MEPS HC-051A: 2000 Prescribed Medicines
April 2003
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 Codebook Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Naming
2.4.1 General
2.4.2 Expenditure and Source of Payment
Variables
2.5 Data Collection
2.5.1 Methodology for Collecting Household
Reported Variables
2.5.2 Methodology for Collecting Pharmacy
Reported Variables
2.6 File Contents
2.6.1 Survey Administration Variables
2.6.1.1 Person Identifier Variables
(DUID, PID, DUPERSID)
2.6.1.2 Record Identifier Variables
(RXRECIDX, LINKIDX)
2.6.1.3 Round Variable
(PURCHRD)2.6.2 Characteristics of Prescribed Medicine
Events
2.6.2.1 Date When Prescribed Medicine
Was First Taken (RXBEGDD-RXBEGYR)
2.6.2.2 Prescribed Medicine Attributes
(RXNAME-RXSTRUNT)
2.6.2.3 Type of Pharmacy
(PHARTP1-PHARTP7)
2.6.2.4 Analytic Flag Variables
(RXFLG-DIABFLG)
2.6.2.5 The Sample Variable (SAMPLE)
2.6.2.6 Condition Codes
(RXICD1X-RXICD3X) and Clinical Classification Codes
(RXCCC1X-RXCCC3X)
2.6.3 Expenditure Variables (RXSF00X-RXXP00X)
2.6.3.1 Definition of Expenditures
2.6.3.2 Sources of Payment
2.6.4 Sample Weight (PERWT00F)
2.6.4.1 Overview
2.6.4.2 Details on Person Weights
Construction
2.6.4.3 MEPS Panel 4 Weight
2.6.4.4 MEPS Panel 5 Weight
2.6.4.5 The Final Weight for 2000
2.6.4.6 Coverage
3.0 General Data Editing and Imputation
Methodology
3.1 Rounding
3.2 Edited/Imputed Expenditure Variables
(RXSF00X-RXXP00X)
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 2000 Conditions File and/or the
Other 2000 MEPS Event Files to the 2000 Prescribed Medicines File
5.3 Limitations/Caveats of RXLK and CLNK
References
D. Variable-Source Crosswalk
Attachment 1: Definitions of Abbreviations for RXFORM
Attachment 2: Definitions of Codes and Abbreviations
for RXFRMUNT
Attachment 3: Definitions
of Abbreviations, Codes and Symbols for RXSTRUNT
A. Data
Use Agreement
Individual identifiers have been removed from the
microdata contained in the files on this CD-ROM. 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.
Return to Table of Contents
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 drawn- and 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.
Return to Table of Contents
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.
Return to Table of Contents
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 Web site.
Return to Table of Contents
C. Technical
Information
1.0
General Information
This documentation describes one in a series of public use
event files from the 2000 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 2000. As illustrated below, this file consists of MEPS survey data
obtained in the 2000 portion of Round 3 and Rounds 4 and 5 for Panel 4, as well
as Rounds 1, 2, and the 2000 portion of Round 3 for Panel 5 of the MEPS HC
(i.e., the rounds for MEPS panels covering calendar year 2000).
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 2000
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 2000 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>.
Return to Table of Contents
2.0
Data File Information
This public use data set contains 182,677 prescribed
medicine records. Each record represents one household reported prescribed
medicine that was purchased or obtained during calendar year 2000. Of the
182,677 prescribed medicine records, 179,417 records are associated with persons
having a positive person level weight (PERWT00F). The persons represented on
this file had to meet either criterion a or b below:
a) Be classified as a key inscope person who
responded for his or her entire period of 2000 eligibility (i.e., persons
with a positive 2000 full-year person level sampling weight (PERWT00F >
0)), or
b) 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 2000 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 2000
eligibility, and at least one family member has a positive 2000 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 2000
full-year MEPS family level weight (FAMWT00F >0)).
Please refer to Attachment 1 for definitions of key,
non-key, inscope and eligible. Persons with no prescribed medicine use for 2000
are not included on this file (but are represented on MEPS person level files).
A codebook for the data file is provided (in file H51ACB.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 2000 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 2.6.2.5)
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 2000 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
2000 Medical Conditions File and additional MEPS 2000 event files. Please see
the 2000 Appendix File for details on how to link MEPS data files.
Panel 4 cases (PANEL00=4 on the 2000 person-level file)
can be linked back to the 1999 MEPS HC Public Use Data Files. However, the user
should be aware, at this time, no weight is being provided to facilitate 2-year
analysis of Panel 4 data.
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2.1
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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2.2
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. 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://meps.ahrq.gov/survey_comp/survey.jsp
and clicking on the link in the Prescribed Medicines box.
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2.3 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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2.4
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."
2.4.1
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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2.4.2
Expenditure and Source 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 |
XP - sum
of payments |
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 |
|
The fifth and sixth characters indicate the year (00). All
imputed/edited expenditure variables end with an "X."
For example, RXSF00X is the edited/imputed amount paid by
self or family for the 2000 prescribed medicine expenditure.
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2.5
Data Collection
Data regarding prescription drugs were obtained through
the HC questionnaire and a pharmacy follow-back component (within the
Medical Provider Component).
2.5.1
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 not collected in the pharmacy
follow-back component (unless the purchase was an insulin or diabetic
supply/equipment event; 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 2000 and 2001 based on the number of times
the respondent said the drug was purchased in 2000, 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 to 2000 instead of 2001.
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2.5.2
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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2.6
File Contents
2.6.1
Survey Administration Variables
2.6.1.1
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 2000 Full
Year Population Characteristics File.
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2.6.1.2
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 2000 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 (00364021802), 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 |
00364021802 |
00002026 |
000020260083002 |
000020260083 |
00364021802 |
00002026 |
000020260083003 |
000020260083 |
00364021802 |
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2.6.1.3
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 4. Similarly, Rounds 1, 2, and 3 are associated with data collected from
Panel 5.
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2.6.2
Characteristics of Prescribed Medicine Events
2.6.2.1
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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2.6.2.2
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:
-
Medication name - pharmacy reported (RXNAME)
-
Medication name - household reported (RXHHNAME)
-
National drug code (RXNDC)
-
Quantity of the prescribed medicine dispensed (RXQUANTY);
e.g., number of tablets in the prescription
-
Form of the prescribed medicine (RXFORM);
e.g., powder
-
Unit of measurement for form of Rx/prescribed
medicine (RXFRMUNT); e.g., oz
-
Strength of the dose of the medicine prescribed (RXSTRENG);
e.g., 10
-
Unit of measurement for the strength of the dose
of the prescribed medication (RXSTRUNT); e.g., gm (In previous PUFs, this
variable was named RXUNIT. The name was changed to make the name more
consistent with the variable meaning.)
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 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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2.6.2.3
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, and (4)
drug store. A -1 value for PHARTPn indicates that the household did not report
an "nth" pharmacy.
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2.6.2.4 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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2.6.2.5
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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2.6.2.6
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 2000 Medical Conditions File. Details on how
to link to the MEPS 2000 Medical Conditions File are provided in the 2000
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 2000 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 2000 Medical Conditions File. For frequencies of conditions
by event type, please see the 2000 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 2000 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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2.6.3 Expenditure
Variables (RXSF00X-RXXP00X)
2.6.3.1
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)
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2.6.3.2
Sources of Payment
In addition to total expenditures, variables are provided
which itemize expenditures according to major source of payment categories.
These categories are:
-
Out of pocket by user or family
-
Medicare
-
Medicaid
-
Private Insurance
-
Veteran's Administration
-
TRICARE
-
Other Federal sources - includes Indian Health
Service, Military Treatment Facilities, and other care by the Federal
government
-
Other State and Local Source - includes community
and neighborhood clinics, State and local health departments, and State
programs other than Medicaid
-
Worker's Compensation
-
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:
-
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
-
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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2.6.4 Sample Weight (PERWT00F)
2.6.4.1
Overview
There
is a single full year person-level weight (PERWT00F) 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 2000. 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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2.6.4.2
Details on Person Weights Construction
The person-level weight PERWT00F was developed in several
stages. Person level weights for Panels 4 and 5 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 2000 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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2.6.4.3
MEPS Panel 4 Weight
The person level weight for MEPS Panel 4 was developed
using the 1999 full year weight for an individual as a "base" weight
for survey participants present in 1999. For key, in-scope respondents who
joined a RU some time in 2000 after being out of scope in 1999, the 1999 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
2000. These control figures were derived by scaling back the population totals
obtained from the March 2000 CPS to reflect the December, 2000 CPS estimated
population distribution across age and sex categories as of December, 2000.
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, 2000 is 275,158,755. Key,
responding persons not in-scope on December 31, 2000 but in-scope earlier in the
year retained, as their final Panel 4 weight, the weight after the nonresponse
adjustment.
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2.6.4.4 MEPS Panel 5 Weight
The person level weight for MEPS Panel 5 was developed
using the MEPS Round 1 person-level weight as a "base" weight. For
key, in-scope respondents who joined a 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 2000 portion of Round 3 as well
as poststratification to the same population control figures for December 2000
used for the MEPS Panel 4 weights. The same five variables employed for Panel 4
poststratification (census region, MSA status, race/ethnicity, sex, and age)
were used for Panel 5 poststratification. Similarly, for Panel 5, key,
responding persons not in-scope on December 31, 2000 but in-scope earlier in the
year retained, as their final Panel 5 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 2000 CPS data base.
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2.6.4.5
The Final Weight for 2000
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, 2000 is 275,158,755 (PERWT00F>0 and INSC1231=1). The weights
of some persons out-of-scope on December 31, 2000 were also poststratified.
Specifically, the weights of persons out-of-scope on December 31, 2000 who were
inscope 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 inscope
during 2000 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 population.
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2.6.4.6
Coverage
The target population for MEPS in this file is the 2000
U.S. civilian, noninstitutionalized population. However, the MEPS sampled
households are a subsample of the NHIS households interviewed in 1998 (Panel 4)
and 1999 (Panel 5). New households created after the NHIS interviews for the
respective Panels and consisting exclusively of persons who entered the target
population after 1998 (Panel 4) or after 1999 (Panel 5) are not covered by MEPS.
Neither is 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 proportion 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 2000 Prescribed Medicines
file have been rounded to the nearest penny. Person level expenditure variables
released on the 2000 Full Year Consolidated Data File were rounded to the
nearest dollar. It should be noted that using the 2000 MEPS event files to
create person level totals will yield slightly different totals than those found
on the 2000 Full Year Consolidated Data File. These differences are due to
rounding only. Moreover, in some instances, the number of persons having
expenditures on the 2000 event files for a particular source of payment may
differ from the number of persons with expenditures on the 2000 Full Year
Consolidated Data File for that source of payment. This difference is also an
artifact of rounding only. Please see the 2000 Appendix File for details on such
rounding differences.
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3.2
Edited/Imputed Expenditure Variables (RXSF00X-RXXP00X)
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 (RXXP00X) 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 (RXSF00X), amount paid by Medicare (RXMR00X),
amount paid by Medicaid (RXMD00X), amount paid by private insurance (RXPV00X),
amount paid by the Veterans Administration (RXVA00X), amount paid by TRICARE
(RXTR00X), amount paid by other federal sources (RXOF00X), amount paid by state
and local (non-federal) government sources (RXSL00X), amount paid by Worker's
Compensation (RXWC00X), and amount paid by some other source of insurance
(RXOT00X). As mentioned previously, there are two additional expenditure
variables called RXOR00X and RXOU00X (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 2.6.3 for details on these and all other source
of payment variables.
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4.0 Strategies for Estimation
This file is constructed for efficient estimation of
utilization, expenditure, and sources of payment for outpatient prescribed
medicines and to allow for estimates of number of persons with prescribed
medicine purchases during 2000.
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, Expenditure
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
(PERWT00F) 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 2000 is
estimated as the sum of the weight (PERWT00F) across all prescribed medicines
event records. That is,
Sum of Wj = 2,166,933,732 for all records
(1)
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,
(Sum of WjXj)/(Sum of Wj) = $21.92
(2)
where
Sum of Wj = 2,166,933,732 and Xj =
RXSF00Xj
for all prescription records with RXXP00Xj >
0
This gives $21.92 as the estimated mean amount of
out-of-pocket payment of expenditures associated with prescribed medicines
events and 2,166,933,732 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 2000.
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,
(Sum of WjYj)/(Sum of Wj) = 0.2633
(3)
where
Sum of Wj = 2,166,933,732 and Yj =
RXPV00Xj /RXXP00j for all prescription records with RXXP00Xj >
0
This gives 0.2633 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 2000.
1In this and all other examples, unless otherwise noted, prescribed medicines records include
diabetic supplies\equipment and insulin.
Return to Table of Contents
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 2000 with an RXNDC = "00093310905" (Amoxicillin),
this event file must be used. This would be estimated as
Sum of Wi Xi across all unique persons i
on this file
(4)
where
Wi is the sampling weight (PERWT00F)for person i
and
Xi = 1 if RXNDC = '00093310905" for any
purchase of person i.
= 0 otherwise
Return to Table of 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,
(Sum of WiZi)/(Sum of Wi) across
all unique persons i on this file (5)
where
Wi is the sampling weight (PERWT00F)for person i
and
Zi = Sum of RXXP00Xj across all
prescription purchases for person i.
Return to Table of Contents
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 2000, 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,
(Sum of WiZi)/(Sum of Wi) across
all unique persons i on the MEPS HC-050 file (6)
where
Wi is the sampling weight (PERWT00F)for person i
and
Zi = 1 if RXNDCj =
"00093310905" for any event of person i.
= 0 otherwise.
Return to Table of 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.
Return to Table of Contents
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 2000 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 VARSTR00
and VARPSU00, 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 VARSTR00 and
VARPSU00 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 $0.4237 and
0.0074 for the estimated mean of out-of-pocket payment and the estimated mean
proportion of total expenditures paid by private insurance respectively.
Return to Table of Contents
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
2000 prescribed medicines file with other 2000 MEPS public use files, including
a 2000 person level file, the 2000 conditions file, and the other 2000 event
files.
5.1
Linking a Person Level File to the Prescribed Medicines File
Merging characteristics of interest from other 2000 MEPS
files (e.g., the 2000 Full Year Consolidated File or the 2000 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 2000
Appendix File provides additional details on how to merge 2000 MEPS data files.
-
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.
-
Create data set PMEDS by sorting the prescribed
medicines file by person identifier, DUPERSID.
-
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 AGE SEX EDUC)
OUT=PERSX;
BY DUPERSID;
RUN;
PROC SORT DATA= HC051A OUT=PMEDS;
BY DUPERSID;
RUN;
DATA NEWPMEDS;
MERGE PMEDS (IN=A) PERSX(IN=B);
BY DUPERSID;
IF A;
RUN;
Return to Table of Contents
5.2
Linking the 2000 Conditions File and/or the Other 2000 MEPS Event Files to
the 2000 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 2000 Appendix File.
5.3
Limitations/Caveats of RXLK and CLNK
The RXLK file provides a link between the 2000 prescribed
medicine records and the other 2000 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 2000 Medical
Conditions File and the 2000 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.
Return to Table of Contents
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.
Return to Table of Contents
D. Variable-Source
Crosswalk
MEPS
HC-051A: 2000 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 |
Return to Table of Contents
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 |
RXSF00X |
Amount paid, self or family (Imputed) |
CP11/Edited/Imputed |
RXMR00X |
Amount paid, Medicare (Imputed) |
CP12/CP13/Edited/Imputed |
RXMD00X |
Amount paid, Medicaid (Imputed) |
CP12/CP13/Edited/Imputed |
RXPV00X |
Amount paid, private insurance (Imputed) |
CP12/CP13/Edited/Imputed |
RXVA00X |
Amount paid, Veteran's Administration (Imputed) |
CP12/CP13/Edited/Imputed |
RXTR00X |
Amount paid, TRICARE (Imputed) |
CP12/CP13/Edited/Imputed |
RXOF00X |
Amount paid, other Federal (Imputed) |
CP12/CP13/Edited/Imputed |
RXSL00X |
Amount paid, state and local government (Imputed) |
CP12/CP13/Edited/Imputed |
RXWC00X |
Amount paid, Worker's Compensation (Imputed) |
CP12/CP13/Edited/Imputed |
RXOT00X |
Amount paid, other insurance (Imputed) |
CP12/CP13/Edited/Imputed |
RXOR00X |
Amount paid, other private (Imputed) |
Constructed/Imputed |
RXOU00X |
Amount paid, other public (Imputed) |
Constructed/Imputed |
RXXP00X |
Sum of payments RXSF00X - RXOU00X (Imputed) |
CP12/CP13/Edited/Imputed |
Weights
Variable |
Description |
Source |
PERWT00F |
Poverty/mortality/nursing home adjusted person level
weight |
Constructed |
VARSTR00 |
Variance estimation stratum, 2000 |
Constructed |
VARPSU00 |
Variance estimation PSU, 2000 |
Constructed |
Return to Table of Contents
Attachment 1
Definitions of Abbreviations for RXFORM
Dosage Form |
Definition |
-9 |
NOT ASCERTAINED |
-8 |
don't know |
-7 |
refused |
ACC |
accessory |
AE |
AEROSOL |
AER |
aerosol |
AERO |
aerosol |
AEROSOL |
|
AMP |
ampule |
ARO |
aerosol solid |
AUTO INJ |
auto-injection |
BAG |
|
BAN |
bandage |
BANDAGE |
|
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 |
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 |
|
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 |
|
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) |
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 |
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 |
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 |
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 |
-9 |
not ascertained |
-8 |
don't know |
-7 |
refused |
% |
percent |
09 |
compound |
CC |
cubic centimeters |
G |
gram |
GM |
gram |
GR |
grain |
HR or HRS |
hour, hours |
INH |
inhalation |
IU |
international unit |
MCG |
microgram |
MEQ |
microequivalent |
MG |
milligram |
ML |
milliliter |
SQ CM |
square centimeter |
U |
units |
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