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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Medical Expenditure Panel Survey (MEPS)

Basic Information
Dataset Full Name Medical Expenditure Panel Survey
Dataset Acronym MEPS
Summary

The MEPS is a multi-component national probability sample survey of individuals, families, health care providers, and employers across the United States. This survey was initiated in 1996 with the purpose of providing national-level estimates of health care utilization, health care access, expenditures, and health insurance coverage of the non-institutionalized U.S. civilian population. The MEPS has three major components:

(1) MEPS Household Component - MEPS HC;

(2) MEPS Medical Provider Component - MEPS MPC; and

(3) MEPS Insurance/Employer Component - MEPS IC.

The MEPS HC has been extensively used by researchers as it is a public-use dataset containing key variables of interest; all other MEPS components are only available as restricted-use files.
Key Terms Health Care Expenditure, Health Care Access, Health Care Utilization, Health Insurance and Coverage, Chronic Conditions
Study Design Longitudinal
Data Type(s) Survey
Sponsoring Agency/Entity

Department of Health and Human Services (HHS):

Agency for Healthcare Research and Quality (AHRQ)
Health Conditions/Disability Measures
Health Condition(s)

MEPS "priority conditions"  include: Arthritis, Alzheimer’s/dementia, Anxiety disorders, Cancer, Depression, Diabetes, Stroke 

Detailed health condition data are collected from household respondents as verbatim text  during each round and then coded by professional coders using ICD-9 diagnostic codes (available in the data)
Disability Measures

ACS 6 question disability series, Ambulatory disability, Asthma, Cognitive disability, Functional limitations (ADLs & IADLs), Hearing disability, Independent living disability, Mental health disability, Physical disability, Self-care disability, Special equipment use/assistive technology, Visual disability, Work limitation
Measures/Outcomes of Interest
Topics Health care expenditure, Out-of-pocket payments, Health insurance, Health care access and utilization, Emergency room visits, Inpatient visits, Hospital stay, Dental visits, Outpatient visits, Outpatient procedures, Employment, Obesity, Health behaviors
Sample
Sample Population Civilian households and non-institutionalized group quarters
Sample Size/Notes

A new panel of households is selected each year for inclusion in the MEPS HC from a subsample of the previous year’s NHIS households with oversampling of low-income households. The households participate in five rounds of interviews over two years.  In any given year, the MEPS HC is comprised of two overlapping panels that yield a combined annual sample size of approximately 15,000 households. 
Unit of Observation Individual
Continent(s) North America
Countries

United States
Geographic Coverage National
Geographic Specificity National-level estimates; some state-level estimates possible with pooling of data across several years (may not be very reliable)
Data Collection
Data Collection Mode In-person interviews administered to household representative (age equal to or greater than age of majority) by trained interviewers from U.S. Census Bureau.  One random sample adult from household is interviewed to document adult health status and data is collected on one random household child from an adult household informant.
Years Collected 1996 - present
Data Collection Frequency Annual
Strengths and Limitations
Strengths Only nationally representative dataset collecting information on health care use, expenditure, access to health care and health insurance, ADL and IADL variables. Self-reported medical conditions coded into ICD-9 format allowing a better understanding of disease condition. Detailed information on jobs held. longitudinal panel design allows for estimating changes over two year period for each panel. NHIS MEPS linkages provides further follow-up on common areas. Oversampling of individuals below 200% of the Federal Poverty Line (FPL) provides better estimate of this group
Limitations Only national level statistics.  State-level statistics are possible by pooling data cross years, but they are not very reliable. Does not include population living in institutionalized group quarters. MEPS IC and MEPS MPC components are restricted user files and difficult to access.
Data Details
Primary Website

https://meps.ahrq.gov/mepsweb/
Data Access

https://meps.ahrq.gov/mepsweb/data_stats/download_data_files.jsp
Data Access Requirements

Public Use Dataset:

  • MEPS HC files

Data Use agreement No cost:

  • MEPS HC files with fully-specified ICD-9 diagnostic codes
  • all MEPS IC and MEPS MPC files
Summary Tables/Reports

Summary Data tables:

https://meps.ahrq.gov/mepsweb/data_stats/quick_tables.jsp
Data Components
  • MEPS Household Component - MEPS HC; 
  • MEPS Medical Provider Component - MEPS MPC;
  • MEPS Insurance/Employer Component - MEPS IC
Selected Papers
Other Papers
Technical

Multiple technical reports on methodology

https://meps.ahrq.gov/mepsweb/data_stats/Pub_ProdLookup_Results.jsp?AuthorString=&TitleString=&pubStartDate=&pubEndDate=&mr=1&SearchButton2=Search

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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

Other CLDR supported resources and collaborative opportunities:

Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

For questions or comments please contact disabilitystatistics@cornell.edu



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