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MEPS HC-231 2021 Medical Conditions

August 2023

Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
5600 Fishers Lane
Rockville, MD 20857
(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 Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Naming
2.5 File Contents
2.5.1 Identifier Variables (DUID-CONDRN)
2.5.2 Medical Condition Variables (AGEDIAG-ICD10CDX)
2.5.3 Utilization Variables (OBCOND - RXCOND)
3.0 Survey Sample Information
3.1 Discussion of Pandemic Effects on Quality of 2021 MEPS Data
3.1.1 Summary
3.1.2 Overview
3.1.3 Data Quality Issues for MEPS in 2021 Directly Associated with Data Quality Concerns for the NHIS and CPS
3.1.4 Modifications to the MEPS HC 2021 Sample Design
3.1.5 Data Quality Issues for MEPS FY 2021
3.1.6 Discussion and Guidance
3.2 Sample Weight (PERWT21F)
3.3 Details on Person Weight Construction
3.3.1 MEPS Panel 23 Weight Development Process
3.3.2 MEPS Panel 24 Weight Development Process
3.3.3 MEPS Panel 25 Weight Development Process
3.3.4 MEPS Panel 26 Weight Development Process
3.3.5 The Final Weight for 2021
3.4 Coverage
3.5 Using MEPS Data for Trend Analysis
4.0 National Health Interview Survey (NHIS)
5.0 Longitudinal Analysis
References
D. Variable-Source Crosswalk
Appendix 1: ICD10CDX and CCSR Condition Code Frequencies

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. Furthermore, linkage of the Medical Expenditure Panel Survey and the National Health Interview Survey may not occur outside the AHRQ Data Center, NCHS Research Data Center (RDC) or the U.S. Census RDC network.

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 noninstitutionalized 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 includes five rounds of interviews covering two full calendar years. Additional rounds were added in 2020 and 2021, covering third and fourth years respectively, to compensate for the smaller number of completed interviews in later panels. These extra rounds provide data for examining person-level changes in selected variables such as expenditures, health insurance coverage, and health status. Using computer assisted personal interviewing (CAPI) technology, information about each household member is collected, and the survey builds on this information from interview to interview. All data for a sampled household are reported by a single household respondent.

The MEPS HC was initiated in 1996. Each year a new panel of sample households is selected. Because the data collected are comparable to those from earlier medical expenditure surveys conducted in 1977 and 1987, it is possible to analyze long-term trends. Each annual MEPS HC sample size is about 15,000 households. Data can be analyzed at either the person or event level. Data must be weighted to produce national estimates.

The set of households selected for each panel of the MEPS HC is a subsample of households participating in the previous year’s National Health Interview Survey (NHIS) conducted by the National Center for Health Statistics. The NHIS sampling frame provides a nationally representative sample of the U.S. civilian noninstitutionalized population. 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. NHIS introduced a new sample design in 2016 that discontinued oversampling of these minority groups.

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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 cannot accurately provide. This part of the MEPS is called the Medical Provider Component (MPC) and information is collected on dates of visits, 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 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 micro data files and tables via the MEPS website and datatools.ahrq.gov.

Additional information on MEPS is available from the MEPS project manager or the MEPS public use data manager at the Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality, 5600 Fishers Lane, Rockville, MD 20857 (301-427-1406).

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C. Technical and Programming Information

1.0 General Information

This documentation describes the data contained in MEPS Public Use Release HC-231, which is one in a series of public use data files to be released from the 2021 Medical Expenditure Panel Survey Household Component (MEPS HC). Released as an ASCII file (with related SAS, SPSS, R, and Stata programming statements and data user information), and a SAS data set, SAS transport file, Stata data set, and Excel file, this public use file provides information on household-reported medical conditions collected on a nationally representative sample of the civilian noninstitutionalized population of the United States for calendar year 2021 MEPS HC. The file contains 32 variables and has a logical record length of 113 with an additional 2-byte carriage return/line feed at the end of each record.

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

Data File Information
Survey Sample Information
Merging/Linking MEPS Data Files
Variable-Source Crosswalk
Appendix: ICD10CDX and CCSR Condition Code Frequencies

A codebook of all the variables included in the 2021 Medical Conditions File is provided in an accompanying file.

For more information on the MEPS sample design, see Chowdhury et al. (2019). A copy of the survey instrument used to collect the information on this file is available on the MEPS website.

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2.0 Data File Information

This file contains 94,641 records. Each record represents one current medical condition reported for a household survey member who resides in an eligible responding household and who has a positive person or family weight. A condition is defined as current if it is linked to an event during 2021. Conditions in the Priority Condition Enumeration (PE) section are asked in the context of “has person ever been told by a doctor or other health care professional that they have (condition)?” except joint pain and chronic bronchitis, which ask only about the last 12 months. Persons with a response of Yes (1) to a priority condition question for whom the condition is not current as defined above will not have a record for that condition in this file.

This file consists of MEPS survey data obtained in Rounds 7, 8, and 9 of Panel 23; Rounds 5, 6, and 7 of Panel 24; Rounds 3, 4, and 5 of Panel 25; and Rounds 1, 2, and 3 of Panel 26, the rounds for the MEPS panels covering calendar year 2021. 2021 is the first data year to include four panels of data; Panel 23 was extended to include Rounds 7, 8, and 9 and Panel 24 was extended to include Rounds 6 and 7. In addition, the Panel 24 Round 5 reference period was extended into 2021 instead of ending on 12/31/2020.

For most variables on the file, the codebook provides both weighted and unweighted frequencies. The exceptions to this are weight variables and variance estimation variables. Only unweighted frequencies of these variables are included in the accompanying codebook file. See the Weights Variables list in Section D, Variable-Source Crosswalk.

Person-level data (e.g., demographic or health insurance characteristics) from the 2021 MEPS Full Year Consolidated file (HC-233) can be merged to the records in this file using DUPERSID (see Section 4.0 for details). Since each record represents a single condition reported by a household respondent, some household members may have multiple medical conditions and thus will be represented by multiple records on this file. Other household members may have had no reported medical conditions and thus will have no records on this file. Still other household members may have had a reported medical condition that did not meet the criteria above and thus will have no records on this file. Data from this file also can be merged to 2021 MEPS Event Files (HC-229D through HC-229H) by using the link files provided in HC-229I. (See HC-229I documentation for details.)

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2.1 Codebook Structure

The codebook and data file list variables in the following order:

Unique person identifiers
Unique condition identifiers
Medical condition variables
Utilization variables
Weight and variance estimation variables

Note that the person identifier is unique within this data year.

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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 or the information could not be ascertained
-15 CANNOT BE COMPUTED	Value cannot be derived from data

The value -15 (CANNOT BE COMPUTED) is assigned to MEPS constructed variables in cases where there is not enough information from the MEPS instrument to calculate the constructed variables. “Not enough information” is often the result of skip patterns in the data or from missing information resulting from MEPS responses of -7 (REFUSED) or -8 (DK). Note that reserved code -8 includes cases where the information from the question was “not ascertained” or where the respondent chose “don’t know”.

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2.3 Codebook Format

This codebook describes an ASCII data set (although the data are also being provided in an Excel file, a Stata data set, a SAS data set, and a SAS transport file), and provides the programming identifiers below for each variable:

Variable Programming Identifiers
Identifier	Description
Name	Variable name
Description	Variable descriptor
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. Edited variables end in an “X” and are so noted in the variable label. (CONDIDX, which is an encrypted identifier variable, also ends in an “X”.)

As variable collection, universe, or categories are altered, the variable name will be appended with “_Myy” to indicate in which year the alterations took place. Details about these alterations can be found throughout this document.

Variables contained in this delivery were derived either from the questionnaire itself or from the CAPI. The source of each variable is identified in Section D, Variable-Source Crosswalk. Sources for each variable are indicated in one of three ways: (1) variables derived from CAPI or assigned in sampling are so indicated; (2) variables collected at one or more specific questions have those numbers and questionnaire sections indicated in the “SOURCE” column; and (3) variables constructed from multiple questions using complex algorithms are labeled “Constructed” in the “SOURCE” column.

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2.5 File Contents

2.5.1 Identifier Variables (DUID-CONDRN)

The definitions of Dwelling Units (DUs) in the MEPS HC are generally consistent with the definitions employed for the National Health Interview Survey (NHIS). The Dwelling Unit ID (DUID) is a seven-digit ID number consisting of a 2-digit panel number followed by a five-digit random number assigned after the case was sampled for MEPS. A three-digit person number (PID) uniquely identifies each person within the DU. The variable DUPERSID is the combination of the variables DUID and PID. IDs begin with a 2-digit panel number.

CONDN is the condition number and uniquely identifies each condition reported for an individual. The range on this file for CONDN is 1-901. A CONDN beginning with “9” reflects a condition that was added during the editing process.

The variable CONDIDX uniquely identifies each condition (i.e., each record on the file) and is the combination of DUPERSID and CONDN. CONDIDX has a length of 13 with DUPERSID (10) and CONDN (3) combined.

PANEL is a constructed variable used to specify the panel number for the interview in which the condition was reported. PANEL will indicate Panel 23, Panel 24, Panel 25, or Panel 26. The panel number is included as the first two digits of the DUID and DUPERSID.

CONDRN indicates the round in which the condition was first reported. For a small number of cases, conditions that actually began in an earlier round were not reported by respondents until subsequent rounds of data collection. During file construction, editing was performed for these cases in order to reconcile the round in which a condition began and the round in which the condition was first reported.

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2.5.2 Medical Condition Variables (AGEDIAG-ICD10CDX)

This file contains variables describing medical conditions reported by respondents in several sections of the MEPS questionnaire, and all questionnaire sections collecting information about health provider visits and/or prescription medications (see Variable-Source Crosswalk in Section D for details).

Priority Conditions and Injuries

Certain conditions were a priori designated as “priority conditions” due to their prevalence, expense, or relevance to policy. Some of these are long-term, life-threatening conditions, such as cancer, diabetes, emphysema, high cholesterol, hypertension, ischemic heart disease, and stroke. Others are chronic, manageable conditions, including arthritis and asthma. The only mental health condition on the priority conditions list is attention deficit hyperactivity disorder/attention deficit disorder.

When a condition was first mentioned, respondents were asked whether it was due to an accident or injury (INJURY=1). Only non-priority conditions (i.e., conditions reported in a section other than PE) are eligible to be injuries. The interviewer is prevented from selecting priority conditions as injuries.

Complete List of Conditions Asked in Priority Conditions Enumeration Section:

Angina/Angina Pectoris

Arthritis

Asthma

Attention Deficit Hyperactivity Disorder (ADHD)/Attention Deficit Disorder (ADD)

Cancer/Malignancy

Chronic Bronchitis

Coronary Heart Disease

Diabetes/Sugar Diabetes

Emphysema

Heart Attack/Myocardial Infarction (MI)

High Cholesterol

Hypertension/High Blood Pressure

Joint Pain

Other Heart Disease (not coronary heart disease, angina, or heart attack)

Stroke/Transient Ischemic Attack (TIA)/Mini-stroke

Age Priority Condition Began

The age of diagnosis (AGEDIAG) was collected for all priority conditions, except joint pain. For confidentiality reasons, AGEDIAG is set to Inapplicable (-1) for cancer conditions.

To ensure confidentiality, age of diagnosis was top-coded to 85. This corresponds with the age top-coding in person-level PUFs.

Follow-up Questions for Injuries

When a respondent reported that a condition resulted from an accident or injury (INJURY=1), respondents were asked during the round in which the injury was first reported whether the accident/injury occurred at work (ACCDNWRK). This question was not asked about persons aged 15 and younger; the condition had ACCDNWRK coded to inapplicable (-1) for those persons.

Sources for Conditions on the MEPS Conditions File

The records on this file correspond with medical condition records collected by CAPI and stored on a person’s MEPS conditions roster. Conditions can be added to the MEPS conditions roster in several ways. A condition can be reported in the Priority Condition Enumeration (PE) section in which persons are asked if they have been diagnosed with specific conditions. The condition can be identified as the reason reported by the household respondent for a particular medical event (hospital stay, outpatient visit, emergency room visit, home health episode, prescribed medication purchase, or office-based medical provider visit). Some condition information is collected in the Medical Provider Component of MEPS. However, since it is not available for everyone in the sample, it is not used to supplement, replace, or verify household-reported condition data. Conditions reported in the PE section that are not current are not included on this file.

Treatment of Data from Rounds Not Occurring in 2021

Prior to the 2008 file, priority conditions reported during Rounds 1 and 2 of the second year panel were included on the file even if the conditions were not related to an event or reported as a serious condition occurring in the second year of the panel. Beginning in 2008, priority conditions are included on the file only if they are also current conditions. From 2008-2017, a current condition was defined as a condition linked to an event or a condition the person was currently experiencing (i.e., a condition selected in the Condition Enumeration (CE) section). However, starting in Panel 21 Round 5 and Panel 22 Round 3, a current condition is defined only as a condition linked to a current year event. Conditions from Panel 23 Rounds 6 and 7 as well as Panel 24 Rounds 3-5 and Panel 25 Rounds 1-3 that are not included in the 2021 file may be available in the 2020 Medical Conditions File if the person had a positive person or family weight in 2020.

Note: Priority conditions are generally chronic conditions. Even though a person may not have reported an event in 2021 due to the condition, analysts should consider that the person may still be experiencing the condition. If a Panel 25 person reported a priority condition in Round 1 or 2 and did not have an event for the condition in Round 3, 4, or 5, the condition will not be included on the 2021 Medical Conditions File. Similarly: if a Panel 24 person reported a priority condition in Round 1, 2, 3, or 4 and did not have an event for the condition in Round 5, 6, or 7, or if a Panel 23 person reported a priority condition in Round 1, 2, 3, 4, 5, or 6 and did not have an event for the condition in Round 7, 8, or 9, the condition will not be included on the 2021 Medical Conditions File.

Rounds in Which Conditions Were Reported/Selected (CRND1 - CRND9)

A set of constructed variables indicates the round in which the condition was first reported (CONDRN), and the subsequent round(s) in which the condition was selected (CRND1 - CRND9). The condition may be reported or selected when the person reports an event that occurred due to the condition. For example, consider a condition for which CRND1 = 0, CRND2 = 1, and CRND3 = 1. For non-priority conditions (conditions not asked in the PE section), this sequence of indicators on a condition record implies that the condition was not present during Round 1 (CRND1 = 0), was first mentioned during Round 2 (CRND2 = 1, CONDRN = 2), and was selected again during Round 3 (CRND3 = 1). For priority conditions, this sequence of indicators implies that the condition was reported in the PE section in Round 1 (CONDRN = 1, CRND1 = 0) but was not connected with an event until Rounds 2 and 3 (CRND2 = 1, CRND3 = 1). Because priority conditions are asked in the context of “has person ever been told by a doctor or other health care professional that they have (condition)?” except joint pain and chronic bronchitis, which ask only about the last 12 months, a priority condition might not be selected in the round in which it was first reported. A condition is current if it is linked to an event that occurred in 2021.

Diagnosis Codes

Medical conditions reported by the Household Component respondent were recorded by the interviewer using a condition pick-list with ICD-10-CM codes already assigned to conditions in the list. Reported conditions not in the pick-list were recorded as verbatim text and then were coded to ICD-10-CM codes (ICD10CDX) by professional coders.

Coders followed specific guidelines in coding missing values to the ICD-10-CM diagnosis condition variable when a verbatim text string could not be matched to an ICD-10-CM code through the pick-list. ICD10CDX was coded -15 (Cannot be Computed) where the verbatim text fell into one of three categories: (1) the text indicated that the condition was unknown (e.g., DK); (2) the text indicated the condition could not be diagnosed by a doctor (e.g., doctor doesn’t know); or (3) the specified condition was not codable. If the text indicated a procedure and the condition associated with the procedure could be discerned from the text, the condition itself is coded. For example, “cataract surgery” is coded as the condition “other cataract” (ICD10CDX is set to code “H26”). If the condition could not be discerned (e.g. “outpatient surgery”), ICD10CDX is set to -15.

In order to preserve confidentiality, all of the conditions provided on this file have been collapsed to 3-digit diagnosis code categories rather than the fully-specified ICD-10-CM code. For example, the ICD10CDX value of J02 “Acute pharyngitis” includes the fully-specified subclassifications J020 and J029; the value F31 “Bipolar disorder” includes the fully-specified subclassifications F3110 through F319. Table 1 in Appendix 1 provides unweighted and weighted frequencies for all ICD-10-CM condition code values reported on the file. Less than 1 percent of the ICD-10-CM codes on this file were edited further by collapsing two or more 3-digit codes into one 3-digit code. This includes clinically rare conditions that were recoded to broader codes by clinicians. A condition is determined to be clinically rare if it appears on the National Institutes of Health’s list of rare diseases.

For confidentiality purposes, approximately 7% of ICD-10-CM codes were recoded to -15 (Cannot be Computed) for conditions where the frequency was fewer than 40 for the total unweighted population in the file or less than 400,000 for the weighted population. Additional factors used to determine recoding include age and gender.

In a small number of cases, diagnosis and condition codes were recoded to -15 (Cannot be Computed) if they denoted a pregnancy for a person younger than 18 or older than 44. Less than one-tenth of 1 percent of records were recoded in this manner on the 2021 Medical Conditions file. The person’s age was determined by linking the 2021 Medical Conditions file to the 2020 and 2021 Population Characteristics File. If the person’s age is under 18 or over 44 in the round in which the condition was reported, the appropriate condition code was recoded to -15 (Cannot be Computed).

Users should note that because of the design of the survey, most deliveries (i.e., births) are coded as pregnancies. For more accurate estimates for deliveries, analysts should use RSNINHOS “Reason Entered Hospital” found on the Hospital Inpatient Stays Public Use File (HC-229D).

Each year, a few conditions on the final file may fall below the confidentiality threshold. This is due to the multistage file development process. The confidentiality recoding is performed on the preliminary version of the Conditions file each year. This preliminary version is used in the development of other event PUFs and, in turn, these event PUFs are used in the development of the final Conditions file. During this process, some records from the preliminary file are dropped because only records that are relevant to the current data year are reflected in the final Conditions PUF.

Conditions file data can be merged with the 2021 MEPS Event Files using the 2021 MEPS Condition-Event Linking file (HC-229I). Because the conditions have been collapsed to 3-digit diagnosis code categories rather than the fully-specified ICD-10-CM code, it is possible for there to be duplicate ICD-10-CM condition codes linked to a single medical event when different fully-specified conditions are coded to the same 3-digit code.

Conditions were reported in several sections of the HC questionnaire (see Variable-Source Crosswalk in Section D). Labels for all values of ICD10CDX, as shown in Table 1 of Appendix 1, are provided in the SAS programming statements included in this release (see the H231SU.TXT file).

Clinical Classification Software Refined

Clinical Classification Software Refined (CCSR) are used alongside ICD-10-CM diagnosis codes to group medical conditions into clinically meaningful categories. Although ICD-10-CM diagnosis codes can map to multiple CCSR codes, for the purposes of this PUF, one ICD-10-CM diagnosis code may map to up to three CCSR categories (CCSR1X, CCSR2X, CCSR3X) using the v2022.2 release of the CCSR for ICD-10-CM diagnoses. The CCSR categories on this PUF are listed in alphabetical order and do not indicate a primary and secondary diagnosis. For more information on CCSR, visit the user guide for CCSR.

For confidentiality purposes, less than 2% of the CCSR categories were collapsed into a broader code for the appropriate body system where the frequency was less than 40 for the total unweighted population in the file or less than 400,000 for the weighted population. For example, BLD001 (Nutritional Anemia), may be recoded to BLD000 (Disease of Blood and Disorders Involving Immune Mechanism), thus revealing only the body system. Less than 1% of CCSR codes were recoded to -15 (Cannot be Computed) based on frequencies of ICD10CDX and CCSR pairs.

Table 2 in Appendix 1 provides unweighted and weighted frequencies for CCSR combinations reported on the file.

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2.5.3 Utilization Variables (OBCOND - RXCOND)

The variables OBCOND, OPCOND, HHCOND, IPCOND and ERCOND indicate that at least one 2021 event can be linked to each condition record on the current file, i.e., office-based, outpatient, home health, inpatient hospital stays and emergency room visits. Note that the HHCOND variable includes all home health types, including informal care, and OBCOND and OPCOND include telehealth visits. The variable RXCOND is an indicator of any prescribed medicine purchase associated with the condition.

These event indicators were derived from Expenditure Event Public Use Files (HC-229G, HC-229F, HC-229H, HC-229D, and HC-229E). Events associated with conditions include all utilization that occurred between January 1, 2021 and December 31, 2021.

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3.0 Survey Sample Information

3.1 Discussion of Pandemic Effects on Quality of 2021 MEPS Data

3.1.1 Summary

The challenges associated with MEPS data collection in 2020 after the onset of the COVID-19 pandemic continued into 2021. The major modifications to the standard MEPS study design remained in effect, permitting data to be collected safely but with accompanying concerns related to the quality of the data obtained. These data quality issues are discussed below. The suggestion made in the documentation for the 2020 MEPS Full Year Consolidated PUF data (as well as for most federal major in-person surveys conducted in 2021 and 2020) still holds. Researchers are counseled to take care in the interpretation of estimates based on data collected from these two calendar years. This includes the comparison of such estimates to those of other years and corresponding trend analyses.

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3.1.2 Overview

Section 3.1 of the documentation for the 2020 Full Year Consolidated Data File provides a general discussion of the impact of the COVID-19 pandemic on several other major in-person federal surveys as well as on MEPS. In addition, it offers a detailed look at how MEPS was modified to permit safe data collection and the development of useful estimates at a time when the way the U.S. health care system functioned underwent many transformations in order to meet population needs.

In this corresponding 2021 document, focus is placed mostly on MEPS data quality in 2021. However, it also includes how data quality issues related to the two federal surveys most closely connected to it, the National Health Interview Survey (NHIS) carried out by the National Center for Health Statistics (NCHS) and the Current Population Survey (CPS) carried out by the Census Bureau, have an impact on the data quality issues of MEPS.

Specifically, the following discussion describes: 1) data quality issues experienced by the NHIS and CPS that affect MEPS; 2) modifications to the MEPS sample design in 2021 due to the continuing pandemic; and 3) potential data quality issues in the FY 2021 MEPS data related to the COVID-19 pandemic.

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3.1.3 Data Quality Issues for MEPS in 2021 Directly Associated with Data Quality Concerns for the NHIS and CPS

Households fielded for Round 1 of MEPS in each year have been selected as a subsample from among the NHIS responding households from the prior year. The MEPS first year panel in 2021 was Panel 26. The households fielded for MEPS in Round 1 of Panel 26 were thus selected from NHIS responding households in 2020. It is important to note here that the NHIS households eligible for use in MEPS are restricted to the first three quarters of the NHIS as the fourth quarter households cannot be made available in time for MEPS data collection early in the next calendar year.

The onset of the pandemic in 2020 at a national level took place in mid-March of that year, when the NHIS data collection for the first quarter of 2020 was virtually completed and that of the second quarter was about to begin. The NHIS had to make a rapid transition from in-person to telephone interviewing to attempt to gather NHIS data for the second quarter of 2020. While NCHS was able to make the transition, assessments made by NCHS at the time indicated a much lower response rate than is typically experienced during Quarter 2 and the quality of Quarter 2 data was of particular concern. NCHS thus modified the 2020 NHIS sample design for Quarters 3 and 4. A randomly selected subsample of the sampled housing units originally selected for fielding in Quarters 3 and 4 of 2020 was removed from the sample to be fielded. This reduced sample for Quarters 3 and 4 was then enhanced by randomly selecting responding households from the 2019 NHIS for interviewing in 2020 as well. In consideration of the data quality issues and sample design modifications associated with the 2020 NHIS, the MEPS sample design for FY 2021 was modified, as discussed shortly below.

The quality of CPS data is always of particular importance to MEPS as March CPS-ASEC estimates serve as the basis of control totals for the raking component of the MEPS weighting process. These control totals incorporate the following demographic variables: age, sex, race/ethnicity, region, MSA status, educational attainment, and poverty status. The CPS estimates of educational attainment and poverty status used in the development of the FY 2021 MEPS PUFs were of particular concern. Evaluations of these estimates undertaken by the Census Bureau have shown that they suffered from bias due to survey nonresponse with CPS income estimates being on the high side and the estimate of those under the poverty threshold being on the low side. The impact of these CPS estimates on the quality of MEPS estimates has been carefully considered. The approach used for the 2021 MEPS Full Year Consolidated PUF sample weights is discussed in Section 3.3.

References (Bramlett et al., 2021; Dahlhamer et al., 2021; Lau et al, 2021; Rothbaum & Bee, 2021, 2022; Zuvekas & Kashihara, 2021) discussing the fielding of these surveys during the pandemic and possible bias concerns, can be found in the References section of this document.

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3.1.4 Modifications to the MEPS HC 2021 Sample Design

The MEPS sample is usually selected from Quarters 1 to 3 of NHIS Panels 1 and 3. However, 2020 NHIS Quarter 2 data quality and sample size issues needed to be considered in planning for selecting and fielding a MEPS sample for 2021. It became clear that it would be prudent to modify the 2021 MEPS sample design for MEPS Panel 26 by replacing 2020 NHIS Quarter 2 with another quarter from 2020 NHIS Panels 2 and 4. Action had to be taken immediately because the MEPS sample selection from NHIS responding households begins in the late summer/early fall of each year.

AHRQ contacted NCHS, reviewing the various issues and asking if responding households in NHIS Panels 2 and 4 from Quarter 1 of 2020 could be made available for MEPS sample selection. Virtually all of these households were interviewed in-person prior to the major onset of the pandemic, so the Quarter 1 response rates for all four NHIS panels were consistent with prior years and the data quality issues associated with the pandemic could be avoided. NCHS was fully supportive of this approach and made NHIS Panels 2 and 4 for Quarter 1 available for use by MEPS. Thus, for MEPS Panel 26, the NHIS responding households subsampled for MEPS were selected among all NHIS responding households in all four NHIS panels in Quarter 1 as well as those responding in Quarter 3 of NHIS Panels 1 and 3.

As an adjunct to this modification, it was decided to take advantage of the additional PSUs (sampled localities) available from NHIS Panels 2 and 4 and appearing in the MEPS sample for the first time. State level estimation is of interest to MEPS, and the added PSUs would serve to increase the precision of variance estimation for state level estimates. State estimates that would be expected to benefit the most from these added PSUs were the “middle-sized” states where sample sizes were marginal but usually not enough PSUs for variance estimation. The largest states already had large sample sizes while precision for the smallest states would remain low. As a result, from Quarter 1 of 2020 NHIS Panels 2 and 4, the MEPS sample focused on oversampling the “middle-sized” states rather than Asians, Blacks, and Hispanics.

Finally, it was decided to collect 2021 data for nine rounds of Panel 23 and seven rounds of Panel 24, so that these two panels will contribute to MEPS estimates for four calendar years for Panel 23 and three calendar years for Panel 24. In so doing, the number of respondents to MEPS will be kept at a relatively high level despite the decline in response rates due to the pandemic. The MEPS FY 2021 PUF records thus consist of data obtained from the following MEPS Panels and corresponding rounds: Panel 23, Rounds 7-9; Panel 24, Rounds 5-7; Panel 25, Rounds 3-5; and Panel 26, Rounds 1-3.

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3.1.5 Data Quality Issues for MEPS for FY 2021

Three sources of potential bias were identified for MEPS for FY 2020: long recall period for Round 6 of Panel 23; switching from in-person to telephone interviewing which likely had a larger impact on Panel 25; and the impact of CPS bias on the MEPS weights. A number of statistically significant differences were found between panels for FY 2020. Those findings are discussed in the documentation for the 2020 Full Year Consolidated PUF.

With this in mind, there were a number of uncertainties for FY 2021 warranting examination. Would Panel 23 data quality increase substantially once the issue of an extensive recall period was eliminated? Would the switching from in-person to telephone interview in Round 1 continue to impact Panel 25 estimates? Since Panel 26 was the first year MEPS panel in 2021, would Panel 26 estimates tend to be different than those of the other three panels?

Analyses undertaken to examine the quality of MEPS FY 2021 data appearing on the Consolidated PUF have been focused on the comparison of health care utilization and health insurance status distribution (some private insurance, some public insurance, no health insurance) for the MEPS target population between the panels fielded. These comparisons were undertaken for the full sample and the three age groups of 0-17, 18-64, and 65+.

Comparisons of health care utilization data for Panel 24 and Panel 23 found no statistically significant differences in any of the analysis variables, suggesting that Panel 23 data quality increased substantially once the issue of an extensive recall period was eliminated. Comparisons of Panel 26 and Panel 24 health care utilization data did not detect any notable differences among event types of a salient nature.

Similar to FY 2020, comparisons of Panel 25 health care utilization data with those from other panels found that the difference in estimates reached statistical significance for several event types, with those from Panel 25 generally being higher. However, the gap between the Panel 25 estimates and other panels has shown a sizeable decrease, suggesting that the Panel 25 data quality has improved.

Another set of analyses compared estimates based on the four panels pooled together using the FY 2021 Consolidated PUF weight compared to the estimates based on the individual panel data and weights. Analyses indicated that event estimates combining data from all four panels show little difference from event estimates of the individual panels.

The analyses undertaken for health insurance status distribution suggest no major differences between the four panels for the various event type estimates. Even though slight differences were observed with Panel 25 (e.g., the distribution associated with the age range 18-64 showed a higher percentage of all public insurance compared to the other three panels while those at least 65 years of age showed a lower percentage of some private insurance compared to the other three panels), no statistically significant differences were detected.

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3.1.6 Discussion and Guidance

The various actions taken in the development of the person-level weights for the MEPS FY 2021 Consolidated PUF were designed to limit the potential for bias in the data due to changes in data collection and response bias. However, evaluations of MEPS data quality in 2021, consistent with those of other Federal surveys fielded in 2021, suggest that users of the MEPS FY 2021 Consolidated PUF should exercise caution when interpreting estimates and assessing analyses based on these data as well as in comparing 2021 estimates to those of prior years.

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3.2 Sample Weight (PERWT21F)

There is a single full-year person-level weight (PERWT21F) assigned to each record for each key, in-scope person who responded to MEPS for the full period of time that they were in-scope during 2021. A key person was either a member of a responding NHIS household at the time of the interview or joined a family associated with such a household after being out-of-scope at the time of the NHIS (the latter circumstance includes newborns as well as those returning from military service, an institution, or residence in a foreign country). A person is in-scope whenever they are a member of the civilian, noninstitutionalized portion of the U.S. population.

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3.3 Details on Person Weight Construction

The person-level weight PERWT21F was developed in several stages. Preliminary person-level weights for Panel 23, Panel 24, Panel 25, and Panel 26 were first created separately. The weighting process for each panel included an adjustment for nonresponse over time and calibration to independent population figures. The calibration was initially accomplished separately for each panel by raking the corresponding sample weights for those in-scope at the end of the calendar year to Current Population Survey (CPS) population estimates based on six variables. The six variables used in the establishment of the person-level control figures were: educational attainment of the reference person (no degree, high school/GED no college or some college, bachelor’s degree or higher); census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic; Black, non-Hispanic; Asian, non-Hispanic; and other); sex; and age. A composite weight was then formed by multiplying each weight from Panel 23 by the factor .22, each weight from Panel 24 by the factor .22, each weight from Panel 25 by the factor .25, and each weight from Panel 26 by the factor .31. The choice of factors reflected the relative effective sample sizes of the four panels, helping to limit the variance of estimates obtained from pooling the four samples. Weights for the 2021 Full Year Population Characteristics PUF were then developed by raking the composite weight to the same set of CPS-based control totals.

The standard approach for establishing the 2021 Full Year Consolidated PUF weight is as follows. When the poverty status information derived from income variables becomes available, a final raking is undertaken. The full sample weight appearing on the Population Characteristics PUF for a given year is re-raked, establishing control figures reflecting poverty status rather than educational attainment. Thus, control totals are established using poverty status (five categories: below poverty, from 100 to 125 percent of poverty, from 125 to 200 percent of poverty, from 200 to 400 percent of poverty, at least 400 percent of poverty) as well as the other five variables previously used in the weight calibration.

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3.3.1 MEPS Panel 23 Weight Development Process

The person-level weight for MEPS Panel 23 was developed using the 2020 full-year weight for an individual as a “base” weight for 2020 survey participants present in 2021. For key, in-scope members who joined an RU some time in 2021 after being out-of-scope in 2020, the initially assigned person-level weight was the corresponding 2020 family weight. The weighting process included an adjustment for person-level nonresponse over Rounds 8 and 9 as well as raking to population control figures for December 2021 for key, responding persons in-scope on December 31, 2021. These control totals were derived by scaling back the population distribution obtained from the March 2022 CPS to reflect the December 31, 2021 estimated population total (estimated based on Census projections for January 1, 2022). Variables used for person-level raking included: education of the reference person (three categories: no degree; high school/GED only or some college; Bachelor’s or higher degree); Census region (Northeast, Midwest, South, West); MSA status (MSA, non-MSA); race/ethnicity (Hispanic; Black, non-Hispanic; Asian, non-Hispanic; and other); sex; and age. (It may be noted that for confidentiality reasons, the MSA status variables are no longer released for public use.) The final weight for key, responding persons who were not in-scope on December 31, 2021 but were in-scope earlier in the year was the nonresponse-adjusted person weight without raking.

The 2020 full-year weight used as the base weight for Panel 23 was derived from the 2018 MEPS Round 1 weight and reflected adjustment for nonresponse over the remaining data collection rounds in 2018, 2019, and 2020 as well as raking to the December 2018, December 2019, and December 2020 population control figures.

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3.3.2 MEPS Panel 24 Weight Development Process

The person-level weight for MEPS Panel 24 was developed using the 2020 full-year weight for an individual as a “base” weight for survey participants present in 2021. For key, in-scope members who joined an RU some time in 2021 after being out-of-scope in 2020, the initially assigned person-level weight was the corresponding 2020 family weight. The weighting process included an adjustment for person-level nonresponse over Rounds 6 and 7 as well as raking to the same population control totals for December 2021 used for the MEPS Panel 23 weights for key, responding persons in-scope on December 31, 2021. The same six variables employed for Panel 23 raking (education level, census region, MSA status, race/ethnicity, sex, and age) were also used for Panel 24 raking. Similar to Panel 23, the Panel 24 final weight for key, responding persons not in-scope on December 31, 2021 but in-scope earlier in the year was the nonresponse-adjusted person weight without raking.

Note that the 2020 full-year weight that was used as the base weight for Panel 24 was derived using the 2019 MEPS Round 1 weight and reflected adjustment for nonresponse over the remaining data collection rounds in 2019 and 2020 as well as raking to the December 2019 and December 2020 population control figures.

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3.3.3 MEPS Panel 25 Weight Development Process

The person-level weight for MEPS Panel 25 was developed using the 2020 full-year weight for an individual as a “base” weight for survey participants present in 2021.

For key, in-scope members who joined an RU sometime in 2021 after being out-of-scope in 2020, the initially assigned person-level weight was the corresponding 2020 family weight. The weighting process also included an adjustment for person-level nonresponse over Rounds 4 and 5 as well as raking to the same population control figures for December 2021 used for the MEPS Panels 23 and 24 weights for key, responding persons in-scope on December 31, 2021. The same six variables employed for Panels 23 and 24 raking (education level, census region, MSA status, race/ethnicity, sex, and age) were also used for Panel 25 raking. Similar to Panels 23 and 24, the Panel 25 final weight for key, responding persons not in-scope on December 31, 2021 but in-scope earlier in the year was the nonresponse-adjusted person weight without raking.

Note that the 2020 full-year weight that was used as the base weight for Panel 25 was derived using the 2020 MEPS Round 1 weight and reflected adjustment for nonresponse over the remaining data collection rounds in 2020 as well as raking to the December 2020 population control figures.

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3.3.4 MEPS Panel 26 Weight Development Process

The person-level weight for MEPS Panel 26 was developed using the 2021 MEPS Round 1 person-level weight as a “base” weight. The MEPS Round 1 weights incorporated the following components: the original household probability of selection for the NHIS adjusted to reflect the NHIS subsample reserved for MEPS and an adjustment for NHIS nonresponse, the probability of selection for MEPS from NHIS, an adjustment for nonresponse at the dwelling unit level for Round 1, and poststratification to control figures at the person level obtained from the March CPS of 2021. For key, in-scope members who joined an RU after Round 1, the Round 1 DU weight served as a “base” weight.

The weighting process also included an adjustment for nonresponse over the remaining data collection rounds in 2021 as well as raking to the same population control figures for December 2021 used for the MEPS Panel 23, Panel 24, and Panel 25 weights for key, responding persons in-scope on December 31, 2021. The same six variables employed for Panel 23, Panel 24, and Panel 25 raking (education level of the reference person, census region, MSA status, race/ethnicity, sex, and age) were also used for Panel 26 raking. Similar to Panel 23, Panel 24, and Panel 25, the Panel 26 final weight for key, responding persons who were not in-scope on December 31, 2021 but were in-scope earlier in the year was the nonresponse-adjusted person weight without raking.

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3.3.5 The Final Weight for 2021

The final raking of those in-scope at the end of the year has been described above. In addition, the composite weights of two groups of persons who were out-of-scope on December 31, 2021 were adjusted for expected undercoverage. Specifically, the weights of those who were in-scope some time during the year, out-of-scope on December 31, and entered a nursing home during the year and still residing in a nursing home at the end of the year were poststratified to an estimate of the number of persons who were residents of Medicare- and Medicaid-certified nursing homes for part of the year (approximately 3-9 months) during 2014. This estimate was developed from data on the Minimum Data Set (MDS) of the Center for Medicare and Medicaid Services (CMS). The weights of persons who died while in-scope were poststratified to corresponding estimates derived using data obtained from the Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), Underlying Cause of Death, 2018-2021 on CDC WONDER Online Database, released in 2023, the latest available data at the time. Separate decedent control totals were developed for the “65 and older” and “under 65” civilian noninstitutionalized populations.

Overall, the weighted population estimate for the civilian noninstitutionalized population for December 31, 2021 is 327,209,772 (PERWT21F >0 and INSC1231=1). The sum of person-level weights across all persons assigned a positive person-level weight is 331,249,393.

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3.4 Coverage

The target population for MEPS in this file is the 2021 U.S. civilian, noninstitutionalized population. However, the MEPS sampled households are a subsample of the NHIS households interviewed in 2017 (Panel 23), 2018 (Panel 24), 2019 (Panel 25), and 2020 (Panel 26). New households created after the NHIS interviews for the respective panels and consisting exclusively of persons who entered the target population after 2017 (Panel 23), after 2018 (Panel 24), after 2019 (Panel 25), or after 2020 (Panel 26) are not covered by MEPS. Neither are previously out-of-scope persons who join an existing household but are unrelated to the current household residents. Persons not covered by a given MEPS panel thus include some members of the following groups: immigrants; persons leaving the military; U.S. citizens returning from residence in another country; and persons leaving institutions. Those not covered represent a small proportion of the MEPS target population.

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3.5 Using MEPS Data for Trend Analysis

First, of course, we note that there are uncertainties associated with 2020 and 2021 data quality as discussed earlier in the data quality section (Section 3.1). Evaluations of important MEPS estimates suggest that they are of reasonable quality. Nevertheless, analysts are advised to exercise caution in interpreting these estimates, particularly in terms of trend analyses since access to health care was substantially affected by the COVID-19 pandemic as were related factors such as health insurance and employment status for many people.

MEPS began in 1996, and the utility of the survey for analyzing health care trends expands with each additional year of data; however, when examining trends over time using MEPS, the length of time being analyzed should 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.

With respect to methodological considerations, in 2013 MEPS introduced an effort focused on field procedure changes such as interviewer training to obtain more complete information about health care utilization from MEPS respondents with full implementation in 2014. This effort likely resulted in improved data quality and a reduction in underreporting starting in the second half of 2013 and throughout 2014 full year files and have had some impact on analyses involving trends in utilization across years. The changes in the NHIS sample design in 2016 and 2018 could also potentially affect trend analyses. The new NHIS sample design is based on more up-to-date information related to the distribution of housing units across the U.S. As a result, it can be expected to better cover the full U.S. civilian, noninstitutionalized population, the target population for MEPS, as well as many of its subpopulations. Better coverage of the target population helps to reduce the potential for bias in both NHIS and MEPS estimates.

A significant change to the Conditions file occurred in 2016 when ICD-10-CM condition codes replaced ICD-9-CM codes. As a result of this transition, CCS codes were replaced with CCSR codes. Up to three CCSR codes can be assigned to a single condition on this file; previously, a single CCS code was assigned to each condition (see Section 2.5.2 for details). Also in 2018, the inclusion criteria for conditions changed; therefore, fewer conditions are on the 2018 and later files compared to previous years. See section 2.0 for a discussion of conditions included on the file.

Another change with the potential to affect trend analyses involved major modifications to the MEPS instrument design and data collection process, particularly in the events sections of the instrument. These were introduced in the Spring of 2018 and thus affected data beginning with Round 1 of Panel 23, Round 3 of Panel 22, and Round 5 of Panel 21. Since the Full Year 2017 PUFs were established from data collected in Rounds 1-3 of Panel 22 and Rounds 3-5 of Panel 21, they reflected two different instrument designs. In order to mitigate the effect of such differences within the same full year file, the Panel 22 Round 3 data and the Panel 21 Round 5 data were transformed to make them as consistent as possible with data collected under the previous design. The changes in the instrument were designed to make the data collection effort more efficient and easy to administer. In addition, expectations were that data on some items, such as those related to health care events, would be more complete with the potential of identifying more events. Increases in service use reported since the implementation of these changes are consistent with these expectations. Data users should be aware of possible impacts on the data and especially trend analyses for these data years due to the design transition.

Process changes, such as data editing and imputation, may also affect trend analyses. For example, users should refer to Section 2.5.11 in the 2021 Full Year Consolidated file (HC-233) and, for more detail, the documentation for the prescription drug file (HC-229A) when analyzing prescription drug spending over time.

As always, it is recommended that data users review relevant sections of the documentation for descriptions of these types of changes that might affect the interpretation of changes over time before undertaking trend analyses.

Analysts may also wish to consider using statistical techniques to smooth or stabilize analyses of trends using MEPS data such as comparing pooled time periods (e.g. 1996-1997 versus 2011-2012), 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, statistical significance tests should be conducted to assess the likelihood that observed trends are not attributable to sampling variation. In addition, researchers should be aware of the impact of multiple comparisons on Type I error. Without making appropriate allowance for multiple comparisons, undertaking numerous statistical significance tests of trends increases the likelihood of concluding that a change has taken place when one has not.

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4.0 National Health Interview Survey (NHIS)

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 MEPS/NHIS link files please see the AHRQ website.

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5.0 Longitudinal Analysis

Panel-specific longitudinal files are available for downloading in the data section of the MEPS website. For all four panels (Panel 23, Panel 24, Panel 25, and Panel 26), the longitudinal file comprises MEPS survey data obtained in all rounds of the panel and can be used to analyze changes over the entire length of the panel. For Panel 24, a file representing a three-year period will also be established and updated to cover four years with the release of 2022 data. For Panel 23, a file representing a four-year period will be established. Variables in the file pertaining to survey administration, demographics, employment, health status, disability days, quality of care, patient satisfaction, health insurance, and medical care use and expenditures were obtained from the MEPS full-year Consolidated files from the years covered by each panel. For more details or to download the data files, please see Longitudinal Data Files at the AHRQ website.

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References

Bramlett, M.D., Dahlhamer, J.M., & Bose, J. (2021, September). Weighting Procedures and Bias Assessment for the 2020 National Health Interview Survey.Centers for Disease Control and Prevention.

Chowdhury, S.R., Machlin, S.R. & Gwet, K.L. Sample Designs of the Medical Expenditure Panel Survey Household Component, 1996-2006 and 2007-2016. Methodology Report #33. January 2019. Agency for Healthcare Research and Quality, Rockville, MD.

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

Current Population Survey: 2021 Annual Social and Economic (ASEC) Supplement. (2021). U.S. Census Bureau.

Dahlhamer, J.M., Bramlett, M.D., Maitland, A., & Blumberg, S.J. (2021). Preliminary evaluation of nonresponse bias due to the COVID-19 pandemic on National Health Interview Survey estimates, April-June 2020. National Center for Health Statistics.

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

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

Johnson, Ayah E., and Sanchez, Maria Elena. (1993), “Household and Medical Reports on Medical Conditions: National Medical Expenditure Survey.” Journal of Economic and Social Measurement, 19, 199-223.

Lau, D.T., Sosa, P., Dasgupta, N., & He, H. (2021). Impact of the COVID-19 Pandemic on Public Health Surveillance and Survey Data Collections in the United States.American Journal of Public Health, 111 (12), pp. 2118-2121.

Rothbaum, J. & Bee, A. (2021, May 3). Coronavirus Infects Surveys, Too: Survey Nonresponse Bias and the Coronavirus Pandemic. U.S. Census Bureau.

Rothbaum, J. & Bee, A. (2022, September 13). How Has the Pandemic Continued to Affect Survey Response? Using Administrative Data to Evaluate Nonresponse in the 2022 Current Population Survey Annual Social and Economic Supplement. U.S. Census Bureau.

Zuvekas, S.H. & Kashihara, D. (2021). The Impacts of the COVID-19 Pandemic on the Medical Expenditure Panel Survey. American Journal of Public Health, 111 (12), pp. 2157-2166.

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D. Variable-Source Crosswalk