MEPS HC-122: MEPS Panel 12 Longitudinal Data File
December 2010
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 Variables
2.1.1 Variables from Annual Full-Year Consolidated Files
2.1.2 Constructed Variables for Selection of Analytic Group Files
2.1.3 Estimation Variables
2.1.4 Prescription Medications Use and Expenditures
and Total Expenditures
A. Data Use Agreement
Individual identifiers have been
removed from the micro-data contained in these files. Nevertheless,
under sections 308 (d) and 903 (c) of the Public Health Service Act
(42 U.S.C. 242m and 42 U.S.C. 299 a-1), data collected by the Agency
for Healthcare Research and Quality (AHRQ) and/or the National Center
for Health Statistics (NCHS) may not be used for any purpose other
than for the purpose for which they were supplied; any effort to determine
the identity of any reported cases is prohibited by law.
Therefore in accordance with the above referenced Federal Statute,
it is understood that:
- No one is to use the data in this data set in any way except
for statistical reporting and analysis; and
- If the identity of any person or establishment should be discovered
inadvertently, then (a) no use will be made of this knowledge,
(b) the Director Office of Management AHRQ will be advised of
this incident,
(c) the information that would identify any individual or establishment
will be safeguarded or destroyed, as requested by AHRQ, and
(d) no one else will be informed of the discovered identity;
and
- No one will attempt to link this data set with individually
identifiable records from any data sets other than the Medical
Expenditure Panel
Survey or the National Health Interview Survey.
By using these data you signify your agreement to comply with the
above stated statutorily based requirements with the knowledge
that deliberately
making a false statement in any matter within the jurisdiction
of any department or agency of the Federal Government violates
Title
18 part
1 Chapter 47 Section 1001 and is punishable by a fine of up to
$10,000 or up to 5 years in prison.
The Agency for Healthcare Research and Quality requests that users
cite AHRQ and the Medical Expenditure Panel Survey as the data
source in any publications or research based upon these data. Return To Table Of Contents
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 noninstitutionalized 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. Return To Table Of Contents
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.
Return To Table Of Contents
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).
Return To Table Of Contents
C. Technical and Programming Information 1.0 General Information
For MEPS Panels 1-8, longitudinal weight
files that were released contained a limited number of variables that could
be merged with data from two consecutive full-year consolidated files to
create a longitudinal file for analysis. Beginning with Panel 9, AHRQ has
replaced the longitudinal weight files with more complete and analytically
useful panel-specific files that contain the variables from the consolidated
full-year files.
This documentation describes the Panel 12 longitudinal data file from the
Medical Expenditure Panel Survey Household Component (MEPS-HC). Released
as an ASCII file (with related SAS and SPSS programming statements and data
use information) and a SAS transport dataset, this public use file provides
information collected on a nationally representative sample of the civilian
noninstitutionalized population of the United States for the two-year period
2007-08. The file contains 3,438 variables and has a logical record length
of 9,753 with an additional 2-byte carriage return/line feed at the end of
each record.
This file consists of MEPS survey data obtained in Rounds 1-5 of MEPS Panel
12 and can be used to analyze changes over a two-year period. Variables in
the file pertaining to survey administration, demographics, employment, health
status, disability days, quality of care, patient satisfaction, health insurance
and medical care use and expenditures were obtained from the MEPS 2007 and
2008 Full-Year Consolidated Files (HC-113 and HC-121, respectively).
The following documentation offers a brief overview of the contents and
structure of the files and programming information. A codebook of all
the variables included in the Panel 12 data file is provided in a separate
file
(H122CB.PDF). A database of all MEPS products released to date and
a variable locator indicating the major MEPS data items on public use
files that have
been released to date can be found on the MEPS Web site: www.meps.ahrq.gov.
Return To Table Of Contents
2.0 Data File Information
This public use file contains records
for 12,440 persons in Panel 12 who were respondents for the period they were
in-scope for the survey (i.e., a member of the civilian non-institutionalized
population) during the two-year period. Data are available for all five rounds
for 91% of the cases (11,348). The remaining 9% (1,092 persons) do not have
data for one or more rounds but were in-scope for all rounds they participated
in the survey. These persons are those who were born, died, were in the military
or an institution, or left the country during the two-year period. In constrast,
persons in the panel who participated in the survey for only part of the
period they were in-scope are not included in this file. To compensate for
this attrition, adjustments were made in the construction of the panel weight
variable included in this file (LONGWT). The codebook provides both weighted
and unweighted frequencies for each variable on the data file. The LONGWT
variable should be used to produce national estimates for the two-year period.
Each MEPS panel can 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 http://www.meps.ahrq.gov/mepsweb/data_stats/more_info_download_data_files.jsp. Return To Table Of Contents
2.1 Variables
2.1.1 Variables from Annual Full-Year Consolidated Files
Most variables on this file were
obtained from the MEPS 2007 and 2008 Full-Year Consolidated Files (HC-113
and HC-121, respectively). However, names for time dependent variables
from these files were modified in order to: 1) eliminate duplicate
variable names for data reflecting different time periods during the
panel, and 2) standardize variable names to facilitate pooling of multiple
MEPS panels for analysis.1 Generally, annual variables with
a suffix of “07” and “08” are renamed with
a suffix of “Y1” and “Y2”, respectively. Variables
with a suffix of “31”, “42”, and “53” are
renamed with a suffix denoting the round the data was collected (i.e., “1” , “2” or “3” for
variables originating from Rounds 1-3 on the 2007 full-year file and “3”, “4”,
or “5” for variables originating from Rounds 3-5 on the
2008 full-year file).2 It is necessary to use this crosswalk in conjunction
with documentation for the 2007 and 2008 full-year consolidated files
to obtain a full description of variables on this file. Table 1 below
provides the crosswalk summarizing the scheme used for renaming variables
from the annual files.
Return To Table Of Contents
Table 1: Crosswalk of Variable Names between the Full-Year Consolidated Files and the Longitudinal File
| Type of Variable |
Full-Year Consolidated File Variable Name
Suffix |
Longitudinal File Variable Name
Suffix |
Specific Cases or Examples |
Constant (i.e., not round or year specific) |
No suffixes |
No suffixes |
All variables:
DOBMM=DOBMM
DOBYY=DOBYY
DUID=DUID
PID=PID
DUPERSID=DUPERSID
EDUCYR=EDUCYR
HIDEG=HIDEG HISPANX=HISPANX
HISPCAT=HISPCAT
INTVLANG=INTVLANG
RACEAX=RACEAX
RACEBX=RACEBX
RACEWX=RACEWX
RACEX=RACEX
RACETHNX=RACETHNX
SEX=SEX
VARPSU=VARPSU
VARSTR=VARSTR
|
Annual, family related variables |
YR |
Y1 or YR1
Y2 or YR2 |
All variables:
FAMIDYR=FAMIDYR1 (2007 file)
FAMRFPYR=FAMRFPY1 (2007 file)
FAMSZEYR=FAMSZEY1 (2007 file)
FAMIDYR=FAMIDYR2 (2008 file)
FAMRFPYR=FAMRFPY2 (2008 file)
FAMSZEYR=FAMSZEY2 (2008 file)
|
Annual, CPS family identifiers |
No suffix |
Y1
Y2 |
All variables:
CPSFAMID= CPSFAMY1 (2007)
CPSFAMID= CPSFAMY2 (2008)
|
Annual,
health insurance eligibility units |
No suffix |
Y1
Y2 |
All variables:
HIEUIDX=HIEUIDY1 (2007)
HIEUIDX=HIEUIDY2 (2008)
|
Annual, inscope variables |
No suffixes |
YR1
YR2 |
All variables:
INSCOPE=INSCPYR1 (2007 file)
INSCOPE=INSCPYR2 (2008 file)
|
12/31 status variables |
1231 in 2007 file
1231 in 2008 file |
Y1
Y2 |
All variables:
FAMS1231=FAMSY1 (2007 file)
FCRP1231=FCRPY1 (2007 file)
FCSZ1231= FCSZY1 (2007 file)
FMRS1231= FMRSY1 (2007 file)
INSC1231=INSCY1 (2007 file)
FAMS1231=FAMSY2 (2008 file)
FCRP1231=FCRPY2 (2008 file)
FCSZ1231= FCSZY2 (2008 file)
FMRS1231= FMRSY2 (2008 file)
INSC1231=INSCY2 (2008 file)
|
Annual |
07, 07X, 07F, or 07C
08, 08X, 08F, or 08C
|
Y1, Y1X, Y1F, or Y1C
Y2, Y2X, Y2F, or Y2C
|
Examples:
TOTEXP07=TOTEXPY1 (2007 file)
AGE07X=AGEY1X
TOTEXP08=TOTEXPY2 (2008 file)
AGE08X=AGEY2X |
Variables for health insurance prior to January 1, 2007
(data collected in round 1 only) |
No suffixes |
No suffixes |
All variables:
PREVCOVR=PREVCOVR
COVRMM=COVRMM
COVRYY=COVRYY
WASESTB=WASESTB
WASMCARE=WASMCARE
WASMCAID=WASMCAID
WASCHAMP=WASCHAMP
WASVA=WASVA
WASPRIV=WASPRIV
WASOTGOV=WASOTGOV
WASAFDC=WASAFDC
WASSSI=WASSSI
WASSTAT1=WASSTAT1
WASSTAT2=WASSTAT2
WASSTAT3=WASSTAT3
WASSTAT4=WASSTAT4
WASOTHER=WASOTHER
NOINSBEF=NOINSBEF
NOINSTM=NOINSTM
NOINUNIT=NOINUNIT
MORECOVR=MORECOVR
INSENDMM=INSENDMM
INSENDYY=INSENDYY
|
Annual |
No suffixes 3 |
Y1
Y2 |
All variables:
KEYNESS=KEYNESY1 (2007 file)
SAQELIG=SAQELIY1 (2007 file)
EVRWRK=EVRWRKY1 (2008 file)
EVRETIRE=EVRETIY1 (2007 file)
EVRUNAT=EVRUNAY1 (2007 file)
EVRUNINS=EVRUINY1 (2007 file)
KEYNESS=KEYNESY2 (2008 file)
SAQELIG=SAQELIY2 (2008 file)
EVRWRK=EVRWRKY2 (2008 file)
EVRETIRE=EVRETIY2 (2008 file)
EVRUNAT=EVRUNAY2 (2008 file)
EVRUNINS=EVRUINY2 (2008file)
|
Monthly |
2-character month + 07
2-character month + 08 |
2-character month + Y1
2-character month + Y2 |
Example:
PRIJA07=PRIJAY1 (2007 file)
PRIJA08=PRIJAY2 (2008 file)
|
Round Specific |
31 or 31X in 2007 file
42 or 42X in 2007 file
53 or 53X in 2007 file
31 or 31X in 2008 file
42 or 42X in 2008 file
53 or 53X in 2008 file
|
1 or 1X for 2007
2 or 2X for 2007
3 or 3X for 2007
3 or 3X for 2008
4 or 4X for 2008
5 or 5X for 2008
|
Example:
RTHLTH31 = RTHLTH1 (2007 file)
RTHLTH42 =RTHLTH2 (2007 file)
RTHLTH53 =RTHLTH3 (2007 file if YRIND=2)
RTHLTH31 = RTHLTH3 (2008 file if YEARIND=1 or 3)
RTHLTH42 =RTHLTH4 (2008 file)
RTHLTH53 =RTHLTH5
(2007 file)
|
Diabetes preventive care 4 |
0653, 0753, and 0853 in 2007
file
0753,
0853, and 0953 in 2008 file |
Y0R3 for 2006 data
Y1R3 for 2007 data
Y2R3 for 2008 data
Y1R5 for 2007 data
Y2R5 for 2008 data
Y3R5 for 2009 data
|
All cases:
DSEB0653=DSEBY0R3 (2007 file)
DSEY0653=DSEYY0R3
(2007 file)
DSEY0753=DSEYY1R3
(2007 file)
DSEY0853=DSEYY2R3
(2007 file)
DSEB0753=DSEBY1R5 (2008 file)
DSEY0753=DSEYY1R5
(2008 file)
DSEY0853=DSEYY2R5
(2008 file)
DSEY0953=DSEYY3R5
(2008 file)
|
Job Change |
3142
4253 |
12 for 2007
23 for 2007
34 for 2008
45 for 2008
|
All cases:
CHJ3142=CHJ12(2007 file)
CHJ4253=CHGJ23(2007 file)
YCHJ3142=YCHJ12(2007 file)
YCHJ4253=YCHGJ23(2007 file)
CHJ3142=CHGJ34 (2008 file)
CHJ4253=CHGJ45 (2008 file)
YCHJ3142=YCHGJ34 (2008 file)
YCHJ4253=YCHGJ45 (2008 file)
|
2.1.2. Constructed Variables for Selection of Analytic Group
The following eight variables were
constructed and included on the file to facilitate the selection of
appropriate cases for various analyses. Table 2 below contains descriptive
statistics for these variables.
| YEARIND |
1=both years, 2=in 2007 only, and
3=in 2008 only |
| ALL5RDS |
Inscope and data collected in all 5
rounds (0=no, 1=yes) |
| DIED |
Died during the two-year survey
period (0=no, 1=yes) |
| INST |
Institutionalized for some time during
the two-year survey period (0=no, 1=yes) |
| MILITARY |
Active duty military for some time
during the two-year survey period (0=no, 1=yes) |
| ENTRSRVY |
Entered survey after beginning of panel
(mainly births; also includes persons
who had no initial chance of selection
who
moved into a MEPS sample household) (0=no, 1=yes) |
| LEFTUS |
Moved out of the country after beginning
of panel (0=no, 1=yes) |
| OTHER |
Not identified in any of the above
analytic groups (0=no, 1=yes) |
Table 2: Frequencies and Percentage for Constructed Variables
| Variable |
Number of Records |
Percentage of Records (N=12,440) |
| YEARIND=1 (i.e., person in both
years) |
12,111 |
97.4 |
| ALL5RDS=1 (yes) |
11,348 |
91.2 |
| DIED=1 (yes) |
139 |
1.1 |
| INST=1 (yes) |
43 |
0.4 |
| MILITARY=1 (yes) |
28 |
0.2 |
| ENTRSRVY=1 (yes) |
780 |
6.3 |
| LEFTUS=1 (yes) |
53 |
0.4 |
| OTHER=1 (yes) |
64 |
0.5 |
Following are examples of situations where these
variables would be useful in selecting records for analysis:
- Analysts interested in working only with persons who were
in-scope and had data for all five rounds of the panel should subset
to cases where ALL5RDS=1.
- If a researcher wanted to include persons who were in-scope and had
data for all five rounds of the panel as well as those in the survey
at the beginning of the panel who subsequently died, then they
would include cases where ALL5RDS=1 or (ENTRSRVY=0 and DIED=1).
- If a researcher wanted to include persons who were in-scope and
had data for all five rounds of the panel as well as those who died
in the second year of the panel, then they would include cases where ALL5RDS=1
or (DIED=1 and YEARIND=1).
Return To Table Of Contents
2.1.3 Estimation Variables
Longitudinal Estimations for Panel 12
The file contains a weight variable (LONGWT) and variance estimation
variables (VARSTR, VARPSU) that should be applied when producing national
estimates for longitudinal analyses. For example, LONGWT applied to the
11,348 cases where ALL5RDS=1 produces a weighted population estimate of
279.6 million. This represents an estimate of the number of persons in
the civilian noninstitutionalized population for the entire two-year period
from 2007-08. To obtain estimates of variability (such as the standard
error of sample estimates or corresponding confidence intervals) for estimates
based on MEPS survey data, one needs to take into account the complex sample
design of MEPS by specifying the estimation variables including stratum
of sample selection (VARSTR), primary sampling unit (VARPSU) and longitudinal
weight (LONGWT).
Pooled Estimations
When analyzing subpopulations and/or
low prevalence events, it may be desirable to pool together more than
one panel of MEPS-HC data to yield sample sizes large enough to generate
reliable estimates. If only data from Panels 7 and beyond are being
pooled, then simply use the strata and psu variables provided on the
longitudinal files for pooled estimation.5 However, because Panels
1-6 MEPS longitudinal weight files were released with panel-specific
variance structures, it is necessary to obtain the set of appropriate
variance estimation variables from the HC-036 Pooled Estimation File
when pooling involves these panels. This Panel 12 file also includes
the set of variance estimation variables (STRA9608, PSU9608) that should
be applied when producing estimates using any of the first six MEPS
panels. STRA9608 and PSU9608 reconcile the differences in the variance
units between the units on the released annual MEPS public use files
(see HC-036 file documentation for more information).
Return To Table Of Contents 2.1.4 Prescription
Medications Use and Expenditures and Total Expenditures
This section describes an editing
change in the prescription drug variables and differences in variable
values between the 2007 full year consolidated file and this longitudinal
file for some persons. Nearly all users of this file can simply use
the summary use and expenditure variables on this file. For users who
augment the longitudinal file with information from the prescription
medicine files, this section provides additional information about
how to account for some fills that are in both the 2007 and 2008 Prescription
Medicine files.
In the third interview, where the reference period typically spans
the later part of one year and the early part of the next, for each
drug, the household respondent is asked to report both the number of
times the drug was obtained since the last interview and the number
of times the drug was obtained in the current year. When this information
is missing, the total number of fills for the drug is allocated to
each year (2007 or 2008). Starting with the 2008 prescription medicine
data, improvements were made in the allocation method. The new method
tends to allocate more of the total round 3 fills to the second year
and fewer to the first year. Implementing this reallocation of fills
resulted in a one-time problem for Panel 12: some fills are represented
in both the 2007 and 2008 the prescription drug files. This duplication
was removed from the values of the prescription drug use and expenditures
for year 1 (RXTOTY1, RXEXPY1, RXSLFY1, RXMCRY1, RXMCDY1, RXPRVY1, RXVAY1,
RXTRIY1, RXOFDY1, RXSTLY1, RXWCPY1, RXOSRY1, RXOPRY1, RXOPUY1, RXPTRY1,
RXOTHY1) and total expenditures for year 1 (TOTEXPY1, TOTSLFY1, TOTMCRY1,
TOTMCDY1, TOTPRVY1, TOTVAY1, TOTTRIY1, TOTOFDY1, TOTSTLY1, TOTWCPY1,
TOTOSRY1, TOTOPRY1, TOTOPUY1, TOTPTRY1, TOTOTHY1) on the Panel 12 longitudinal
file. Thus, for 1,667 persons the values of these variables differ
from those of the corresponding variables on the 2007 full year consolidated
file. (The duplicate fills were also used to construct the summary
measures in the 2007 and 2008 full year consolidated files. However,
the duplication does not affect summary analyses of those files, because
the change was implemented for both panels 12 and 13.)
Some longitudinal file users conduct analyses that require additional
information about the types of drugs acquired, for example, the number
of times a person obtained a specific drug (say, Lipitor) during the
two-year period. These details are obtained from the 2007 and 2008
Prescription Medicine files. For Panel 12, these users will need to
remove duplicate round 3 records from either the 2007 or 2008 Prescription
Medicine file.
For users summarizing information over the two-year period (for example,
number of Lipitor fills 2007 through 2008) or summarizing information
in each round (number of Lipitor fills in rounds 1, 2, 3, 4, and 5),
there is a simple method to remove duplicates. This method is also
consistent with the way fills were allocated in Panels 1 through 11,
so it is most appropriate when combining Panel 12 with prior panels.
The variable DUP2007 identifies records on the 2008 Prescription Medicine
file that duplicate acquisitions on the 2007 Prescription Medicine
file. Delete the 2008 records with DUP2007=1. Note, however, that deleting
the 2008 records with DUP2007=1 and aggregating the remaining 2008
prescription drug records will yield year 2 use and expenditures that
differ from the 2008 full year file, but the totals for year 1 will
agree with the 2007 full year file at the person level.
Users summarizing information separately by year (for example, Lipitor
fills in 2007 compared with Lipitor fills in 2008) or combining Panel
12 and subsequent panels need to remove duplicate fills from 2007 Prescription
Medicine file rather than the 2008 Prescription Medicine file. The
following steps are recommended:
- From the 2008 Prescription Medicine file, select the records
with DUP2007=1. Create a person-drug level (LINKIDX) file containing
a
variable counting the number of records (fills) for each LINKIDX.
- From the 2007 Prescription Medicine file, select the panel 12
round 3 records (PANEL=12 and PURCHRD=3). Create a person-drug
level (LINKIDX)
file containing a variable counting the number of records (fills)
for each LINKIDX.
- Merge the information about the drugs with duplicate fills
(from the 2008 data) onto the 2007 round 3 drugs by LINKIDX.
- Reduce the 2007 round 3 fills for each drug by the number
of duplicate fills.
For most person-drugs, the adjusted 2007 round 3 expenditures are
the total across fills on the 2007 file minus the total across
the 2008
duplicate fills. Similarly, for each source of payment, the adjusted
2007 round 3 expenditures for a drug are the amount from the 2007
file minus the amount on the 2008 fills. This was the method used
to create
values of the summary expenditure variables for the most persons
on the longitudinal file. Removing the duplicate expenditures is
complicated,
however, in two situations. (1) For a few person-drugs, total expenditures
on the 2008 duplicate fills exceed the total from the 2007 round
3 records. (This occurs due to variation between the years in matching
drugs reported by pharmacies to those reported by households.)
(2) For some person-drugs, the sources of payment in 2008 differ
from
those
in 2007. (This occurs due to improvements, also implemented starting
with the 2008 data, in reconciling sources of payments between
the pharmacy and household when the pharmacy information is imputed.)
In both types of problem cases, subtracting the 2008 expenditures
for
the duplicate records from 2007 round 3 expenditure variables would
yield negative amounts. For both types of problem cases, the method
used to produce the year 1 summary variables in the longitudinal
file was to reduce 2007 round 3 total expenditures on the drug
in
proportion
to the number of fills that are duplicates; that is, adjusted 2007
round 3 total expenditures for drug = (2007 round 3 total expenditures
for drug) – [(number of duplicate fills) ÷ (number of
fills on the 2007 Prescription Medicine file)] × (2007 round
3 expenditures for drug). Similarly, for each payer, reduce that payer’s
expenditures by the same proportion. For example, for these person-drugs,
adjusted 2007 round 3 Medicare expenditures = 2007 round 3 Medicare
expenditures – [(number of duplicate fills) ÷ (number
of fills on the 2007 Prescription Medicine file)] × (2007 round
3 Medicare expenditures for drug).
The reallocation was made to improve the accuracy of the microdata,
so the second deduplication method (removing 2007 records) is preferred
in most other situations. For example, the second method may be better
when users combine Panel 12 with both preceding and subsequent panels
and summarize information annually. The impact of the specific method
selected may be smallest for users combining Panel 12 with both preceding
and subsequent panels and summarizing drug expenditures over the two-year
window or by round.
Return To Table Of
Contents
1 A variable named
PANEL is also included to facilitate pooling across panels. This variable
is simply the panel number and is therefore constant across all records
within a longitudinal file.
2 While round
3 values were obtained for most observations from the 2008 Full Year
Consolidated File, they were obtained from the 2007 Full Year Consolidated
File for sample persons where YEARIND=2 (i.e., in 2007 only).
3 To maintain
the 8-character naming convention, some variable names had the last
character or two dropped in the renaming process.
4 Diabetic
foot exams, lipid profiles, and flu shots starting in 2008.
5 Note
that variable names for strata and psu are VARSTR and VARPSU respectively
in longitudinal files for panel 9 and
beyond. These variables were named differently in the longitudinal
files for panel 7 (varstrp7, varpsup7) and panel 8 (varstrp8, varpsup8)
and need to be standardized when pooling with subsequent panels. Return To Table Of Contents
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