Blog & News
Now Available on State Health Compare: New 2022 Estimates from the ACS and CPS
March 04, 2024:
2022 estimates from the American Community Survey (ACS) and Current Population Survey (CPS) are now available for eight measures on SHADAC’s State Health Compare.
Updated measures using new ACS data include:
Coverage Type
Health insurance coverage by type of coverage (private, public, employer-sponsored, Medicare, Medicaid/CHIP, individual, and uninsured) available by a variety of breakdowns, including by income, disability status, race/ethnicity, and more.
Broadband Internet Access
This measure allows the user to view state-level percentages of people who have access to high-speed internet, which is an increasingly important tool for individuals to access health care (via telehealth), find employment, and connect with a range of other services. The measure has multiple layers of breakdowns by income, disability status, and metropolitan status, among others.
Child Poverty
Children who experience poverty can be more prone to many different negative health outcomes, often lacking in access to health care, education, shelter, sanitation, and more compared to children not considered to be in poverty. This is a vulnerable population that needs to be monitored continuously. This measure provides state-level data on children <100% Federal Poverty Guideline for both the total population and by race and ethnicity.
Income Inequality
Lower incomes are correlated to effects like housing instability, food insecurity, and more that can lead to negative health outcomes. This measure presents state-level data on income inequality as measured by the Gini coefficient.
Unaffordable Rents
Stable housing is a key component of health and wellbeing. Unaffordable Rents on State Health Compare measures the share of renters who may be struggling to afford their rents, thus contributing to unstable housing. This measure is available by a number of policy-relevant breakdowns, including race/ethnicity, Medicaid enrollment, and household income.
Updated measures using new CPS data include:
Percent of People with High Medical Cost Burden
Out-of-pocket spending on health care can make up a large share of income, creating burdens for those with large health care expenses. This measure can help us understand trends and disparities in healthcare affordability. These data are available both by insurance coverage type and by race/ethnicity.
Median Medical Out-of-Pocket (OOP) Spending
This measure shows the amount that the typical individual spends using their own money on health care costs, including health insurance coverage premiums, forms of insurance cost sharing (e.g., co-pays, deductibles), and services not covered by health insurance and/or paid by uninsured individuals. The 2022 estimates are available to be viewed by total and specifically by those with employer-sponsored insurance.
Health Status
Stable housing is a key component of health and wellbeing. Unaffordable Rents on State Health Compare measures the share of renters who may be struggling to afford their rents, thus contributing to unstable housing. This measure is available by a number of policy-relevant breakdowns, including race/ethnicity, Medicaid enrollment, and household income.
Be sure to check out a recent analysis of new data where we add context to the Health Insurance Coverage by Race/Ethnicity measure.
Other Related Reading:
Publication
Using Enrollment Records to Evaluate Self-Reports of Monthly Coverage in the Redesigned Current Population Survey Health Insurance Module
This journal article was originally published on January 23, 2024, in Health Services Research.
Introduction
This article, authored by SHADAC Investigator Dr. Kathleen T. Call alongside colleagues from the U.S. Census Bureau Angela R. Fertig and Joanne Pascale, explores the veracity of self-reports of month-level health insurance coverage in the Current Population Survey Annual Social and Economic Supplement (CPS ASEC).
The CHIME (Comparing Health Insurance Measurement Error) study used health insurance enrollment records from a large regional Midwest insurer as the sample for primary data collection in spring of 2015. In this study, a sample of individuals enrolled in a range of public and private coverage types (including Medicaid and marketplace) was administered the CPS health insurance module, which included questions about month-level coverage, by type, over a 17–18-month time span. Survey data was then matched to enrollment records covering that same time frame, and concordance between the records and self-reports was assessed.
Principal Findings
For 91% of the overall sample, coverage status and type were reported accurately for at least 75% of observed months.
Among those who were continuously covered throughout the 17–18 month observation period (64% of the overall sample), that level of reporting accuracy was observed for 94% of the sample. For those who had censored spells (34% of the overall sample), the figure was 87%. Among those with gaps and/or changes according to the records (2% of the overall sample), for 82% of the group at least 75% of months were reported accurately.
These findings suggest that reporting accuracy of month-level coverage is high - thus, this survey could become a new data source for studying overall dynamics of health insurance coverage, namely the Medicaid unwinding.
To read the full article, visit this link.
Learn more about: