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MEPS HC-059A: 2001 Prescribed Medicines
February 2004
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 (HC)
2.0 Medical Provider Component (MPC)
3.0 Insurance Component (IC)
4.0 Survey Management
C. Technical Information
1.0 General Information
2.0 Data File Information
2.1 Using MEPS Data for Trend and
Longitudinal Analysis
2.2 Codebook Structure
2.3 Reserved Codes
2.4 Codebook Format
2.5 Variable Naming
2.5.1 General
2.5.2 Expenditure and Sources of Payment Variables
2.6 Data Collection
2.6.1 Methodology for
Collecting Household Reported Variables
2.6.2 Methodology for
Collecting Pharmacy Reported Variables
2.7 File Contents
2.7.1 Survey Administration
Variables
2.7.1.1 Person Identifier
Variables (DUID, PID, DUPERSID)
2.7.1.2 Record Identifier
Variables (RXRECIDX, LINKIDX)
2.7.1.3 Round Variable (PURCHRD)
2.7.2 Characteristics of
Prescribed Medicine Events
2.7.2.1 Date When
Prescribed Medicine Was First Taken (RXBEGDD-RXBEGYR)
2.7.2.2 Prescribed Medicine
Attributes (RXNAME-RXSTRUNT)
2.7.2.3 Type of Pharmacy
(PHARTP1-PHARTP7)
2.7.2.4 Analytic Flag Variables
(RXFLG-DIABFLG)
2.7.2.5 The Sample Variable
(SAMPLE)
2.7.2.6 Condition Codes
(RXICD1X-RXICD3X) and Clinical Classification Codes (RXCCC1X-RXCCC3X)
2.7.3 Expenditure Variables
(RXSF01X-RXXP01X)
2.7.3.1
Definition of Expenditures
2.7.3.2 Sources
of Payment
2.7.4 Sample
Weight (PERWT01F)
2.7.4.1 Overview
2.7.4.2 Details on Person
Weights Construction
2.7.4.3 MEPS Panel 5 Weight
2.7.4.4 MEPS Panel 6 Weight
2.7.4.5 The Final Weight for
2001
2.7.4.6 Coverage
3.0 General Data
Editing and Imputation Methodology
3.1 Rounding
3.2 Edited/Imputed
Expenditure Variables (RXSF01X-RXXP01X)
4.0 Strategies for Estimation
4.1 Variables with Missing
Values
4.2 Basic Estimates of Utilization,
Expenditure and Sources of Payment
4.3 Estimates of the Number of
Persons with Prescribed Medicine Events
4.4 Person-Based Ratio Estimates
4.4.1 Person-Based Ratio
Estimates Relative to Persons with Prescribed Medicine Events
4.4.2 Person-Based
Ratio Estimates Relative to the Entire Population
4.5 Sampling Weights for
Merging Previous Releases of MEPS Household Data with this Event File
4.6 Variance Estimation
5.0 Merging/Linking MEPS
Data Files
5.1 Linking a Person Level
File to the Prescribed Medicines File
5.2 Linking the 2001
Conditions File and/or the Other 2001 MEPS Event Files to the 2001 Prescribed
Medicines File
5.3 Limitations/Caveats of RXLK and
CLNK
References
D. Variable-Source Crosswalk
Attachment 1
Attachment 2
Attachment 3
A. Data Use Agreement
Individual identifiers have been removed from the
microdata contained in these file(s). 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.
- 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.
- No one will attempt to link this data set with individually identifiable
records from any data sets other than the Medical Expenditure Panel Survey
or the National Health Interview Survey.
By using these data you signify your agreement to comply
with the above-stated statutorily based requirements, with the knowledge that
deliberately making a false statement in any matter within the jurisdiction of
any department or agency of the Federal Government violates Title 18 Part 1
Chapter 47 section 1001 and is punishable by a fine of up to $10,000 or up to 5
years in prison.
The Agency for Healthcare Research and Quality requests that users cite AHRQ and
the Medical Expenditure Panel Survey as the data source in any publications or
research based upon these data.
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B. Background
This documentation describes one in a series of public use files from the
Medical Expenditure Panel Survey (MEPS). The survey provides a new and extensive
data set on the use of health services and health care in the United States.
MEPS is conducted to provide nationally representative estimates of health care
use, expenditures, sources of payment, and insurance coverage for the U.S.
civilian noninstitutionalized population. MEPS is cosponsored by the Agency for
Healthcare Research and Quality (AHRQ) and the National Center for Health
Statistics (NCHS).
MEPS is a family of three surveys. The Household Component (HC) is the core
survey and forms the basis for the Medical Provider Component (MPC) and part of
the Insurance Component (IC). Together these surveys yield comprehensive data
that provide national estimates of the level and distribution of health care use
and expenditures, support health services research, and can be used to assess
health care policy implications.
MEPS is the third in a series of national probability surveys conducted by AHRQ
on the financing and use of medical care in the United States. The National
Medical Care Expenditure Survey (NMCES) was conducted in 1977, and the National
Medical Expenditure Survey (NMES) was conducted in 1987. Since 1996, MEPS has
continued this series with design enhancements and efficiencies that provide a
more current data resource to capture the changing dynamics of the health care
delivery and insurance system.
The design efficiencies incorporated into MEPS are in accordance with the
Department of Health and Human Services (DHHS) Survey Integration Plan of June
1995, which focused on consolidating DHHS surveys, achieving cost efficiencies,
reducing respondent burden, and enhancing analytical capacities. To advance
these goals, MEPS includes linkage with the National Health Interview Survey (NHIS)-a
survey conducted by NCHS from which the sample for the MEPS HC is drawnand
enhanced longitudinal data collection for core survey components. The MEPS HC
augments NHIS by selecting a sample of NHIS respondents, collecting additional
data on their health care expenditures, and linking these data with additional
information collected from the respondents' medical providers, employers, and
insurance providers.
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1.0 Household Component (HC)
The MEPS
HC, a nationally representative survey of the U.S. civilian noninstitutionalized
population, collects medical expenditure data at both the person and household
levels. The HC collects detailed data on demographic characteristics, health
conditions, health status, use of medical care services, charges and payments,
access to care, satisfaction with care, health insurance coverage, income, and
employment.
The HC uses an overlapping panel design in which data are collected through a
preliminary contact followed by a series of five rounds of interviews over a 2½
year period. Using computer assisted personal interviewing (CAPI) technology,
data on medical expenditures and use for 2 calendar years are collected from
each household. This series of data collection rounds is launched each
subsequent year on a new sample of households to provide overlapping panels of
survey data and, when combined with other ongoing panels, will provide
continuous and current estimates of health care expenditures.
The sampling frame for the MEPS HC is drawn from respondents to NHIS. NHIS
provides a nationally representative sample of the U.S. civilian
noninstitutionalized population, with oversampling of Hispanics and blacks.
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2.0 Medical Provider Component (MPC)
The MEPS MPC supplements and/or replaces information on
medical care events reported in the MEPS HC by contacting medical providers and
pharmacies identified by household respondents. The MPC sample includes all home
health agencies and pharmacies reported by HC respondents. Office-based
physicians, hospitals, and hospital physicians are also included in the MPC but
may be subsampled at various rates, depending on burden and resources, in
certain years.
Data are collected on medical and financial characteristics of medical and
pharmacy events reported by HC respondents. The MPC is conducted through
telephone interviews and record abstraction.
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3.0 Insurance Component (IC)
The MEPS IC collects data on health insurance plans
obtained through private and public sector employers. Data obtained in the IC
include the number and types of private insurance plans offered, benefits
associated with these plans, premiums, contributions by employers and employees,
and employer characteristics.
Establishments participating in the MEPS IC are selected through three sampling
frames:
- A list of employers or other insurance providers
identified by MEPS HC respondents who report having private health insurance
at the Round 1 interview.
- A Bureau of the Census list frame of private sector
business establishments.
- The Census of Governments from the Bureau of the
Census.
To provide an integrated picture of health insurance, data
collected from the first sampling frame (employers and other insurance providers
identified by MEPS HC respondents) are linked back to data provided by those
respondents. Data collected from the two Census Bureau sampling frames are used
to produce annual national and State estimates of the supply and cost of private
health insurance available to American workers and to evaluate policy issues
pertaining to health insurance. National estimates of employer contributions to
group health insurance from the MEPS IC are used in the computation of Gross
Domestic Product (GDP) by the Bureau of Economic Analysis.
The MEPS IC is an annual panel survey. Data are collected from the selected
organizations through a prescreening telephone interview, a mailed
questionnaire, and a telephone follow-up for nonrespondents.
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4.0 Survey Management
MEPS data are collected under the
authority of the Public Health Service Act. They are edited and published in
accordance with the confidentiality provisions of this act and the Privacy Act.
NCHS provides consultation and technical assistance.
As soon as data collection and editing are completed, the MEPS survey
data are released to the public in staged releases of summary reports, microdata
files, and compendiums of tables. Data are also released through MEPSnet, an
online interactive tool developed to give users the ability to statistically
analyze MEPS data in real time. Summary reports and compendiums of tables are
released as printed documents and electronic files. Microdata files are released
on CD‑ROM and/or as electronic files.
Printed documents and selected public use file data on CD ROMs are
available through the AHRQ Publications Clearinghouse. Write or call:
AHRQ Publications Clearinghouse
Attn: (publication number)
P.O. Box 8547
Silver Spring, MD 20907
800 358 9295
410 381 3150 (callers outside the United States only)
888 586 6340 (toll free TDD service; hearing impaired only)
Be sure to specify the AHRQ number of
the document or CD ROM you are requesting. Selected electronic files are
available through the Internet on the MEPS Web site:
http://www.meps.ahrq.gov
Additional information on MEPS is
available from the MEPS project manager or the MEPS public use data manager at
the Center for Financing, Access and Cost Trends, Agency for Healthcare Research
and Quality, 540 Gaither Road, Rockville, MD 20850 (301/427-1406).
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C. Technical Information
1.0 General Information
This documentation describes one in a series of public use
event files from the 2001 Medical Expenditure Panel Survey Household Component (MEPS
HC) and Medical Provider Component (MPC). Released as an ASCII data file and SAS
transport file, this public use file provides detailed information on household
reported prescribed medicines for a nationally representative sample of the
civilian noninstitutionalized population of the United States and can be used to
make estimates of prescribed medicine utilization and expenditures for calendar
year 2001. As illustrated below, this file consists of MEPS survey data obtained
in the 2001 portion of Round 3 and Rounds 4 and 5 for Panel 5, as well as Rounds
1, 2 and the 2001 portion of Round 3 for Panel 6 (i.e., the rounds for the MEPS
panels covering calendar year 2001).
301 Moved Permanently
301 Moved Permanently
Each record on this event file represents a unique
prescribed medicine event; that is, a prescribed medicine reported as being
purchased or otherwise obtained by the household respondent. In addition to
expenditures related to the prescribed medicine, each record contains household
reported characteristics and medical conditions associated with the prescribed
medicine.
Data from this event file can be merged with other 2001 MEPS HC data files, for
purposes of appending person characteristics such as demographic or health
insurance coverage to each prescribed medicine record.
Counts of prescribed medicine utilization are based entirely on household
reports. Information from the Pharmacy Component (PC) (within the MEPS Medical
Provider Component (MPC), see section B.2.0 for more details on the MPC) was
used to provide expenditure and payment data, as well as details of the
medication (e.g., strength, quantity, etc.).
The file can be used to construct summary variables of expenditures, sources of
payment, and other aspects of utilization of prescribed medicines. Aggregate
annual person level information on the use of prescribed medicines and other
health services use is provided on the 2001 Full Year Consolidated Data File,
where each record represents a MEPS sampled person.
The following documentation offers a brief overview of the types and levels of
data provided and the content and structure of the files and the codebook. It
contains the following sections:
Data File Information
Sample Weight
Merging MEPS Data Files
References
Variable to Source Crosswalk
For more information on MEPS HC survey
design see S. Cohen, 1997; J. Cohen, 1997; and S. Cohen, 1996. For information
on the MEPS MPC design, see S. Cohen, 1998. A copy of the survey
instrument used to collect the information on this file is available on the MEPS
web site at the following address: <http://www.meps.ahrq.gov>.
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2.0 Data File Information
This public use data set contains 277,866 prescribed
medicine records. Each record represents one household reported prescribed
medicine that was purchased or obtained during calendar year 2001. Of the
277,866 prescribed medicine records, 272,697 records are associated with persons
having a positive person level weight (PERWT01F). The persons represented on
this file had to meet either criterion a or b below:
- Be classified as a key inscope person who responded for his or her entire
period of 2001 eligibility (i.e., persons with a positive 2001 full-year
person level sampling weight (PERWT01F > 0)), or
-
Be classified as either an eligible non-key
person or an eligible out-of-scope person who responded for his or her entire
period of 2001 eligibility, and belonged to a family (i.e., all persons with
the same value for a particular FAMID variable) in which all eligible family
members responded for their entire period of 2001 eligibility, and at least
one family member has a positive 2001 full-year person weight (i.e., eligible
non-key or eligible out-of-scope persons who are members of a family, all of
whose members have a positive 2001 full-year MEPS family level weight
(FAMWT01F >0)).
Please refer to Attachment 1 for definitions of key,
non-key, inscope and eligible. Persons with no prescribed medicine use for 2001
are not included on this file (but are represented on MEPS person level files).
A codebook for the data file is provided (in file H59ACB.PDF).
This file includes prescribed medicine records for all household survey
respondents who resided in eligible responding households and reported at least
one prescribed medicine. Only prescribed medicines that were purchased or
otherwise obtained in calendar year 2001 are represented on this file. This file
includes prescribed medicines identified in the Prescribed Medicines section of
the HC survey instrument, as well as those prescribed medicines identified in
association with medical events. Each record on this file represents a single
acquisition of a prescribed medicine reported by household respondents. Some
household respondents may have multiple acquisitions of prescribed medicines and
thus will be represented in multiple records on this file. Other household
respondents may have reported no acquisitions of prescribed medicines and thus
will have no records on this file.
When diabetic supplies, such as syringes and insulin, were mentioned in the
Other Medical Equipment section of the MEPS HC, the interviewer was directed to
collect information on these items in the Prescription Medicines section of the
MEPS questionnaire. The respondent was asked the questions in the Charge and
Payment section of the HC. To the extent that these items are purchased without
a prescription, they represent a non-prescription addition to the MEPS
prescription drug expenditure and utilization data. Although these items may be
purchased without a prescription, a prescription purchase may be required to
obtain third party payments. Analysts are free to code and define diabetic
supply/equipment and insulin events utilizing their own coding mechanism. If
desired, this would enable analysts to subset the Prescribed Medicines file to
exclude these types of events.
It should also be noted that refills are included on this file. The HC obtains
information on the name of the prescribed medicine and the number of refills, if
any, associated with it. The data collection design for the HC does not allow
separate records to be created for multiple acquisitions of the same prescribed
medicine. However, in the PC, each original purchase, as well as any refill, is
considered a unique prescribed medicine event. Therefore, for the purposes of
editing, imputation and analysis, all records in the HC were "unfolded" to
create separate records for each original purchase and each refill. Please note,
MEPS did not collect information in the HC to distinguish multiple acquisitions
of the same drug between the original purchase and refills. The survey only
collected data on the number of times a prescribed medicine was acquired during
a round. In some cases, all purchases may have been refills of an original
purchase in a prior round or prior to the survey year. The file also includes a
variable, (SAMPLE), which indicates whether or not the household received a free
sample of that drug in that round. (To obtain more details on free samples,
please see section 2.7.2.5.)
Each record on this file includes the following: an identifier for each unique
prescribed medicine; detailed characteristics associated with the event (e.g.,
national drug code (NDC), medicine name, etc.); conditions, if any, associated
with the medicine; the date on which the person first used the medicine; total
expenditure and sources of payments; types of pharmacies that filled the
household's prescriptions; whether the prescription is one in which the
household received a free sample of it during the round; and a full-year person
level weight.
Data from this file can be merged with previously released MEPS HC person level
data using the unique person identifier, DUPERSID, to append person
characteristics such as demographic or health insurance coverage to each record.
Data from this file can also be merged with the 2001 Full Year Consolidated Data
File to estimate expenditures for persons with prescribed medicines. The
Prescribed Medicines event file can also be linked to the MEPS 2001 Medical
Conditions File and additional MEPS 2001 event files. Please see the 2001
Appendix File for details on how to link MEPS data files.
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2.1 Using MEPS Data for Trend and
Longitudinal Analysis
MEPS began in 1996 and several annual data
files have been released. As more years of data are produced, MEPS will become
increasingly valuable for examining health care trends. However, it is important
to consider a variety of factors when examining trends over time using MEPS.
Statistical significance tests should be conducted to assess the likelihood that
observed trends are attributable to sampling variation. MEPS expenditures
estimates are especially sensitive to sampling variation due to the underlying
skewed distribution of expenditures. For example, 1 percent of the population
accounts for about one-quarter of all expenditures. The extent to which
observations with extremely high expenditures are captured in the MEPS sample
varies from year to year (especially for smaller population subgroups), which
can produce substantial shifts in estimates of means or totals that are simply
an artifact of the sample(s). The length of time being analyzed should also be
considered. In particular, large shifts in survey estimates over short periods
of time (e.g. from one year to the next) that are statistically significant
should be interpreted with caution, unless they are attributable to known
factors such as changes in public policy or MEPS survey methodology. Looking at
changes over longer periods of time can provide a more complete picture of
underlying trends. Analysts may wish to consider using techniques to smooth or
stabilize trends analyses of MEPS data such as pooling time periods for
comparison (e.g. 1996-97 versus 1998-99), working with moving averages, or using
modeling techniques with several consecutive years of MEPS data to test the fit
of specified patterns over time. Finally, researchers should be aware of the
impact of multiple comparisons on Type I error because performing numerous
statistical significance tests of trends increases the likelihood of
inappropriately concluding a change is statistically significant.
Panel 5 cases (PANEL01=5 on the 2001 person-level file) can be linked back to
the 2000 MEPS HC Public Use Data Files. The weight LONGWTP5 on file HC-060
should be used when performing 2-year analysis of Panel 5 data.
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2.2 Codebook Structure
For each variable on the file, both
weighted and unweighted frequencies are provided. The codebook and data file
sequence list variables in the following order:
Unique person identifiers
Unique prescribed medicine identifiers
Other survey administration variables
Prescribed medicine characteristics variables
ICD-9 codes
Clinical Classification Software codes
Expenditure variables
Weight and variance estimation variables
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2.3 Reserved Codes
The following reserved code values are used:
| Value |
Definition |
| -1 INAPPLICABLE |
Question was not asked due to skip pattern. |
| -7 REFUSED |
Question was asked and respondent refused to answer question. |
| -8 DK |
Question was asked and respondent did not know answer. |
| -9 NOT ASCERTAINED |
Interviewer did not record the data. |
| -13 VALUE SUPPRESSED |
Data suppressed. |
| -14 NOT YET TAKEN/USED |
Respondent answered that the
medicine has not yet been used. |
Generally, values of -1, -7, -8 and -9 have not been
edited on this file. However, this is not true if the pharmacist determined a
prescription drug name to be a confidentiality risk. In these instances,
generally, -9 was replaced for the drug name determined a confidentiality risk.
The values of -1 and -9 can be edited by analysts by following the skip patterns
in the questionnaire. The value of -13 was assigned when originally reported HC
data were suppressed because imputed versions of the variable are available on
the Public Use File. The value -14 was a valid value only for the variable
representing the year the respondent reported having first used the medicine (RXBEGYR).
RXBEGYR= -14 means that when the interviewer asked the respondent the year
he/she first started using the medicine, he/she responded that he/she had not
yet starting using the medicine.
A copy of the Household Component questionnaire can be found on the World Wide
Web at
http://www.meps.ahrq.gov/mepsweb/survey_comp/survey.jsp.
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2.4 Codebook Format
The codebook describes an ASCII data set
(although the data are also being provided in a SAS transport file). The
following codebook items are provided for each variable:
| Identifier |
Description |
| Name |
Variable name (maximum of 8
characters) |
| Description |
Variable descriptor (maximum of 40
characters) |
| Format |
Number of bytes |
| Type |
Type of data: numeric (indicated by
NUM) or character (indicated by CHAR) |
| Start |
Beginning column position of variable
in record |
| End |
Ending column position of variable in
record |
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2.5 Variable Naming
In general, variable names reflect the
content of the variable, with an 8 character limitation. Generally,
imputed/edited variables end with an "X".
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2.5.1 General
Variables contained on this file were derived from the HC
questionnaire itself, the MPC data collection instrument, or from the CAPI. The
source of each variable is identified in section D, entitled "Variable-Source
Crosswalk." Sources for each variable are indicated in one of four ways: (1)
variables which are derived from CAPI or assigned in sampling are so indicated;
(2) variables which come from one or more specific questions have those numbers
and the questionnaire section indicated in the "Source" column; (3) variables
constructed from multiple questions using complex algorithms are labeled
"Constructed" in the "Source" column; and (4) variables which have been imputed
are so indicated.
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2.5.2 Expenditure and Sources of Payment
Variables
Only imputed/edited versions of the
expenditure variables are provided on the file. Expenditure variables on this
event file follow a standard naming convention and are 7 characters in length.
The 12 source of payment variables and one sum of payments variable are named
consistently in the following way:
The first two characters indicate the type
of event:
| IP - inpatient stay |
OB - office-based visit |
| ER - emergency room visit |
OP - outpatient visit |
| HH - home health visit |
DV - dental visit |
| OM - other medical equipment |
RX - prescribed medicine |
In the case of the source of payment
variables, the third and fourth characters indicate:
| SF - self or family |
OF - other Federal Government |
| MR - Medicare |
SL - State/local government |
| MD - Medicaid |
WC - Worker's Compensation |
| PV - private insurance |
OT - other insurance |
| VA - Veterans |
OR - other private |
| TR - TRICARE |
OU - other public |
| XP - sum of payments |
|
The fifth and sixth characters
indicate the year (01). All imputed/edited expenditure variables end with an
"X".
For example, RXSF01X is the edited/imputed amount paid by self or family for the
2001 prescribed medicine expenditure.
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2.6 Data Collection
Data regarding prescription drugs were obtained through
the HC questionnaire and a pharmacy follow-back component (within the Medical
Provider Component).
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2.6.1 Methodology for
Collecting Household Reported Variables
During each round of the MEPS HC, all respondents were
asked to supply the name of any prescribed medicine they or their family members
purchased or otherwise obtained during that round. For each medicine in each
round, the following information was collected: whether any free samples of the
medicine were received; the name(s) of any health problems the medicine was
prescribed for; the number of times the prescription medicine was obtained or
purchased; the year, month, and day on which the person first used the medicine;
and a list of the names, addresses, and types of pharmacies that filled the
household's prescriptions. In the HC, respondents were asked if they send in
claim forms for their prescriptions or if their pharmacy providers do this
automatically for them at the point of purchase. For those that said their
pharmacy providers automatically send in claims for them at the point of
purchase, charge and payment information was collected in the pharmacy
follow-back component (unless the purchase was an insulin or diabetic
supply/equipment event that was mentioned in the household component; see
section 3.0 for details). However, charge and payment information was collected
for those that said they send in their own prescription claim forms, because it
was thought that payments by private third-party payers for those that filed
their own claim forms for prescription purchases would not be available from
pharmacies. Uninsured persons were treated in the same manner as those whose
pharmacies filed their prescription claims at the point of purchase. Persons who
said they did not know if they sent in their own prescription claim forms were
treated as those who said they did send in their own prescription claim forms.
An inaccuracy in the number of times a household reported purchasing or
otherwise obtaining a prescription drug in a particular round for a small
percentage of household reported medications was discovered. This inaccuracy was
due to an instrument design flaw, which caused interviewer error, and in
isolated cases, resulted in mis-reported large numbers of prescription refills
for a medicine in a given round. This inaccuracy was confined to only a very
small percentage of unique drugs on the original data delivered. Outlier values
where this situation occurred were determined by comparing the number of days a
respondent was in the round and the number times the person reported having
purchased or otherwise obtained the drug in the round, and were determined in
consultation with an industry expert. For these events, a new value for the
number of times a drug was purchased or otherwise obtained by a person in a
round was imputed. In addition, the prescribed medicine events in which a
household respondent did not know/remember the number of times a certain
prescribed medicine was purchased or otherwise obtained were imputed a value for
that variable.
For those rounds that spanned two years, drugs mentioned in that round were
allocated between the years based on the number of times the respondent said the
drug was purchased in the respective year, the year the person started taking
the drug, the length of the person's round, the dates of the person's round, and
the number of drugs for that person in the round. In addition, a "folded"
version of the PC on an event level, as opposed to an acquisition level, was
used for these types of events to assist in determining how many acquisitions of
the drug should be allocated between the years.
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2.6.2 Methodology for Collecting Pharmacy Reported Variables
If the respondent with the prescription gave written
permission to release his or her pharmacy records, pharmacy providers identified
by the household were contacted by telephone for the pharmacy follow-back
component. Following an initial telephone contact, the signed permission forms
and materials explaining the study were faxed (or mailed) to cooperating
pharmacy providers. The materials informed the providers of all persons
participating in the survey who had prescriptions filled at their place of
business and requested a computerized printout of all prescriptions filled for
each person. For each medication listed, the following information was
requested: date filled; national drug code (NDC); medication name; strength of
medicine (amount and unit); quantity (package size/amount dispensed); total
charge; and payments by source.
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2.7
File Contents
2.7.1
Survey Administration Variables
2.7.1.1
Person Identifier Variables (DUID, PID, DUPERSID)
The dwelling unit ID (DUID) is a 5-digit
random number assigned after the case was sampled for MEPS. The 3-digit person
number (PID) uniquely identifies each person within the dwelling unit. The
8-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 2001 Full Year Population Characteristics File.
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2.7.1.2
Record Identifier Variables (RXRECIDX, LINKIDX)
The variable RXRECIDX uniquely identifies each record on
the file. This 15-character variable is comprised of the following components:
prescribed medicine event generated through the HC (positions 1-12) +
enumeration number (positions 13-15). The prescribed medicine event generated
through the HC (positions 1-12) can be used to link a prescribed medicine event
to the conditions file and to other event files, via link files, and is provided
on this file as the variable LINKIDX. (For more details on linking, please refer
to section 5.2 and to the 2001 Appendix File.)
The following hypothetical example illustrates the structure of these ID
variables. This example illustrates a person in Round 1 of the household
interview who reported having purchased Amoxicillin three times. The following
example shows three acquisition level records, all having the same RXNDC
(00093310905), for one person (DUPERSID=00002026) in one round. Only one NDC is
associated with a prescribed medicine event because matching was performed at an
event level, as opposed to an acquisition level. (For more details on matching,
please see section 3.0). The LINKIDX (000020260083) remains the same for all
three records, whereas the RXRECIDX (000020260083001, 000020260083002,
000020260083003) differs for all three records.
| DUPERSID |
RXRECIDX |
LINKIDX |
RXNDC |
| 00002026 |
000020260083001 |
000020260083 |
00093310905 |
| 00002026 |
000020260083002 |
000020260083 |
00093310905 |
| 00002026 |
000020260083003 |
000020260083 |
00093310905 |
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2.7.1.3.
Round Variable (PURCHRD)
The variable PURCHRD indicates the round in which the
prescribed medicine was obtained/purchased and takes on the value of 1, 2, 3, 4,
or 5. Rounds 3, 4, and 5 are associated with MEPS survey data collection from
Panel 5. Similarly, Rounds 1, 2, and 3 are associated with data collected from
Panel 6.
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2.7.2
Characteristics of Prescribed Medicine Events
2.7.2.1
Date When Prescribed Medicine Was First Taken (RXBEGDD-RXBEGYR)
There are three variables which indicate when a prescribed
medicine was first taken (used), as reported by the household. They are the
following: RXBEGDD indicates the day a person first started taking a medicine,
RXBEGMM denotes the month in which a person first started taking a medication,
and RXBEGYR reflects the year in which a person first started taking a medicine.
These "first taken" questions are only asked the first time a prescription is
mentioned by the household. These questions are not asked of refills of the
prescription for a person in subsequent rounds and result in a value of -1 being
assigned to those types of events for these variables. These variables are
unedited.
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2.7.2.2
Prescribed Medicine Attributes (RXNAME-RXSTRUNT)
For each prescribed medicine included on this file,
several data items collected describe in detail the medication obtained or
purchased. These data items are the following:
| a. |
Medication name - pharmacy
reported (RXNAME) |
| b. |
Medication name -
household reported (RXHHNAME) |
| c. |
National drug code (RXNDC) |
| d. |
Quantity of the prescribed
medicine dispensed (RXQUANTY); e.g., number of tablets in the prescription |
| e. |
Form of the prescribed
medicine (RXFORM); e.g., powder |
| f. |
Unit of measurement for
form of Rx/prescribed medicine (RXFRMUNT); e.g., oz |
| g. |
Strength of the dose of
the prescribed medicine (RXSTRENG); e.g., 10 |
| h. |
Unit of measurement for
the strength of the dose of the prescribed medicine (RXSTRUNT); e.g., gm |
Please refer to Attachments 1, 2, and 3 for definitions
for RXFORM, RXFRMUNT, and RXSTRUNT abbreviations, codes and symbols.
The national drug code (NDC) generally, and on this file, is an 11-digit code.
The first 5 digits indicate the manufacturer of the prescribed medicine. The
next 4 digits indicate the form and strength of the prescription, and the last 2
digits indicate the package size from which the prescription was dispensed. NDC
values were imputed from a proprietary database to certain PC prescriptions
because the NDC reported by the pharmacy provider did not match to the
proprietary database. These records are identified by RXFLG=3. AHRQ's licensing
agreement for the proprietary database precludes the release of these imputed
NDC values to the public, so for these prescriptions, the household reported
name of the prescription (RXHHNAME) and the original NDC (RXNDC) and
prescription name (RXNAME) reported by the pharmacist are provided to allow
users to do their own imputation. Otherwise, the imputed NDC values for the
RXFLG=3 cases may be accessed through the MEPS Data Center. For those events not
falling in the RXFLG=3 category, the reserve code (-13) is assigned to the
household reported medication name (RXHHNAME). For information on accessing
confidential data through the MEPS Data Center, contact the MEPS Project
Director by email at: <mepspd@ahrq.gov>.
Imputed data on this event file, unlike other MEPS event files, may still have
missing data. This is because imputed data on this file are imputed from the PC
or from a proprietary database. These sources did not always include complete
information for each variable but did include an NDC, which would typically
enable an analyst to obtain any missing data items. For example, although there
are a substantial number of missing values for the strength of the prescription
that were not supplied by the pharmacist, these missing values were not imputed
because this information is embedded in the NDC.
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2.7.2.3
Type of Pharmacy (PHARTP1-PHARTP7)
Household respondents were asked to list the type of
pharmacy from which their medications were purchased. A household could list
multiple pharmacies associated with their prescriptions in a given round, or
over the course of all rounds combined covering the survey year. As a result,
this file contains, at most, seven of these household reported pharmacies, but
there was no link in the survey or in the data file enabling users to know the
type of pharmacy from which a specific prescription was obtained, if multiple
pharmacies are listed. The set of variables (PHARTP1-PHARTP7) identify the types
of pharmacy providers from which the person's prescribed medicines were
purchased or otherwise obtained. The possible types of pharmacies include the
following: (1) mail-order, (2) another store, (3) HMO/clinic/hospital, (4) drug
store, and (5) on-line. A -1 value for PHARTPn indicates that the household did
not report an "nth" pharmacy.
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2.7.2.4
Analytic Flag Variables (RXFLG-DIABFLG)
There are five flag variables included on this file (RXFLG,
PCIMPFLG, CLMOMFLG, INPCFLG, and DIABFLG).
The variable RXFLG indicates how the NDC for a specific prescribed medicine
event was imputed. This variable indicates whether or not there was any
imputation performed on this record for the NDC variable, and if imputed, from
what source the NDC was imputed. If no imputation was performed, RXFLG=1. If the
imputation source was another PC record, RXFLG=2. Similarly, if the imputation
source was a secondary, proprietary database and not the PC database, RXFLG=3.
For these RXFLG=3 records, all the original data reported by the pharmacy and
the household reported medication name are included on the record. Including
only the original pharmacy reported data for these records was necessary in
order to comply with legal restrictions associated with using the secondary data
source as an imputation source. The imputed NDC value for the RXFLG=3 cases was
used in the data editing, but is not available for public release. However, the
imputed NDCs for the RXFLG=3 cases are available through the MEPS Data Center.
Information on this topic can be obtained through the MEPS Project Director at <mepspd@ahrq.gov>.
PCIMPFLG indicates the type of match between a household reported event and a PC
reported event. There are only two possible values for this variable (PCIMPFLG
=1 or =2). These values indicate the possible "match-types" and are the
following: =1 is an exact match for a specific event for a person between the PC
and the HC and =2 is not an exact match between the PC and HC for a specific
person (not an exact match means that a person's household reported event did
not have a matched counterpart in their corresponding PC records). PCIMPFLG
assists analysts in determining which records have the strongest link to data
reported by a pharmacy. It should be noted that whenever there are multiple
purchases of a unique prescribed medication in a given round, MEPS did not
collect information that would enable designating any single purchase as the
"original" purchase at the time the prescription was first filled, and then
designating other purchases as "refills." The user needs to keep this in mind
when the purchases of a medication are referred to as "refills" in the
documentation. Because matching was performed at an event level as opposed to an
acquisition level, the values for PCIMPFLG are either =1 or =2. Additionally,
matching on an event versus acquisition level results in only one NDC being
associated with a prescribed medicine event. (For more details on general data
editing/imputation methodology, please see section 3.0).
CLMOMFLG indicates if a prescription medicine event went through the charge and
payment section of the HC. Prescription medicine events that went through the
charge and payment section of the HC include: (1) events where the person filed
their own prescription claim forms to their insurance company, (2) events for
persons who responded they did not know if they filed their own prescription
claim forms to their insurance company, and (3) insulin and diabetic
supply/equipment events (OMTYPE=2 or =3) that were mentioned in the Other
Medical section of the HC. For these types of events information on payment
sources was retained to the extent that these data were reported by the
household in the charge and payment section of the HC.
INPCFLG denotes whether or not a household respondent had at least one
prescription drug purchase in the PC (0=no, 1=yes).
When diabetic supplies, such as syringes and insulin, were mentioned in the
Other Medical Equipment section of the MEPS HC, the interviewer was directed to
collect information on these items in the Prescription Medicines section of the
MEPS questionnaire. To the extent that these items are purchased without a
prescription, they represent a non-prescription addition to the MEPS
prescription drug expenditure and utilization data. Although these items may be
purchased without a prescription, a prescription purchase may be required to
obtain third party payments. Diabetic supplies can be identified in the file by
using the variable, DIABFLG (0=not a diabetic supply/equipment or insulin, 1=is
a diabetic supply/equipment or insulin). Diabetic supply/equipment and insulin
events were identified with the assistance of an industry expert by utilizing a
proprietary database, which assisted in assigning codes to each prescribed
medicine event. This code assignment took into account the characteristics of
the event. However, if desired, analysts are free to code and define diabetic
supply/equipment and insulin events utilizing their own coding mechanism. If
desired, DIABFLG can also be used by analysts to exclude diabetic
supplies/equipment from their analyses.
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2.7.2.5
The Sample Variable (SAMPLE)
SAMPLE indicates if a respondent reported receiving a free
sample of the prescription medicine in the round (0=no, 1=yes). Each household
respondent was asked in each round whether or not they received any free samples
of a reported prescribed medicine during the round. However, respondents were
not asked to report the number of free samples received, nor was it made clear
that any free samples received were included in the count of the number of times
that the respondent reported purchasing or otherwise obtaining the prescribed
medicine during the round. Therefore, SAMPLE=1 for all acquisitions that a
respondent reported for a person for a specific prescription medicine during the
round. This allows individual analysts to determine for themselves how free
samples should be handled in their analysis.
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2.7.2.6
Condition Codes (RXICD1X-RXICD3X) and Clinical Classification Codes
(RXCCC1X-RXCCC3X)
Information on household reported medical
conditions associated with each prescribed medicine event are provided on this
file. There are up to three condition and clinical classification codes listed
for each prescribed medicine event (99.8% of prescribed medicine events have 0-3
condition records linked). To obtain complete information associated with an
event, the analyst must link to the 2001 Medical Conditions File. Details on how
to link to the MEPS 2001 Medical Conditions File are provided in the 2001
Appendix File. The user should note that due to confidentiality restrictions,
provider reported condition information (for non-prescription medicines events)
is not publicly available. Provider reported condition data (again, for
non-prescription medicines events) can be accessed through the MEPS Data Center
only.
The medical conditions reported by the HC respondent were recorded by the
interviewer as verbatim text, which were then coded to fully-specified 2001
ICD-9-CM codes, including medical condition, V codes, and a small number of E
codes, by professional coders. Although codes were verified and error rates did
not exceed 2.5 percent for any coder, 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. For detailed
information on conditions, please refer to the documentation on the 2001 Medical
Conditions File. For frequencies of conditions by event type, please see the
2001 Appendix File.
The ICD-9-CM condition codes were aggregated into clinically meaningful
categories. These categories, included on the file as RXCCC1X-RXCCC3X, were
generated using Clinical Classification Software (CCS) (formerly known as
Clinical Classifications for Health Care Policy Research (CCHPR)), which
aggregates conditions and V-codes into 260 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
3-digit code categories. The reported ICD-9-CM code values were mapped to the
appropriate clinical classification category prior to being collapsed to the
3-digit categories.
The condition codes (and clinical classification codes) linked to each
prescribed medicine event are sequenced in the order in which the conditions
were reported by the household respondent, which was in chronological order of
reporting and not in order of importance or severity. Analysts who use the 2001
Medical Conditions file in conjunction with this prescribed medicines event file
should note that the conditions on this file are sorted differently than they
appear on the Medical Conditions file.
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2.7.3
Expenditure Variables (RXSF01X-RXXP01X)
2.7.3.1
Definition of Expenditures
Expenditures on this file refer to what is paid for health care services. More
specifically, expenditures in MEPS are defined as the sum of payments for care
received, including out of pocket payments and payments made by private
insurance, Medicaid, Medicare and other sources. The definition of expenditures
used in MEPS differs slightly from its predecessors, the 1987 NMES and 1977
NMCES surveys, where "charges" rather than "sum of payments" were used to
measure expenditures. This change was adopted because charges became a less
appropriate proxy for medical expenditures during the 1990's due to the
increasingly common practice of discounting charges. Although measuring
expenditures as the sum of payments incorporates discounts in the MEPS
expenditure estimates, the estimates do not incorporate any manufacturer or
other rebates associated with Medicaid or other purchases. 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. For details on expenditure definitions,
please reference the following, "Informing American Health Care Policy" (Monheit,
Wilson, Arnett, 1999).
If examining trends in MEPS expenditures or performing longitudinal analysis on
MEPS expenditures, please refer to section C, sub-section 2.1 for more
information.
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2.7.3.2
Sources of Payment
In addition to total expenditures,
variables are provided which itemize expenditures according to major source of
payment categories. These categories are:
| 1. |
Out of pocket by user or
family |
| 2. |
Medicare |
| 3. |
Medicaid |
| 4. |
Private Insurance |
| 5. |
Veteran's Administration |
| 6. |
TRICARE |
| 7. |
Other Federal sources -
includes Indian Health Service, Military Treatment Facilities, and other
care by the Federal government |
| 8. |
Other State and Local
Source - includes community and neighborhood clinics, State and local
health departments, and State programs other than Medicaid |
| 9. |
Worker's Compensation |
| 10. |
Other Unclassified Sources
- includes sources such as automobile, homeowner's, liability, and other
miscellaneous or unknown sources |
Two additional source of payment variables were created to
classify payments for particular persons that appear inconsistent due to
differences between survey questions on health insurance coverage and sources of
payment for medical events. These variables include:
| 11. |
Other Private - any type
of private insurance payments reported for persons not reported to have
any private health insurance coverage during the year as defined in MEPS;
and |
| 12. |
Other Public - Medicaid
payments reported for persons who were not reported to be enrolled in the
Medicaid program at any time during the year |
Though relatively small in magnitude,
users should exercise caution when interpreting the expenditures associated with
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
program.
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2.7.4
Sample Weight (PERWT01F)
2.7.4.1
Overview
There is a single full year person-level
weight (PERWT01F) 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
2001. A key person either was a member of an NHIS household at the time of the
NHIS interview, or became a member of such a household after being out-of-scope
at the time of the NHIS (examples of the latter situation include newborns and
persons returning from military service, an institution, or living outside the
United States). A person is in-scope whenever he or she is a member of the
civilian noninstitutionalized portion of the U.S. population.
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2.7.4.2
Details on Person Weights Construction
The person-level weight PERWT01F was developed in several
stages. Person level weights for Panels 5 and 6 were created separately. The
weighting process for each panel included an adjustment for nonresponse over
time and poststratification. Poststratification was achieved by controlling to
Current Population Survey (CPS) population estimates based on five variables.
Variables used in the establishment of person-level poststratification control
figures included: census region (Northeast, Midwest, South, West); MSA status (MSA,
non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and
age. A 2001 composite weight was then formed by multiplying each panel weight by
.5 and then poststratifying the resulting weight to the same set of CPS-based
control totals. When poverty status information derived from income variables
became available, a final poststratification was done on the resulting weight
variable, including 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) as well as the original five poststratification
variables in the establishment of control totals.
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2.7.4.3
MEPS Panel 5 Weight
The person-level weight for MEPS Panel 5
was developed using the 2000 full year weight for an individual as a "base"
weight for survey participants present in 2000. For key, in-scope respondents
who joined an RU some time in 2001 after being out-of-scope in 2000, the 2000
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 poststratification to population control figures for December
2001. These control figures were derived by scaling back the population totals
obtained from the March 2001 CPS to reflect the December 2001 CPS estimated
population distribution across age and sex categories as of December 2001.
Variables used in the establishment of person-level poststratification control
figures included: census region (Northeast, Midwest, South, West); MSA status (MSA,
non-MSA); race/ethnicity (Hispanic, black but non-Hispanic, and other); sex; and
age. Overall, the weighted population estimate for the civilian
noninstitutionalized population on December 31, 2001 is 280,791,812. Key,
responding persons not in-scope on December 31, 2001 but in-scope earlier in the
year retained, as their final Panel 5 weight, the weight after the nonresponse
adjustment.
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2.7.4.4
MEPS Panel 6 Weight
The person-level weight for MEPS Panel 6 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 2001 portion of Round 3 as well as poststratification to
the same population control figures for December 2001 used for the MEPS Panel 5
weights. The same five variables employed for Panel 5 poststratification (census
region, MSA status, race/ethnicity, sex, and age) were used for Panel 6
poststratification. Similarly, for Panel 6, key, responding persons not in-scope
on December 31, 2001 but in-scope earlier in the year retained, as their final
Panel 6 weight, the weight after the nonresponse adjustment.
Note that the MEPS Round 1 weights (for both panels with one exception as noted
below) 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 2001 CPS data
base.
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2.7.4.5
The Final Weight for 2001
Variables used in the establishment of person-level
poststratification 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, black but non-Hispanic, and other); sex; and age. Overall, the
weighted population estimate for the civilian noninstitutionalized population
for December 31, 2001 is 280,791,812 (PERWT01F>0 and INSC1231=1). The weights of
some persons out-of-scope on December 31, 2001 were also poststratified.
Specifically, the weights of persons out-of-scope on December 31, 2001 who were
in-scope some time during the year and also entered a nursing home during the
year were poststratified to a corresponding control total obtained from the 1996
MEPS Nursing Home Component. The weights of persons who died while in-scope
during 2001 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.
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2.7.4.6
Coverage
The target population for MEPS in this file is the 2001
U.S. civilian noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 1999 (Panel 5)
and 2000 (Panel 6). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 1999 (Panel 5) or after 2000 (Panel 6) are not covered by MEPS.
Neither are previously out-of-scope persons who join an existing household but
are unrelated to the current household residents. Persons not covered by a given
MEPS panel thus include some members of the following groups: immigrants;
persons leaving the military; U.S. citizens returning from residence in another
country; and persons leaving institutions. The set of uncovered persons
constitutes only a small segment of the MEPS target population.
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3.0
General Data Editing and Imputation Methodology
The general approach to preparing the
household prescription data for this file was to utilize the PC prescription
data to impute information collected from pharmacy providers to the household
drug mentions. For events that went through the charge and payment section of
the HC (events where the person filed their own prescription claim forms to
their insurance company, events for persons who responded they did not know if
they filed their own prescription claim forms to their insurance company, and
insulin and diabetic supply/equipment events (OMTYPE=2 or =3) that were
mentioned in the Other Medical section of the HC), information on payment
sources was retained to the extent that these data were reported by the
household in the charge and payment section of the HC. A matching program was
adopted to link PC drugs and the corresponding drug information to household
drug mentions. To improve the quality of these matches, all drugs on the
household and pharmacy files were coded using a proprietary database on the
basis of the medication names provided by the household and pharmacy, and, when
available, the NDC provided in the pharmacy follow-back component. The matching
process was done at an event level, as opposed to an acquisition level.
Considerable editing was done prior to the matching to correct data
inconsistencies in both data sets and to fill in missing data and correct
outliers on the pharmacy file.
Drug price-per-unit outliers were analyzed on the pharmacy file by first
identifying the average wholesale unit price (AWUP) of the drug by linkage
through the NDC to a secondary data file. In general, prescription drug unit
prices were deemed to be outliers by comparing unit prices reported in the
pharmacy database to the AWUP reported in the secondary data file and were
edited, as necessary. Outlier thresholds were established in consultation with
industry experts.
Drug matches between household drug mentions and pharmacy drug events for a
person in the PC were based on drug code, medication name, and the round in
which the drug was reported. The matching of household drug mentions to pharmacy
drugs was performed so that the most detailed and accurate information for each
prescribed medicine event was obtained. Exact dates of purchase were only
available from the follow-back component. The matching program assigned scores
to potential matches. Numeric variables required exact matches to receive a high
score, while partial scores could be assigned to matches between character
variables, such as prescription name, depending on the degree of similarity in
the spelling and sound of the medication names. Household drug mentions that
were deemed exact matches to PC drugs for the same person in the same round
required sufficiently high scores to reflect a high quality match. Exact matches
were used only once and were taken out of the donor pool from that point on
(i.e., these matches were made without replacement). Any refill of a household
drug mention that had been matched to a pharmacy drug event was also matched to
the same pharmacy drug event. All remaining unmatched household drug mentions
for persons either in or out of the PC were statistically matched to the entire
pharmacy donor base with replacement by medication name, drug code, type of
third party coverage, health conditions, age, sex, and other characteristics of
the individual. Potential PC donor records were omitted from these matches
whenever a NDC was imputed to the PC record and was not an exact match on a
generic product code applied to all records in the HC and PC.
For more information on the MEPS Prescribed Medicines editing and imputation
procedures, please see J. Moeller, 2001.
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3.1 Rounding
Expenditure variables on the 2001
Prescribed Medicines file have been rounded to the nearest penny. Person level
expenditure variables released on the 2001 Full Year Consolidated Data File were
rounded to the nearest dollar. It should be noted that using the 2001 MEPS event
files to create person level totals will yield slightly different totals than
those found on the 2001 Full Year Consolidated Data File. These differences are
due to rounding only. Moreover, in some instances, the number of persons having
expenditures on the 2001 event files for a particular source of payment may
differ from the number of persons with expenditures on the 2001 Full Year
Consolidated Data File for that source of payment. This difference is also an
artifact of rounding only. Please see the 2001 Appendix File for details on such
rounding differences.
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3.2
Edited/Imputed Expenditure Variables (RXSF01X-RXXP01X)
There are 13 expenditure variables
included on this event file. All of these expenditures have gone through an
editing and imputation process and have been rounded to the second decimal
place. There is a sum of payments variable (RXXP01X) which for each prescribed
medicine event sums all the expenditures from the various sources of payment.
The 12 sources of payment expenditure variables for each prescribed medicine
event are the following: amount paid by self or family (RXSF01X), amount paid by
Medicare (RXMR01X), amount paid by Medicaid (RXMD01X), amount paid by private
insurance (RXPV01X), amount paid by the Veterans Administration (RXVA01X),
amount paid by TRICARE (RXTR01X), amount paid by other federal sources
(RXOF01X), amount paid by state and local (non-federal) government sources
(RXSL01X), amount paid by Worker's Compensation (RXWC01X), and amount paid by
some other source of insurance (RXOT01X). As mentioned previously, there are two
additional expenditure variables called RXOR01X and RXOU01X (other private and
other public, respectively). These two expenditure variables were created to
maintain consistency between what the household reported as their private and
public insurance status for hospitalization and physician coverage and third
party prescription payments from other private and public sources (such as a
separate private prescription policy or prescription coverage from the Veterans
Administration, the Indian Health Service, or a State assistance program other
than Medicaid). Users 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. Please see section 2.7.3 for details on these and all other source
of payment variables.
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Contents
4.0 Strategies for Estimation
This file is constructed for efficient estimation of
utilization, expenditure, and sources of payment for outpatient care and to
allow for estimates of number of persons with prescribed medicine purchases
during 2001.
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Contents
4.1 Variables with Missing Values
It is essential that the analyst examine all variables for
the presence of negative values used to represent missing values. For continuous
or discrete variables, where means or totals may be taken, it may be necessary
to set minus values to values appropriate to the analytic needs. That is, the
analyst should either impute a value or set the value to one that will be
interpreted as missing by the computing language used. For categorical and
dichotomous variables, the analyst may want to consider whether to recode or
impute a value for cases with negative values or whether to exclude or include
such cases in the numerator and/or denominator when calculating proportions.
Methodologies used for the editing/imputation of expenditure variables are
described in Section 3.0.
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4.2 Basic Estimates of Utilization, Expenditures, and
Sources of Payment
While the examples described below
illustrate the use of event level data in constructing person level total
expenditures, these estimates can also be derived from the person level
expenditure file unless the characteristic of interest is event specific.
In order to produce national estimates related to prescribed medicines
utilization, expenditure and sources of payment, the value in each record
contributing to the estimates must be multiplied by the weight (PERWT01F)
contained on that record.
Example 1
For example, the total number of
prescribed medicines events1 for the civilian non-institutionalized population of
the U.S. in 2001 is estimated as the sum of the weight (PERWT01F) across all
prescribed medicines event records. That is,
301 Moved Permanently
301 Moved Permanently
|
= 2,493,748,994 |
for all records |
(1) |
_____________________
1 In this and all other examples,
unless otherwise noted, prescribed medicines records include diabetic
supplies\equipment and insulin.
Example 2
Subsetting to records based on characteristics of interest
expands the scope of potential estimates. For example, the estimate for the mean
out-of-pocket payment per prescription medicine purchase should be calculated as
the weighted mean of amount paid by self/family. That is,
301 Moved Permanently
301 Moved Permanently
|
= $23.67 |
(2) |
where
301 Moved Permanently
301 Moved Permanently
|
= 2,493,748,994 and Xj = RXSF01Xj |
This gives $23.67 as the estimated mean amount of
out-of-pocket payment of expenditures associated with prescribed medicines
events and 2,493,748,994 as an estimate of the total number of prescription
medicine purchases. Both of these estimates are for the civilian
non-institutionalized population of the U.S. in 2001.
Example 3
Another example would be to estimate the average
proportion of total expenditures paid by private insurance per prescription
medicine purchase. This should be calculated as the weighted mean of the
proportion of the total prescription medicine purchase paid by private insurance
at the prescribed medicines event level. That is,
301 Moved Permanently
301 Moved Permanently
|
= 0.2796 |
(3) |
where
301 Moved Permanently
301 Moved Permanently
|
= 2,493,748,994 and Yj = RXPV01Xj / RXXP01Xj |
This gives 0.2796 as the estimated mean proportion of
total expenditures paid by private insurance per prescription medicine purchase
for the civilian non-institutionalized population of the U.S. in 2001.
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4.3
Estimates of the Number of Persons with Prescribed Medicine Events
When calculating an estimate of the total number of
persons with prescribed medicine events, users can use a person-level file or
this event file. However, this event file must be used when the measure of
interest is defined at the event level. For example, to estimate the number of
persons in the civilian non-institutionalized population of the U.S. with a
prescribed medicine purchase in 2001 with an RXNDC = "00093310905"
(Amoxicillin), this event file must be used. This would be estimated as
301 Moved Permanently
301 Moved Permanently
|
across all unique persons i on this
file |
(4) |
where
Wi is the sampling weight (PERWT01F) for person i
and
Xi = 1 if RXNDC = '00093310905" for any purchase of person
i.
= 0 otherwise
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Contents
4.4 Person-Based Ratio Estimates
4.4.1
Person-Based Ratio Estimates Relative to Persons with Prescribed Medicine Events
This file may be used to derive person-based ratio
estimates. However, when calculating ratio estimates where the denominator is
persons, care should be taken to properly define and estimate the unit of
analysis up to person level. For example, the mean expense for persons with
prescribed medicine purchases is estimated as,
301 Moved Permanently
301 Moved Permanently
|
across all unique persons i on this
file |
(5) |
where
Wi is the sampling weight (PERWT01F) for person i
and
|
Zi = |
301 Moved Permanently
301 Moved Permanently
|
RXXP01Xj
across all prescription purchases for person i. |
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4.4.2
Person-Based Ratio Estimates Relative to the Entire Population
If the ratio relates to the entire population, this file
cannot be used to calculate the denominator, as only those persons with at least
one prescribed medicine event are represented on this data file. In this case
the person level file, which has data for all sampled persons, must be used to
estimate the total number of persons (i.e. those with use and those without
use). For example, to estimate the proportion of civilian non-institutionalized
population of the U.S. with at least one prescribed medicine event with RXNDC =
"00093310905" (Amoxicillin) in 2001, the numerator would be derived from data on
this event file, and the denominator would be derived from data on the
person-level file. That is,
301 Moved Permanently
301 Moved Permanently
|
across all unique persons i on the MEPS
HC-055 file |
(6) |
where
Wiis the sampling weight (PERWT01F) for person i
and
Zi = 1 if RXNDCj = "00093310905" for any event of
person i.
= 0 otherwise.
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Contents
4.5
Sampling Weights for Merging Previous Releases of MEPS Household Data with this
Event File
There have been several previous releases of MEPS
Household Survey public use data. Unless a variable name common to several files
is provided, the sampling weights contained on these data files are
file-specific. The file-specific weights reflect minor adjustments to
eligibility and response indicators due to birth, death, or institutionalization
among respondents.
For estimates from a MEPS data file that do not require merging with variables
from other MEPS data files, the sampling weight(s) provided on that data file
are the appropriate weight(s). When merging a MEPS Household data file to
another, the major analytical variable (i.e. the dependent variable) determines
the correct sampling weight to use.
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4.6 Variance Estimation
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. Various approaches can be used to develop such estimates of
variance including use of the Taylor series or various replication
methodologies. Replicate weights have not been developed for the MEPS 2001 data.
Variables needed to implement a Taylor series estimation approach are provided
in the file and are described in the paragraph below.
Using a Taylor Series approach, variance estimation strata and the variance
estimation PSUs within these strata must be specified. The corresponding
variables on the MEPS full year utilization database are VARSTR01 and VARPSU01,
respectively. Specifying a "with replacement" design in a computer software
package such as SUDAAN (Shah, 1996) should provide 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), there are over 100 degrees of
freedom associated with the corresponding estimates of variance. The following
illustrates these concepts using two examples from section 4.2.
Examples 2 and 3 from Section 4.2
Using a Taylor Series approach, specifying VARSTR01 and
VARPSU01 as the variance estimation strata and PSUs (within these strata)
respectively and specifying a "with replacement" design in a computer software
package SUDAAN will yield standard error estimates of $0.3419 and 0.0054 for the
estimated mean of out-of-pocket payment and the estimated mean proportion of
total expenditures paid by private insurance respectively.
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5.0 Merging/Linking MEPS Data Files
Data from this event file can be used alone or in
conjunction with other files. This section provides instructions for linking the
2001 prescribed medicines file with other 2001 MEPS public use files, including
a 2001 person level file, the 2001 conditions file, and the other 2001 event
files.
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Contents
5.1
Linking a Person Level File to the Prescribed Medicines File
Merging characteristics of interest from other 2001 MEPS
files (e.g., the 2001 Full Year Consolidated File or the 2001 Office Based
Provider File) expands the scope of potential estimates. For example, to
estimate the total number of prescribed medicines purchased or otherwise
obtained by persons with specific characteristics (e.g., age, race, and sex),
population characteristics from a person level file need to be merged onto the
prescribed medicines file. This procedure is illustrated below. The 2001
Appendix File provides additional details on how to merge 2001 MEPS data files.
| 1. |
Create data set PERSX by sorting a Full
Year Population Characteristics File (file HCXXX), by the person
identifier, DUPERSID. Keep only variables to be merged on to the
prescribed medicines file and DUPERSID. |
| 2. |
Create data set PMEDS by sorting the
prescribed medicines file by person identifier, DUPERSID. |
| 3. |
Create final data set NEWPMEDS by
merging these two files by DUPERSID, keeping only records on the
prescribed medicines file. |
The following is an example of SAS code, which completes
these steps:
PROC SORT DATA=HCXXX(KEEP=DUPERSID AGE31X SEX RACEX) OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA= HC059A OUT=PMEDS;
BY DUPERSID;
RUN;
DATA NEWPMEDS;
MERGE PMEDS (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
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5.2
Linking the 2001 Conditions File and/or the Other 2001 MEPS Event Files to the
2001 Prescribed Medicines File
Due to survey design issues, there are limitations/caveats
that an analyst must keep in mind when linking the different files. Those
limitations/caveats are listed below. For detailed linking examples, including
SAS code, analysts should refer to the 2001 Appendix File.
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5.3 Limitations/Caveats of RXLK and CLNK
The RXLK file provides a link between the 2001 prescribed
medicine records and the other 2001 MEPS event files. When using RXLK, analysts
should keep in mind that a prescribed medicine event may link to more than one
medical event. When this occurs, it is up to the analyst to determine how the
prescribed medicine expenditures should be allocated among those events. In
order to obtain complete information about those other event files, the analyst
must link to the other public use event files.
The CLNK provides a link between the 2001 Medical Conditions File and the 2001
Prescribed Medicines file. When using the CLNK, analysts should keep in mind
that (1) conditions are self reported and (2) there may be multiple conditions
associated with a drug purchase. Analysts need to verify that a particular
medication is indeed an appropriate medication in treating the condition.
Moreover, there may be some drugs that were purchased to treat a specific health
condition for which there is no such link to the condition file because the
respondent did not report the condition as being related to the prescribed
medicine.
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References
Cohen, S.B. (1998). Sample Design of the 1996 Medical
Expenditure Panel Survey Medical Provider Component. Journal of Economic and
Social Measurement. Vol 24, 25-53.
Cohen, S.B. (1997). Sample Design of the 1996 Medical
Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health
Care Policy and Research; 1997. MEPS Methodology Report, No. 2. AHCPR Pub. No.
97-0027.
Cohen, J.W. (1997). Design and Methods of the Medical
Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health
Care Policy and Research; 1997. MEPS Methodology Report, No. 1. AHCPR Pub. No.
97-0026.
Cohen, S.B. (1996). The Redesign of the Medical
Expenditure Panel Survey: A Component of the DHHS Survey Integration Plan.
Proceedings of the COPAFS Seminar on Statistical Methodology in the Public
Service.
Cox, B.G. and Cohen, S.B. (1985). Chapter 8: Imputation
Procedures to Compensate for Missing Responses to Data Items. In Methodological
Issues for Health Care Surveys. Marcel Dekker, New York.
Moeller J.F., Stagnitti, M., Horan, E., et al. Outpatient
Prescription Drugs: Data Collection and Editing in the 1996 Medical Expenditure
Panel Survey (HC-010A). Rockville (MD): Agency for Healthcare Research and
Quality; 2001. MEPS Methodology Report No. 12. AHRQ Pub. No. 01-0002.
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.
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D. Variable-Source Crosswalk
MEPS HC-059A: 2001 Prescribed Medicines
Events
Survey Administration Variables
Variable |
Description |
Source |
|
DUID |
Dwelling unit ID |
Assigned in sampling |
|
PID |
Person number |
Assigned in sampling |
|
DUPERSID |
Sample person ID (DUID + PID) |
Assigned in sampling |
|
RXRECIDX |
Record ID - Unique
Prescribed Medicine Identifier |
Constructed |
LINKIDX |
Link to condition and other
event files |
CAPI derived |
PURCHRD |
Round in which the
Rx/prescribed medicine was obtained/purchased |
CAPI derived |
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Prescribed Medicines Events Variables
Variable |
Description |
Source |
RXBEGDD |
Day person first used
medicine |
PM11OV1 |
RXBEGMM |
Month person first used
medicine |
PM11OV2 |
RXBEGYR |
Year person first used
medicine |
PM11 |
RXNAME |
Medication name (Imputed) |
Imputed |
RXHHNAME |
Household reported
medication name |
PM05 |
RXNDC |
National drug code (Imputed) |
Imputed |
RXQUANTY |
Quantity of Rx/prescribed
medicine (Imputed) |
Imputed |
RXFORM |
Form of Rx/prescribed
medicine (Imputed) |
Imputed |
RXFRMUNT |
Unit of measurement for form
of Rx/prescribed medicine (Imputed) |
Imputed |
RXSTRENG |
Strength of Rx/prescribed
medicine dose (Imputed) |
Imputed |
RXSTRUNT |
Unit of measurement for
strength of Rx/prescribed medicine dose (Imputed) |
Imputed |
PHARTP1-PHARTP7 |
Type of pharmacy provider -
(1st-7th) |
PM16 |
RXFLG |
Flag variable indicating
imputation source for NDC on pharmacy donor record |
Constructed |
PCIMPFLG |
Flag indicating type of
household to pharmacy prescription match |
Constructed |
CLMOMFLG |
Charge/payment, Rx claim
filing, and OMTYPE =2 or =3 (insulin and diabetic supply equipment events) status |
CP01/Constructed |
INPCFLG |
Flag indicating if the
person has at least one record in the pharmacy component |
Constructed |
DIABFLG |
Flag indicating whether or
not prescribed medicine was classified as insulin or diabetic supply/equipment |
Constructed |
SAMPLE |
Flag indicating if a
respondent received a free sample of this drug in the round |
CAPI derived |
RXICD1X |
3 digit ICD-9 condition code |
PM09 |
RXICD2X |
3 digit ICD-9 condition code |
PM09 |
RXICD3X |
3 digit ICD-9 condition code |
PM09 |
RXCCC1X |
Modified Clinical
Classification Code |
Constructed/Edited |
RXCCC2X |
Modified Clinical
Classification Code |
Constructed/Edited |
RXCCC3X |
Modified Clinical
Classification Code |
Constructed/Edited |
RXSF01X |
Amount paid, self or family
(Imputed) |
CP11/Edited/Imputed |
RXMR01X |
Amount paid, Medicare
(Imputed) |
CP12/CP13/Edited/Imputed |
RXMD01X |
Amount paid, Medicaid
(Imputed) |
CP12/CP13/Edited/Imputed |
RXPV01X |
Amount paid, private
insurance (Imputed) |
CP12/CP13/Edited/Imputed |
RXVA01X |
Amount paid, Veteran's
Administration (Imputed) |
CP12/CP13/Edited/Imputed |
RXTR01X |
Amount paid, TRICARE
(Imputed) |
CP12/CP13/Edited/Imputed |
RXOF01X |
Amount paid, other Federal
(Imputed) |
CP12/CP13/Edited/Imputed |
RXSL01X |
Amount paid, state and local
government (Imputed) |
CP12/CP13/Edited/Imputed |
RXWC01X |
Amount paid, Worker's
Compensation (Imputed) |
CP12/CP13/Edited/Imputed |
RXOT01X |
Amount paid, other insurance
(Imputed) |
CP12/CP13/Edited/Imputed |
RXOR01X |
Amount paid, other private
(Imputed) |
Constructed/Imputed |
RXOU01X |
Amount paid, other public
(Imputed) |
Constructed/Imputed |
RXXP01X |
Sum of payments RXSF01X -
RXOU01X (Imputed) |
CP12/CP13/Edited/Imputed |
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Weights
Variable |
Description |
Source |
PERWT01F |
Poverty/mortality/nursing
home adjusted person level weight |
Constructed |
VARSTR01 |
Variance estimation stratum,
2001 |
Constructed |
VARPSU01 |
Variance estimation PSU,
2001 |
Constructed |
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Contents
Attachment 1
Definitions of Abbreviations for RXFORM
|
Dosage
Form |
Definition |
|
-7 |
refused |
|
-8 |
don't know |
|
-9 |
not ascertained |
|
ACC |
accessory |
|
ADR |
acetic acid drop |
|
AE |
aerosol |
|
AER |
aerosol |
|
AERO |
aerosol |
|
AEROSOL |
|
|
AMP |
ampule |
|
ARO |
aerosol solid |
|
AUTO INJ |
auto-injection |
|
BACK SUPPORT BELT |
|
|
BAG |
|
|
BAN |
bandage |
|
BANDAGE |
|
|
BATTERY |
|
|
BOT |
bottle |
|
BOTTLE |
|
|
BOX |
|
|
BOXES |
|
|
BUT |
butterfly |
|
C |
capsules , or cream (varies) |
|
C12 |
12 hour extended-release
capsule |
|
C24 |
24 hour extended-release
capsule |
|
CA |
capsule |
|
CANE |
|
|
CAP |
capsule |
|
CAP DR |
delayed-release capsule |
|
CAP ER |
extended-release capsule |
|
CAP SA |
slow-acting capsule |
|
CAPLET |
|
|
CAPLT |
caplet |
|
CAPS |
capsules |
|
CAPSULE |
|
|
CAPSULE SA |
slow-acting capsule |
|
CC |
cubic centimeter |
|
CER |
extended-release capsule |
|
CHEW |
chewable tablet |
|
CHEW TAB |
chewable tablet |
|
CHEW TABS |
chewable tablets |
|
CHEWABLE |
|
|
CHW |
chewable tablets |
|
COMBO |
|
|
COMPOUND |
|
|
CON |
condom |
|
CONDOM |
|
|
CPSR |
slow-release capsule |
|
CR |
cream |
|
CRE |
cream |
|
CREA |
cream |
|
CREAM |
|
|
CRM |
cream |
|
CTB |
chewable tablets |
|
CTG |
cartridge |
|
CUTTER |
|
|
DEV |
device |
|
DEVICE |
|
|
DIA |
diaper |
|
DIAPER |
|
|
DIS |
disk |
|
DISK |
|
|
DOS PAK |
dose pack |
|
DR |
drop |
|
DRE |
dressing |
|
DRESSING |
|
|
DROP |
|
|
DROPS |
|
|
DROPS OPTH OTI |
ophthalmic/otic drops |
|
DROPS SUSP |
drops suspension |
|
DRP |
drop |
|
DRPS |
drops |
|
DSK |
disk |
|
DSPK |
tablets in a dose pack |
|
EAR DROP |
|
|
EAR DROPS |
|
|
EAR SUSP |
ear suspension |
|
EC TABS |
enteric coated tablets |
|
ECC |
enteric coated capsules |
|
ECT |
enteric coated tablets |
|
ELI |
elixir |
|
ELIX |
elixir |
|
ELIXIR |
|
|
ELX |
elixir |
|
EMERGENCY KIT |
|
|
ENEMA |
|
|
ERTA |
extended-release tablets |
|
EXTN CAP |
extended-release capsule |
|
EXTRACT |
|
|
EYE DRO |
eye drop |
|
EYE DROP |
|
|
EYE DROPS |
|
|
EYE SO |
eye solution |
|
FIL |
film |
|
FILM ER |
film, extended-release |
|
FILMTAB |
|
|
FILMTABS |
|
|
FOA |
foam |
|
FOAM |
|
|
GAU |
gauze |
|
GAUZE |
|
|
GEF |
effervescent granules |
|
GEL |
|
|
GFS |
gel-forming solution |
|
GLOVE |
|
|
GRA |
granules |
|
GRR |
grams |
|
GTT |
drops |
|
GUM |
|
|
HOSE |
medical hosiery |
|
HU |
capsule |
|
ICR |
control-release insert |
|
IN |
injectible |
|
INH |
inhalant |
|
INH AER |
inhalant aerosol |
|
INHAL |
inhalant |
|
INHAL SOL |
Inhalant solution |
|
INHALER |
|
|
INHL |
inhalant |
|
INJ |
injectible |
|
INJECTION (S) |
|
|
INSULIN |
|
|
IV |
intravenous |
|
JEL |
jelly |
|
JELLY |
|
|
KIT |
|
|
L |
lotion |
|
LANCET |
|
|
LANCET (S) |
|
|
LI |
liquid |
|
LIQ |
liquid |
|
LIQUID |
|
|
LOT |
lotion |
|
LOTION |
|
|
LOZ |
lozenge |
|
LOZENGE |
|
|
MASK |
|
|
MCG |
microgram |
|
MG |
milligram |
|
MIS |
miscellaneous |
|
MIST |
|
|
MOUTHWASH |
|
|
NAS |
nasal spray |
|
NASAL |
|
|
NASAL INHALER |
|
|
NASAL POCKET HL |
nasal inhaler, pocket |
|
NASAL SOLN |
nasal solution |
|
NASAL SPR |
nasal spray |
|
NASAL SPRAY |
|
|
NDL |
needle |
|
NE |
nebulizer |
|
NEB |
nebulizer |
|
NEBULIZER |
|
|
NMA |
enema |
|
NMO |
nanomole, millimicromole |
|
ODR |
ophthalmic drop (ointment) |
|
ODT |
oral disintegrating tablet |
|
OIL |
|
|
OIN |
ointment |
|
OINT |
ointment |
|
OINT TOP |
topical ointment |
|
OINTMENT |
|
|
ONT |
ointment |
|
OP |
ophthalmic solution |
|
OP DROPS |
ophthalmic drops |
|
OP SOL |
ophthalmic solution |
|
OPH S |
ophthalmic solution or
suspension |
|
OPH SOL |
ophthalmic solution |
|
OPH SOLN |
ophthalmic solution |
|
OPHTH DROP (S) |
ophthalmic drops |
|
OPHTH OINT |
ophthalmic ointment |
|
OPHTH SOLN |
ophthalmic solution |
|
OPT SLN |
ophthalmic solution |
|
OPT SOL |
ophthalmic solution |
|
OPTH |
ophthalmic solution or
suspension or ointment |
|
OPTH S |
ophthalmic solution or
suspension |
|
OPTH SLN |
ophthalmic solution |
|
OPTH SOL |
ophthalmic solution |
|
OPTH SUSP |
ophthalmic suspension |
|
OPTIC |
|
|
ORAL |
|
|
ORAL INHL |
oral inhalant |
|
ORAL PWD |
oral powder |
|
ORAL RINSE |
|
|
ORAL SOL |
oral solution |
|
ORAL SUS |
oral suspension |
|
ORAL SUSP |
oral suspension |
|
OTI |
otic solution |
|
OTIC |
|
|
OTIC SOL |
otic solution |
|
OTIC SOLN |
otic solution |
|
OTIC SUSP |
otic suspension |
|
PA |
tablet pack, pad or patch
(varies) |
|
PAC |
pack |
|
PAD |
|
|
PADS |
|
|
PAK |
pack |
|
PAS |
paste |
|
PAT |
patch |
|
PATCH |
|
|
PCH |
patch |
|
PDR |
powder |
|
PDS |
powder for reconstitution |
|
PEDIATRIC DROPS |
|
|
PI1 |
powder for injection, 1 month |
|
PIH |
powder for inhalation |
|
PKG |
package |
|
PKT |
packet |
|
PLEDGETS |
|
|
PO-SYRUP |
syrup by mouth (oral syrup) |
|
POPSICLE |
|
|
POW |
powder |
|
POWD |
powder |
|
POWDER |
|
|
POWDER/SUSPENS |
powder/suspension |
|
PRO |
prophylactic |
|
PULVULE |
|
|
PWD |
powder |
|
PWD F/SOL |
powder for solution |
|
RCTL SUPP |
rectal suppository |
|
RECTAL CREAM |
|
|
REDITABS |
|
|
ROLL |
|
|
S |
syrup, suspension, solution
(varies) |
|
SA CAPS |
slow-acting capsules |
|
SA TAB |
slow-acting tablet |
|
SA TABLETS |
slow-acting tablets |
|
SA TABS |
slow-acting tablets |
|
SAL |
salve |
|
SER |
extended-release suspension |
|
SGL |
soft B23gel cap |
|
SHA |
shampoo |
|
SHAM |
shampoo |
|
SHMP |
shampoo |
|
SHOE |
|
|
SLT |
sublingual tablet |
|
SL TAB |
sublingual tablet |
|
SO |
solution |
|
SOL |
solution |
|
SOLN |
solution |
|
SOLUTION |
|
|
SP |
spray |
|
SPONGE |
|
|
SPR |
spray |
|
SPRAY |
|
|
SRN |
syringe |
|
STP |
strip |
|
STR |
strip |
|
STRIP |
|
|
STRIPS |
|
|
SU |
suspension, solution,
suppository, powder, or
granules
for reconstitution
(varies) |
|
SUB |
sublingual |
|
SUP |
suppository |
|
SUPP |
suppository |
|
SUPPOSITORIES |
|
|
SUPPOSITORY |
|
|
SUS |
suspension |
|
SUS/LIQ |
suspension/liquid |
|
SUSP |
suspension |
|
SUSPEN |
suspension |
|
SUSPENDED RELEASE
CAPLET |
|
|
SUSPENSION |
|
|
SWA |
swab |
|
SWAB |
|
|
SWABS |
|
|
SYP |
syrup |
|
SYR |
syrup |
|
SYRINGE |
|
|
SYRP |
syrup |
|
SYRUP |
|
|
T |
tablet |
|
T12 |
12 hour extended-release
tablet |
|
T24 |
24 hour extended-release
tablet |
|
TA |
tablet |
|
TAB |
tablet |
|
TAB CHEW |
chewable tablet |
|
TAB DR |
delayed-release tablet |
|
TAB EC |
enteric coated tablet |
|
TAB SL |
slow-acting tablet |
|
TABL |
tablet |
|
TABLET (S) |
|
|
TABLETS (S) |
|
|
TABS |
tablets |
|
TAP |
tape |
|
TAPE |
|
|
TB |
tablet |
|
TBCH |
chewable tablet |
|
TBSL |
sublingual tablet |
|
TBSR |
slow-release tablet |
|
TCP |
tablet, coated particles |
|
TDM |
extended-release film |
|
TEF |
effervescent tablet |
|
TER |
extended-release tablet |
|
TES |
test |
|
TEST |
|
|
TEST STRIP |
|
|
TEST STRIPS |
|
|
TIN |
tincture |
|
TOP CREAM |
topical cream |
|
TOP OINT |
topical ointment |
|
TOP SOL |
topical solution |
|
TOP SOLN |
topical solution |
|
TOPICAL CREAM |
|
|
TOPICAL SOLUTION |
|
|
TRO |
troche |
|
TUB |
tube |
|
TUBE |
|
|
UNIT DOSE |
|
|
UNT |
unit |
|
VAGINAL CREAM |
|
|
VIAL |
|
|
VIAL (S) |
|
|
VIL |
vial |
|
WAF |
wafer |
|
WALKER |
|
|
WIPES |
|
|
Z-PAK |
|
Return To Table Of
Contents
Attachment 2
Definitions of Codes and Abbreviations for RXFRMUNT
|
Code |
Description |
|
-8 |
don't know |
|
-9 |
not ascertained |
|
CC |
cubic centimeters |
|
GM |
grams |
|
L |
liters |
|
ML |
milliliters |
|
OZ |
ounces |
Return To Table Of
Contents
Attachment 3
Definitions of Abbreviations, Codes and Symbols for
RXSTRUNT
|
Abbreviations,
Codes and Symbols |
Definition |
|
-7 |
refused |
|
-8 |
don't know |
|
-9 |
not ascertained |
|
% |
percent |
|
09 |
compound |
|
CC |
cubic centimeters |
|
DRP |
drop |
|
G |
gram |
|
GM |
gram |
|
GR |
grain |
|
HR or HRS |
hour, hours |
|
INH |
inhalation |
|
IU |
international unit |
|
MCG |
microgram |
|
MEQ |
microequivalent |
|
MG |
milligram |
|
ML |
milliliter |
|
MU |
million units |
|
SQ CM |
square centimeter |
|
U |
units |
Return To Table Of Contents
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