MEPS HC-102H: 2006 Home Health Visits
August 2008
Agency for Healthcare Research and Quality
Center for Financing, Access and Cost Trends
540 Gaither Road
Rockville, MD 20850
(301) 427-1406

Table of Contents

A. Data Use Agreement
B. Background
1.0 Household Component
2.0 Medical Provider Component
3.0 Survey Management and Data Collection
C. Technical And Programming Information
1.0 General Information
2.0 Data File Information
2.1 Codebook Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Source and Naming Conventions
2.4.1 Variable-Source Crosswalk
2.4.2 Expenditure and Source of Payment Variables
2.5 File Contents
2.5.1 Survey Administration Variables
2.5.1.1 Person Identifiers (DUID, PID, DUPERSID)
2.5.1.2 Record Identifier (EVNTIDX)
2.5.1.3 Round Indicator (EVENTRN)
2.5.1.4 Panel Indicator (PANEL)
2.5.2 Home Health Event Variables
2.5.2.1 Date of Event (HHDATEYR, HHDATEMM)
2.5.2.2 Characteristics of Event (MPCELIG-OTHCWOS)
2.5.2.3 Treatments, Therapies, and Services (HOSPITAL-OTHSVCOS)
2.5.2.4 Frequency of Event (FREQCY-HHDAYS)
2.5.3 Flat Fee Variables
2.5.4 Condition, Procedure, and Clinical Classification Codes
2.5.5 Expenditure Data
2.5.5.1 Definition of Expenditures
2.5.5.2 Data Editing and Imputation Methodologies of Expenditure Variables
2.5.5.2.1 General Data Editing Methodology
2.5.5.2.2 General Hot-Deck Imputation
2.5.5.2.3 Home Health Data Editing and Imputation
2.5.5.3 Imputation Flag Variable (IMPFLAG)
2.5.5.4 Flat Fee Expenditures
2.5.5.5 Zero Expenditures
2.5.5.6 Sources of Payment
2.5.5.7 Home Health Expenditure Variables (HHSF06X - HHXP06X)
2.5.5.8 Rounding
3.0 Sample Weight (PERWT06F)
3.1 Overview
3.2 Details on Person Weight Construction
3.2.1 MEPS Panel 10 Weight
3.2.2 MEPS Panel 11 Weight
3.2.3 The Final Weight for 2006
3.2.4 Coverage
3.3 Using MEPS Data for Trend Analysis
4.0 Strategies for Estimation
4.1 Developing Event-Level Estimates
4.2 Person-Based Estimates for Home Health Care
4.3 Variables with Missing Values
4.4 Variance Estimation (VARPSU, VARSTR)
5.0 Merging/Linking MEPS Data Files
5.1 Linking to the Person-Level File
5.2 Linking to the Prescribed Medicines File
5.3 Linking to the Medical Conditions File
5.4 Pooling Annual Files
5.5 Longitudinal Analysis
   References
D. Variable-Source Crosswalk

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:

1. No one is to use the data in this data set in any way except for statistical reporting and analysis; and

2. 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

3. 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

1.0 Household Component

The Medical Expenditure Panel Survey (MEPS) provides nationally representative estimates of health care use, expenditures, sources of payment, and health insurance coverage for the U.S. civilian non-institutionalized population. The MEPS Household Component (HC) also provides estimates of respondents' health status, demographic and socio-economic characteristics, employment, access to care, and satisfaction with health care. Estimates can be produced for individuals, families, and selected population subgroups. The panel design of the survey, which includes 5 Rounds of interviews covering 2 full calendar years, provides data for examining person level changes in selected variables such as expenditures, health insurance coverage, and health status. Using computer assisted personal interviewing (CAPI) technology, information about each household member is collected, and the survey builds on this information from interview to interview.  All data for a sampled household are reported by a single household respondent.

The MEPS-HC was initiated in 1996. Each year a new panel of sample households is selected.  Because the data collected are comparable to those from earlier medical expenditure surveys conducted in 1977 and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample size is about 15,000 households.  Data can be analyzed at either the person or event level.  Data must be weighted to produce national estimates.

The set of households selected for each panel of the MEPS HC is a subsample of households participating in the previous year's National Health Interview Survey (NHIS) conducted by the National Center for Health Statistics. The NHIS sampling frame provides a nationally representative sample of the U.S. civilian non-institutionalized population and reflects an oversample of blacks and Hispanics. MEPS oversamples additional policy relevant sub-groups such as Asians and low income households. The linkage of the MEPS to the previous year's NHIS provides additional data for longitudinal analytic purposes.

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2.0 Medical Provider Component

Upon completion of the household CAPI interview and obtaining permission from the household survey respondents, a sample of medical providers are contacted by telephone to obtain information that household respondents can not accurately provide. This part of the MEPS is called the Medical Provider Component (MPC) and information is collected on dates of visit, diagnosis and procedure codes, charges and payments. The Pharmacy Component (PC), a subcomponent of the MPC, does not collect charges or diagnosis and procedure codes but does collect drug detail information, including National Drug Code (NDC) and medicine name, as well as date filled and sources and amounts of payment. The MPC is not designed to yield national estimates. It is primarily used as an imputation source to supplement/replace household reported expenditure information.

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3.0 Survey Management and Data Collection

MEPS HC and MPC data are collected under the authority of the Public Health Service Act. Data are collected under contract with Westat, Inc. Data sets and summary statistics are edited and published in accordance with the confidentiality provisions of the Public Health Service Act and the Privacy Act. The National Center for Health statistics (NCHS) provides consultation and technical assistance.

As soon as data collection and editing are completed, the MEPS survey data are released to the public in staged releases of summary reports, micro data files, and tables via the MEPS Web site: www.meps.ahrq.gov. Selected data can be analyzed through MEPSnet, an on-line interactive tool designed to give data users the capability to statistically analyze MEPS data in a menu-driven environment.

Additional information on MEPS is available from the MEPS project manager or the MEPS public use data manager at the Center for Financing Access and Cost Trends, Agency for Healthcare Research and Quality, 540 Gaither Road, Rockville, MD 20850 (301-427-1406).

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This documentation describes one in a series of public use event files from the 2006 Medical Expenditure Panel Survey (MEPS) Household Component (HC) and Medical Provider Component (MPC). Released as an ASCII data file (with related SAS and SPSS programming statements) and a SAS transport file, the 2006 Home Health public use file provides detailed information on home health events for a nationally representative sample of the civilian noninstitutionalized population of the United States. Data from the Home Health event file can be used to make estimates of home health event utilization and expenditures for calendar year 2006. The file contains 68 variables and has a logical record length of 297 with an additional 2-byte carriage return/line feed at the end of each record. As illustrated below, this file consists of MEPS survey data obtained in the 2006 portion of Round 3, and Rounds 4 and 5 for Panel 10, as well as Rounds 1, 2, and the 2006 portion of Round 3 for Panel 11 (i.e., the rounds for the MEPS panels covering calendar year 2006).

Counts of home health utilization are based entirely on household reports. Agency home health providers were sampled into the MEPS MPC (see Section B. 2.0). Only those providers for whom the respondent signed a permission form were included in MPC. Information from MPC was used to supplement expenditure and payment data reported by the household, and does not affect use estimates.

Data from this event file can be merged with other 2006 MEPS HC data files for the purposes of appending person-level data such as demographic characteristics or health insurance coverage to each home health record.

This file can also be used to construct summary variables for expenditures, sources of payment, and related aspects of home health events for calendar year 2006. Aggregate annual person-level information on the use of home health providers and other health services use is provided on the 2006 Population Characteristics File, where each record represents a MEPS sampled person.

The following documentation offers a brief overview of the types and levels of data provided, and the content and structure of the file and the codebook. It contains the following sections:

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, 1999. A copy of the survey instruments used to collect the information on this file is available on the MEPS Web site at the following address: www.meps.ahrq.gov.

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The 2006 Home Health public use data set consists of one event-level data file. The file contains characteristics associated with the home health event and imputed expenditure data.

The Home Health use data set contains characteristics associated with the home health event and imputed expenditure data. The home health services represented on this file are provided by three kinds of home health providers: formal (paid) home health agency providers, paid independent providers (self-employed), and informal providers who do not reside in the same household as the MEPS sampled person (care from informal providers who live in the same household as the sampled person are not represented on this file).

Each record on this file represents a household-reported home health event. A home health event is a MONTH of similar services provided to a sampled person by the same PROVIDER (i.e., an employer in the case of formal agency care and an individual in the case of paid independent and informal care providers). For example, if a person received, from Provider Agency A, four visits events from a nurse, ten visits events from a homemaker, and four visits events from a physical therapist each from the same provider one for each month every month during the months of January, February, and March, and also received, from Provider B, a physician visit in the month of January and February, there would be five event records on the file (NOT 56 records). There would be one event record representing all the visits from Provider A for the month of January, another record for Provider A's February visits, a third Provider A record for the March visits, a fourth record representing the Provider B physician visit in January and a fifth representing the Provider B physician visit in February. Data were collected (and represented on this file) in this manner because agencies, hospitals, and nursing homes provide MEPS expenditure data in this manner. In order to be consistent with the definition of what is considered a home health event on this file, this same definition (i.e., a month of similar services) was applied to all types of home health providers.

This public use data set contains 5,457 home health records; of the records, 5,381 are associated with persons having a positive person-level weight (PERWT06F). It includes all records related to home health events for all household survey respondents who resided in eligible responding households and reported at least one home health event. Each record represents one household-reported home health event that occurred during calendar year 2006. Some household respondents may have multiple events and thus will be represented in multiple records on the file. Other household respondents may have reported no events and thus will have no records on this file. These data were collected during the 2006 portion of Round 3, and Rounds 4 and 5 for Panel 10, as well as Rounds 1, 2, and the 2006 portion of Round 3 for Panel 11 of the MEPS HC. The persons represented on this file had to meet either (a) or (b):

1. Be classified as a key in-scope person who responded for his or her entire period of 2006 eligibility (i.e., persons with a positive 2006 full-year person-level weight (PERWT06F > 0)), or

2. Be an eligible member of a family all of whose key in-scope members have a positive person-level weight (PERWT06F > 0). (Such a family consists of all persons with the same value for FAMIDYR.) That is, the person must have a positive full-year family-level weight (FAMWT06F > 0). Note that FAMIDYR and FAMWT06F are variables on the 2006 Population Characteristics file.

Persons with no home health events for 2006 are not included on this event-level HH file but are represented on the person-level 2006 Full Year Population Characteristics file.

Home health providers include formal or paid, and informal or unpaid providers. Formal or paid providers include: home health agency and other independent paid providers. Informal or unpaid providers include family and friends that reside outside of the sampled person’s household.

For home health agencies it is important to distinguish between the provider and the home health worker. In these cases, the provider is the agency or the facility that employs the workers. The home health workers are the people who administer the care. Examples of home health care workers are the following: nurses, physical therapists, home health aides, homemakers, and hospice workers, among others. These examples are generally the types of workers associated with agencies. Paid independent providers generally include companions, nursing assistants, physicians, etc. For each record on this file, one or more types of workers can be reported. The respondent is asked to mention all of the types of home health workers who provided home health care (since records represent a month of service, there can be more than one type of worker on a single record). For example, an agency that provides two types of aides that provide home health care to the same person during a specific month is represented as one event on the file even though two workers employed at the same agency provided care. When using this file, analysts must keep in mind that a record on the file corresponds to a provider entity, not an individual or particular worker.

Expenditure data for home health agency events are collected exclusively in the MPC. Expenditure data for other paid independent home health care events are collected from the household, since these types of events are not included in the MPC. Friends, family and volunteers providing home health care to a person are considered unpaid and are not included in the MPC. No expenditure information is available for them.

Each home health record also includes the following: the month the provider visited the household; type of provider; types of services provided and if this was a repeat event; whether or not care was received due to hospitalization; whether or not a person was taught how to use medical equipment; imputed sources of payment, total payment and total charge for the home health event expenditure; and a full-year person-level weight.

Data from this file can be merged with previously released 2006 MEPS HC person-level data, such as the MEPS 2006 Full-Year Population Characteristics file, using the person identifier, DUPERSID, to append person-level information, such as demographic or health insurance coverage, to each record. Home Health events can also be linked to the MEPS 2006 Medical Conditions File. Please see Section 5.0 or the MEPS 2006 Appendix File, HC-102I, for details on how to link MEPS data files.

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2.1 Codebook Structure

For each variable on the Home Health event file, both weighted and unweighted frequencies are provided in the accompanying codebook. The codebook and data file sequence list variables in the following order:

Note that the person identifier is unique within this data year. See the section on pooling annual files, 5.4, for details.

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2.2 Reserved Codes

The following reserved code values are used:

Generally, values of -1, -7, -8, and -9 for non-expenditure variables have not been edited on this file. The values of -1 and -9 can be edited by the data users/analysts by following the skip patterns in the HC survey questionnaire (located on the MEPS Web site: www.meps.ahrq.gov/survey_comp/survey_questionnaires.jsp).

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The codebook describes an ASCII data set (although the data are also being provided in a SAS transport file). The following codebook items are provided for each variable:

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2.4 Variable Source and Naming Conventions

In general, variable names reflect the content of the variable, with an eight-character limitation. Generally, imputed/edited variables end with an "X".

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2.4.1 Variable-Source Crosswalk

Variables were derived either from the HC questionnaire itself, the MPC data collection instrument, or from the CAPI. The source of each variable is identified in Section D "Variable - Source Crosswalk" in one of four ways:

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The names of the expenditure and source of payment variables follow a standard convention, are seven characters in length, and end in an "X" indicating edited/imputed. Please note that imputed means that a series of logical edits, as well as an imputation process to account for missing data, have been performed on the variable.

The total sum of payments and the 12 source of payment variables are named in the following way:

The first two characters indicate the type of event:

In the case of source of payment variables, the third and fourth characters indicate:

In addition, the total charge variable is indicated by TC in the variable name.

The fifth and sixth characters indicate the year (06). The seventh character, "X", indicates the variable is edited/imputed.

For example, HHSF06X is the edited/imputed amount paid by self or family for 2006 home health expenditures.

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The dwelling unit ID (DUID) is a five-digit random number assigned after the case was sampled for MEPS. The three-digit person number (PID) uniquely identifies each person within the dwelling unit. The eight-character variable DUPERSID uniquely identifies each person represented on the file and is the combination of the variables DUID and PID. For detailed information on dwelling units and families, please refer to the documentation for the 2006 Full Year Population Characteristics file.

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EVNTIDX uniquely identifies each event (i.e., each record on the home health file) and is the variable required to link home health events to data files containing details on conditions (MEPS 2006 Medical Conditions File). For details on linking see Section 5.0 or the MEPS 2006 Appendix File, HC-102I.

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EVENTRN indicates the round in which the home health event was reported. Please note: Rounds 3, 4, and 5 are associated with MEPS survey data collected from Panel 10. Likewise, Rounds 1, 2, and 3 are associated with data collected from Panel 11.

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PANEL is a constructed variable used to specify the panel number for the person. PANEL will indicate either Panel 10 or Panel 11 for each person on the file. Panel 10 is the panel that started in 2005, and Panel 11 is the panel that started in 2006.

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This file contains variables describing home health events reported by household respondents in the Home Health Section of the MEPS HC survey questionnaire.

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The date variables (HHDATEYR and HHDATEMM) indicate the year and month that the household respondent reported as the year and month of occurrence for this type of home health event. An artifact of the data collection for the variable HHDATEYR is that a person may have started receiving that type of home health care from that provider prior to 2006. These variables should not be interpreted as "true" start dates.

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The HC questionnaire asked the respondent to indicate whether the home health provider event(s) for each month’s services were provided through an agency or an independent paid provider (SELFAGEN). The response to the SELFAGEN question dictated the skip pattern CAPI followed regarding the questions in the home health section of the HC questionnaire. The questionnaire also asked respondents if the provider was paid or whether a friend, relative, or volunteer (HHTYPE) provided the home health services. The constructed variable MPCELIG indicates whether the home health provider event was eligible for MPC data collection and the type of imputation process the event went through. MPCELIG is a more accurate variable for determining whether the event was an agency, a paid independent or an informal care event. However, SELFAGEN is a more accurate variable for determining the home health questions asked of the respondent. All respondents receiving care from an agency, hospital or nursing home were asked to identify the type of home health worker (CNA-SPEECTHP) they saw – for example, certified nursing assistant, home health aide, registered nurse, etc.

Analysts should keep in mind that these identifications by household respondents are subjective in nature, are not mutually exclusive or collectively exhaustive, and should not be used to make certain estimates. For example, a person on one type of insurance may identify an individual providing home health care services to them as a personal care attendant while an individual having a different type of insurance coverage may identify that same worker as a home care aide. Making estimates of personal care attendants or home care aides based on their identification by household respondents and treating these types of workers as mutually exclusive groups will result in inaccurate estimates. Respondents may also have indicated that they were seen by more than one home health care worker during a single event. For example, since an event is a month of services, a respondent may have reported being seen by a nurse, a physical therapist, and/or a home health aide during a single event. Respondents were also asked to identify other non-skilled, skilled, and other workers seen during that month of care (NONSKILL-OTHCWOS). However, "other specify" variables (SKILLWOS and OTHCWOS) were not reconciled with the type of health care worker variable (CNA-SPEECTHP). In addition, the type of health care worker variables (CNA-SPEECTHP) were not reconciled with MPCELIG, SELFAGEN and HHTYPE, so inconsistencies between these variables are possible.

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2.5.2.3 Treatments, Therapies, and Services (HOSPITAL-OTHSVCOS)

Regardless of the type of provider, all respondents were asked if the home health services received were due to a hospitalization (HOSPITAL), whether services were due to a medical condition (VSTRELCN), if the person was helped with daily activities (DAILYACT), if the person received companionship services (COMPANY), and whether or not the person received any other type of services (OTHSVCE and OTHSVCOS). Only persons receiving care from a formal provider were asked if they were taught how to use medical equipment (MEDEQUIP) and whether or not they received a medical treatment (TREATMT).

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Several variables identify the frequency and length of home health events (FREQCY-MINLONG) and whether or not the same services were received during each month (SAMESVCE). Frequency of event variables (FREQCY- TMSPDAY) were used as building blocks to construct HHDAYS. HHDAYS indicates the number of days the person received care during that event (i.e., month of care). Frequency variables can be combined to get a measure of the intensity of care. For example, HHDAYS can be used in conjunction with HRSLONG and TMSPDAY to form a measure of intensity of care, that is, how many hours of care were provided in one month.

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A flat fee is the fixed dollar amount a person is charged for a package of health care services provided during a defined period of time. Because MEPS does not collect flat fee information about home health events, no flat fee variables are included in this file.

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Information on household reported medical conditions and procedures (including condition codes, procedure codes, and clinical classification codes) associated with each home health event are NOT provided on this file. To obtain complete condition information associated with an event, the analyst must link to the 2006 Medical Conditions File. Details on how to link to the MEPS 2006 Medical Conditions File are provided in the MEPS 2006 Appendix File, HC-102I.

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2.5.5 Expenditure Data

Expenditures on this file refer to what is paid for health care services. More specifically, expenditures in MEPS are defined as the sum of payments for care received, including out-of-pocket payments and payments made by private insurance, Medicaid, Medicare and other sources. The definition of expenditures used in MEPS differs slightly from its predecessors, 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 1990s due to the increasingly common practice of discounting. Although measuring expenditures as the sum of payments incorporates discounts in the MEPS expenditure estimates, these estimates do not incorporate any payment not directly tied to specific medical care events, such as bonuses or retrospective payment adjustments paid by third party payers. Another general 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 charge data are provided on this file, data users/analysts should use caution when working with this data because a charge does not typically represent actual dollars exchanged for services or the resource costs of those services, nor are they directly comparable to the expenditures defined in the 1987 NMES (for details on expenditure definitions, see Monheit et al, 1999). For details on expenditure definitions, please refer to the following, "Informing American Health Care Policy" (Monheit et al., 2000). AHRQ has developed factors to apply to the 1987 NMES expenditure data to facilitate longitudinal analysis. These factors can be accessed via the CFACT Data Center. For more information, see the Data Center section of the MEPS Web site at www.meps.ahrq.gov/data_stats/onsite_datacenter.jsp. If examining trends in MEPS expenditures or performing longitudinal analysis on MEPS expenditures, please refer to section C, sub-section 3.3 for more information.

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The general methodology used for editing and imputing expenditure data is described below. However, please note, the MPC included home health events provided by an agency and did not include home health care provided by paid independent providers. Although the general procedures remain the same for all home health events, there were some differences in the editing and imputation methodologies applied to those events followed in the MPC and those events not followed in the MPC. Analysts should note that home health care provided by friends, family, or volunteers was assumed to be free and was not included in any imputation process. Please see below for details on the differences between these editing/imputation methodologies.

Home health expenditure data for agency, hospital, and nursing home providers were collected exclusively from the MPC (i.e., household respondents were not asked to report home health expenditures from these types of providers). The MPC contacted 100 percent of the agency, hospital, and nursing home health providers identified by household respondents. Since paid independent home health providers were not included in the MPC, all expenditure data from these providers were collected from household respondents.

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Logical edits were used to resolve internal inconsistencies and other problems in the HC and MPC survey-reported data. The edits were designed to preserve partial payment data from households and providers, and to identify actual and potential sources of payment for each household-reported event. In general, these edits accounted for outliers, co-payments 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 mis-classifications between Medicare and Medicaid and between Medicare HMOs and private HMOs as payment sources. These edits produced a complete vector of expenditures for some events, and provided the starting point for imputing missing expenditures in the remaining events.

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A weighted sequential hot-deck procedure was used to impute for missing expenditures, as well as total charge. This procedure uses survey data from respondents to replace missing data, while taking into account the respondents’ weighted distribution in the imputation process. Classification variables vary by event type in the hot-deck imputations, but total charge and insurance coverage are key variables in all of the imputations. Separate imputations were performed for nine categories of medical provider care: inpatient hospital stays, outpatient hospital department visits, emergency room visits, visits to physicians, visits to non-physician providers, dental services, home health care by certified providers, home health care by paid independents, and other medical expenses. Within this file, simple events were imputed separately. After the imputations were finished, visits to physician and non-physician providers were combined into a single medical provider file. The two categories of home care also were combined into a single home health file.

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Expenditures for home health events were developed in a sequence of logical edits and imputations. (Analysts should note that home health care provided by friends, family, or volunteers was assumed not to have associated expenditures and was not included in any imputation process. All expenditures for home health care provided by informal care providers were assigned "–1" (INAPPLICABLE) because those types of events were skipped out (never asked) of the questions regarding expenditures.) "Household" edits were applied to sources and amounts of payment for all household-reported events for paid independent providers and unmatched agency providers. "MPC" edits were applied to provider-reported sources and amounts of payment for records matched to household-reported events for all agency home health providers. Both sets of edits were used to correct obvious errors in the reporting of expenditures. Imputations for independent paid providers and for agencies were conducted separately. Within this file, separate imputations were performed for simple events.

Logical edits were used to sort each event into a specific category for the imputations. Events with complete expenditures were flagged as potential donors for the hot-deck imputations while events with missing expenditure data were assigned to various recipient categories. Each event with missing expenditure data was assigned to a recipient category based on the extent of its missing charge and expenditure data. For example, an event with a known total charge but no expenditure information was assigned to one category, while an event with a known total charge and partial expenditure information was assigned to a different category. Similarly, events without a known total charge and no or partial expenditure information were assigned to various recipient categories.

The logical edits produced eight recipient categories for HHP and eight recipient categories for HHA for events with missing data. Expenditures were imputed through separate hot-deck imputations for each of the eight recipient categories. The donor pool in these imputations includes events with complete expenditures from the HC for HHP or the MPC for HHA.

The donor pool included "free events" because, in some instances, providers are not paid for their services. These events represent charity care, bad debt, provider failure to bill, and third party payer restrictions on reimbursement in certain circumstances. (This does not include MPCELIG=3 (informal) events. As stated previously, home health care provided by friends, family, or volunteers (informal, MPCELIG=3) was assumed not to have expenditures associated with it and was not included in any imputation process.)

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IMPFLAG is a six-category variable that indicates if the event contains complete Household Component (HC) or Medical Provider Component (MPC) data, was fully or partially imputed, or was imputed in the capitated imputation process. The following list identifies how the imputation flag is coded; the categories are mutually exclusive.

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A flat fee is the fixed dollar amount a person is charged for a package of health care services provided during a defined period of time. Because MEPS does not collect flat fee information about home health events, there are no flat fee expenditure data included in this file.

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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) follow-up events were provided without a separate charge (e.g., after a surgical procedure), or (4) the event was paid for through government or privately-funded research or clinical trials. If all of the medical events for a person fell into one of these categories, then the total annual expenditures for that person would be zero. All expenditures for home health care provided by informal care providers (family, friends, or volunteers, MPCELIG=3) were assigned –1 "INAPPLICABLE" because those types of events were skipped out (never asked) of the questions regarding expenditures.

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

Two additional source of payment variables were created to classify payments for events with apparent inconsistencies between insurance coverage and sources of payment based on data collected in the survey. These variables include:

Though relatively small in magnitude, data users/analysts should exercise caution when interpreting the expenditures associated with these two additional sources of payment. While these payments stem from apparent inconsistent responses to 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 sampled 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 from persons who were not enrolled in Medicaid, but were presumed eligible by a provider who ultimately received payments from the public payer.

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2.5.5.7 Home Health Expenditure Variables (HHSF06X - HHXP06X)

Home health agency, hospital, and nursing home events are sampled at a rate of 100% for the MPC. Households were not asked any expenditure-related questions in regards to these types of events; therefore, there are no household reported expenditure data for these events. Conversely, paid independent providers are not included in the MPC. Household reported responses are the only data available for these types of events. All expenditure data for paid independent providers are fully imputed from household reported expenditures. There are no expenditure data for informal care providers. Informal care (MPCELIG=3, unpaid care provided by family, friends, or volunteers) was assigned -1, "INAPPLICABLE", in all expenditure categories.

The constructed variable MPCELIG is provided on this file. MPCELIG indicates whether the home health provider event was eligible for MPC data collection, and MPCELIG determines the imputation process applied to that event.

All of these expenditures have gone through an editing and imputation process and have been rounded to the nearest penny. HHSF06X - HHOT06X are the 12 sources of payment. HHTC06X is the total charge, and HHXP06X is the sum of the 12 sources of payment for the home health expenditures. The 12 sources of payment are: self/family (HHSF06X), Medicare (HHMR06X), Medicaid (HHMD06X), private insurance (HHPV06X), Veterans Administration (HHVA06X), TRICARE/CHAMPVA (HHTR06X), other Federal sources (HHOF06X), State and Local (non-federal) government sources (HHSL06X), Workers’ Compensation (HHWC06X), other private insurance (HHOR06X), other public insurance (HHOU06X), and other insurance (HHOT06X). Analysts can determine if a home health event was provided by an agency or by some other paid independent provider by subsetting the variable MPCELIG to the appropriate and desired value.

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Expenditure variables on the 2006 home health event file have been rounded to the nearest penny. Person-level expenditure information released on the 2006 Person-Level Expenditure File was rounded to the nearest dollar. It should be noted that using the 2006 MEPS event files to create person-level totals will yield slightly different totals than those on the person-level expenditure file. These differences are due to rounding only. Moreover, in some instances, the number of persons having expenditures on the event files for a particular source of payment may differ from the number of persons with expenditures on the person-level expenditure file for that source of payment. This difference is also an artifact of rounding only. Please see the MEPS 2006 Appendix File, HC-102I, for details on such rounding differences.

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There is a single full year person-level weight (PERWT06F) assigned to each record for each key, in-scope person who responded to MEPS for the full period of time that he or she was in-scope during 2006. A key person either was a member of an NHIS household at the time of the NHIS interview, or became a member of a family associated with such a household after being out-of-scope at the time of the NHIS (the latter circumstance includes newborns as well as persons returning from military service, an institution, or living outside the United States). A person is in-scope whenever he or she is a member of the civilian noninstitutionalized portion of the U.S. population.

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3.2 Details on Person Weight Construction

The person-level weight PERWT06F was developed in several stages. Person-level weights for Panels 10 and 11 were created separately. The weighting process for each panel included an adjustment for nonresponse over time and calibration to independent population figures. The calibration was initially accomplished separately for each panel by raking the corresponding sample weights to Current Population Survey (CPS) population estimates based on five variables. The five variables used in the establishment of the initial person-level control figures were: census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, non-Hispanic with black as sole reported race, non-Hispanic with Asian as sole reported race, and other); sex; and age. A 2006 composite weight was then formed by multiplying each weight from Panel 10 by the factor .47 and each weight from Panel 11 by the factor .53. The choice of factors reflected the relative sample sizes of the two panels, helping to limit the variance of estimates obtained from pooling the two samples. The composite weight was again raked to the same set of CPS-based control totals. When poverty status information derived from income variables became available, a final raking was undertaken on the previously established weight variable. Control totals were established using poverty status (five categories: below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty) as well as the original five variables used in the previous calibrations.

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The person-level weight for MEPS Panel 10 was developed using the 2005 full year weight for an individual as a "base" weight for survey participants present in 2005. For key, in-scope respondents who joined an RU some time in 2006 after being out-of-scope in 2005, the 2005 family weight associated with the family the person joined served as a "base" weight. The weighting process included an adjustment for nonresponse over Rounds 4 and 5 as well as raking to population control figures for December 2006. These control figures were derived by scaling back the population totals obtained from the March 2007 CPS to correspond to a national estimate for the civilian noninstitutionalized population provided by the Census Bureau for December 2006. Variables used in the establishment of person-level control figures included: census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, Asian but non-Hispanic, and other); sex; and age. Overall, the weighted population estimate for the civilian noninstitutionalized population on December 31, 2006 is 295,668,762. Key, responding persons not in-scope on December 31, 2006 but in-scope earlier in the year retained, as their final Panel 10 weight, the weight after the nonresponse adjustment.

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The person-level weight for MEPS Panel 11 was developed using the MEPS Round 1 person-level weight as a "base" weight. For key, in-scope respondents who joined an RU after Round 1, the Round 1 family weight served as a "base" weight. The weighting process included an adjustment for nonresponse over Round 2 and the 2006 portion of Round 3 as well as raking to the same population control figures for December 2006 used for the MEPS Panel 10 weights. The same five variables employed for Panel 10 raking (census region, MSA status, race/ethnicity, sex, and age) were used for Panel 11 raking. Similarly, for Panel 11, key, responding persons not in-scope on December 31, 2006 but in-scope earlier in the year retained, as their final Panel 11 weight, the weight after the nonresponse adjustment.

Note that the MEPS Round 1 weights incorporated the following components: the original household probability of selection for the NHIS; ratio-adjustment to NHIS-based national population estimates at the household (occupied dwelling unit) level; adjustment for nonresponse at the dwelling unit level for Round 1; and poststratification to figures at the family and person level obtained from the March CPS data base of the corresponding year (i.e., 2005 for Panel 10 and 2006 for Panel 11).

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Variables used in the establishment of person-level control figures included: poverty status (below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty); census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic, non-Hispanic with black as sole reported race, non-Hispanic with Asian as sole reported race, and other); sex; and age. Overall, the weighted population estimate for the civilian noninstitutionalized population for December 31, 2006 is 295,668,762 (PERWT06F>0 and INSC1231=1). In addition, the weights of two groups of persons who were out-of-scope on December 31, 2006 were poststratified. Specifically, the weights of those who were in-scope some time during the year, out-of-scope on December 31, and entered a nursing home during the year were poststratified to a corresponding control total obtained from the 1996 MEPS Nursing Home Component. Those who died while in-scope during 2006 were poststratified to corresponding estimates derived using data obtained from the Medicare Current Beneficiary Survey (MCBS) and Vital Statistics information provided by the National Center for Health Statistics (NCHS).  Separate control totals were developed for the "65 and older" and "under 65" civilian noninstitutionalized populations. The sum of the person-level weights across all persons assigned a positive person level weight is 299,267,035.

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The target population for MEPS in this file is the 2006 U.S. civilian noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 2004 (Panel 10) and 2005 (Panel 11). New households created after the NHIS interviews for the respective Panels and consisting exclusively of persons who entered the target population after 2004 (Panel 10) or after 2005 (Panel 11) are not covered by MEPS. Neither are previously out-of-scope persons who join an existing household but are unrelated to the current household residents. Persons not covered by a given MEPS panel thus include some members of the following groups: immigrants; persons leaving the military; U.S. citizens returning from residence in another country; and persons leaving institutions. The set of uncovered persons constitutes only a small segment of the MEPS target population.

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MEPS began in 1996, and the utility of the survey for analyzing health care trends expands with each additional year of data. However, it is important to consider a variety of factors when examining trends over time using MEPS. Statistical significance tests should be conducted to assess the likelihood that observed trends may be attributable to sampling variation. The length of time being analyzed should also be considered. In particular, large shifts in survey estimates over short periods of time (e.g. from one year to the next) that are statistically significant should be interpreted with caution, unless they are attributable to known factors such as changes in public policy, economic conditions, or MEPS survey methodology. Looking at changes over longer periods of time can provide a more complete picture of underlying trends. Analysts may wish to consider using techniques to smooth or stabilize analyses of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97 versus 2004-05), working with moving averages, or using modeling techniques with several consecutive years of MEPS data to test the fit of specified patterns over time. Finally, researchers should be aware of the impact of multiple comparisons on Type I error. Without making appropriate allowance for multiple comparisons, undertaking numerous statistical significance tests of trends increases the likelihood of inappropriately concluding that a change has taken place.

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The data in this file can be used to develop national 2006 event level (i.e., monthly) estimates for the U.S. civilian noninstitutionalized population on expenditures and sources of payment for home health care medical provider visits. The weight assigned to each home health care medical provider event reported is the person-level weight of the person who was visited. If a person had several events reported, each event is assigned that individual’s person-level weight. Estimates must be weighted by PERWT06F to be nationally representative. For example, the appropriate estimate for the overall mean out-of-pocket payment per month of care is computed as follows (the subscript ‘j’ identifies each event and represents a numbering of events from 1 through the total number of events in the file):

Estimates and corresponding standard errors (SE) can be derived using an appropriate computer software package for complex survey analysis such as SAS, Stata, SUDAAN or SPSS (www.meps.ahrq.gov/survey_comp/standard_errors.jsp).

The tables below contain the correct event-level estimates for several key variables on this file. Informal care (MPCELIG = 3) is not included in the tables because, by definition, there are no payments for those events and, therefore, no expenditure data are collected.

Selected Event-Level Estimates

Expenditures: Home Health Agency & Paid Independents (MPCELIG = 1, 2):

Expenditures: Home Health Agency Providers only (MPCELIG=1)

Expenditures: Paid Independent Providers only (MPCELIG=2)

*Zero payment events can occur in MEPS for the following reasons: (1) there was no charge for a follow-up event, (2) the provider was never paid by an individual, insurance plan, or other source for services provided, (3) charges were included in another bill, or (4) the event was paid for through government or privately-funded research or clinical trials.

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To enhance analyses of home health care, analysts may link information about the home health care received by sample persons in this file to the annual full year consolidated file (which has data for all MEPS sample persons), or conversely, link person-level information from the full year consolidated file to this event level file. Both this file and the full year consolidated file may be used to derive estimates relative to persons with home health care and annual estimates of total expenditures. However, if the estimate relates to the entire population, this file cannot be used to calculate the denominator, as only those persons with at least one month in which home health care was provided are represented on this data file. Therefore, the full year consolidated file must be used for person-level analyses that include both those with and without home health care.

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It is essential that the analyst examine all variables for the presence of negative values used to represent missing values. For continuous or discrete variables, where means or totals may be taken, it may be necessary to set negative values to values appropriate to the analytic needs. That is, the analyst should either impute a value or set the value to one that will be interpreted as missing by the computing language used. For categorical and dichotomous variables, the analyst may want to consider whether to recode or impute a value for cases with negative values or whether to exclude or include such cases in the numerator and/or denominator when calculating proportions. Methodologies used for the editing/imputation of expenditure variables (e.g., sources of payment and zero expenditures) are described in Section 2.5.5.2.

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MEPS has a complex sample design. To obtain estimates of variability (such as the standard error of sample estimates or corresponding confidence intervals) for MEPS estimates, analysts need to take into account the complex sample design of MEPS for both person-level and family-level analyses. Several methodologies have been developed for estimating standard errors for surveys with a complex sample design, including the Taylor-series linearization method, balanced repeated replication, and jackknife replication. Various software packages provide analysts with the capability of implementing these methodologies. Replicate weights have not been developed for the MEPS data. Instead, the variables needed to calculate appropriate standard errors based on the Taylor-series linearization method are included on this file as well as all other MEPS public use files. Software packages that permit the use of the Taylor-series linearization method include SUDAAN, Stata, SAS (version 8.2 and higher), and SPSS (version 12.0 and higher). For complete information on the capabilities of each package, analysts should refer to the corresponding software user documentation.

Using the Taylor-series linearization method, variance estimation strata and the variance estimation PSUs within these strata must be specified. The variance strata variable is named VARSTR, while the variance PSU variable is named VARPSU. Specifying a "with replacement" design in a computer software package, such as SUDAAN, provides standard errors appropriate for assessing the variability of MEPS survey estimates. It should be noted that the number of degrees of freedom associated with estimates of variability indicated by such a package may not appropriately reflect the actual number available. For MEPS sample estimates for characteristics generally distributed throughout the country (and thus the sample PSUs), one can expect at least 100 degrees of freedom for the 2006 full year data associated with the corresponding estimates of variance.

Prior to 2002, MEPS variance strata and PSUs were developed independently from year to year, and the last two characters of the strata and PSU variable names denoted the year. However, beginning with the 2002 Point-in-Time PUF, the variance strata and PSUs were developed to be compatible with MEPS data associated with the NHIS sample design used through 2006. Such data can be pooled and the variance strata and PSU variables provided can be used without modification for variance estimation purposes for estimates covering multiple years of data. There are 203 variance estimation strata, each stratum with either two or three variance estimation PSUs.

Note: A new NHIS sample design is being implemented beginning in 2006. As a result, the MEPS variance estimation structure will be modified for MEPS data collected in 2007 and beyond.

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Data from this file can be used alone or in conjunction with other files for different analytic purposes. This section provides instructions, or the details on where to find the instructions, for linking the 2006 home health provider events with other 2006 MEPS public use files, including the 2006 person-level and conditions files. Each MEPS panel can also be linked back to the previous years’ National Health Interview Survey public use data files. For information on obtaining MEPS/NHIS link files please see www.meps.ahrq.gov/data_stats/more_info_download_data_files.jsp.

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Merging characteristics of interest from other 2006 MEPS files (e.g., the 2006 Full Year Population Characteristics File or the 2006 Prescribed Medicines File) expands the scope of potential estimates. For example, to estimate the total number of home health provider events of persons with specific characteristics (e.g., age, race, and sex), population characteristics from a person-level file need to be merged onto the home health provider file. This procedure is illustrated below. The MEPS 2006 Appendix File, HC-102I, provides additional details on how to merge 2006 MEPS data files.

1. Create data set PERSX by sorting the 2006 Full Year Population Characteristics File by the person identifier, DUPERSID. Keep only variables to be merged on to the home health provider event file and DUPERSID.
    
2. Create data set HVIS by sorting the home health provider event file by person identifier, DUPERSID.
    
3. Create final data set NEWHVIS by merging these two files by DUPERSID, keeping only records on the home health provider event file.

The following is an example of SAS code, which completes these steps:

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The RXLK provides a link from 2006 MEPS event files to the 2006 Prescribed Medicines File. Because prescribed medicines data are not collected for home health events, this Home Health File cannot be linked to the 2006 Prescribed Medicines File.

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5.3 Linking to the Medical Conditions File

The CLNK provides a link from 2006 MEPS event files to the 2006 Medical Conditions File. When using the CLNK, data users/analysts should keep in mind that (1) conditions are self-reported and (2) there may be multiple conditions associated with a home health provider event. Data users/analysts should also note that not all home health provider events link to the condition file. For detailed linking examples, including SAS code, data users/analysts should refer to the MEPS 2006 Appendix File, HC-102I.

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To facilitate analysis of subpopulations and/or low prevalence events, it may be desirable to pool together more than one year of data to yield sample sizes large enough to generate reliable estimates. For more details on pooling MEPS data files see www.meps.ahrq.gov/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-036.

Starting in Panel 9, values for DUPERSID from previous panels will occasionally be re-used. Therefore, it is necessary to use the panel variable (PANEL) in combination with DUPERSID to ensure unique person-level identifiers across panels. Creating unique records in this manner is advised when pooling MEPS data across multiple annual files that have one or more identical values for DUPERSID.

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MEPS Panel Longitudinal Weight files containing estimation variables to facilitate longitudinal analysis are available for downloading in the data section of the MEPS Web site.

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References

Cohen, S.B. (1999). Sample Design of the 1996 Medical Expenditure Panel Survey Medical Provider Component. Journal of Economic and Social Measurement. Vol 24, 25-53.

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

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

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

Cox, B.G. and Cohen, S.B. (1985). Chapter 8: Imputation Procedures to Compensate for Missing Responses to Data Items. In Methodological Issues for Health Care Surveys. Marcel Dekker, New York.

Monheit, A.C., Wilson, R., and Arnett, III, R.H. (Editors) (1999). Informing American Health Care Policy. Jossey-Bass Inc, San Francisco.

Shah, B.V., Barnwell, B.G., Bieler, G.S., Boyle, K.E., Folsom, R.E., Lavange, L., Wheeless, S.C., and Williams, R. (1996). Technical Manual: Statistical Methods and Algorithms Used in SUDAAN Release 7.0, Research Triangle Park, NC: Research Triangle Institute.

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D. Variable-Source Crosswalk

VARIABLE-SOURCE CROSSWALK

FOR MEPS HC-102H: 2006 HOME HEALTH VISITS

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