MEPS HC-110D: 2007 Hospital Inpatient Stays

Individual identifiers have been removed from the micro-data contained in these files. Nevertheless, under sections 308 (d) and 903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or the National Center for Health Statistics (NCHS) may not be used for any purpose other than for the purpose for which they were supplied; any effort to determine the identity of any reported cases is prohibited by law.

Therefore in accordance with the above referenced Federal Statute, it is understood that:

By using these data you signify your agreement to comply with the above stated statutorily based requirements with the knowledge that deliberately making a false statement in any matter within the jurisdiction of any department or agency of the Federal Government violates Title 18 part 1 Chapter 47 Section 1001 and is punishable by a fine of up to $10,000 or up to 5 years in prison.

The Agency for Healthcare Research and Quality requests that users cite AHRQ and the Medical Expenditure Panel Survey as the data source in any publications or research based upon these data.

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

The MEPS-HC was initiated in 1996. Each year a new panel of 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. In 2006, the NHIS implemented a new sample design, which included Asian persons in addition to households with black and Hispanic persons in the oversampling of minority populations. MEPS further oversamples additional policy relevant sub-groups such as low income households. The linkage of the MEPS to the previous year’s NHIS provides additional data for longitudinal analytic purposes.

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.

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).

This documentation describes one in a series of public use event files from the 2007 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 SAS transport file, the 2007 Hospital Inpatient Stays (STAZ) public use file provides detailed information on hospital inpatient stays for a nationally representative sample of the civilian noninstitutionalized population of the United States. Data from the STAZ event file can be used to make estimates of hospital inpatient stay utilization and expenditures for calendar year 2007. The file contains 63 variables and has a logical record length of 359 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 from the 2007 portion of Round 3 and Rounds 4 and 5 for Panel 11, as well as Rounds 1, 2 and the 2007 portion of Round 3 for Panel 12 (i.e., the rounds for the MEPS panels covering calendar year 2007).

Hospital stay events reported in Panel 12 Round 3 and known to have begun after December 31, 2007 are not included on this file.

Each record on the inpatient hospital event file represents a unique hospital inpatient stay reported by the household respondent. In addition to expenditures related to the stay, each record contains household-reported medical conditions and procedures associated with the hospitalization and information on the length of stay.

Annual counts of hospital inpatient stay utilization are based entirely on household reports. Information from the MEPS MPC is 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 2007 MEPS HC data files for purposes of appending person-level data such as demographic characteristics or health insurance coverage to each hospital inpatient stay record.

This file can also be used to construct summary variables of expenditures, sources of payment, and related aspects of hospital inpatient care. Aggregate annual person-level information on the use of hospital inpatient stays and other health services use is provided on the MEPS 2007 Full Year Consolidated Data File, where each record represents a MEPS sampled person.

This documentation offers an overview of the types and levels of data provided, and the content and structure of the files and the codebook. It contains the following sections:

Any variables not found on this file but released on previous years’ files were excluded because they contained only missing data.

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. Copies of the HC and the MPC survey instruments used to collect the information on the STAZ file are available in the Survey Instruments section on the MEPS Web site at the following address: www.meps.ahrq.gov.

The 2007 Hospital Inpatient Stays public use data set consists of one event-level data file. The file contains characteristics associated with the STAZ event and imputed expenditure data.

The 2007 STAZ public use data set contains variable and frequency distributions for a total of 3,040 hospital inpatient stay records reported during the 2007 portion of Round 3 and Rounds 4 and 5 for Panel 11, as well as Rounds 1, 2, and the 2007 portion of Round 3 for Panel 12 of the MEPS Household Component. This file includes hospital inpatient stay records for all household survey respondents who resided in eligible responding households and reported at least one hospital inpatient stay. Hospital inpatient stay records known to have ended before January 1, 2007 or after December 31, 2007 are not included on this file. Some household respondents may have multiple hospital inpatient stays and, thus, will be represented in multiple records on this file. Other household respondents may have reported no hospital inpatient stays and, thus, will have no records on this file. Of the 3,040 hospital inpatient stay records, 2,929 are associated with persons having a positive person-level weight (PERWT07F). The persons represented on this file had to meet the following three criteria:

One caveat that should be noted is that in the case of a newborn and the hospital inpatient stay associated with the newborn’s birth, a separate hospital inpatient stay record exists on the file only if the newborn was discharged after the mother. Thus, hospital stays associated with a normal birth are generally represented on the file as a single record (i.e., the mother’s hospital inpatient stay record, covering expenditure data for both the mother and baby). In situations where the newborn was discharged after the mother, the birth event will be represented as two records: one record for the mother and one record for the baby. For newborns re-admitted to the hospital during the reference year, each subsequent re-admission will have a separate record.

Each inpatient record includes the following: start and end dates of the hospital inpatient stay; number of nights in the hospital; reason entered the hospital; condition(s) associated with the hospital inpatient stay; medicines prescribed at discharge; flat fee information; imputed sources of payment; total payment and total charge for both the facility and physician portions of the hospital inpatient stay expenditure; a full-year person-level weight; variance strata; and variance PSU.

To append person-level information such as demographic or health insurance coverage to each event record, data from this file can be merged with 2007 MEPS HC person-level data (e.g. Full Year Consolidated or Full Year Population Characteristics files) using the person identifier, DUPERSID. Hospital inpatient stay events can also be linked to the MEPS 2007 Medical Conditions File and the MEPS 2007 Prescribed Medicines File. Please see Section 5.0 or the MEPS 2007 Appendix File, HC-110I, for details on how to merge MEPS data files.

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

Generally, the 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 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).

The STAZ 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:

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

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

The names of the expenditure and source of payment variables follow a standard convention, are eight 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 12 sources of payment variables are named in the following way:

For expenditure variables on the IP file, the third character indicates whether the expenditure is associated with the facility (F) or the physician (D).

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

The sixth and seventh characters indicate the year (07). The eighth character, "X", indicates whether the variable is edited/imputed.

For example, IPFSF07X is the edited/imputed amount paid by self or family for the facility portion of the hospital inpatient stay expenditure incurred in 2007.

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 2007 Full Year Population Characteristics File.

EVNTIDX uniquely identifies each hospital inpatient stay/event (i.e., each record on the STAZ file) and is the variable required to link hospital inpatient stay events to data files containing details on conditions and/or prescribed medicines (MEPS 2007 Medical Conditions File and MEPS 2007 Prescribed Medicines File, respectively). For details on linking, see Section 5.0 or the MEPS 2007 Appendix File, HC-110I.

ERHEVIDX is a constructed variable identifying a STAZ record that includes the facility expenditures for the preceding emergency room visit. This variable is derived from provider-reported information on linked emergency room and inpatient stay events that matched to corresponding events reported by the household. The variable ERHEVIDX contains the EVNTIDX of the linked event. On the 2007 STAZ file, there are 497 hospital stays linked to a preceding emergency room visit, that is, there are records with a valid ERHEVIDX value. ERHEVIDX has not been reconciled with the unedited variable EMERROOM. Please note that, the physician expenditures associated with the emergency room visit remain on the emergency room file.

FFEEIDX is a constructed variable which uniquely identifies a flat fee group, that is, all events that were a part of a flat fee payment. For example, dialysis treatments are typically covered in a flat fee arrangement where all visits are covered under one flat fee dollar amount. These events would have the same value for FFEEIDX.

EVENTRN indicates the round in which the hospital inpatient stay was first reported. Please note that Rounds 3, 4, and 5 are associated with MEPS survey data collected from Panel 11. Likewise, Rounds 1, 2, and 3 are associated with data collected from Panel 12.

PANEL is a constructed variable used to specify the panel number for the person. PANEL will indicate either Panel 11 or Panel 12 for each person on the file. Panel 11 is the panel that started in 2006, and Panel 12 is the panel that started in 2007.

MPCDATA is a constructed variable which indicates whether or not MPC data were collected for the hospital inpatient stay. While all hospital inpatient events are sampled into the Medical Provider Component, not all hospital inpatient stay records have MPC data associated with them. This is dependent upon the cooperation of the household respondent to provide permission forms to contact the hospital as well as the cooperation of the hospital to participate in the survey.

This file contains variables describing hospital inpatient stays/events reported by household respondents in the Hospital Stays section of the MEPS HC questionnaire. The questionnaire contains specific probes for determining details about the hospital inpatient stay.

This file contains variables describing hospital inpatient stays reported by household respondents in the Hospital Stays section of the MEPS HC questionnaire. There are three variables which indicate the day, month, and year a hospital stay began (IPBEGDD, IPBEGMM, and IPBEGYR, respectively). Similarly, there are three variables which indicate the day, month, and year a hospital stay ended (IPENDDD, IPENDMM, and IPENDYR, respectively). These variables have not been edited.

NUMNIGHX denotes the length of a hospital inpatient stay. For stays beginning in 2006 and ending in 2007, this variable would include the nights associated with the entire visit. It was edited using the above mentioned begin and end dates of the hospital inpatient stay (Section 2.5.3.1). If the dates were unknown, then NUMNIGHX used the number from the unedited variable NUMNIGHT (number of nights in the hospital). If both the dates and NUMNIGHT were missing data, then NUMNIGHX was imputed. Users should note that NUMNIGHT was only asked for events with missing date information. Hence, it contains large amounts of missing data and cannot be used alone but rather in conjunction with date information.

The variable EMERROOM was derived directly from the Hospital Inpatient Stays section of the HC survey instrument and is unedited. EMERROOM describes whether or not the hospital inpatient stay began with an emergency room visit. Data users/analysts should be aware that no attempt was made to reconcile EMERROOM with information from the Emergency Room Visit File. Furthermore, no attempt has been made to reconcile the unedited EMERROOM variable with the edited ERHEVIDX variable (see section 2.5.1.2).

Also provided are the following unedited variables: hospital inpatient stays related to a medical condition (SPECCOND); the reason the person entered the hospital (RSNINHOS); any operation or surgery performed while the respondent was in the hospital (ANYOPER). The category "Pregnancy-Related Complications" was added to RSNINHOS starting in Panel 12 Round 1; it was not added to Panel 11 Rounds 3 through 5. Therefore, in 2007 only, this category was recoded to "Other" (RSNINHOS = 91) on applicable Panel 12 records. "Pregnancy-Related Complications" will be included as a separate category in the 2008 version of this file.

With respect to RSNINHOS, please note that while there were 407 cases where RSNINHOS = 4 (reason entered hospital – to give birth to a baby), this does not mean that there were actually 407 new births. In fact, it may have been reported that the mother went to the hospital for delivery (hence, the interviewer would have assigned the event RSNINHOS = 4), but the mother could have had, for example, false labor pains or a stillbirth. Thus, this unedited self-reported variable may be inconsistent with reported number of births (see the 2007 Full Year Population Characteristics File, Section 2.5.2 "Navigating the MEPS Data with Information on Person Disposition Status"). In addition, RSNINHOS has not been edited to ensure alignment with the ICD-9-CM condition codes, the procedure codes, or the CCC codes associated with an event.

VAPLACE, a constructed variable that indicates whether the service was provided at a VA facility, was dropped from this file for confidentiality purposes beginning in 2007.

Information on household-reported medical conditions and procedures associated with each hospital inpatient stay event is provided on this file. There are up to four condition and CCC codes (IPICD1X-IPICD4X, IPCCC1X-IPCCC4X) and up to two procedure codes (IPPRO1X and IPPRO2X) listed for each hospital inpatient stay event. In order to obtain complete condition information associated with an event, the data user/analyst must link to the MEPS 2007 Medical Conditions File. Details on how to link the 2007 STAZ file to the MEPS 2007 Medical Conditions File are provided in Section 5.2 and the MEPS 2007 Appendix File, HC-110I. The data user/analyst should note that provider-reported condition information is not publicly available because of confidentiality restrictions.

The medical conditions and procedures reported by the Household Component respondent were recorded by the interviewer as verbatim text, which was then coded by professional coders to fully-specified 2007 ICD-9-CM codes, including medical condition and V codes (Health Care Financing Administration, 1980). Although codes were verified and error rates did not exceed 2.5 percent for any coder, data users/analysts should not presume this level of precision in the data; the ability of household respondents to report condition data that can be coded accurately should not be assumed (Cox and Cohen, 1985; Cox and Iachan, 1987; Edwards, et al., 1994; and Johnson and Sanchez, 1993). For detailed information on how conditions and procedures were coded, please refer to the documentation on the MEPS 2007 Medical Conditions File. For frequencies of conditions by event type, please see the MEPS 2007 Appendix File, HC-110I.

The ICD-9-CM condition codes were aggregated into clinically meaningful categories. These categories, included on the file as IPCCC1X-IPCCC4X, were generated using Clinical Classification Software [formerly known as Clinical Classifications for Health Care Policy Research (CCHPR), (Elixhauser, et al., 1998)] which aggregates conditions and V-codes into mutually exclusive categories, most of which are clinically homogeneous.

In order to preserve respondent confidentiality, nearly all of the condition codes provided on this file have been collapsed from fully-specified codes to three-digit code categories. The reported ICD-9-CM code values were mapped to the appropriate clinical classification category prior to being collapsed to the three-digit categories. Similarly, the procedure codes have been collapsed from fully-specified codes to two-digit code categories. Because of this collapsing, it is possible for there to be duplicate ICD-9-CM condition or procedure codes linked to a single medical event when different fully-specified codes are collapsed into the same code. For more information on ICD-9-CM codes, see the MEPS 2007 Medical Conditions File documentation.

The condition (and clinical classification codes) and procedure codes linked to each hospital inpatient stay event are sequenced in the order in which the conditions were reported by the household respondent, which was in order of input into the database and not in order of importance or severity. Data users/analysts who use the MEPS 2007 Medical Conditions File in conjunction with this hospital inpatient stay event file should note that the order of conditions on this file is not identical to that on the Medical Conditions file.

The user should also note that because of the design of the HC survey instrument, most hospital stays that are reported as being for a delivery (RSNINHOS=4) link to condition codes that are for pregnancy rather than a delivery. In addition, RSNINHOS has not been reconciled with the ICD-9-CM condition codes, the procedure codes, or the CCC codes that are on the file.

Analysts should use the clinical classification codes listed in the Conditions PUF document (HC-112) and the Appendix to the Event Files (HC-110I) document when analyzing MEPS conditions data. Although there is a list of clinical classification codes and labels on the Healthcare Cost and Utilization Project (HCUP) Web site, if updates to these codes and/or labels are made on the HCUP Web site after the release of the 2007 MEPS PUFs, these updates will not be reflected in the 2007 MEPS data.

DSCHPMED is derived directly from the Hospital Stays Section of the HC survey instrument. DSCHPMED indicates whether or not any medicines were prescribed at discharge.

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. Examples would be: obstetrician’s fee covering a normal delivery, as well as pre- and post-natal care; or a surgeon’s fee covering surgical procedure and post-surgical care. A flat fee group is the set of medical services (i.e., events) that are covered under the same flat fee payment. The flat fee groups represented on the STAZ file include flat fee groups where at least one of the health care events, as reported by the HC respondent, occurred during 2007. By definition, a flat fee group can span multiple years. Furthermore, a single person can have multiple flat fee groups.

As noted earlier in Section 2.5.1.2 "Record Identifiers," the variable FFEEIDX uniquely identifies all events that are part of the same flat fee group for a person. On any 2007 MEPS event file, every event that is part of a specific flat fee group will have the same value for FFEEIDX. Note that prescribed medicine and home health events are never included in a flat fee group and FFEEIDX is not a variable on those event files. Because there were no 2007 flat fee events, this variable was omitted from this file.

FFIPTYPE indicates whether the 2007 hospital stay is the "stem" or "leaf" of a flat fee group. A stem (records with FFIPTYPE = 1) is the initial medical service (event) which is followed by other medical events that are covered under the same flat fee payment. The leaves of the flat fee group (records with FFIPTYPE = 2) are those medical events that are tied back to the initial medical event (the stem) in the flat fee group. These "leaf" records have their expenditure variables set to zero. For the hospital inpatient stays that are not part of a flat fee payment, the FFIPTYPE is set to –1, "INAPPLICABLE." Because there were no 2007 flat fee events, this variable was omitted from this file.

As explained in Section 2.5.4.1, a flat fee payment covers multiple events and the multiple events could span multiple years. For situations where the hospital inpatient stay/event occurred in 2007 as a part of a group of events, and some event occurred before or after 2007, counts of the known events are provided on the STAZ record. Variables that indicate events occurred before or after 2007 are as follows:

If there are no 2006 events on the file, FFBEF07 will be omitted. Likewise, if there are no 2008 events on the file, FFTOT08 will be omitted. If there are no flat fee data related to the records in this file, FFEEIDX and FFIPTYPE will be omitted as well. Please note that the crosswalk in this document lists all possible flat fee variables.

There are no hospital inpatient stays/events that are identified as being part of a flat fee payment group. In general, every flat fee group should have an initial visit (stem) and at least one subsequent visit (leaf). There are some situations where this is not true. For some of these flat fee groups, the initial visit reported occurred in 2007, but the remaining visits that were part of this flat fee group occurred in 2008. In this case, the 2007 flat fee group would consist of one event, the stem. The 2008 events that are part of this flat fee group are not represented on the file. Similarly, the household respondent may have reported a flat fee group where the initial visit began in 2006 but subsequent visits occurred during 2007. In this case, the initial visit would not be represented on the file. This 2007 flat fee group would then only consist of one or more leaf records and no stem.

Expenditure variables 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 for each hospital stay, 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 visits, 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, please reference the following, "Informing American Health Care Policy" (Monheit, et al., 1999). 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 www.meps.ahrq.gov.

Expenditure data related to hospital inpatient events are broken out by facility and separately billing doctor expenditures. This file contains six categories of expenditure variables per stay: basic hospital facility expenses; expenses for doctors who billed separately from the hospital for any inpatient services provided during hospital stay; total expenses, which is the sum of the facility and physician expenses; facility charge; physician charge; and total charges, which is the sum of the facility and physician charges. 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.

The expenditure data included on this file were derived from both the MEPS Household (HC) and Medical Provider Components (MPC). The MPC contacted medical providers identified by household respondents. The charge and payment data from medical providers were used in the expenditure imputation process to supplement missing household data. For all hospital inpatient stays, MPC data were used if available; otherwise, HC data were used. Missing data for hospital inpatient stays where HC data were not complete and MPC data were not collected, or MPC data were not complete, were imputed during the imputation process.

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, 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 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.

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 each event type file, separate imputations were performed for flat fee and simple events. 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.

Facility expenditures for hospital inpatient stays were developed in a sequence of logical edits and imputations. "Household" edits were applied to sources and amounts of payment for all events reported by HC respondents. "MPC" edits were applied to provider-reported sources and amounts of payment for records matched to household-reported events. Both sets of edits were used to correct obvious errors (as described above) in the reporting of expenditures. After the data from each source were edited, a decision was made as to whether household- or MPC-reported information would be used in the final editing and hot-deck imputations for missing expenditures. The general rule was that MPC data would be used for events where a household-reported event corresponded to a MPC-reported event (i.e., a matched event), since providers usually have more complete and accurate data on sources and amounts of payment than households.

Separate imputations were performed for flat fee and simple events. Most hospital inpatient stays were imputed as simple events because facility charges for an inpatient hospital stay are rarely grouped with other events. (See Section 2.5.4 for more details on flat fee groups.)

Logical edits also 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 in which all events had a common extent of missing data. Separate hot-deck imputations were performed on events in each recipient category. For hospital inpatient and emergency room events, the donor pool was restricted to events with complete expenditures from the MPC. Due to the low ratio of donors to recipients for hospital outpatient and office-based events, there were no donor pool restrictions.

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. If free events were excluded from the donor pool, total expenditures would be over-counted because the distribution of free events among complete events (donors) would not be represented among incomplete events (recipients).

Expenditures for services provided by separately billing doctors in hospital settings were also edited and imputed. These expenditures are shown separately from hospital facility charges for hospital inpatient, outpatient, and emergency room care.

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 (for OP and MV events only). The following list identifies how the imputation flag is coded; the categories are mutually exclusive.

The approach used to count expenditures for flat fees was to place the expenditure on the first visit of the flat fee group. The remaining visits have zero facility payments, while physician’s expenditures may be still present. Thus, if the first visit in the flat fee group occurred prior to 2007, all of the events that occurred in 2007 will have zero payments. Conversely, if the first event in the flat fee group occurred at the end of 2007, the total expenditure for the entire flat fee group will be on that event, regardless of the number of events it covered after 2007. See Section 2.5.4 for details on the flat fee variables.

There are some medical events reported by respondents where the payments were zero. Zero payment events can occur in MEPS for the following reasons: (1) the stay was covered under a flat fee arrangement (flat fee payments are included only on the first event covered by the arrangement), (2) there was no charge for a follow-up stay, (3) the provider was never paid by an individual, insurance plan, or other source for services provided, (4) charges were included in another bill, or (5) the event was paid for through government or privately-funded research or clinical trials.

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.

Expenditure data for newborns were edited to exclude discharges after birth when the newborn left the hospital before or on the same day as the mother. As a result, inpatient expenditures reported for 2007 births were usually applied to the mother and not treated as separate expenditures for the infant. However, if a newborn was discharged at a later date than the mother’s discharge date, then the hospitalization was treated as a separate hospital stay for the newborn.

This means that, in most cases, expenditure data for the newborn is included on the mother’s record. A separate record for the newborn only exists if the newborn was discharged after the mother. In this case, the expenditure for the newborn is on the newborn’s record.

Although a person may have indicated that there was an emergency room visit that preceded this hospital stay (EMERROOM), there was no verification that, in fact, the emergency room visit was actually recorded within the Emergency Room section of the questionnaire.

While it is true that all of the event files can be linked by DUPERSID, there is no unique record link between hospital inpatient stays and emergency room visits. That is, a person could have one hospital inpatient stay and three emergency room visits during the calendar year. While the hospital inpatient stay record may indicate that it was preceded by an emergency room visit, there is no unique record link to the appropriate (of the three) emergency room visit.

However, wherever relationships could be identified (using the MPC start and end date of the events as well as other information from the provider), the facility expenditure associated with the emergency room visit was moved to the hospital facility expenditure. Hence, for some hospital stays, facility expenditures for a preceding emergency room visit are included. In these situations, the corresponding emergency room record on the MEPS 2007 Emergency Room Visit File will have its facility expenditure information zeroed out to avoid double-counting. The variable ERHEVIDX identifies these hospital stays whose expenditures include the facility expenditures for the preceding emergency room visit (see ERHEVIDX in Section 2.5.1.2). It should also be noted that for these cases, there is only one hospital stay associated with the emergency room stay.

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 health insurance coverage and sources of payment based on data collected in the survey. These variables include:

Though these two sources are 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.

This file contains two sets of imputed expenditure variables: facility expenditures and physician expenditures.

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.

IPFSF07X - IPFOT07X are the 12 sources of payment. The 12 sources of payment are: self/family (IPFSF07X), Medicare (IPFMR07X), Medicaid (IPFMD07X), private insurance (IPFPV07X), Veterans Administration (IPFVA07X), TRICARE/CHAMPVA (IPFTR07X), other Federal sources (IPFOF07X), State and Local (non-federal) government sources (IPFSL07X), Workers’ Compensation (IPFWC07X), other private insurance (IPFOR07X), other public insurance (IPFOU07X), and other insurance (IPFOT07X). IPFXP07X is the sum of the 12 sources of payment for the Hospital Facility expenditures, and IPFTC07X is the total charge.

Wherever an emergency room visit record is linked to a hospital inpatient stays record (identified by the variable ERHEVIDX, see Section 2.5.1.2), the facility source of payment variables on the emergency room visit record were zeroed out because the emergency room expenditures were already included in the hospital facility source of payment variables.

Separately billing doctor (SBD) expenses typically cover services provided to patients in hospital settings by providers like anesthesiologists, radiologists, and pathologists, whose charges are often not included in hospital bills.

For medical doctors who bill separately (i.e., outside the hospital bill), a separate data collection effort within the Medical Provider Component was performed to obtain this same set of expenditure information from each separately billing doctor. It should be noted that there could be several separately billing doctors associated with a medical event. For example, a hospital inpatient stay could have a radiologist, anesthesiologist, pathologist and a surgeon associated with it. If their services are not included in the hospital bill then this is one medical event with four separately billing doctors. The imputed expenditure information associated with the separately billing doctors for a hospital inpatient stay is combined (i.e., the expenditures incurred by the radiologist + anesthesiologist + pathologist + surgeon) and is provided on the file. IPDSF07X - IPDOT07X are the 12 sources of payment; IPDXP07X is the sum of the 12 sources of payments; and IPDTC07X is the physician’s total charge.

Data users/analysts need to take into consideration whether to analyze facility and SBD expenditures separately, combine them within service categories, or collapse them across service categories (e.g., combine SBD expenditures with expenditures for physician visits to offices and/or outpatient departments).

Data users/analysts interested in total expenditures should use the variable IPXP07X, which includes both facility and physician amounts. Those interested in total charges should use the variable IPTC07X, which includes both facility and physician charges (see Section 2.5.5.1 for an explanation of the "charge" concept).

Expenditure variables have been rounded to the nearest penny. Person-level expenditure information released on the MEPS 2007 Person-Level Use and Expenditure File were rounded to the nearest dollar. It should be noted that using the MEPS 2007 event files to create person-level totals will yield slightly different totals than those found 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 MEPS 2007 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 2007 Appendix File, HC-110I, for details on such rounding differences.

There is a single full year person-level weight (PERWT07F) 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 2007. 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.

There has been an important change in the MEPS sample design that is worth noting. The MEPS sample of households for Round 1 of a given MEPS panel is a subsample of the responding households to the previous year’s National Health Interview Survey (NHIS). A new NHIS sample design was implemented in 2006 with a new sample of PSUs and segments, independent of the sample design used from 1995-2005. Thus, MEPS Panel 12 households fielded initially in 2007, selected from the 2006 NHIS household respondents, are from a sample design independent of those sampled for MEPS Panel 11 from among 2005 NHIS household respondents. As a result, with two national samples of PSUs and segments fielded for MEPS and with a somewhat reduced sample size for Panel 12, the amount of clustering is reduced with the expectation of some increase in precision for 2007 MEPS estimates. There will also be more degrees of freedom due to more variance strata available for variance estimation purposes. The trade-off for these expected increases in precision and degrees of freedom is that it is more expensive to field a sample that is less concentrated. In 2008 both MEPS panels will have been sampled from the new NHIS sample design, with corresponding reductions in survey costs, precision, and degrees of freedom.

The person-level weight PERWT07F was developed in several stages. Person-level weights for Panels 11 and 12 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 2007 composite weight was then formed by multiplying each weight from Panel 11 by the factor .56 and each weight from Panel 12 by the factor .44. The choice of factors reflected the relative sample sizes of the two panels, helping to limit the variance of estimates obtained from pooling the two samples. The composite weight was again raked to the same set of CPS-based control totals. When poverty status information derived from income variables became available, a final raking was undertaken on the previously established weight variable. Control totals were established using poverty status (five categories: below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty) as well as the original five variables used in the previous calibrations.

The person-level weight for MEPS Panel 11 was developed using the 2006 full year weight for an individual as a "base" weight for survey participants present in 2006. For key, in-scope respondents who joined an RU some time in 2007 after being out-of-scope in 2006, the 2006 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 2007. These control figures were derived by scaling back the population totals obtained from the March 2008 CPS to correspond to a national estimate for the civilian noninstitutionalized population provided by the Census Bureau for December 2007. 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, 2007 is 297,823,930. Key, responding persons not in-scope on December 31, 2007 but in-scope earlier in the year retained, as their final Panel 11 weight, the weight after the nonresponse adjustment.

The person-level weight for MEPS Panel 12 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 2007 portion of Round 3 as well as raking to the same population control figures for December 2007 used for the MEPS Panel 11 weights. The same five variables employed for Panel 11 raking (census region, MSA status, race/ethnicity, sex, and age) were used for Panel 12 raking. Similarly, for Panel 12, key, responding persons not in-scope on December 31, 2007 but in-scope earlier in the year retained, as their final Panel 12 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., 2006 for Panel 11 and 2007 for Panel 12).

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, 2007 is 297,823,930 (PERWT07F>0 and INSC1231=1). In addition, the weights of two groups of persons who were out-of-scope on December 31, 2007 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 2007 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 301,309,149.

The target population for MEPS in this file is the 2007 U.S. civilian noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 2005 (Panel 11) and 2006 (Panel 12). New households created after the NHIS interviews for the respective Panels and consisting exclusively of persons who entered the target population after 2005 (Panel 11) or after 2006 (Panel 12) 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.

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 concluding that a change has taken place when one has not.

The data in this file can be used to develop national 2007 event level estimates for the U.S. civilian noninstitutionalized population on inpatient hospital stays as well as expenditures, and sources of payment for these stays. Estimates of total stays are the sum of the weight variable (PERWT07F) across relevant event records while estimates of other variables must be weighted by PERWT07F to be nationally representative. The tables below contain event-level estimates for selected variables.

* Zero payment events can occur in MEPS for the following reasons: (1) the stay was covered under a flat fee arrangement (flat fee payments are included only on the first event covered by the arrangement), (2) there was no charge for a follow-up stay, (3) the provider was never paid by an individual, insurance plan, or other source for services provided, (4) charges were included in another bill, or (5) the event was paid for through government or privately-funded research or clinical trials.

To enhance analyses of hospital inpatient stays, analysts may link information about inpatient stays 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 (see Section 5 below for more details). Both this file and the full year consolidated file may be used to derive estimates for persons with hospital inpatient 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 inpatient event are represented on this data file. Therefore, the full year consolidated file must be used for person-level analyses that include both persons with and without inpatient care.

It is essential that the data user/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 minus values to values appropriate to the analytic needs. That is, the data user/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 data user/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, flat fee, and zero expenditure) are described in Section 2.5.5.

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 2007 full year data associated with the corresponding estimates of variance and usually substantially more.

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 2005.

As a result of the change in the NHIS sample design in 2006, a new set of variance strata and PSUs have been established for variance estimation purposes for use with MEPS Panel 12 and subsequent MEPS panels. There were 203 variance estimation strata associated with MEPS Panel 11 and 165 variance strata associated with MEPS Panel 12, or 368 variance strata in all, providing a substantial number of degrees of freedom for subgroups as well as the nation as a whole. Each variance stratum contains either two or three variance estimation PSUs.

Data from this file can be used alone or in conjunction with other files for different analytic purposes. This section summarizes various scenarios for merging/linking MEPS event files. The set of households selected for MEPS is a subsample of those participating in the National Health Interview Survey (NHIS), thus, each MEPS panel can also be linked back to the previous year’s NHIS 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.

Merging characteristics of interest from other MEPS files (e.g., MEPS 2007 Full-Year Consolidated File) expands the scope of potential estimates. For example, to estimate the total number of hospital inpatient stays for persons with specific demographic characteristics (such as, age, race, sex, and education), population characteristics from a person-level file need to be merged onto the hospital inpatient stays file. This procedure is illustrated below. The MEPS 2007 Appendix File, HC-110I, provides additional detail on how to merge MEPS data files.

The RXLK file provides a link from the MEPS event files to the Prescribed Medicine Event File. When using RXLK, data users/analysts should keep in mind that one inpatient stay can link to more than one prescribed medicine record. Conversely, a prescribed medicine event may link to more than one inpatient stay visit or different types of events. When this occurs, it is up to the data user/analyst to determine how the prescribed medicine expenditures should be allocated among those medical events. For detailed linking examples, including SAS code, data users/analysts should refer to the MEPS 2007 Appendix File, HC-110I.

The CLNK provides a link from MEPS event files to the 2007 Medical Conditions File. When using the CLNK, data users/analysts should keep in mind that (1) conditions are self-reported, (2) there may be multiple conditions associated with a hospital inpatient stay, and (3) a condition may link to more than one hospital inpatient stay or any other type of visit. Data users/analysts should also note that not all hospital inpatient stays link to the medical conditions file.

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 6: A Comparison of Household and Provider Reports of Medical Conditions. In Methodological Issues for Health Care Surveys. Marcel Dekker, New York.

Cox, B. and Iachan, R. (1987). A Comparison of Household and Provider Reports of Medical Conditions. Journal of the American Statistical Association 82(400):1013-18.

Edwards, W.S., Winn, D.M., Kurlantzick V., et al. (1994). Evaluation of National Health Interview Survey Diagnostic Reporting. National Center for Health Statistics, Vital Health 2(120).

Elixhauser, A., Steiner, C.A., Whittington, C.A., and McCarthy, E. Clinical Classifications for Health Policy Research: Health Inpatient Statistics, 1995. Healthcare Cost and Utilization Project, HCUP-3 Research Note. Rockville, MD: Agency for Health Care Policy and Research: 1998. AHCPR Pub. No. 98-0049.

Health Care Financing Administration (1980). International Classification of Diseases, 9^th Revision, Clinical Modification (ICD-CM). Vol. 1. (DHHS Pub. No. (PHS) 80-1260). DHHS: U.S. Public Health Services.

Johnson, A.E. and Sanchez, M.E. (1993). Household and Medical Provider Reports on Medical Conditions: National Medical Expenditure Survey, 1987. Journal of Economic and Social Measurement. Vol. 19, 199-233.

Monheit, A.C., Wilson, R., and Arnett, III, R.H. (Editors). Informing American Health Care Policy. (1999). 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.

Variable	Description	Source
DUID	Dwelling unit ID	Assigned in sampling
PID	Person number	Assigned in sampling
DUPERSID	Person ID (DUID + PID)	Assigned in sampling
EVNTIDX	Event ID	Assigned in sampling
EVENTRN	Event Round number	CAPI derived
ERHEVIDX	Event ID for corresponding emergency room visit	Constructed
FFEEIDX	Flat fee ID	CAPI derived
PANEL	Panel Number	Constructed
MPCDATA	MPC Data Flag	Constructed

Variable	Description	Source
IPBEGYR	Event start date – year	CAPI derived
IPBEGMM	Event start date – month	CAPI derived
IPBEGDD	Event start date – day	CAPI derived
IPENDYR	Event end date – year	CAPI derived
IPENDMM	Event end date – month	CAPI derived
IPENDDD	Event end date – day	CAPI derived
NUMNIGHX	# of nights in hospital - Edited/Imputed	(Edited/Imputed)
NUMNIGHT	Number of nights stayed at provider	HS01
EMERROOM	Did stay begin with emergency room visit	HS02
SPECCOND	Hospital stay related to condition	HS03
RSNINHOS	Reason entered hospital	HS05
ANYOPER	Any operations or surgeries performed	HS06
IPICD1X	3 digit ICD-9-CM condition code	Edited
IPICD2X	3 digit ICD-9-CM condition code	Edited
IPICD3X	3 digit ICD-9-CM condition code	Edited
IPICD4X	3 digit ICD-9-CM condition code	Edited
IPPRO1X	2 digit ICD-9-CM procedure code	Edited
IPPRO2X	2 digit ICD-9-CM procedure code	Edited
IPCCC1X	Modified Clinical Classification Code	Constructed/Edited
IPCCC2X	Modified Clinical Classification Code	Constructed/Edited
IPCCC3X	Modified Clinical Classification Code	Constructed/Edited
IPCCC4X	Modified Clinical Classification Code	Constructed/Edited
DSCHPMED	Medicines prescribed at discharge	HS08

Variable	Description	Source
IPFSF07X	Facility amount paid, self/family (Imputed)	CP Section (Edited)
IPFMR07X	Facility amount paid, Medicare (Imputed)	CP Section (Edited)
IPFMD07X	Facility amount paid, Medicaid (Imputed)	CP Section (Edited)
IPFPV07X	Facility amount paid, private insurance (Imputed)	CP Section (Edited)
IPFVA07X	Facility amount paid, Veterans Administration (Imputed)	CP Section (Edited)
IPFTR07X	Facility amount paid, TRICARE/CHAMPVA (Imputed)	CP Section (Edited)
IPFOF07X	Facility amount paid, other federal (Imputed)	CP Section (Edited)
IPFSL07X	Facility amount paid state & local government (Imputed)	CP Section (Edited)
IPFWC07X	Facility amount paid, workers’ compensation (Imputed)	CP Section (Edited)
IPFOR07X	Facility amount paid, other private (Imputed)	Constructed
IPFOU07X	Facility amount paid, other pub (Imputed)	Constructed
IPFOT07X	Facility amount paid, other insurance (Imputed)	CP Section (Edited)
IPFXP07X	Facility sum payments IPFSF07X – IPFOT07X	Constructed
IPFTC07X	Total facility charge (Imputed)	CP Section (Edited)

Variable	Description	Source
IPDSF07X	Doctor amount paid, family (Imputed)	Constructed
IPDMR07X	Doctor amount paid, Medicare (Imputed)	Constructed
IPDMD07X	Doctor amount paid, Medicaid (Imputed)	Constructed
IPDPV07X	Doctor amount paid, private insurance (Imputed)	Constructed
IPDVA07X	Doctor amount paid, Veterans Administration (Imputed)	Constructed
IPDTR07X	Doctor amount paid, TRICARE/CHAMPVA (Imputed)	Constructed
IPDOF07X	Doctor amount paid, other federal (Imputed)	Constructed
IPDSL07X	Doctor amount paid, state & local government (Imputed)	Constructed
IPDWC07X	Doctor amount paid, workers’ compensation (Imputed)	Constructed
IPDOR07X	Doctor amount paid, other private insurance (Imputed)	Constructed
IPDOU07X	Doctor amount paid, other public insurance (Imputed)	Constructed
IPDOT07X	Doctor amount paid, other insurance (Imputed)	Constructed
IPDXP07X	Doctor sum payments IPDSF07X–IPDOT07X	Constructed
IPDTC07X	Total doctor charge (Imputed)	Constructed
IMPFLAG	Imputation status	Constructed

301 Moved Permanently

Connect With Us

Sign up for Email Updates

Agency for Healthcare Research and Quality