Lukanen, Elizabeth
Stewart, Andrea

2023 NHIS Early Release: Estimates from Quarter 3 (July to September) Hold Steady

The National Center for Health Statistics (NCHS) has released quarterly estimates of health insurance coverage beginning in July 2022 through September 2023 from the National Health Interview Survey (NHIS) as part of the NHIS Early Release Program. Each quarter covers a three-month span, and this blog specifically looks at survey data from the most recent quarter (Q3 - July to September 2023) and notes any differences compared to the same time period in 2022.

Between Q3 of 2022 and Q3 of 2023, rates of uninsurance, public coverage, and private coverage for adults (age 18-64) remained mostly unchanged. There was a small increase in the rate of public coverage for all ages and a small decrease in the rate of uninsurance overall, but these changes were not statistically significant.

Figure 1: Health Insurance Coverage Rates by Type (Adults Age 18-64), Q3 2022 vs. Q3 2023

Walsh, Elliot
Research Dissemination Coordinator

e wals0421@umn.edu

Minnesota Community and Uninsured Profile Updated to Include 2022 American Community Survey Estimates

• Provide information on Minnesota uninsured people and populations 
• Assist policymakers in developing & evaluating enrollment and outreach strategies
• Understand uninsured community and population characteristics in Minnesota
• Create a tool that can be used to understand and evaluate equity work, inform strategic planning, assess community needs, and support grant writing for related and relevant programs

• How to Use - an overview on using the uninsured profile to both identify and gather information communities of interest
• Community and Uninsured Profile - the profile itself with breakdowns at the county, MNsure rating area, ZIP code, economic development region, and state levels
• ZIP Code Uninsured Rates - includes all reported Census-defined ZIP Codes, regions, and counties in Minnesota along with both the number and percent of uninsured within those communities

Interactive Map

Learn more about the profile and download the data here, where you can also find out how to use the profile, including a tutorial video.

Want to learn more about how we made this profile? Curious about its applications? Contact us here – we are always happy to discuss.

Natalie Mac Arthur
Senior Research Associate

e shadac@umn.edu

New Data on Health Insurance Coverage by Race/Ethnicity Added to State Health Compare

State Health Access Data Assistance Center (SHADAC) has added two new racial/ethnic population groups to our measures of health insurance coverage available on State Health Compare.

Using micro-data from the American Community Survey (ACS), we were able to add health insurance coverage measures for American Indian/Alaska Native (AIAN) and Native Hawaiian Pacific Islander (NHPI) populations. Specifically, SHADAC has added insurance coverage data for AIAN and NHPI populations at both the national and state level (when sample size permits) from the years 2008-2022. Estimates for these groups are also available by age and poverty status.

This update now allows users to download estimates of insurance coverage for all of the minimum race categories for data collection outlined by the Office of Management and Budget (OMB), which are: American Indian or Alaska Native (AIAN), Asian, Black or African American, Native Hawaiian or Other Pacific Islander (NHPI), and White.

In this analysis, we used this newly available data from State Health Compare to examine differences in uninsurance from 2021 to 2022 by race/ethnicity for adults ages 19-64. Over this period, the overall uninsured rate for non-elderly adults dropped nearly a percentage point, reaching 11.2%. The largest drop in uninsurance was seen among AIAN adults, lowering by 2.4 percentage points. Hispanic and Black adults also saw improvements in coverage of greater than one percentage point (1.5 and 1.3 percentage points, respectively). More modest gains in coverage were reported by adults who were White, Asian, and Other/Multiple races.

Significant decreases were seen consistently across populations by race/ethnicity except for the NHPI adult population, which did not see this same decrease in uninsurance. While estimates were limited by sample size and changes were not significant, uninsurance rates for this group increased from 12.1% to 13.6%. These concerning rates of uninsured NHPI adults contrasted with the overall trend of decreased uninsurance rates and thus warrant further observation.

While encouraging to see a trend of decreasing uninsurance amongst non-elderly adults, disparities in insurance coverage between racial/ethnic groups are persistent. For example, in 2022, more than one in five adults were uninsured among both the Hispanic/Latino and AIAN populations. Uninsurance was also high for NHPI and Black adults, at 13.6% and 12.1%, respectively. The substantial differences in coverage between racial/ethnic populations illustrate the ongoing priority of improving health equity, including health care access. We plan to continue monitoring insurance coverage in light of ongoing post-pandemic policy changes. Providing more granular estimates by race/ethnicity will support efforts to understand and reduce disparities in health care access.

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.

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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.

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Learn more about:

• The Medicaid Unwinding
• Current Population Survey data
• Other CHIME products

SHADAC’s Primary Source of Coverage Hierarchy for American Community Survey (ACS) Estimates on State Health Compare

January 2024:

This updated brief from SHADAC defines a “primary source of coverage hierarchy,” and how and when researchers can use this tool to determine which payer is primary when an individual reports multiple sources of health insurance coverage on the American Community Survey (ACS).

Using a hierarchy provides multiple benefits for researchers, including the ability to ensure that individuals who report having multiple types of coverage are only counted once, reducing the rate of over-reporting for a specific type of coverage, and making coverage estimates more comparable across different surveys. However, SHADAC researchers caution that there is not one specific, singular hierarchy that should always be imposed; rather, there are a multiplicity of possible hierarchies with orders of coverage varying based on the research focus and requirements of each individual analysis (e.g., if a researcher would like to look at a range of coverage over time, or examine coverage for a singular year or specific subpopulations).

When performing national, state, and sub-state analysis of ACS coverage data, SHADAC imposes a particular coverage hierarchy that places respondents into two categories, age 0-18 and age 19 and older, and then ranks possible coverage options—Medicare, Medicaid/CHIP, Employer/Military (TRICARE, VA), Direct purchase, and Uninsured —in descending order for which respondents in each age group will be sorted.

The reason for this separation by age is that for all adults age 19 and older, Medicare is considered the primary source as it is the primary payer for covered medical services. Children age 0-18 are not eligible for Medicare (except in one rare and specific instance) and therefore Employer/Military is considered primary, as many dependents draw this source of coverage from an adult parent or caregiver.

In addition to exploring the different hierarchy possibilities, the brief also walks the user through an example application of SHADAC’s coverage hierarchy on data from the 2022 American Community Survey, and how this affects the rates of reported coverage for each insurance source for the two age groups, both separately and together.

For more on the data produced using SHADAC’s primary source of coverage hierarchy, visit our State Health Compare web tool and explore the “Health Insurance Coverage Type” measure.

Download a PDF of SHADAC’s Coverage Hierarchy for American Community Survey (ACS) Estimates on State Health Compare brief.