MEPS HC-135I: Appendix to MEPS 2010 Event Files HC-135A - HC-135H 
September 2012 
Agency for Healthcare Research and Quality 
Center for Financing, Access, and Cost Trends 
540 Gaither Road 
Rockville, MD 20850 
(301) 427-1406
 
Table of Contents 
A. Data Use Agreement 
B. Background 
1.0 Household Component 
2.0 Medical Provider Component 
3.0 Survey Management and Data Collection 
C. Technical and Programming Information 
1.0 General Information 
2.0 Data File Information 
2.1 Codebook Format 
2.2 Variable Naming and Source 
2.3 Contents of File 1: Condition-Event Link File (CLNK) 
2.4 Contents of File 2: Prescribed Medicines-Event Link File (RXLK) 
2.5 2010 Condition-Event Frequency Table 
3.0 Merging/Linking MEPS Data Files 
3.1 Example A: Using the CLNK (HC-135IF1) and RXLK (HC-135IF2) Files with the Medical Conditions File (HC-137), 
the Prescribed Medicines and Office-Based Medical Provider Visits Event Files (HC-135A and HC-135G) 
3.2 Example B: Using the CLNK File (HC-135IF1) with the Medical Conditions File 
(HC-137) and the Prescribed Medicines Event File (HC-135A) 
3.3 Example C: Using the CLNK File with the Medical Conditions File (HC-137) and Office-Based Medical Provider Visits Event File (HC-135G) 
3.4 Limitations/Caveats of the CLNK File 
3.5 Limitations/Caveats of the RXLK File 
3.6 National Health Interview Survey 
3.7 Using MEPS Data for Trend Analysis 
3.8 Longitudinal Analysis 
Attachment 1: Clinical Classification Code to ICD-9-CM Code Crosswalk 
Attachment 2: Sample SAS Jobs for Linking Example 
A. Data Use Agreement 
Individual identifiers have been removed from the 
micro-data contained in these files. Nevertheless, under sections 308 (d) and 
903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1), 
data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or 
the National Center for Health Statistics (NCHS) may not be used for any purpose 
other than for the purpose for which they were supplied; any effort to determine 
the identity of any reported cases is prohibited by law. 
Therefore in accordance with the above referenced 
Federal Statute, it is understood that: 
	- No one is to use the data in this data set in any way except 
	for statistical reporting and analysis; and
 
  
	- If the identity of any person or establishment should be 
	discovered inadvertently, then (a) no use will be made of this 
	knowledge, (b) the Director Office of Management AHRQ will be 
	advised of this incident, (c) the information that would 
	identify any individual or establishment will be safeguarded or 
	destroyed, as requested by AHRQ, and (d) no one else will be 
	informed of the discovered identity; and
 
  
	- No one will attempt to link this data set with individually 
	identifiable records from any data sets other than the Medical 
	Expenditure Panel Survey or the National Health Interview 
	Survey.
 
 
By using these data you signify your agreement to 
comply with the above stated statutorily based requirements with the knowledge 
that deliberately making a false statement in any matter within the jurisdiction 
of any department or agency of the Federal Government violates Title 18 part 1 
Chapter 47 Section 1001 and is punishable by a fine of up to $10,000 or up to 5 
years in prison. 
The Agency for Healthcare Research and Quality 
requests that users cite AHRQ and the Medical Expenditure Panel Survey as the 
data source in any publications or research based upon these data.  
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B. Background 
1.0 Household Component 
The Medical Expenditure Panel Survey (MEPS) provides 
nationally representative estimates of health care use, expenditures, sources of 
payment, and health insurance coverage for the U.S. civilian 
non-institutionalized population. The MEPS Household Component (HC) also 
provides estimates of respondents’ health status, demographic and socio-economic 
characteristics, employment, access to care, and satisfaction with health care. 
Estimates can be produced for individuals, families, and selected population 
subgroups. The panel design of the survey, which includes 5 Rounds of interviews 
covering 2 full calendar years, provides data for examining person level changes 
in selected variables such as expenditures, health insurance coverage, and 
health status. Using computer assisted personal interviewing (CAPI) technology, 
information about each household member is collected, and the survey builds on 
this information from interview to interview. All data for a sampled household 
are reported by a single household respondent. 
The MEPS-HC was initiated in 1996. Each year a new 
panel of sample households is selected. Because the data collected are 
comparable to those from earlier medical expenditure surveys conducted in 1977 
and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample 
size is about 15,000 households. Data can be analyzed at either the person or 
event level. Data must be weighted to produce national 
estimates.  
The set of households selected for each panel of the 
MEPS HC is a subsample of households participating in the previous year’s 
National Health Interview Survey (NHIS) conducted by the National Center for 
Health Statistics. The NHIS sampling frame provides a nationally representative 
sample of the U.S. civilian non-institutionalized population and reflects an 
oversample of blacks and Hispanics. In 2006, the NHIS implemented a new sample 
design, which included Asian persons in addition to households with black and 
Hispanic persons in the oversampling of minority populations. MEPS further 
oversamples additional policy relevant sub-groups such as low income households. 
The linkage of the MEPS to the previous year’s NHIS provides additional data for 
longitudinal analytic purposes. 
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2.0 Medical Provider Component 
Upon completion of the household CAPI interview and 
obtaining permission from the household survey respondents, a sample of medical 
providers are contacted by telephone to obtain information that household 
respondents can not accurately provide. This part of the MEPS is called the 
Medical Provider Component (MPC) and information is collected on dates of visit, 
diagnosis and procedure codes, charges and payments. The Pharmacy Component 
(PC), a subcomponent of the MPC, does not collect charges or diagnosis and 
procedure codes but does collect drug detail information, including National 
Drug Code (NDC) and medicine name, as well as date filled and sources and 
amounts of payment. The MPC is not designed to yield national estimates. It is 
primarily used as an imputation source to supplement/replace household reported 
expenditure information. 
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3.0 Survey Management and Data Collection 
MEPS HC and MPC data are collected under the authority 
of the Public Health Service Act. Data are collected under contract with Westat, 
Inc. (MEPS HC) and Research Triangle Institute (MEPS MPC). Data sets and summary 
statistics are edited and published in accordance with the confidentiality 
provisions of the Public Health Service Act and the Privacy Act. The National 
Center for Health statistics (NCHS) provides consultation and technical 
assistance. 
As soon as data collection and editing are completed, 
the MEPS survey data are released to the public in staged releases of summary 
reports, micro data files, and tables via the MEPS Web site: 
meps.ahrq.gov. 
Selected data can be analyzed through MEPSnet, an on-line interactive tool 
designed to give data users the capability to statistically analyze MEPS data in 
a menu-driven environment.  
Additional information on MEPS is available from the 
MEPS project manager or the MEPS public use data manager at the Center for 
Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality, 
540 Gaither Road, Rockville, MD 20850 (301-427-1406). 
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C. Technical and Programming Information 
1.0 General Information 
This documentation describes the MEPS Public Use 
Release HC-135I, which is the Appendix to MEPS releases HC-135A through HC-135H. 
This release contains two data files, both of which are provided in ASCII (with 
related SAS, SPSS, and Stata programming statements and data user 
information) and SAS versions: 1) the condition-event link file; and 2) the 
prescribed medicines-event link file. Also included in this release is a PDF 
file of the condition-event frequency table. Note that, as of 2008, Table 2, a 
utilization and expenditures summary table, is no longer available. 
This documentation offers a brief overview of the 
content and structure of the files and the accompanying codebook. It contains 
the following sections: 
	Data File Information 
	Merging/Linking MEPS Data Files 
	Crosswalk of Clinical Classification Codes to ICD-9-CM Codes 
	Sample SAS Jobs for Linking 
 
For more information on MEPS HC survey design see T. 
Ezzati-Rice, et al., 1998-2007 and S. Cohen, 1996. For information on the MEPS 
MPC design, see S. Cohen, 1998. These reports, along with a copy of the survey 
instruments used to collect the information on this file, are available on the 
MEPS Web site at the following address: 
meps.ahrq.gov. 
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2.0 Data File Information 
This public use data set consists of two data files 
containing variables for linkage of the MEPS 2010 event-level data files. File 
1, the H135IF1 or CLNK file, is used for linking the MEPS conditions file with 
the MEPS event files; File 2, the H135IF2 or RXLK file, is used for linking the 
MEPS prescribed medicines event file with other MEPS event files. 
The CLNK file contains 6 variables and has a logical 
record length of 59 with an additional 2-byte carriage return/line feed at the 
end of each record. The RXLK file contains 6 variables and has a logical record 
length of 59 with an additional 2-byte carriage return/line feed at the end of 
each record.  
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2.1 Codebook Format 
Each codebook describes an ASCII data set and provides 
the following programming identifiers for each variable: 
	
		| Identifier | 
		Description | 
	 
	
		| Name  | 
		Variable name (maximum of 8 characters) | 
	 
	
		| Description | 
		Variable descriptor (maximum 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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2.2 Variable Naming and Source 
In general, variable names reflect the content of the 
variable, with an 8 character limitation. All variables contained on Files 1 and 
2 were derived from the CAPI.  
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2.3 Contents of File 1: Condition-Event Link File (CLNK) 
File 1 (H135IF1) or the CLNK file, contains the 
variables needed to link each record on the MEPS 2010 conditions file, HC-137, 
with one or more records on the MEPS 2010 event files, HC-135A through HC-135H. 
Section 3.0 contains additional information on completing this linkage.  
The 8-character variable DUPERSID uniquely identifies 
each person represented on the file. There may be more than one record on the 
CLNK file for a specific DUPERSID value.  
CONDIDX is the ID that uniquely identifies each 
condition for a person and corresponds to a unique record on the MEPS 2010 
Conditions file, HC-137. There may be more than one record on the CLNK file for 
a specific CONDIDX value. 
EVNTIDX is the 12-digit number that uniquely 
identifies each event for a person and corresponds to a unique record on one of 
the MEPS 2010 event files, HC-135B through HC-135H. (EVNTIDX is not included on 
the 2010 Prescribed Medicines event file, HC-135A; rather, on this file the 
variable for linking with EVNTIDX on the CLNK file is LINKIDX.) There may be 
more than one record on the CLNK file for a specific EVNTIDX value.  
CLNKIDX is the 24-digit number that uniquely 
identifies each record on the CLNK file and is the combination of CONDIDX + 
EVNTIDX. There is just one record on this file for each value of CLNKIDX, i.e., 
each unique combination of CONDIDX + EVNTIDX. 
The variable EVENTYPE indicates the type of event 
record identified by EVNTIDX, and has the following values: 
	1 = MVIS – office-based medical provider visit event 
	contained on MEPS release HC-135G 
	2 = OPAT – outpatient department visit event contained 
	on MEPS release HC-135F 
	3 = EROM – emergency room visit event contained on 
	MEPS release HC-135E 
	4 = STAZ – inpatient hospital stay event contained on 
	MEPS release HC-135D 
	7 = HVIS – home health visit event contained on MEPS 
	release HC-135H 
	8 = PMED – prescribed medicines event contained on 
	MEPS release HC-135A 
 
PANEL is a constructed variable used to specify the 
panel number for the interview in which the condition was reported. PANEL will 
indicate either Panel 14 or Panel 15. 
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2.4 Contents of File 2: Prescribed Medicines-Event 
Link File (RXLK) 
File 2 (H135IF2) or the RXLK file, contains the 
variables needed to link each record on the MEPS 2010 Prescribed Medicines file, 
HC-135A, with one or more records on the MEPS 2010 event files, HC-135B and 
HC-135D through HC-135G. Section 3.0 contains additional information on 
completing this linkage.  
The 8-character variable DUPERSID uniquely identifies 
each person represented on the file. There may be more than one record on the 
RXLK file for a specific DUPERSID value.  
EVNTIDX is the 12-digit number that uniquely 
identifies each event for a person and corresponds to a unique record on one of 
the MEPS 2010 event files, HC-135B through HC-135G. There may be more than one 
record on the RXLK file for a specific EVNTIDX value. 
LINKIDX is the 12-digit number that identifies the 
record(s) on the prescribed medicines file, HC-135A which link to an event 
record. There may be more than one record on the RXLK file for a specific 
LINKIDX value, and there may be more than one record on the HC-135A file for a 
specific LINKIDX value. 
RXLKIDX is the 24-digit number that uniquely 
identifies each record on the RXLK file, and is the combination of EVNTIDX + 
LINKIDX. There is just one record on this file for each value of RXLKIDX, i.e., 
each unique combination of EVNTIDX + LINKIDX. 
The variable EVENTYPE indicates the type of event 
record identified by EVNTIDX, and has the following values: 
	1 = MVIS – office-based medical provider visit event 
	contained on MEPS release HC-135G 
	2 = OPAT – outpatient department visit event contained 
	on MEPS release HC-135F 
	3 = EROM – emergency room visit event contained on 
	MEPS release HC-135E 
	4 = STAZ – inpatient hospital stay event contained on 
	MEPS release HC-135D 
	5 = DVIS – dental visit event contained on MEPS 
	release HC-135B 
 
For 1996-2004, records for purchases of insulin and 
diabetic supplies in a round were included in the Other Medical Expenses event 
files. Beginning with the 2005 file, these records are not included in 
the Other Medical Expenses file because the expenditures have always been 
included in the Prescribed Medicines file. As a consequence, there are no 
records in this file where the variable EVENTYPE = 6, the value used in 
1996-2004 to identify OMED type of event record.  
PANEL is a constructed variable used to specify the 
panel number for the interview in which the condition was reported. PANEL will 
indicate either Panel 14 or Panel 15. 
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2.5 2010 Condition-Event Frequency Table 
Table 1 contains the MEPS 2010 Condition-Event 
Frequency table. This table contains unweighted and weighted counts of records 
on the MEPS 2010 event files, HC-135A through HC-135H, for each of the 
condition, procedure, and clinical classification codes contained on the MEPS 
2010 Conditions file, HC-137. Attachment 1 contains a crosswalk of the clinical 
classification codes to ICD-9-CM codes.  
Analysts should use the clinical classification codes 
listed in the Conditions PUF document (HC-137) and the Appendix to the Event 
Files (HC-135I) document when analyzing MEPS conditions data. Although there is 
a list of clinical classification codes and labels on the Healthcare Cost and 
Utilization Project (HCUP) Web site, if updates to these codes and/or labels are 
made on the HCUP Web site after the release of the 2010 MEPS PUFs, these updates 
will not be reflected in the 2010 MEPS data. 
Note that, for conditions related to certain medical 
events, the ICD-9-CM codes on the Conditions file are also released in the 
Prescribed Medicines, Emergency Room Visits, Office-based Medical Provider 
Visits, Outpatient Department Visits, and Inpatient Hospital Stays Event Files. 
ICD-9-CM codes are collapsed into broader codes to ensure confidentiality. 
Because of this collapsing, it is possible for there to be duplicate ICD-9-CM 
condition or procedure codes linked to a single medical event when different 
fully-specified codes are collapsed into the same code. For more information on 
ICD-9-CM codes, see the HC-137 documentation.  
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3.0 Merging/Linking MEPS Data Files 
This section provides information on using each of the 
two HC-135I files, RXLK and CLNK, to link with the files contained in MEPS 
releases HC-137 and HC-135A through HC-135H. The linking procedure is described 
using several examples of deriving MEPS-based estimates. Also included in this 
section are several caveats related to using the RXLK and CLNK files.  
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3.1 Example A: Using the CLNK (HC-135IF1) and RXLK 
(HC-135IF2) Files with the Medical Conditions File (HC-137), the Prescribed 
Medicines and Office-Based Medical Provider Visits Event Files (HC-135A and 
HC-135G) 
This example calculates the total expenditures for 
prescribed medicines associated with office-based medical provider visits for 
asthma, using these files: the Conditions file (HC-137), the CLNK file 
(HC-135IF1), the office-based medical provider visit event file (HC-135G), the 
RXLK file (HC-135IF2), and the prescribed medicines event file (HC-135A). It 
includes the following major steps: 
	- From HC-137 file, select only records with condition coded 
	as asthma.
 
  
	- Use the CLNK file to obtain unique record IDs of events 
	which are linked to each of the selected asthma condition 
	records.
 
  
	- From the HC-135G file, select only records for non-telephone 
	office-based medical provider visits for persons with a positive 
	weight. 
 
  
	- Using the selected record IDs obtained from the CLNK file, 
	with the selected HC-135G records, identify only those visits 
	which were for asthma. 
 
  
	- Use the RXLK file with the selected visit records which were 
	for asthma to obtain unique record IDs of prescribed medicine 
	records from file HC-135A linked to those visits.
 
  
	- Using these record IDs, obtain the linked records from the 
	HC-135A file and calculate the weighted mean of the expenditure 
	variable.
 
 
Attachment 2 contains a copy of the SAS job for this 
example.  
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3.2 Example B: Using the CLNK File (HC-135IF1) with 
the Medical Conditions File (HC-137) and the Prescribed Medicines Event 
File (HC-135A) 
This example calculates the total expenditure for 
prescribed medicines associated with asthma, using the Conditions file (HC-137), 
the CLNK file (HC-135IF1) and the prescribed medicines event file (HC-135A). It 
includes the following major steps: 
	- From HC-137 file, select only records with condition coded 
	as asthma.
 
  
	- Use the CLNK file to obtain unique record IDs of events 
	which are linked to each of the asthma condition records.
 
  
	- Using these record IDs, obtain linked records from the 
	HC-135A file and calculate the weighted mean of the expenditure 
	variable.
 
 
Attachment 2 contains a copy of the SAS job for this 
example. 
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3.3 Example C: Using the CLNK File with the Medical 
Conditions File (HC-137) and Office-Based Medical Provider Visits Event File 
(HC-135G) 
This example calculates the total expenditures for 
office-based medical provider visits associated with asthma, using the 
Conditions file (HC-137), the CLNK file (HC-135IF1) and the office-based medical 
provider visits event file (HC-135G). It includes the following major steps: 
	- From HC-137 file, select only records with condition coded 
	as asthma.
 
  
	- Use the CLNK file to obtain unique record IDs of events 
	which are linked to each of the asthma condition records.
 
  
	- From the HC-135G file, select only records for non-telephone 
	office-based medical provider visits for persons with a positive 
	weight. 
 
  
	- Using the selected record IDs obtained from the CLNK file, 
	with the selected HC-135G records, identify only those visits 
	which were for asthma and calculate the weighted mean of the 
	expenditure variable.
 
 
Attachment 2 contains a copy of the SAS job for this example. 
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3.4 Limitations/Caveats of the CLNK File 
When using the CLNK file, analysts should keep in mind 
that (1) conditions are self-reported and (2) there may be multiple conditions 
associated with an event. Users should also note that not all events link to the 
Conditions file. 
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3.5 Limitations/Caveats of the RXLK File 
When using the RXLK file, analysts should keep in mind 
that one event record can link to more than one prescribed medicine record. 
Conversely, a prescribed medicine record may link to more than one event record 
in the same event file and/or more than one event record in other event files. 
When this occurs, it is up to the analyst to determine how the prescribed 
medicine expenditures should be allocated among those medical events. 
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3.6 National Health Interview Survey 
Data from this file can be used alone or in 
conjunction with other files for different analytic purposes. Each MEPS panel 
can also be linked back to the previous years’ National Health Interview Survey 
public use data files. For information on obtaining MEPS/NHIS link files please 
see 
meps.ahrq.gov/data_stats/more_info_download_data_files.jsp. 
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3.7 Using MEPS Data for Trend 
Analysis 
MEPS began in 1996, and the utility of the survey for 
analyzing health care trends expands with each additional year of data. However, 
it is important to consider a variety of factors when examining trends over time 
using MEPS. Statistical significance tests should be conducted to assess the 
likelihood that observed trends may be attributable to sampling variation. The 
length of time being analyzed should also be considered. In particular, large 
shifts in survey estimates over short periods of time (e.g. from one year to the 
next) that are statistically significant should be interpreted with caution, 
unless they are attributable to known factors such as changes in public policy, 
economic conditions, or MEPS survey methodology. Looking at changes over longer 
periods of time can provide a more complete picture of underlying trends. 
Analysts may wish to consider using techniques to smooth or stabilize analyses 
of trends using MEPS data such as comparing pooled time periods (e.g. 1996-97 
versus 2005-06), 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 (i.e., the chance of declaring an observed 
difference to be statistically significant when there is no difference in the 
population parameters). Performing numerous statistical significance tests 
without making appropriate allowance for multiple comparisons increases the 
likelihood of a Type I error. 
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3.8 Longitudinal Analysis 
For Panels 1 through 8, panel-specific files (called 
Longitudinal Weight Files) containing estimation variables to facilitate 
longitudinal analysis are available for downloading in the data section of the 
MEPS Web site. To create longitudinal files for these panels, it is necessary to 
link data from two subsequent annual files that contain data for the first and 
second years of the panel, respectively. Starting with Panel 9, it is not 
necessary to link files for longitudinal analysis because Longitudinal Data 
Files have been constructed and are available for downloading on the Web. 
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Attachment 1: Clinical Classification Code to ICD-9-CM Code Crosswalk (link to separate file) 
Attachment 2: Sample SAS Jobs for Linking Examples (link to separate file) 
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