Understanding the High Prevalence of Low-Prevalence Chronic Disease Combinations: Databases and Methods for Research. University of Michigan Dataset


Health & Retirement Study
Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations & Multiple Chronic Conditions and Disparities.
Sponsorship: University of Michigan
Description: The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 27,000 Americans over the age of 50 every two years. This study is supported by the National Institute on Aging and the Social Security Administration and is designed to examine changes in labor force participation and the health transitions that individuals experience at the end of their working lives and into the years that follow. It is the leading resource for data on combined health and economic circumstance of Americans over the age of 50.
Database: (Scope, Size, Setting, Population, Age Range) The HRS study surveys more than 27,000 Americans over the age of 50 who represent the Nation’s diversity of economic conditions, racial and ethnic backgrounds, health, marital histories and family compositions, occupations and employment histories, living arrangements, and other aspects of life. As individuals drop out of the sample, they are replaced by new participants in their 50’s; it is nationally representative of the U.S. population over age 50.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) Research study and associated database.
Database Source/Origin: Participant Interviews
Date or Frequency of Data Collection: Interviews are conducted every two years.
Longitudinal vs. Cross-sectional Database: This is a longitudinal panel survey that following individuals over multiple years.
Data Collection Methodology: The majority of interviews are done by telephone, although exceptions are made when respondents have health limitations that would make an hour-long session on the telephone difficult of impossible. The preferred mode of data collection is face-to-face for the first wave of data collect, followed by subsequent waves of data collection conducted over the phone.
Sampling Strategy: HRS uses a national area probability sample of U.S. households with supplemental oversamples of Blacks, Hispanics and residents of the state of Florida. Participation in this study/survey is optional, but there are incentives.
Unit of Analysis: Individual
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis) Self-reported Diagnosis
Diagnosis Codes: (ICD-9, ICD-10, SNOMED) Self-reported Diagnosis
Number of Diagnoses Captured: n/a
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) Out-of-pocket expenditures
Measures of Healthcare Utilization: (Number of Visits, Any Procedures/Number of Procedures/Type of Procedure, Number of Admission/Type of Admission, Length of Stay, Hospitalizations, Emergency Department Utilization, etc.) Health Service Use by Type (i.e. Hospital, Nursing Home, etc.), Number of visits, etc.
Measures of Healthcare Access: n/a
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Age, Educational Attainment, Disability Status, Race, Ethnicity, Language, Sex, and Marital Status.
Clinical Information: (BMI, Medical Conditions [high blood pressure], Smoker Status, History of Various Conditions, Preventative Health Measures , Activities of Daily Living, Instrumental Activities of Daily Living) Disease history, Medicare Use, Physical Activity, Height, Weight, Measurements of Lung Function, Blood Pressure, Grip Strength, and Walking Speed.
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) Occupation, Employment Status, Income
Site of Service Information: Location of Health Service Type
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions) Self-reported health status and measure of functional status.
Strengths, Limitations & Feasibility
Data Strengths: There are multiple years of data available (longitudinal data). Comprehensive documentation is available for all respondents across a variety of key policy issues. There is a low sample attrition rate.
Data Limitations: Limited granularity in diagnosis coding, unless linked with Medicare claims data.
Data Access Restrictions: Data are available to the public at no cost. Detailed race/ethnicity data are available on a restricted basis.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) Respondent information can be linked to social security data, Medicare claims data and supplemental employer surveys.
Related Grouping Systems: n/a


National Institute on Aging, National Institutes of Health, U.S. Department of Health and Human Services. Growing Older in America: The Health & Retirement Study. 2007. NIH Publication No. 07-5757


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