NORC - The Nonpartisan and Objective Research Organization NORC at the University of Chicago

General description

1. Database primary purpose - Disseminate key information to individuals all around the country and the entire world
2. Overall data type - Health outcomes
3. Dataset type - Cross-sectional
4. Data source - Survey
5. Data level - Patient level
6. Geographic location of the data collection sites - United States (the 50 states and the District of Columbia)
7. Sponsor, manager, or home institution - NORC at University of Chicago
8. Date range - 2021
9. Geolocation data - State and census region
10. Clinical areas of interest - all
11. Number of records - The following studies are available:

• Long-Term Care in America: Americans Want to Age at Home - 1,113 adults age 18 and older representing the 50 states and the District of Columbia completed the survey
• Long-term care in America: how well can communities support ageing at home? - 1,071 adults aged 18 and older completed the survey
• Coronavirus worries and social isolation among older adults - 1,015 adults aged 50 and older completed the survey
• Telehealth and equity - 1,000 adults age 50 and older completed the survey
• Most Americans Agree that Nurses and Aides are Underpaid, While Few Support Using Federal Dollars to Increase Pay for Doctors - 1,071 adults age 18 and older completed the survey
• June 21 PUF - 1,125 adults aged 18 and over

12. Variables that are uniquely present in this dataset - The panel provides sample coverage of approximately 97% of the U.S. household population
13. Database caveats and limitations - Were excluded from the sample: people with P.O. Box only addresses, some addresses not listed in the USPS Delivery Sequence File, some newly constructed dwellings population, adults age 50 and older who live in some institutional types of settings (e.g., skilled nursing facilities or nursing homes)

Applicable methods

1. Association methods, such as logistic regression models (1, 2), linear regression (3, 4)
2. Cluster analysis (5)
3. Exploratory analysis (6, 7)
4. Machine learning (8)
5. Propensity scores (9)
6. Sensitivity analysis (10)
7. Structural equation model (11)

Data dictionary

To access the NORC data dictionary, click here

Variable categories

1. Patient demographics (e.g., age, sex, race, ethnicity, marital status, household income, employment status)
2. Healthcare receiving (e.g., concerns or issues regarding provider, coverage, scheduling, information security)
3. Retirement community/nursing home (e.g., patient feelings, concerns, preferences)
4. Telehealth access (e.g., high-speed internet access, devices)
5. COVID-19 (e.g., being infected, vaccinated)