider seen.

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Hospital Events

Separate utilization variables for hospital care are provided for each type of setting (inpatient, outpatient department, and emergency room) along with two expense variables per setting; one for basic hospital facility expenses and another for payments to physicians who billed separately for services provided at the hospital. These payments are referred to as "separately billing doctor" or SBD expenses.

Hospital facility expenses include all expenses for direct hospital care, including room and board, diagnostic and laboratory work, x-rays, and similar charges, as well as any physician services included in the hospital charge. Separately billing doctor (SBD) expenses typically cover services provided to patients in hospital settings by providers like radiologists, anesthesiologists, and pathologists, whose charges are often not included in hospital bills.

Hospital Outpatient Visits

Variables for the total number of reported visits to hospital outpatient departments in 1997 (OPTOTV97) as well as the number of outpatient department visits to physicians (OPDRV97) and non-physician providers (OPOTHV97) are contained in this file. For a small proportion of sample persons, the sum of the physician and non-physician visit variables (OPDRV97+OPOTHV97) is less than the total number of outpatient visits variable (OPTOTV97) because OPTOTV97 contains reported visits where the respondent did not provide information on the type of provider seen.

Expenditure variables (both facility and SBD) associated with all medical provider visits, physician visits, and non-physician visits in outpatient departments can be identified in Appendix 3 of the 1997 Full Year Public Use File Documentation. As for the corresponding utilization variables, the sum of the physician and non-physician expenditure variables (e.g. OPVEXP97+OPOEXP97 for facility expenses) is less than the variable for total outpatient department expenditures (OPFEXP97) for a small proportion of sample persons. This can occur because OBFEXP97 includes visits where the respondent did not know the type of provider seen. No expenditure variables are provided for health care consultations that occurred over the telephone.

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Hospital Emergency Room Visits

The variable ERTOT97 represents a count of all emergency room visits reported for the survey year. Expenditure variables associated with ERTOT97 are identified in Appendix 3 of the 1997 Full Year Public Use File Documentation. It should be noted that hospitals usually include expenses associated with emergency room visits that immediately result in an inpatient stay with the charges and payments for the inpatient stay. Therefore, to avoid the potential for double counting when imputing missing expenses, separately reported expenditures for emergency room visits that were identified in the MPC as directly linked to an inpatient stay were included as part of the inpatient stay only (see below). This strategy to avoid double counting resulted in $0 expenditures for these emergency room visits. However, these $0 emergency room visits are still counted as separate visits in the utilization variable ERTOT97.

Hospital Inpatient Stays

Two measures of total inpatient utilization are provided on the file: (1) total number of hospital discharges (IPDIS97) and (2) the total number of nights associated with these discharges (IPNGTD97). IPDIS97 includes hospital stays where the dates of admission and discharge were reported as identical. These "zero night stays" can be included or excluded from inpatient analyses at the users’ discretion (see last paragraph of this section). If the number of nights in the hospital could not be computed for any reported stay for a person, then IPNGTD97 was assigned a missing value.

Expenditure variables associated with hospital inpatient stays are identified in Appendix 3 of the 1997 Full Year Public Use File Documentation. To the extent possible, payments associated with emergency room visits that immediately preceded an inpatient stay are included with the inpatient expenditures (see above) and payments associated with healthy newborns are included with expenditures for the mother (see next paragraph for more detail).

Data used to construct the inpatient utilization and expenditure variables for newborns were edited to exclude stays where the newborn left the hospital on the same day as the mother. This edit was applied because discharges for infants without complications after birth were not consistently reported in the survey and charges for newborns without complications are typically included in the mother’s hospital bill. However, if the newborn was discharged at a later date than the mother was discharged, then the discharge was considered a separate stay for the newborn when constructing the utilization and expenditure variables.

Some analysts may prefer to exclude zero night stays from inpatient analyses and/or count these stays as ambulatory visits. Therefore, a separate use variable is provided which contains a count of the number of inpatient events where the reported dates of admission and discharge were the same (IPZERO97). This variable can be subtracted from IPDIS97 to exclude zero night stays from inpatient utilization estimates. In addition, separate expenditure variables are provided for zero night facility expenses (ZIFEXP97) and for separately billing doctor expenses (ZIDEXP97). Analysts who choose to exclude zero-night stays from inpatient expenditure analyses need to subtract the zero-night expenditure variable from the corresponding expenditure variable for total inpatient stays (e.g. IPFEXP97-ZIFEXP97 for facility expenses, IPDEXP97-ZIDEXP97 for separately billing doctor expenses).

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Dental Visits

The total number of dental visits variable (DVTOT97) includes those to any person(s) for dental care including general dentists, dental hygienists, dental technicians, dental surgeons, orthodontists, endodontists, and periodontists. Additional variables are provided for the numbers of dental visits to general dentists (DVGEN97) and to orthodontists (DVORTH97). For a small proportion of sample persons, the sum of the general dentist and orthodontist visit variables (DVGEN97+DVORTH97) is greater than the total number of dental visits (DVTOT97). This result can only occur for persons who were reported to have seen both a general dentist and orthodontist in the same visit(s). When this occurred, expenditures for the visit were included as orthodontist expenses but not as general dentist expenses. Expenditure variables for all three categories of dental providers can be identified in Appendix 3 of the 1997 Full Year Public Use File Documentation.

Home Health Care

In contrast to other types of medical events where data were collected on a per visit basis, information on home health care utilization is collected in MEPS on a per month basis. Variables are provided which indicate the total number of days in 1997 where home health care was received from any type of paid or unpaid caregiver (HHTOTD97), agencies, hospitals, or nursing homes (HHAGD97), self-employed persons (HHINDD97), and unpaid informal caregivers not living with the sample person (HHINFD97). The number of provider days represents the sum across months of the number of days on which home health care was received, with days summed across all providers seen. For example, if a person received care in one month from one provider on 2 different days, then the number of provider days would equal 2. The number of provider days would also equal 2 if a person received care from 2 different providers on the same day. However, if a person received care from 1 provider 2 times in the same day, then the provider days would equal 1. These variables were assigned missing values if the number of provider days could not be computed for any month in which the specific type of home health care was received.

Separate expenditure variables are provided for agency-sponsored home health care (includes care provided by home health agencies, hospitals, and nursing homes) and care provided by self-employed persons. A table in Appendix 3 of the 1997 Full Year Public Use File Documentation identifies the home health care utilization and expenditure variables contained in the file.

Vision Aids

Expenditure variables for the purchase of glasses and/or contact lenses are identified in Appendix 3 of the 1997 Full Year Public Use File Documentation. Due to the data collection methodology, it was not possible to determine whether vision items that were reported in round 3 had been purchased in 1997 or 1998. Therefore, expenses reported in round 3 were only included if more than half of the person’s reference period for the round was in 1997.

Other Medical Equipment and Services

This category includes expenditures for ambulance services, orthopedic items, hearing devices, prostheses, bathroom aids, medical equipment, disposable supplies, alterations/modifications, and other miscellaneous items or services that were obtained, purchased or rented during the year. Respondents were only asked once (in round 3) about their total annual expenditures and were not asked about their frequency of use of these services. Expenditure variables representing the combined expenses for these supplies and services are identified in Appendix 3 of the 1997 Full Year Public Use File Documentation.

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Prescribed Medicines

There is one total utilization variable (RXTOT97) and 13 expenditure variables included on the 1997 full-year file relating to prescribed medicines. These 13 expenditure variables include an annual total expenditure variable (RXEXP97) and 12 corresponding annual source of payment variables (RXSLF97, RXMCR97, RXMCD97, RXPRV97, RXVA97, RXCHM97, RXOFD97, RXSTL97, RXWCP97, RXOSR97, RXOPR97, and RXOPU97). Unlike the other event types, the prescribed medicine events have some remaining inconsistencies in the data when comparing information from the insurance section of the Household Component and source of payment information from the Pharmacy Component (more specifically, discrepancies between Medicare only household insurance responses and Medicaid source of payment provided by pharmacy providers). These inconsistencies remain unedited because there was strong evidence from the Pharmacy Component that these were indeed Medicaid payments. All of these types of Household Component events were either exact matches to events in the Pharmacy Component or refills of exact matches, and in addition, all of these types of events were purchases by persons with positive weights. The total utilization variable is a count of all prescribed medications initially purchased or otherwise obtained during 1997, as well as any additional acquisitions of the medication. The total expenditure variable sums all amounts paid out-of-pocket and by third party payers for each prescription purchased in 1997. No variables reflecting charges for prescription medicines are included because a large proportion of respondents to the pharmacy component survey did not provide charge data (see below).

Prescribed Medicines Data Collected

Data regarding prescription drugs were obtained through the household questionnaire and a pharmacy component survey. During each round of the MEPS HC, all respondents were asked to supply the name of any prescribed medication they or their family members purchased or otherwise obtained during that round. For each medication and in each round, the following information was collected: whether any free samples of the medication were received; the name(s) of any health problems the medication was prescribed for; the number of times the prescription drug was obtained or purchased; the year, month, and day on which the person first used the medication; and a list of the names, addresses, and types of pharmacies that filled the household=s prescriptions. Also, during the Household Component, respondents were asked if they send in claim forms for their prescriptions (self-filers) or if their pharmacy providers do this automatically for them at the point of purchase (non-self-filers). For non-self-filers, charge and payment information was collected in the pharmacy component survey. However, charge and payment information was collected for self-filers in the household questionnaire, because payments by private third party payers for self-filers’ purchases would not be available from a pharmacy follow-back survey.

Pharmacy providers identified by the household were contacted by mail for the pharmacy component survey if permission was obtained in writing from the person with the prescription to release their pharmacy records. The signed permission forms were provided to the various establishments prior to making any requests for information. Each establishment was informed of all persons participating in the survey that had prescriptions filled there in 1997 and a computerized printout containing information about these prescriptions was sought. For each medication listed, the following information was requested: date filled; national drug code (NDC); medication name; strength of medicine (amount and unit); quantity (package size and amount dispensed); total charge; and payments by source.

When diabetic supplies, such as syringes and insulin, were reported in the other medical supply section of the MEPS HC questionnaire as having been obtained during the round, the interviewer was directed to collect information on these items in the prescription drug section of MEPS. Data on expenses for these items were collected in and imputed from the pharmacy component survey.

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Prescribed Medicines Data Editing and Imputation

The general approach to preparing the household prescription data for this file was to utilize the pharmacy component prescription data to assign expenditure values to the household drug mentions. For self-filers, information on payment sources was retained to the extent that these data were reported by the household in the charge and payment section of the household questionnaire. A matching program was adopted to link pharmacy survey drugs and the corresponding drug information to household drug mentions. To improve the quality of these matches, all drugs on the household and pharmacy files were coded based on the medication names provided by the household and pharmacy, and when available, the national drug code (NDC) provided in the pharmacy survey. Considerable editing was done prior to the matching to correct data inconsistencies in both data sets and fill in missing data and correct outliers on the pharmacy file.

Drug price per unit outliers were analyzed on the pharmacy file by first identifying the average wholesale unit price (AWUP) of the drug by linkage through the NDC to a proprietary data base. In general, prescription drug unit prices were deemed to be outliers by comparing unit prices reported in the pharmacy data base to the AWUP and were edited, as necessary.

Round 3 household drug mentions in MEPS were not identified in the HC as 1997 or 1998 drug events for persons in households in which their Round 3 began in 1997 and ended in 1998. All exact matches to pharmacy survey drug events for persons whose pharmacies participated were classified as 1997 drug purchases. Any remaining Round 3 household drug mentions for persons with Round 3 spanning both years were randomly allocated to 1997 or 1998 based on the proportion of the households Round 3 period in each year.

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Variable Description Summary

SURVEY ADMINISTRATION VARIABLES

VARIABLE     

LABEL

DESCRIPTION

PANEL97

Panel Number

PANEL97 is a constructed variable used to specify the panel number (Panel 1 or 2) for each interview.

FCSZ1231

Family Size Responding 12/31 CPS Family

Number of persons in the CPS defined Families in the Civilian Noninstitutionalized Population on 12/31/97   

FAMSZEYR

Size of Responding Annualized Family

Number of persons in the MEPS Family in the Civilian Noninstitutionalized Population on 12/31/97       

REGION

Census Region

The variable REGION indicates the Census region for the RU for 1997 .

MSA

Metropolitan Statistical Area

The variable MSA indicates whether or not the RU is found in a metropolitan statistical area for 1997.

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DEMOGRAPHIC VARIABLES

VARIABLE      

LABEL

DESCRIPTION

AGE

Age

Age was constructed from the round specific Age variables using the algorithm: data was taken from the Dec 31st variable; if missing then data from Round 5/3; else if missing then data was taken from Round 4/2; else if missing then data was taken from Round 3/1.

SEX

Sex

Data on the sex of each RU member (SEX) were initially determined from the 1995 NHIS for Panel 1 and from the 1996 NHIS for Panel 2. The SEX variable was verified and, if necessary, corrected during each MEPS interview.

RACEX

Race (Edited/Imputed)

Race (RACEX) and Hispanic ethnicity (HISPANX) questions were initially asked for each RU member during the Round 1 MEPS interview. If this information was not obtained in Round 1, the questions were asked in subsequent Rounds.

RACETHNX

Race/Ethnicity (Edited/Imputed)

The variable RACETHNX indicating both race and ethnicity (e.g., with categories such as "Hispanic" and "black but not Hispanic") reflects the imputations done for RACEX and HISPANX.

HISPANX

Hispanic Ethnicity (Edited/Imputed)

Race (RACEX) and Hispanic ethnicity (HISPANX) questions were initially asked for each RU member during the Round 1 MEPS interview. If this information was not obtained in Round 1, the questions were asked in subsequent Rounds.

HISPCAT

Specific Hispanic Ethnicity Group

HISPCAT is an unedited variable that provides the specific Hispanic ethnicity group of the person.

MARRY

Marital Status for 1997

Current marital status was collected and/or updated during every Round of the MEPS interview. This information was obtained in RE13 and RE97 and summarized as MARRY. Persons under the age of 16 were coded as 6 (under 16 – inapplicable). If marital status of a specified round differed from that of the previous Round, then the marital status of the specified Round was edited to reflect a change during the Round (e.g., married in Round, divorced in Round, separated in Round, or widowed in Round).

Marital status was constructed from the round specific marital status variables using the algorithm: data was taken from the Dec 31st variable; if missing then data from Round 5/3; else if missing then data was taken from Round 4/2; else if missing then data was taken from Round 3/1.

This variable corresponds to MARRY97X on the public use file.

EDUCAT

Education Status for 1997

Completed years of education are summarized in the variable EDUCAT. Information was obtained from questions RE 103-105. Children who are 5 years of age or older and who never attended school were coded as 0; children under the age of 5 years were coded as -1 (Inapplicable) regardless of whether or not they attended school. However, among the cases coded as inapplicable, there is no distinction between those who were under the age of five and others who were inapplicable, such as persons who may be institutionalized for an entire round.

Education status was constructed from the round specific education status variables using the algorithm: data was taken from the Dec 31st variable; if missing then data from Round 5/3; else if missing then data was taken from Round 4/2; else if missing then data was taken from Round 3/1.

This variable corresponds to EDUCYR97 on the public use file.

DIDSERVE

Ever Served In Armed Forces

The variable DIDSERVE is only collected during Round 1 of the MEPS interview. It indicates if the person ever served in the Armed Forces. Persons under the age of 16 were coded as 3 (Under 16 – Inapplicable). Individuals currently on active duty military service were coded as 4 (Now active duty). Those individuals entering a MEPS household after Round 1 have DIDSERVE set to –1 (Inapplicable). Like DIDSERVE, data on service in specific eras was only collected during Round 1 of the MEPS interview.

Because DIDSERVE and veteran status variables are only asked during Round 1, and because the 1997 FY file only contains data from Rounds 3, 4, and 5 of Panel 1, these variables would have been missing for persons in Panel 1. Consequently, an analyst would have had to go back to the 1996 full year file (MEPS HC-008) in order to determine the military service and veteran status values for those Panel 1 persons.

Therefore, to provide a better estimation of military service and veteran status for this 1997 dataset, DIDSERVE from Panel 1, Round 1 (on the 1996 file) were brought forward onto the 1997 dataset.

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INCOME VARIABLES

VARIABLE     

LABEL

DESCRIPTION

TTLP97X

PERSON’S TOTAL INCOME

Total person-level income (TTLP97X) is the sum of all income components: annual earnings from wages, salaries, bonuses, tips, commissions; business and farm gains and losses; unemployment and workman’s compensation; interest and dividends; alimony, child support, and other private cash transfers; private pensions, IRA withdrawals, social security, and veterans payments; supplemental security income and cash welfare payments from public assistance, Aid to Families with Dependent Children, and Aid to Dependent Children; gains or losses from estates, trusts, partnerships, S corporations, rent, and royalties; and a small amount of "other"income.

Having constructed total income in this manner, we then top-coded.Finally, we scaled the components of income up or down in order to make the sources of income consistent with the newly-adjusted totals.

POVCAT97

FAMILY INCOME AS PERCENT OF POVERTY LINE

POVCAT97 is a categorical variable for 1997 family income as a percentage of poverty. Family income was derived by constructing person-level total income comprising annual earnings from wages, salaries, bonuses, tips, commissions; business and farm gains and losses; unemployment and workman’s compensation; interest and dividends; alimony, child support, and other private cash transfers; private pensions, IRA withdrawals, social security, and veterans payments; supplemental security income and cash welfare payments from public assistance, Aid to Families with Dependent Children, and Aid to Dependent Children; gains or losses from estates, trusts, partnerships, S corporations, rent, and royalties; and a small amount of "other"income. Family income excluded tax refunds and capital gains. Person-level income totals were then summed over family members as defined by the CPS to yield the family-level total. POVCAT97 is constructed by dividing family income by the applicable poverty line (based on family size and composition), with the resulting percentages grouped into 5 categories; negative or poor (less than 100%), near poor (100 to less than 125%), low income (125 to less than 200%), middle income (200 to less than 400%), and high income (400%+).

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EMPLOYMENT VARIABLES

VARIABLE     

LABEL

DESCRIPTION

EMPLOY

Employment Status for 1997

Employment status was constructed from the round specific employment status variables using the algorithm: data was taken from the Dec 31st variable; if missing then data from Round 5/3; else if missing then data was taken from Round 4/2; else if missing then data was taken from Round 3/1.

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HEALTH INSURANCE VARIABLES

VARIABLE      

LABEL

DESCRIPTION

PRVEV97

Ever have private insurance during 97

The variable PRVEV97 summarizes health insurance coverage for the person in 1997 for private insurance. This variable was constructed based on the values of the corresponding 12 month to month private health insurance variables found on the public use file. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered by private health insurance for all of 1997.

CHPEV97

Ever have CHAMPUS/CHAMPVA during 97

The variable CHPEV97 summarizes health CHAMPUS/CHAMPVA coverage for the person in 1997. This variable was constructed based on the values of the corresponding 12 month to month CHAMPUS/CHAMPVA insurance variables found on the public use file. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered by CHAMPUS/CHAMPVA for all of 1997.

MCDEV97

Ever have Medicaid during 97

The variable MCDEV97 summarizes Medicaid coverage for the person in 1997. This variable was constructed based on the values of the corresponding 12 month to month Medicaid variables found on the public use file. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered by Medicaid for all of 1997.

MCREV97

Ever have Medicare during 97

The variable MCREV97 summarizes Medicare coverage for the person in 1997. This variable was constructed based on the values of the corresponding 12 month to month Medicare insurance variables found on the public use file. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered by Medicare for all of 1997.

OPAEV97

Ever have other public A during 97

The variable OPAEV97summarizes other public coverage for a person where the person reported some type of managed care and paid something (type A) in 1997. This variable was constructed based on the values of the corresponding 12 month to month other public insurance (type A) variables found on the public use file. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered by other public insurance (type A) for all of 1997.

OPBEV97

Ever have other public B during 97

The variable OPBEV97summarizes other public coverage for a person where the person did not report any type of managed care (type B) in 1997. This variable was constructed based on the values of the corresponding 12 month to month other public insurance (type B) variables found on the public use file. A value of 1 indicates that the person was covered for at least one day of at least one month during 1997. A value of 2 indicates that the person was not covered by other public insurance (type B) for all of 1997.

UNINS97

Uninsured all of 97

The variable UNINS97 summarizes health insurance status as being uninsured using PRVEV97-OPBEV97. Where PRVEV97-OPBEV97 are all equal to 2, then UNINS97 equals 1; person was uninsured for all of 1997. Otherwise UNINS97 is set to 2, not uninsured for some portion of 1997.

INSURCOV

Full year insurance coverage status

For user convenience this file contains a constructed variable INSCOV97 that summarizes health insurance coverage for the person in 1997, with the following values:

1    <65, ANY PRIVATE ( Person had any private insurance coverage (including Champus/VA) any time during 1997)
<65, ANY PUBLIC

( Person had any public insurance coverage any time during 1997)

3 <65, UNINSURED ( Person was uninsured during all of 1997)
65+, MEDICARE ONLY ( Person had only Medicare coverage during 1997)
5 65+, MEDICARE AND PRIVATE (Person had private insurance coverage (including Champus/VA) and Medicare coverage during 1997)
6 65+, MEDICARE AND OTHER PUBLIC (Person had Medicare coverage and some other public coverage during 1997)
7 65+, UNINSURED  (Person was over 65 and uninsured during all of 1997)
8 65+, NO MEDICARE & OTHER INS (Person was over 65 and had no Medicare or other insurance during all of 1997)

Please note this variable categorizes Champus as private coverage. If an analyst wishes to consider Champus public coverage, the variable can easily be reconstructed using the PRVEV97 and CHMPEV97 variables.

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HEALTH STATUS VARIABLES

VARIABLE     

LABEL

DESCRIPTION

HEALTH

Perceived Health Status for 1997

Perceived health status was constructed from the round specific perceived health status variables using the algorithm: data was taken from the Dec 31st variable; if missing then data from Round 5/3; else if missing then data was taken from Round 4/2; else if missing then data was taken from Round 3/1.

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