SHADAC Staff

p 612.624.4802
e shadac@umn.edu

FPG vs. FPL: What's the Difference?

This blog was originally posted on April 18, 2023 and updated on April 3, 2024

The terms "FPG" and "FPL" are often used interchangeably, but they are not actually the same thing; there are, in fact, important functional differences between the two concepts.

The federal poverty level (FPL) is the income threshold below which a “family,” and every individual in it, is considered to be in poverty.¹ The poverty definition is based on money income before taxes and does not include capital gains or non-cash benefits. The official FPL is calculated annually in order to reflect inflation by the Census Bureau and is used primarily for statistical purposes—for example, to estimate the number of Americans in poverty each year. The Census Bureau assigns each person or family a singular threshold out of a possible 48, which can vary by family size (designated up to a nine-person family unit or more), number of children, and—in the case of one-person and two-person households—elderly status. The FPL is the same, however, for all 50 states and the District of Columbia (D.C.).

Table 1. Poverty thresholds for 2023 by size of family and number of related children under 18 years ($)

Source: U.S. Census Bureau. (2024). Poverty thresholds.
Note; The source of the weighted average thresholds is the 2024 Current Population Survey Annual Social and Economic Supplement (CPS ASEC). 

The federal poverty guideline (FPG) is a poverty threshold issued by the Department of Health and Human Services (HHS) for administrative purposes—for example, determining financial eligibility for federal programs. FPG, like FPL, varies by family size. However, elderly status is not considered in FPG calculations. Additionally, FPG is not uniform nationally: The 48 contiguous states and D.C. use the same FPG, while Alaska and Hawaii each have their own FPG. Reflective of new administrative practices for the Office of Economic Opportunity (OEO) during the 1966-1970 period, separate guidelines were established for Alaska and Hawaii. Other U.S. territories, such as Puerto Rico and the U.S. Virgin Islands, for instance, do not have separate guidelines, and FPG determinations use either the rate for the 48 contiguous states or some other calculation made by local program officials.

Table 2. 2024 Poverty guidelines (FPG) ($) 

Source: Office of the Assistant Secretary for Planning and Evaluation (ASPE). Poverty Guidelines. Department of Health and Human Services (HHS). https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines

Ultimately, FPL and FPG identify different numbers of people below the same poverty threshold, with FPG generally placing more people in lower poverty categories than FPL. Additionally, the two measures are released at different times relative to the year to which they apply: The Census Bureau issues its final FPL calculations in the year after the year for which poverty is being measured (e.g., the 2022 FPL, which reflects the calendar year 2022, was issued in April 2023). FPG, on the other hand, is issued by HHS in late January after the year for which poverty is being measured but is named for the year in which it is released (e.g., the 2024 FPG was issued in January 2024, but reflects price changes through calendar year 2023 only). Although the naming conventions for the FPL and the FPG seem to reflect different years, they do, in fact, provide measures for the same year and are therefore comparable.

Current and future eligibility for Medicaid is based on FPG, as are the exchange-based, cost-sharing, and premium subsidies that take place under the federal Affordable Care Act (ACA). Given that these programs affect a substantial and growing number of people, it is important to acknowledge that FPG is distinct from FPL in ways that have significant ramifications on a practical level.

Sources on FPL and FPG

Office of the Assistant Secretary for Planning and Evaluation (ASPE). Poverty Guidelines. Department of Health and Human Services (HHS).
https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines

Office of the Assistant Secretary for Planning and Evaluation (ASPE). Poverty guidelines, research, and measurement. Department of Health and Human Services (HHS).
https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines/prior-hhs-poverty-guidelines-federal-register-references 

U.S. Census Bureau. Poverty Thresholds.
https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html

U.S. Census Bureau. How the Census Bureau measures poverty.
https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html

Walsh, Elliot
Lukanen, Elizabeth

AHIP Presentation 2024: Improving Health Equity Through Better Demographic Data Collection in Medicaid

On March 12, 2024, SHADAC Deputy Director Elizabeth Lukanen presented at the AHIP Medicare, Medicaid, Duals & Commercial Markets Forum as a part of the “Improving Health Equity Through Better Data Collection” session series. Elizabeth's presentation focused specifically on demographic data collection in Medicaid.

The conference itself focused on the pressing policy priorities, emerging issues, and regulatory updates for Medicare, Medicaid, Duals, and the commercial market. Topics ranged from panel discussions on filling the gaps in the behavioral health care workforce to presentations on advancing Medicaid Long-Term Services and Supports (LTSS) to the latest information on best practices to collect sexual orientation and gender identity (SOGI) data. 

During her session series, Elizabeth shared the stage with other amazing names in public health, including Samantha Artiga, Director for Racial Equity and Health Policy Program at KFF, and Dr. Alex S. Keuroghlian, Associate Professor of Psychiatry at Harvard Medical School and Director of Education & Training at Fenway Health. The session was moderated by Dr. LaShawn McIver, Senior Vice President & Chief Health Equity Officer at AHIP.

Elizabeth’s presentation centered around how better demographic data collection in Medicaid could work towards advancing health equity. She starts by reviewing reasons why data for certain demographics may be of poor quality or missing altogether. She then goes on to discuss issues with demographic data collection for certain populations, like minority racial/ethnic groups, LGBTQ+ individuals, and those with disabilities, and how that can lead to not only data gaps, but also to overall care and access inequities.

Highlighting three states’ equity initiatives, Elizabeth explores how we might work towards improving data collection and utilizing that data to understand inequities and differences between populations served by Medicaid. 

“Good data starts with trust,” Lukanen says. If we want to improve demographic data collection, “[we need to] make demographic data collection a priority.” 

Make it a priority today – start by reading through the full presentation here or by clicking the image below.

You can also learn more about data collection and advancing health equity with some of the following SHADAC resources:

- Sexual Orientation and Gender Identity Data: New and Updated Information on Federal Guidance and Medicaid Data Collection Practices (SHVS Brief)

- Collection of Self-Reported Disability Data in Medicaid Applications: A Fifty-State Review of the Current Landscape (SHVS Brief)

- Health Equity Measurement: Considerations for Selecting a Benchmark (SHVS Brief)

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.

Hest, Robert
Senior Research Fellow

p 612-624-5507
e hestx005@umn.edu

SHADAC Comments on Proposed 2025 American Community Survey Health Insurance Coverage Instrument Changes

The U.S. Census Bureau has released a request for comments regarding proposed revisions and changes for the 2025 American Community Survey. Based on information gained from the 2022 Content Test, proposed changes would affect a variety of topics and questions, including educational attainment, disability, household roster, and, most notably for the State Health Access Data Assistance Center (SHADAC), health insurance coverage.

See an excerpt regarding ACS health insurance coverage question changes below. You can find the full request for comments here in a notice from October 20, 2023. 

Researchers at SHADAC have reviewed the proposed changes regarding health insurance coverage data collection for the American Community Survey 2025 data year. We have crafted the following response letter discussing our opinion that the implementation of these changes be postponed in order to further investigate causes of Medicaid underreporting, and to allow for the ACS 2025 to adequately reflect effects of the Medicaid unwinding.

SHADAC’s Comments 

We appreciate the opportunity to comment on Census’ proposed changes to the 2025 American Community Survey questionnaire. For more than twenty years, the State Health Access Data Assistance Center (SHADAC) has used the American Community Survey (ACS) to provide state officials and other stakeholders with data to inform health policy. Since the health insurance question was added in 2008, we have used the ACS to monitor changes in health insurance coverage.

As frequent and knowledgeable users of the survey, we have a particularly vested interest in the continued ability of the ACS to produce a high-quality measurement of health insurance coverage. With that in mind, we submit the following comments on the proposed changes to the health insurance coverage instrument. We strongly urge postponing the implementation of the proposed changes to the ACS’ health insurance coverage instrument with reasons provided below:

Medicaid Underreporting

While heartened by the commitment to improvements in the measurement of health insurance coverage, we are very concerned that the most recent content test showed significantly reduced reporting of Medicaid coverage in both versions of the test questions.

Given that this request for comment specifically mentions addressing the long-standing problem of Medicaid underreporting as a goal of the new instrument, we view this increase in Medicaid underreporting as disqualifying. In our view, Census needs to conduct further investigation to determine the cause for this demonstrated decrease in Medicaid reporting and use that information to revise the test questions to address this substantial problem.

Timing and Medicaid Unwinding Data

Though we understand that the timing for this change is driven by Census’ standard process for adding or changing survey content, we view the proposed timing of this change as inappropriate because of the ongoing, large-scale redetermination of Medicaid eligibility (“unwinding”) that began in April 2023 with the end of the pandemic-era continuous coverage requirement. This unwinding will continue into 2024.

The unwinding of the Medicaid continuous coverage requirement represents the largest nationwide coverage transition since the Affordable Care Act, and there is significant interest in monitoring the impacts. ACS data year 2025 will be the first full year of data after the completion of the unwinding.

If changes to health insurance coverage questions are implemented in 2025, we will never be able to reliably learn about the full impacts of the unwinding on health insurance coverage. Postponing revisions would allow us to better compare data and understand the impacts of the unwinding on key populations in the first full year post-unwinding completion. This is especially important for state-level populations of interest (including those relevant to furthering critical health equity goals) and for substate geographies, as the ACS is the only source of this information.

Thank you for your consideration. We know you face many important decisions and appreciate the chance to comment on this important and impactful data collection change.

See SHADAC’s comments on the newly proposed Sexual Orientation and Gender Identity (SOGI) questions on our blog here.

SHADAC Staff

p 612.624.4802
e shadac@umn.edu

Health Leads Joins SHADAC and RWJF for Next Phase of Medicaid Equity Monitoring Tool Project

The State Health Access Data Assistance Center (SHADAC) is partnering with Health Leads for the second phase of its Medicaid Equity Monitoring Tool project.

Supported by the Robert Wood Johnson Foundation (RWJF), the project explores the possibility of using a national Medicaid equity monitoring tool to hold state Medicaid programs accountable for improving population health by advancing health equity.

“Medicaid offers a huge opportunity to increase health equity in the United States,” said Aingyea Fraser, program officer at RWJF. “Medicaid covers millions of people across all 50 states and is the single largest insurer for children, which means it has the ability to make meaningful, widespread change. I am excited to see how this partnership builds on the first phase and helps us explore all opportunities of the tool.”

The project aims to identify and, if possible, track the contributions of state Medicaid programs toward achieving health equity while also highlighting areas for improvement and, importantly, ensuring that the perspectives of those most affected by health inequities are heard.

Christina Worrall, co-project lead alongside Lynn Blewett, founding director of SHADAC, echoes the importance of focusing on who Medicaid serves, noting: “SHADAC is grateful to RWJF for this chance to work alongside Health Leads to fulfill one of the recommendations from our first phase Advisory Committee, which was to continue to center the voice of those experiencing health inequities in state Medicaid programs in the discussions of a potential monitoring tool.”

Health Leads works both nationally and locally to shift power and decision-making to community members who are best positioned to inform, design, and lead interventions. With a wealth of tangible knowledge and experience in authentic and effective community engagement, Health Leads will convene Medicaid community members to better understand and uplift how they define and measure health.

“SHADAC and RWJF have a vision for how Medicaid can be strengthened by input and direction from its members," said Dominique Morgan, chief operating officer at Health Leads. “This collaboration presents a real opportunity and potentially replicable model for how community can shape and drive equity into policy and the implementation of critical health services.”

The input from community members will be central to informing the work of facilitating discussions with Medicaid subject matter experts around data collection and measure inclusion that SHADAC is doing with ongoing consultation from RACE for Equity. At the end of this phase, SHADAC, RACE for Equity, and Health Leads will make recommendations about the feasibility of moving forward with designing and developing a Medicaid equity monitoring tool.