VISIT STATE HEALTH COMPARE
Blog & News
2023 NHIS Full-Year Health Insurance Estimates Early Release: Decreasing Uninsured Rates Overall and for Certain Groups of Nonelderly Adults
August 28, 2024:
This post is a part of our Survey Data Season series where we examine data from various surveys that are released annually from the summer through early fall. Find all of the Survey Data Season series posts on our Survey Data Season 2024 page here.
In late June, the National Center for Health Statistics (NCHS) released health insurance coverage estimates for 2023 from the National Health Interview Survey (NHIS) as part of the NHIS Early Release Program. The rates of insurance and uninsurance captured in this report are some of the first available coverage estimates for 2023 from a federal survey.**
National-level estimates are available by breakdowns including age, sex, family income (as a measure of poverty status), race and ethnicity, and by state Medicaid expansion status.[1]
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.
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.
Source
Cohen, R.A., Briones, E.M., & Martinez, M.E. (2024, June 18). Health insurance coverage: Early release of estimates from the National Health Interview Survey, 2023. National Center for Health Statistics (NCHS). https://www.cdc.gov/nchs/data/nhis/earlyrelease/insur202406.pdf
[1] The NHIS full-year estimates for 2023 do not include any state-level data, as has been the case since the survey was redesigned in 2019. However, NCHS periodically releases state-level estimates of coverage via specialized National Health Statistics Reports which can be found here.
Blog & News
Provider Discrimination Based on Sexual Orientation and Gender Identity: Experiences of Transgender/Nonbinary Adults and Sexually Minoritized Adults in Minnesota
September 03, 2024:Background
Understanding the experiences of people with minoritized sexual and gender identities matters for public health. Compared with straight and cisgender adults, these populations face inequitable barriers to health care access1,2 and disparities in health outcomes, including mental and physical health, activity limitations, and chronic conditions.3,4 Accordingly, Sexual Orientation and Gender Identity (SOGI) data collection is foundational in advancing population health and health equity in order to better understand the disparities and inequities these populations face.
As highlighted in our previous blogs, one focused on populations by sexual orientation and the other focused on populations by gender identity, reports of discrimination from health care providers based on sexual orientation or gender identity are high among people with minoritized sexual and gender identities. This discrimination is associated with barriers to health care access. For example, individuals who report discrimination may not receive proper treatment from discriminatory providers, and they may forgo or delay health care to avoid discrimination. Across populations, experiencing discrimination has been shown to negatively affect mental and physical health.5
In this blog, we build on these results by pooling two years of data to look at people’s experiences at the intersection of minoritized sexual and gender identities in reports of provider discrimination based on gender or sexual orientation. We used a survey question asking, ‘how often their gender, sexual orientation, gender identity or gender expression cause health care providers to treat them unfairly.’ Our analysis also illustrates how the commonly used measures for sexual orientation do not adequately encompass the range of options for sexually minoritized people, and how these limitations disproportionately impact the transgender and nonbinary populations.
Study Approach
We used 2021-2023 data from the biennial Minnesota Health Access Survey (MNHA). See Methods here.
Results
Among all adults in Minnesota, over half of the transgender/nonbinary population (56.3%) reported experiencing provider discrimination based on sexual orientation or gender identity – significantly higher compared with cisgender adults’ reported experiences of discrimination (6.7%) (Table 1).
Table 1. Rates of SOGI-Based Provider Discrimination by Sexual Orientation Among Cisgender Adults and Transgender/Nonbinary Adults in Minnesota, 2021-2023.
| Cisgender | Transgender/Nonbinary | ||
| All Adults (18+) | 6.7% | 56.3% | * |
| Sexual Orientation | |||
| Straight | 4.9% | -- | -- |
| Gay or Lesbian | 24.1% | 88.1% | * |
| Bisexual or Pansexual | 31.6% | 40.5% | |
| None of These | 23.9%† | 66.2% | * |
* Significant difference between cisgender and transgender/nonbinary adults in reports of provider discrimination.
† Estimate may be unreliable due to limited data (relative standard error greater than or equal to 30%).
-- Estimate not available to limited data.
Source: SHADAC analysis of the 2021-2023 Minnesota Health Access Survey.
When delving into experiences of provider discrimination among people with diverse gender and sexual identities, we found that reports of provider discrimination from transgender/nonbinary adults who identified as gay/lesbian or ‘none of these’ were significantly higher than for cisgender adults who identify as gay/lesbian or ‘none of these.’
Specifically, provider discrimination based on gender or sexual orientation was reported by:
- Nearly 9 in 10 transgender/nonbinary adults (88.1%) and about one in four (24.1%) cisgender adults who identified as gay/lesbian
- Two thirds of transgender/nonbinary adults (66.1%) and about a quarter of cisgender adults (23.9%) that chose the ‘none of these’ option for sexual orientation
Provider discrimination was also high for people who identified as bisexual/pansexual, and, for this group, not significantly different for transgender/nonbinary adults (40.5%) and cisgender adults (31.6%).
The lowest rates of provider discrimination were reported by straight cisgender adults at 4.9%.
Please note that sample sizes were limited, particularly for comparing straight or bisexual/pansexual adults by gender.
Discussion
Consistently across sexual orientations, reports of provider discrimination based on gender or sexual orientation were higher for transgender/nonbinary adults compared with cisgender adults. This suggests that discrimination associated with sexual minoritization may disproportionately impact transgender/nonbinary populations.
Individuals that experience multiple minoritized identities must contend with discrimination on multiple levels. For example, someone may experience discrimination based on a combination of their sexual orientation, gender identity, race, and/or disability status. Looking at the data from this study, we can illustrate this idea looking at provider discrimination reported by gay/lesbian cisgender adults and gay/lesbian transgender/nonbinary adults. Both of these groups share the same sexual orientation, but differ in gender identity. The group with multiple minoritized identities, the gay/lesbian transgender/nonbinary group, reported significantly higher rates of discrimination (88.1%) compared to cisgender gay/lesbian adults (24.1%), which may be related to their multiple levels of marginalization.
Overall, though, our analysis finds that discrimination remains alarmingly high across all groups of people with minoritized sexual and/or gender identities. Looking across the Minnesota population, this study documents provider discrimination among both transgender/nonbinary and cisgender sexual minorities, including people who identify as gay/lesbian, bisexual/pansexual, or ‘none of these.’
Our study also shows the importance of providing data for groups outside of the largest categories such straight, gay/lesbian, or bisexual. For example, by pooling multiple years of data, we were able to produce estimates for gender and sexual minorities including people who responded ‘none of these’ for sexual orientation. This latter group is important to highlight considering the wide range of sexual identities beyond gay/lesbian, straight, and bisexual. Reports of discrimination were high for both transgender/nonbinary and cisgender people who responded ‘none of these’ for sexual orientation, and significantly higher for the transgender/nonbinary people compared with cisgender.
This study highlights continued evidence of health care provider discrimination in Minnesota, with transgender/nonbinary sexual minorities being particularly impacted. Policies are urgently needed to address this discrimination, particularly for transgender/nonbinary Minnesotans who already face barriers to health care access and disparities in health outcomes compared to cisgender adults.
METHODS
Data
The 2021-2023 Minnesota Health Access (MNHA) survey is a biennial population-based survey on health insurance coverage and access conducted in collaboration with the Minnesota Department of Health. We limited the analysis to adults responding for themselves about experiences of discrimination (n=17,828), and we excluded proxy reports (e.g., a household member answering for a spouse or roommate).
Discrimination Based on Sexual Orientation and Gender Identity in the MNHA Survey
To study discrimination, we looked at a survey question that asks respondents ‘how often their gender, sexual orientation, gender identity or gender expression cause health care providers to treat them unfairly.’ Responses of ‘never’ were coded as no discrimination, and responses of ‘always,’ ‘usually,’ or ‘sometimes’ were coded as discrimination.
Sexual Orientation Measures in the MNHA Survey
Similar to other surveys that collect sexual orientation data, the MNHA asks about sexual orientation using three main response options: ‘gay or lesbian’; ‘straight, that is, not gay or lesbian’; and, ‘bisexual or pansexual.’ Survey respondents could also select ‘don’t know’ or ‘none of these,’ with an option to write in their own answer. We reviewed write-in responses and, when possible, recoded these responses to align with the existing categories.
Recoding write-in responses was a key step in reducing the risk of misclassification in order to include people who selected ‘none of these’ for sexual orientation in analysis. Some straight adults are unfamiliar with terminology for sexual orientation, which can lead to inaccurate responses.6 We reclassified inappropriate write-in answers (such as man, woman, married, or offensive comments) as ‘refused.’
After this step in cleaning the data, we tabulated results separately for two groups: people who responded ‘none of these’ with no write-in, and those who responded ‘none of these’ with an LGBTQ+ write-in response such as ‘queer’ or ‘asexual.’ Rates were similar, which helped to justify combining these subgroups into a single ‘none of these’ variable to improve sample size and produce estimates of reported discrimination for this subpopulation.
MNHA measures of sexual orientation were generally consistent with current best practices (for more information on SOGI data collection practices in Medicaid click here, and click here for our brief on federal survey sample size analysis), our analysis highlights some limitations of commonly used survey measures for sexual orientation. A small difference in the MNHA from typical measures is the inclusion of ‘bisexual or pansexual’ rather than only ‘bisexual’ as a response option. Current recommendations suggest using the phrasing, ‘I use a different term,’ rather than ‘none of these’ as a response option.7
Gender Identity Measures in the MNHA Survey
In 2023, the MNHA switched from a single question measuring gender to a two-step question asking first, ‘how do you describe your gender,’ and second, ‘are you transgender.’ As described in a previous blog, this approach was developed by the Oregon Health Authority through extensive community engagement and has advantages of being clear and inclusive.8 Response options for gender were:
- Man
- Woman
- Gender non-binary or two-spirit
- Agender/no gender
- Another gender (optional write in response)
In contrast, 2021 response options included ‘transmale/transman’ and ‘transfemale/transwoman’ listed after ‘male/man’ and ‘female/woman,’. Although current best practice recommendations for federal surveys list ‘transgender’ as response option after male/female, this approach has the limitation of implying that being transgender is ‘other’ and mutually exclusive from male/female. Similarly, the two-step question currently recommended for federal surveys asks about ‘sex assigned at birth,’ which may be perceived as invalidating and adds cognitive burden, especially for people with low literacy. Using accessible language in survey questions supports user experiences and overall response rates, and helps to reduce data quality problems such as item non-response and misclassifications. Guidance developed by the state of Oregon offers an inclusive approach to measuring gender on population surveys.
Analysis
We tabulated gender and sexual orientation based discrimination by sexual orientation for cisgender and transgender/nonbinary adults in Minnesota. For transparency, we present results for all response categories, even if estimates must be suppressed due to lack of data. Tests for statistical significance were conducted at the 95% confidence level.
References
[1] Bosworth, A., Turrini, G., Pyda, S., Strickland, K., Chappel, A., De Lew, N., Sommers, B.D.. (June 2021). Health Insurance Coverage and Access to Care for LGBTQ+ Individuals: Current Trends and Key Challenges. https://aspe.hhs.gov/sites/default/files/2021-07/lgbt-health-ib.pdf
[2] Kates, J., & Ranji, U. (2024). Health Care Access and Coverage for the Lesbian, Gay, Bisexual, and Transgender (LGBT) Community in the United States: Opportunities and Challenges in a New Era. https://www.kff.org/racial-equity-and-health-policy/perspective/health-care-access-and-coverage-for-the-lesbian-gay-bisexual-and-transgender-lgbt-community-in-the-united-states-opportunities-and-challenges-in-a-new-era/
[3] Baptiste-Roberts, K., Oranuba, E., Werts, N., & Edwards, L. V. (2017). Addressing health care disparities among sexual minorities. Obstetrics and Gynecology Clinics, 44(1), 71-80.
[4] Feir, D., & Mann, S. (2024). Temporal Trends in Mental Health in the United States by Gender Identity, 2014–2021. American Journal of Public Health, (0), e1-e4.
[5] Pascoe, E. A., & Smart Richman, L. (2009). Perceived discrimination and health: a meta-analytic review. Psychological bulletin, 135(4), 531.
[6] Miller, K., & Ryan, J. M. (2011). Design, development and testing of the NHIS sexual identity question. National Center for Health Statistics, 1-33.
[7] Office of the Chief Statistician of the United States. (n.d.). Recommendations on the Best Practices for the Collection of Sexual Orientation and Gender Identity Data on Federal Statistical Surveys. (Washington, D.C.) https://www.whitehouse.gov/wp-content/uploads/2023/01/SOGI-Best-Practices.pdf
[8] Oregon Health Authority. (2021, December 21). OHA/ODHS SOGI Committee Structure and Process used to Develop SOGI Data Recommendations (December 2021). https://www.oregon.gov/oha/EI/Documents/SOGI-Data-Committee-Survey.pdf
Blog & News
Hartman, Lacey
Lukanen, Elizabeth
Changes to Child and Adult Core Sets to Advance Equity (SHVS Cross-Post)
July 02, 2024:
The following Expert Perspective (EP) is cross-posted from State Health & Value Strategies. Authors: Elizabeth Lukanen and Lacey Hartman, SHADAC
Original posting date June 7, 2024. Find the original post here on the SHVS website.
The Child and Adult Core Sets were established to measure the quality of care for Medicaid and Children’s Health Insurance Program (CHIP) enrollees, nationally and at the state level, based on a uniform set of measures. The goal of the Core Sets is to monitor performance and improve the quality of healthcare. Starting in fiscal year (FY) 2025, states will be required to report a subset of Child and Adult Core Set measures (see Table 1) by race and ethnicity, sex, and geography.
By requiring data disaggregation for key populations of interest, policymakers, advocates and researchers will have a new tool to measure, monitor and inform policies and practices that focus on health equity.
Table 1: Core Set Measures Subject to Stratification (10 Measures in Total)
|
Child Core Set Measures (7 of 27 measures) |
|||
|
Measure Name |
National Quality Forum (NQF) # |
Measure Steward |
Data Collection Method |
|
Well-Child Visits in the First 30 Months of Life (W30-CH) |
1392 |
National Committee for Quality Assurance (NCQA) |
Administrative |
|
Child and Adolescent Well-Care Visits (WCV–CH) |
1516 |
NCQA |
Administrative |
|
Oral Evaluation, Dental Services (OEV-CH) |
2517 |
Dental Quality Alliance (DQA) (American Dental Association) |
Administrative |
|
Follow-Up After Hospitalization for Mental Illness: Ages 6 to 17 (FUH-CH) |
576 |
NCQA |
Administrative |
|
Prenatal and Postpartum Care Up to Age 20 (PPC2-CH) |
1517* |
NCQA |
Administrative or hybrid |
|
Live Births Weighing Less Than 2,500 Grams (LBW–CH) – CMS calculates on behalf of states |
1382 |
Centers for Disease Control and Prevention (CDC)/National Center for Health Statistics (NCHS) |
State vital records |
|
Low-Risk Cesarean Delivery (LRCD-CH) – |
Not applicable |
CDC/NCHS |
State vital records |
|
Adult Core Set Behavioral Health Measures (3 of 11 measures) |
|||
|
Measure Name |
NQF # |
Measure Steward |
Data Collection Method |
|
Initiation and Engagement of Substance Use Disorder Treatment (IET-AD) |
0004 |
NCQA |
Administrative or electronic health record |
|
Follow-Up After Emergency Department Visit for Substance Use: Age 18 and Older (FUA-AD) |
3488 |
NCQA |
Administrative |
|
Follow-Up After Hospitalization for Mental Illness: Ages 18 and older (FUH-AD) |
0576 |
NCQA |
Administrative |
*No longer endorsed by NQF.
States will be required to stratify these mandatory measures using the following categories:
- Race and ethnicity: Using the newly released 2024 Revisions to the Office of Management and Budget’s Statistical Policy Directive No. 15: Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity. Minimum categories include:
- American Indian or Alaska Native
- Asian
- Black or African American
- Hispanic or Latino
- Middle Eastern or North African
- Native Hawaiian or Pacific Islander
- White
- Sex: Defined as biologic sex, using the 2011 HHS Implementation Guidance on Data Collection Standards for Race, Ethnicity, Sex, Primary Language, and Disability Status. Categories include:
- Male
- Female
- Geography: Using the core-based statistical area (CBSA), which are county-based statistical areas defined by large population areas, as a minimum standard. Those categories include:
- Metropolitan statistical area (population core of 50,000 or more)
- Micropolitan statistical area (population core of 10,000 to 49,999)
- Outside Core Based statistical area
Background and Context
Every year, the Secretary of the U.S. Department of Health and Human Services is required to review and update the Child and Adult Core Sets. This review is designed to detect measurement gaps and to identify and recommend revisions to improve and strengthen the Core Sets. This review is led by a workgroup that includes input from a variety of stakeholders including states, managed care plans, healthcare providers, and quality experts. In response to the annual review process, state reporting of these measures has evolved and starting in FY 2024, reporting of the Child Core Set and the Core Set of behavioral health measures for adults enrolled in Medicaid became mandatory.
Over time, the Core Sets have been specifically recognized as a critical tool to monitor health disparities. Increasing stratification of the measures is a priority area for the Centers for Medicare & Medicaid Services (CMS) and in guidance released in 2022, CMS explicitly encouraged states to “use Core Set data to identify disparities in care and to develop targeted quality improvement efforts to advance health equity.”
During the review of the 2025 Core Set Measures, the Core Set review workgroup discussed using stratified Core Sets data to advance health equity. Workgroup members who represent state and enrollee perspectives both highlighted the importance of disaggregation for assessing member experience and monitoring equity while also acknowledging the challenges inherent to data collection and reporting. In response to this discussion, the following challenges and considerations were highlighted in the final FY 2025 recommendations report:
- Data on enrollee demographics is of variable quality, with missing and unknown data (enrollees who don’t provide data and related hesitancy).
- Administrative burden to collect this information.
- Political considerations for how the data are collected and reported (balancing state legislative agendas compared to CMS requirements).
- Technical challenges, such as having multiple conflicting sources of data.
- Misalignment of reporting stratification categories with other federal and state program requirements.
- Need to engage enrollees in the collection and use of these data.
- Need for technical assistance to states to meet the new reporting requirements.
Despite these challenges, there was consensus among the workgroup about the importance of stratification, which aligned with the new requirement that 10 measures be reported by race and ethnicity, sex, and geography. Specifically, for FY 2025 reporting, states will be required to report stratified data for the seven Child Core Set measures listed above in Table 1 (25% of the 27 measures) and three of the Adult Core Set behavioral health measures (25% of 11 behavioral health measures).
Required stratification of additional measures will increase over time and the intent is that all eligible mandatory Core Set measures will be disaggregated by FY 2028. States have the option of reporting stratified data for all measures starting in FY 2025.
People’s experience of health inequities based on race and ethnicity, sexual orientation, gender identity, geography, immigration status, and other factors, is a longstanding and pervasive problem that is deeply rooted in discrimination and structural racism. The Medicaid program, through its policy, financial, and programmatic levers, is uniquely situated to address the health inequities experienced by the program’s diverse population of enrollees. Key to these efforts is the availability of comparable state programmatic and performance data to identify and track progress.
For this reason, the move toward disaggregated Core Sets data by race and ethnicity, sex, and geography is an important step to improve the monitoring of health care access and quality for Medicaid enrollees, to further identify where disparities exist and to develop and evaluate quality improvement efforts. However, this is a small step that needs to expand to identify other groups that have been economically and socially marginalized such as those with a disability, individuals who identify as lesbian, gay, bisexual, transgender, queer, intersex, or outside the gender binary (LGBTQI+), and those with limited English proficiency.
In addition to expanding data disaggregation to include a broader range of groups, it will also be important to provide states with the necessary resources and technical assistance to analyze and report these data in an accurate and comparable way. As was also noted in comments to the workgroup, enrollee engagement in the collection and use of these data is also key for advancing health equity. Community engagement is a way to establish and build trust and to develop interventions informed by the lived experience of Medicaid enrollees.
Finally, it will be critical to provide states, providers, and community partners with the resources and tools necessary to ensure that timely action is taken to actually address, and not just report on, systemic inequities.
Want to stay informed on the latest data collection practices, survey updates, and more? Sign up for our monthly newsletter here, and find health equity resources here on the SHVS site.
Blog & News
2023 National Health Interview Survey (NHIS) Early Release: Estimates from Quarter 4 (October to December) Hold Steady
June 05, 2024:The National Center for Health Statistics (NCHS) has released quarterly estimates of health insurance coverage beginning in October 2022 through December 2023 from the National Health Interview Survey (NHIS) as a 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 (Q4 – October to December 2023) and notes any differences compared to the same time period in 2022.
Between Q4 of 2022 and Q4 of 2023, rates of uninsurance, public coverage, and private coverage for adults (age 18-64) remained mostly unchanged. Across all age groups, there were slight decreases in the rates of uninsurance and private coverage, and a slight increase in the rate of public coverage, but none of these changes were statistically significant.
Figure 1: Health Insurance Coverage Rates by Type (Adults Aged 18-64), Q4 2022 vs. Q4 2023*
*No changes were statistically significant at 95% confidence.
- Brief: Comparing Federal Government Surveys That Count the Uninsured: 2023
- Blog: 2023 NHIS Early Release Estimates from Quarter 3 Hold Steady
- Blog: Insurance Coverage Trend Analysis – How Does the Household Pulse Survey Compare?
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Publication
Comparing Federal Government Surveys That Count the Uninsured: 2023
SHADAC has recently updated our annual “Comparing Federal Government Surveys that Count the Uninsured” brief following the release of new insurance coverage estimates from surveys conducted by the US Census Bureau, the Agency for Healthcare Research and Quality (AHRQ), and the Centers for Disease Control and Prevention (CDC).
Accurate estimates of the number of people that do not have insurance coverage (also referred to as uninsured or uninsurance) are important in understanding trends and the impacts of actions (policy changes), events (like public health emergencies), or shifts in the economic landscape (like periods of recession) that may affect health insurance coverage.
The brief provides an annual update to comparisons of uninsurance estimates from five federal surveys. As in prior years, we have included estimates from:
- The American Community Survey (ACS)
- The Current Population Survey (CPS)
- The Medical Expenditure Panel Survey - Household Component (MEPS-HC)
- The National Health Interview Survey (NHIS)
