In this post, we will examine this newly released 2023 NHIS data, delving into demographic breakdowns and their impacts on uninsurance rates.

All Age Groups Saw Uninsured Rates Fall in 2023

The uninsured rate for all ages was 7.6% in 2023 -- a statistically significant change from a rate of 8.4% in 2022, representing 2.6 million people.

Figure 1: Rates of Public, Private, and Uninsured for All Age Groups in 2023

Source: SHADAC analysis of health insurance coverage data from the 2023 National Health Interview Survey (NHIS).

*Statistically significant change at the 95% confidence level. 

Rates of public and private insurance coverage were statistically unchanged across all ages from 2022 to 2023, however; with the former coming in at a rate of 40.5% in 2023 (39.5% in 2022) and the latter showing at 60.7% in 2023 (61% in 2022).

Uninsured Rates Fell for Subgroups of Nonelderly Adults (18-64)

Nonelderly adults (age 18 to 64) saw the most coverage changes across demographic categories from 2022 to 2023. Overall, their uninsured rate fell significantly from 12.2% in 2022 to 10.9% in 2023.

Figure 2: Public, Private, and Uninsured Rates for Nonelderly Adults (Age 18-64)

Source: SHADAC analysis of health insurance coverage data from the 2023 National Health Interview Survey (NHIS).

*Statistically significant change at the 95% confidence level. 

Nonelderly adults were also the group that most consistently saw changes by demographic category.

Family Income (Poverty Status)  

Of the four family income levels measured as a percentage of poverty status, two of those showed nonelderly adults experiencing significant decreases in uninsured rates from 2022 to 2023. For those whose income measured 100-199% of the Federal Poverty Level (FPL), uninsurance dropped from 22.3% to 19.1% between the two years, and for those in the 200-400% FPL category, uninsurance dropped from 14.2% to 11.5%.

Figure 3: Nonelderly Adults Uninsurance Rate by Family Income Levels Measures as a Percentage of Poverty Status

Source: SHADAC analysis of health insurance coverage data from the 2023 National Health Interview Survey (NHIS).

*Statistically significant change at the 95% confidence level. 

Also of note for this age group: nonelderly adults with income measuring 200-400% FPL saw a significant rise in private insurance coverage, increasing from 68.7% in 2022 to 71.1% in 2023 – the only statistically significant change by poverty status for ay type of coverage other than uninsurance.

Race/Ethnicity

Changes in health insurance coverage type for nonelderly adults (18-64) between 2022 and 2023 were much more varied when examining rates for different racial and ethnic groups.

For instance, both Asian nonelderly adults and Black nonelderly adults saw significant decreases in uninsured rates, falling from 7.1% (2022) to 4.4% (2023) for the former and 13.3% (2022) to 10.4% (2023) for the latter.

Figure 4: Nonelderly Adults Uninsurance Rate by Race/Ethnicity

Source: SHADAC analysis of health insurance coverage data from the 2023 National Health Interview Survey (NHIS).

*Statistically significant change at the 95% confidence level. 

Asian nonelderly adults also saw a rise in private coverage, increasing from 75.5% in 2022 to 80.3% in 2023.

Another notable increase was the rise in public coverage for Hispanic nonelderly adults in 2023, measuring at 27.5% from a rate of 23.7% in 2022.

Other Demographic Categories

The 2023 NHIS Early Estimate report also contains data about health insurance coverage estimates by sex and by state Medicaid Expansion status. However, no statistically significant changes were found for either of these categories for any type of coverage (no coverage, public coverage, private coverage) or for any age group (Under 65, 0-17, 18-64).

Notes About the Estimates

All changes described compare full-year 2022 data to full-year 2023 data and are statistically significant at the 95% confidence level unless otherwise specified.

All category breakdowns (Sex, Income, Race/Ethnicity, and Medicaid Expansion Status) refer to nonelderly adults, age 0-64, since adults 65 and older are eligible for Medicare (which tends to be their primary source of coverage). Thus, they represent a very small portion of the NHIS data for other coverage types that is unable to be broken down into subcategories.

The estimates provide a point-in-time measure of health insurance coverage, indicating the percent of persons with that type of coverage at the time of the interview.

**The health insurance data from the NHIS data are the first coverage estimates from 2023, the year in which the process commonly known as or referred to as the “Medicaid unwinding” began. The unwinding refers to the end of the requirement that Medicaid coverage for current enrollees be automatically renewed. This requirement ended on March 31, 2023, and on April 1, 2023, states began redetermination processes. Because of this mid-year shift, 2023 full-year estimates may not fully reflect the impact of the unwinding on health insurance coverage changes. 

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Upcoming and Related Products    

As noted earlier, these health insurance data from the NHIS are the first coverage estimates that reflect the full year of 2023. Data from other major federal surveys – the Medical Expenditure Panel Survey (MEPS), the Behavior Risk Factor Surveillance Systems (BRFSS), the Current Population Survey (CPS), and the American Community Survey (ACS) – will be released over the coming few months, culminating in September.

SHADAC will be covering each of these releases, as we do every year, with a blog, infographic, report, or other product that shares key findings or important data to note from all surveys. Continue to follow us for more information, and watch for notices about our annual webinar with the U.S. Census Bureau, where they will talk more in depth about estimates from two surveys they manage – the ACS and the CPS.

Head over to this page to find an archive of all products released as a part of this ‘Fall Data Release’ series.

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There were, however, statistically significant decreases in uninsurance rates for those with family incomes of 200-400% of the federal poverty level (FPL) across all ages and for every age group (under 65, 0-17, 18-64). The rate of public coverage saw a statistically significant decrease in Black, non-Hispanic adults and a statistically significant increase in Hispanic adults, and the rate of private coverage saw a statistically significant increase in adults with a family income of 200-400% of the FPL, Asian, non-Hispanic adults, and in the South. 

 

Interested in learning more about the NHIS? Check out some of the following SHADAC products:

 

State Health Compare is a user-friendly data tool that allows users to obtain state-level estimates related to health, health care, insurance coverage, health equity, and more. This tool provides interactive maps, graphs, and downloadable data for over 40 measures ranging from telehealth visit data to insurance coverage data to cancer screening data and more.

 

SHADAC researchers update these measures regularly to provide users with the most up-to-date data available. Recently, 9 measures were updated using a variety of data sources, including the National Survey of Children’s Health (NSCH), National Health Interview Survey (NHIS), Drug Enforcement Administration Automated Reports and Consolidated Ordering System (ARCOS) data, and data from the Bureau of Labor Statistics.

 

In this post, we will go over each of the updated measures broken down by each data source used.

NSCH Data was used to update the Adverse Childhood Experiences measure.

Adverse Childhood Experiences (ACEs) are traumatic events that occur during childhood, and include physical and emotional abuse, neglect, and household dysfunction, amongst others. These experiences can have long-term impacts on health and wellness long after childhood.

 

On this measure, updated with 2021-2022 data, users can explore data on the percent of children that have experiences ACEs by race/ethnicity, state, insurance coverage type, number of ACEs, age, and more. Explore the measure here, and learn more about ACEs in our brief titled: The Kids Aren’t Alright: Adverse Childhood Experiences and Implications for Health Equity. 

2021-2022 NHIS data was used to update the following measures:

‘Made Changes to Medical Drugs’ is defined as the rate of individuals who made changes to medical drugs because of cost during the past twelve months by age for the civilian non-institutionalized population. Asking a medical provider to switch to a cheaper medication, taking less medication than prescribed, skipping dosages, using alternative therapies as a replacement, and delaying refills are all examples of how someone could make changes to medical drugs due to cost. Making changes such as these can have negative impacts on both short- and long-term health.

 

Measuring changes in medical drugs sheds light on cost of care, health care accessibility, and overall health care affordability in the United States. Explore this measure here with breakdowns by state, age, and insurance coverage type.

This measure tracks the percentage of people who had trouble paying off their medical bills in the last year. Like the ‘Made Changes to Medical Drugs’ measure, this can help understand and track health care affordability in the United States. This is especially relevant as the United States has some of the highest health care costs in the world.

 

Explore this measure here with breakdowns by state, age, and insurance coverage type.

Visits to the Emergency Department (ED) (also called the Emergency Room) are often costly and, in a surprisingly large number of cases, preventable. It’s estimated that between 13% and 27% of ED visits could be managed in primary care offices, clinics, and/or urgent care centers. 

 

Preventable ED visits can be a result of lack of access to primary care physicians or other health care options, a lack of understanding of how the medical system works, poor care management, and more. These visits are more expensive than a primary care visit would be and can affect the overall efficiency of the ED itself for both providers and other patients.

 

This updated measure on State Health Compare monitors the percentage of people who visit the ED each year. This information can help researchers and policymakers better understand ED utilization to uncover any trends or potential underlying causes resulting in these visits. Explore this measure here with breakdowns by state, age, and insurance coverage type.

Telehealth, also called telemedicine, can expand access to care for many individuals and communities. Telehealth services conducted by phone or by video allow individuals to be connected with a health professional when they cannot get an in-person appointment, cannot safely leave their home, or lack transportation to get to an appointment, among a number of other reasons. Access to telehealth was expanded during the COVID-19 pandemic and has remained a popular way to access care.

 

This measure monitors the percentage of people who had a medical appointment by video or phone in the past year. This measure can also be broken down by state, age, and insurance coverage type.

When individuals do not have a usual source of medical care, health outcomes can be affected. For example, individuals may not seek care when they have a medical issue, which can result in delayed diagnosis of disease, worsening health conditions, etc. Lacking a usual source of care also means that people may miss out on preventative services and/or recommended screenings (like cancer screenings). They may also seek care in an Emergency Department, which we discussed earlier as being more costly and inefficient for both patients and health professionals.

 

This updated measure on State Health Compare tracks the percentage of people who had a usual source of medical care other than the emergency department in the past year by state, age, and insurance coverage type.

Utilization of health care services with a general doctor or provider is an important health-related behavior – seeing a general doctor allows individuals to obtain information about their health status, receive preventative services & screenings, maintain (or improve) their health and well-being, and respond to health problems with guidance from a professional health care provider. Seeing a provider can also form a relationship between patient and doctor/provider, where the doctor knows and monitors the patient over time.

 

However, as we discussed earlier in this post, there are many barriers that prevent individuals from seeing a general doctor or other health care provider, such as the cost of care, lack of transportation, uninsurance, a distrust of the medical system, or a lack of providers in their area, among others. 

 

This updated measure shows the percentage of people who report having a general doctor or provider visit in the last year. This helps in identifying gaps in health care access among subgroups, including by state, age, and coverage type on State Health Compare.

DEA ARCOS Data was used to update the ‘Sales of Opioid Painkillers’ measure.

The Opioid Epidemic in the United States is widespread and destructive - since 2000, the annual number of overdose deaths from any kind of drug in the U.S. has multiplied nearly six times over, rising from 17,500 to over 106,000 people in 2021. Opioids caused a majority of these deaths, including both legal drugs and illicit drugs like heroin and fentanyl.

 

Opioid painkillers, while oftentimes obtained and used legally to manage pain and chronic illness, are addictive and can lead to substance abuse, overdose, and use of other opioid drugs when prescriptions run out. Understanding sales of these painkillers can help us understand how many people are using these drugs along with where the demand lies amongst various regions and populations.

 

This updated measure on State Health Compare tracks prescription opioid painkiller (oxycodone and hydrocodone) sales in kilograms per 100,000 people by state and by drug. Explore the updated measure here.

Data from the Bureau of Labor Statistics was used to update the ‘Unemployment Rate’ measure.

During the COVID-19 pandemic, the unemployment rate in the United States peaked at 14.8% in April 2020, which is the highest unemployment rate since 1948 (when unemployment data collection first began). 

 

While this rate has decreased since, unemployment rate ranges when examined by state and by subpopulation, like by race/ethnicity. This measure has been updated with 2023 data – explore it here. You can also read our researchers’ analysis of this data in our blog post on Unemployment Rate Trends of the Last 5 years.

SHADAC researchers are consistently adding and updating each of the measures on State Health Compare as new data is collected and released. To stay up to date on the latest info, check our blog regularly for SHC measure updates like this, or you can sign up for our newsletter to get notified of our newest products and updates.

- Now Available on State Health Compare: New 2022 Estimates from the ACS and CPS  

 

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

 

- Housing Affordability Matters: Unaffordable Rents Infographics Updated with 2022 Data 

There were, however, statistically significant decreases in uninsurance rates among adults with a family income of 200-400% of the federal poverty level (FPL), and non-Hispanic, Asian adults. Regionally, rates of uninsurance and public coverage were unchanged from 2022 to 2023. The rate of public coverage saw a statistically significant decrease in the Northeast, but otherwise remained unchanged.

 

In April 2022, states resumed normal eligibility redetermination procedures for Medicaid enrollees, a process put on hold during the pandemic - commonly known as “the Medicaid unwinding,” or simply “the unwinding.” Evidence from administrative data suggests that many people have lost Medicaid coverage during this process.¹  While these newly released Q3 data include a portion of the unwinding period, these coverages shifts are not being detected. We will need to continue to monitor federal survey data to gain more information into the coverage impacts of the unwinding process.

 

For some of SHADAC’s work in this area that uses other survey sources, please see our Tracking Health Insurance Coverage During the Unwinding: Monthly Data from the Household Pulse Survey blog post where we monitor Household Pulse survey data.

 

You can also learn more on this topic via our blog series that was produced for State Health & Value Strategies (SHVS):

 

• State-Based Marketplace Transition Data During the Unwinding (Cross-Post)

• State Dashboards to Monitor the Unwinding of the Medicaid Continuous Coverage Requirement (Cross-Post)

• States Reporting of Medicaid Unwinding Reinstatement Data (Cross-Post)

 

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[1] Centers for Medicare & Medicaid Services (CMS). (2023, December 18). Medicaid and CHIP Enrollment: Child and Youth Data Snapshot. https://www.medicaid.gov/sites/default/files/2023-12/medicaid-unwinding-child-data-snapshot.pdf