Assessing PEPFAR’s Impact: Analysis of Mortality in PEPFAR Countries

Authors: Jennifer Kates, Allyala Nandakumar, Gary Gaumer, Dhwani Hariharan, William Crown, Adam Wexler, Stephanie Oum, and Anna Rouw
Published: Sep 27, 2021

Issue Brief

Key Findings

PEPFAR, the U.S. global HIV program and the largest commitment by any nation to address a single disease in history, is at an important juncture nearing its two decade mark. We assessed its health impact by analyzing the change in the mortality rate in 90 PEPFAR recipient countries between 2004-2018 compared to similar low and middle income countries. We find that PEPFAR was associated with large, significant declines in mortality, as follows:

  • The all-cause mortality rate in PEPFAR recipient countries was 20% lower than what would have been expected without PEPFAR support.
  • This effect was strongest where PEPFAR’s investments were greatest; there was an almost 27% reduction in the all-cause mortality rate in countries where PEPFAR had the highest per capita spending compared to a 16% reduction in countries with the lowest per capita PEPFAR spending (relative to control countries).
  • The high investment PEPFAR countries were primarily those engaged in more intensive planning and programming through the PEPFAR “COP” process. PEPFAR COP countries experienced a 26% decline in the mortality rate compared to 17% in PEPFAR countries that did not prepare COPs. Because we did not assess the independent effect of PEPFAR spending in COP countries, it is unclear if mortality declines were due to greater spending, more intensive planning and programming, or some combination of both.
  • Finally, the decline in the mortality rate has continued over the course of the program, including in all three major five-year PEPFAR program phases. The biggest drops occurred in the first two phases, with a more modest, but significant, drop since.
  • These findings provide strong evidence that PEPFAR continues to have a significant and positive impact on health outcomes in the countries in which it works and that future investments would be expected to yield additional reductions in mortality. They also suggest that PEPFAR has had positive spillover effects beyond HIV.

Introduction

PEPFAR, the U.S. global AIDS program and largest commitment by any nation to address a single disease in history, is at an important juncture. First started as an emergency effort, when HIV was ravaging much of sub-Saharan Africa, the program is now nearing its two-decade mark. It also awaits the nomination by the President of a new Coordinator, is in the process of developing its next five-year strategy, and will soon be considered for reauthorization by Congress. As policymakers and others look towards PEPFAR’s future, understanding its impact will be an important input. While its impact has been documented in earlier studies1 , we sought to add to this body of knowledge by providing an assessment of its health impact over 15 years of the program. Working with researchers at Brandeis University, we undertook an analysis of the change in mortality in PEPFAR countries. Specifically, we analyzed the change in the all-cause mortality rate in 90 PEPFAR countries between 2004, the first year in which PEPFAR funding began, and 2018, the most recent year of complete data, compared to a control group of 67 low- and middle-income countries. We explored several model specifications, each of which had statistically significant results. Each specification controlled for numerous baseline variables which may also be expected to influence mortality outcomes and which help make the control group more comparable to the PEPFAR group. Still, it is important to note that there may be other, unobserved ways in which control countries differed from PEPFAR countries. We report the results here for our final model specification. See methodology for more detail and tables with results from all models.

Findings

Our analysis of PEPFAR’s estimated impact on all-cause mortality between 2004 and 2018 finds that:

PEPFAR countries, taken together, were associated with a significant decline in the all-cause mortality rate between 2004 and 2018, compared to what would have been expected. The all-cause mortality rate in PEPFAR countries was 20.4% lower than what would have been expected had PEPFAR been absent, suggesting the program has had a significant and positive impact on health outcomes. While countries that received PEPFAR support had higher mortality rates prior to the initiation of the program compared to controls, they, and control countries, saw a modest decline from 1990 to the introduction of PEPFAR, followed by a rapid decline in mortality in PEPFAR countries. (see Figure 1).

Figure 1: Trends in the All-Cause Mortality Rate, 1990-2018, PEPFAR and Control Countries

The mortality decline was greatest in countries with higher levels of PEPFAR investments. We segmented countries into three groups – high, medium, and low spending intensity – based on cumulative PEPFAR spending per capita in each country. In countries with high PEPFAR spending intensity, the all-cause mortality rate reduction was approximately 26.6% over the 2004-2018 period, compared to the control group. Reductions were less in medium and low intensity countries, respectively (14.0% and 15.7%) but even in these countries, PEPFAR was associated with a significant decline in mortality, compared to the control group (see Figures 2 and 3).

Figure 2: Trends in the All-Cause Mortality Rate, 1990-2018, PEPFAR Countries by Level of PEPFAR Spending​
Figure 3: Percent Change in the All-Cause Mortality Rate, PEPFAR Countries by Characteristic, 2004-2018​

Countries with the greatest PEPFAR investments were primarily countries engaged in more intensive planning and programming through the PEPFAR “COP” process.  Each year, a subset of countries receiving PEPFAR support is required to prepare Country Operational Plans (COPs). COPs document annual funding levels linked to results and serve as budget and target allocation and tracking tools. Country teams work intensively to develop these plans for their HIV programming, in concert with headquarters at the State Department, which approves them for funding.2  Our analysis finds that the all-cause mortality rate in PEPFAR COP countries3  declined by approximately 25.7% over the period, compared to 16.6% in PEPFAR countries that did not prepare COPs. (see Figure 3). Because we did not assess the independent effect of PEPFAR spending in COP countries, it is unclear if mortality declines were due to greater spending, more intensive planning and programming, or some combination of both, and it would be important to examine these different effects further.

Finally, the decline in the mortality rate has continued over the course of the program, including in all three major five-year PEPFAR phases, with the biggest drops occurring in the first two phases, and a more modest, but significant, drop since. We looked at three distinct five-year periods of the program, 2004-2008, 2008-2013 and 2013-2018, corresponding with PEPFAR’s authorization periods, to estimate the incremental mortality effects over time.  We find that the decline in the mortality rate has continued throughout the program, with an 7.9% decline occurring in the first five-year period, followed by an additional decline of 7.1% and 5.3%, respectively, in the two subsequent periods (see Figure 4). This pattern was similar in COP countries, although the mortality decline was greatest in the second five year phase of the program (8.8%, 9.4%, and 7.4%).

Figure 4: Incremental Percent Change in the All-Cause Mortality Rate, PEPFAR Countries, by Five-Year Period​

Implications

These findings build on prior analyses that also found reductions in mortality in PEPFAR countries, relative to others. Here, we offer additional evidence that PEPFAR continues to have a significant and positive impact on health outcomes in the countries in which it works, particularly in those countries where it has concentrated financial investments and engaged in more intensive planning and programming. Moreover, these effects have continued over the course of the program. Our findings also suggest that PEPFAR has had positive spillover effects beyond HIV. At the same time, and despite PEPFAR’s positive impact, HIV continues to take a toll in many low- and middle-income countries.4  Our finding that PEPFAR investments were associated with a continued reduction in mortality over time suggests that further program investments will also yield additional mortality benefits.  Taken together, these findings offer policymakers and other PEPFAR stakeholders new input into discussions concerning PEPFAR’s future, particularly given competing financial pressures and a challenging global health and development landscape.

Methodology

We used a difference-in-difference5 , quasi-experimental design to estimate a “treatment effect” (PEPFAR), based on comparison to a control group (the counterfactual). The difference-in-difference design compares the before and after change in outcomes for the treatment group to the before and after change in outcomes for the control group. Our outcome of interest was the crude death rate, all causes (per 1,000). We chose this outcome, instead of the HIV mortality rate, because available HIV mortality estimates are derived using assumptions that include the role of HIV treatment, which is itself one of PEPFAR’s interventions. We included data on the mortality rate starting in 1990, to assess patterns before and after PEPFAR.

We constructed a panel data set for 157 low- and middle- income countries between 1990 and 2018. Our PEPFAR group included 90 countries that had received PEPFAR support over the period. Our control group included 67 low and middle income countries that had not received any PEPFAR support or had received minimal PEPFAR support (<$1M over the period or <$.05 per capita) between 2004 and 2018.  Data on PEPFAR spending by country were obtained from the U.S. government’s https://foreignassistance.gov/ database and represent U.S. fiscal year disbursements. Data for the mortality rate were obtained from the World Bank’s World Development Indicators (WDI) (https://datatopics.worldbank.org/world-development-indicators/.  We explored several difference-in-difference model specifications. Each specification controlled for numerous baseline variables, compared to an unadjusted model, variables which may be expected to influence mortality outcomes and which help make the control group more comparable to the PEPFAR group.

Our baseline variables and model specifications were as follows:

Table 1: Baseline Variables
VariableData Source
1. GDP per capita (current USD)WDI, https://datatopics.worldbank.org/world-development-indicators/
2. Recipient of U.S. HIV funding prior to 2004 (dummy variable)USAID, https://foreignassistance.gov/
3. Total populationUnited Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects 2019, Online Edition. Rev, https://population.un.org/wpp/
4. Life expectancy at birth (years)WDI, https://datatopics.worldbank.org/world-development-indicators/
5. Total fertility rate (births per woman)WDI, https://datatopics.worldbank.org/world-development-indicators/
6. Percent urban population (of total population)WDI, https://datatopics.worldbank.org/world-development-indicators/
7. School enrollment, secondary (% gross)WDI, https://datatopics.worldbank.org/world-development-indicators/
8. WB country income classificationWorld Bank, https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups
9. HIV prevalence (% of population ages 15-49)WDI, https://datatopics.worldbank.org/world-development-indicators/ (from UNAIDS).To address missing values in some cases, additional data were obtained from the Global Burden of Disease Collaborative Network,Global Burden of Disease Study 2019 (GBD 2019) Results.Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020, http://ghdx.healthdata.org/gbd-results-tool.
10. Per capita donor spending on health (non-PEPFAR)OECD Creditor Reporting System database, https://stats.oecd.org/Index.aspx?DataSetCode=crs1
11. Per capita domestic health spending, government and private, PPP (current $)WDI, https://datatopics.worldbank.org/world-development-indicators/
Table 2: Model Specifications
ModelDifference-in Difference Specification
1Unadjusted model
2Includes baseline variables 1-9
3Includes baseline variables 1-11
4Includes baseline variables 1-9, and yearly per capita donor spending on health (non-PEPFAR) by all donors.

Our final model for main reported results is model 4 which, in addition to baseline variables, includes a yearly estimate of donor health spending from all sources other than PEPFAR (including, for example, U.S. spending on other health areas as well as spending by other bilateral and multilateral donors on health) to adjust for potential confounding influences of these other health investments on all-cause mortality. We did not include domestic health spending as a baseline variable in this model due to the potential confounding with donor health spending. The pre-intervention period for this model started in 2002.

Each of our model specifications produced similar, statistically significant results. In our final model, almost all results were significant at the p<0.001 level; one result was significant at the p<0.01 and three were significant at p<0.05. We also ran all models with and without China and India, the two most populous countries in the world, to assess whether they were influencing the results. In both cases, PEPFAR’s impact was still significant and results were similar.

Despite the strengths of the difference-in-difference design, there are limitations to this approach. While we adjusted for numerous baseline factors that could be correlated with mortality outcomes, there may be other, unobservable factors that are not captured here. Similarly, while our baseline factors are also intended to adjust for selection bias, and make the PEPFAR and control groups more comparable, there may be other ways in which control countries differed from PEPFAR countries (and factors which influenced which countries received PEPFAR support), which could bias the estimates.

Table 3: Baseline Mean Mortality Rate, All Causes, 2004(crude deaths per 1,000)
All PEPFAR countries10.5
COP countries12.6
Non-COP countries9.4
PEPFAR Spending Intensity
High12.3
Medium9.7
Low9.5
Table 4: Estimates of PEPFAR’s Impact on Mortality, 2004-2018(Percent change in all-cause mortality rate)
Model SpecificationModel 1Model 2Model 3Model 4
All PEPFAR countries-19.9%-22.5%-27.4%-20.4%
COP countries-22.8%-26.8%-29.6%-25.7%
Non-COP countries-17.9%-19.7%-25.0%-16.6%
PEPFAR Spending Intensity
High-25.0%-29.3%-30.6%-26.6%
Medium-20.0%-21.4%-28.3%-14.0%
Low-13.3%-15.3%-19.5%-15.7%
Time Period: All PEPFAR countries
2004-2008-9.0%-11.2%-13.9%-7.9%
2004-2013-15.0%-17.3%-21.2%-15.0%
2004-2018-19.9%-22.5%-27.4%-20.4%
Time Period: PEPFAR COP countries
2004-2008-7.8%-11.0%-12.3%-8.8%
2004-2013-15.9%-19.5%-21.5%-18.2%
2004-2018-22.8%-26.8%-29.6%-25.7%
NOTE: Refer to Table 2 for model specifications.
Table 5: Estimates of PEPFAR’s Impact on Mortality, 2004-2018(Percentage point difference-in-difference and standard errors)
Model SpecificationModel 1Model 2Model 3Model 4
All PEPFAR countries-2.095***(0.232)-2.364***(0.190)-2.879***(0.265)-2.139***(0.435)
COP countries-2.875***(0.294)-3.380***(0.262)-3.726***(0.341)-3.232***(0.541)
Non-COP countries-1.682***(0.236)-1.847***(0.179)-2.346***(0.218)-1.565***(0.423)
PEPFAR Spending Intensity
High-3.081***(0.304)-3.608***(0.247)-3.770***(0.299)-3.271***(0.495)
Medium-1.942***(0.304)-2.080***(0.244)-2.744***(0.326)-1.357*(0.542)
Low-1.263***(0.304)-1.451***(0.244)-1.850***(0.315)-1.494**(0.515)
Time Period: All PEPFAR countries
2004-2008-0.949**(0.355)-1.172***(0.261)-1.463***(0.357)-0.830*(0.401)
2004-2013-1.571***(0.269)-1.813***(0.208)-2.224***(0.287)-1.578***(0.413)
2004-2018-2.095***(0.232)-2.364***(0.190)-2.879***(0.265)-2.139***(0.435)
Time Period: PEPFAR COP countries
2004-2008-0.988*(0.434)-1.385***(0.372)-1.547**(0.473)-1.114*(0.502)
2004-2013-2.008***(0.335)-2.457***(0.292)-2.713***(0.376)-2.298***(0.513)
2004-2018-2.875***(0.294)-3.380***(0.262)-3.726***(0.341)-3.232***(0.541)
NOTES: Refer to Table 2 for model specifications. Standard errors are shown in parentheses.

***p < 0.001   **p < 0.01 *p < 0.05

Jen Kates, Adam Wexler, Stephanie Oum, and Anna Rouw are with KFF. Allyala Nandakumar, Gary Gaumer, Dhwani Hariharan, and William Crown are with Brandeis University.

Endnotes

  1. These include: Eran Bendavid E, Bhattacharya J. The President’s Emergency Plan for AIDS Relief in Africa: An Evaluation of Outcomes. Ann Intern Med. 2009;150:688-695. Available at: https://www.acpjournals.org/doi/10.7326/0003-4819-150-10-200905190-00117?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dpubmed&; Bendavid E, Holmes CB, Bhattacharya J, Miller G. HIV Development Assistance and Adult Mortality in Africa. JAMA. 2012;307(19):2060–2067. Available at: https://jamanetwork.com/journals/jama/fullarticle/1157487; Wagner Z, Barofsky J, Sood N. PEPFAR Funding Associated With An Increase In Employment Among Males in Ten Sub-Saharan African Countries. Health Aff (Millwood). 2015;34(6):946-953. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782769/; and Daschle T, Frist B. Building Prosperity, Stability, and Security Through Strategic Health Diplomacy: A Study of 15 Years of PEPFAR. Bipartisan Policy Center, Washington DC, 2018. Available at: https://bipartisanpolicy.org/download/?file=/wp-content/uploads/2019/03/Building-Prosperity-Stability-and-Security-Through-Strategic-Health-Diplomacy-A-Study-of-15-Years-of-PEPFAR.pdf. ↩︎
  2. State Department, PEPFAR 2021 Country and Regional Operational Plan (COP/ROP) Guidance for all PEPFAR Countries, February 11, 2021. Available at: https://www.state.gov/wp-content/uploads/2021/02/PEPFAR-COP21-Guidance-Final.pdf (accessed September 16, 2021). ↩︎
  3. Thirty-one countries. ↩︎
  4. https://www.unaids.org/en/resources/documents/2021/2021-global-aids-update. ↩︎
  5. Gertler, Paul J., Sebastian Martinez, Patrick Premand, Laura B. Rawlings, and Christel M. J. Vermeersch. 2016. Impact Evaluation in Practice, second edition. Washington, DC: Inter-American Development Bank and World Bank. ↩︎
News Release

How Marketplace Costs and Premiums Will Change if American Rescue Plan Subsidies Expire

Published: Sep 24, 2021

In a new Policy Watch, KFF analysts explore the potential impact of the expiration of the American Rescue Plan Act’s enhanced financial help and new eligibility for the Affordable Care Act’s health insurance Marketplace federal subsidies. While the COVID-19 relief legislation passed earlier this year provides greater subsidy assistance through 2022, Democrats in Congress are currently considering making the temporary federal help permanent or extending it as part of their planned budget reconciliation legislation.

The authors describe what is at stake in the current debate, from the additional costs to the federal government if the temporary relief is extended, to premium payments and/or deductibles rising for the millions of people currently receiving enhanced subsidies. The average Marketplace enrollee would see their premiums doubled and would have to pay about $800 more if enrolled the whole year. Low-income people, who are 42% of Marketplace enrollees, pay nothing or a minimal amount in premiums currently and would see the largest percentage increase in premium costs if the subsidies expire.

Also touched on are the potential political implications of the expiration of the enhanced subsidy assistance as Marketplace enrollees would receive their renewal notices in October, 2022, weeks before the midterm congressional elections.

How Marketplace Costs and Premiums will Change if Rescue Plan Subsidies Expire

Authors: Cynthia Cox, Karen Pollitz, and Giorlando Ramirez
Published: Sep 24, 2021

The American Rescue Plan Act (ARPA) passed earlier this year temporarily expanded subsidies available in the Affordable Care Act (ACA) health insurance Marketplaces, building on the ACA’s existing subsidies. Through the end of 2022, low-income families who were already eligible for financial assistance under the ACA are eligible for even more financial help to buy their own health insurance and pay for their copays and deductibles for coverage bought on healthcare.gov or their state’s exchange. Additionally, middle income families who were often priced out of ACA coverage before the ARPA, are now eligible for financial help with their monthly insurance premiums for the first time.

These new and additional subsidies were created under the ARPA as part of a larger pandemic relief strategy, but Democrats have long favored similar strategies to reduce the cost of ACA marketplace plans to enrollees. And the state of California, along with a handful of other states, had already implemented its own state-funded subsidies to address premium affordability. One of the key criticisms of the ACA has been the high and rising premiums, particularly for working families with incomes over four times the poverty level (a little more than $50,000 for a single person or just over $103,000 for a family of four), who previously were not eligible for financial assistance. While the relief package did not directly address high cost-sharing for these enrollees, larger premium subsidies can help them afford plans with lower deductibles.

Now, there is a debate in Congress over whether to make these additional premium subsidies permanent, or at least extend them for a longer time period. On the one hand, if Congress extends the ARPA subsidies or makes them permanent, federal costs would increase. On the other hand, if Congress does not extend these subsidies, premium payments will rise sharply for nearly all marketplace enrollees.

If the ARPA subsidies are extended, federal costs will rise

The Congressional Budget Office (CBO) and Joint Committee on Taxation (JCT) originally estimated that the additional temporary subsidies provided under the ARPA would increase federal deficits by $34.2 billion. Most of that cost is concentrated in the first couple of years since the additional subsidies expire at the end of 2022, though CBO expected some lingering costs as some subsidized people would remain enrolled for a time, even after the ARPA subsidy enhancements end.

The Department of Health and Human Services (HHS) reports that ARPA subsidies for existing consumers cost $537 million per month. It is likely these costs could rise next year as more people take up coverage during open enrollment.

If subsidies expire, premium payments could double for millions of Marketplace enrollees

Average Monthly Premium Payment for Individual Market Enrollees Under American Rescue Plan Act

According to HHS, the 8 million marketplace enrollees who signed up before the ARPA subsidies were enacted are now paying $68 per month, after accounting for an average monthly premium savings due to the ARPA of $67. Without the ARPA subsidies, premiums would double on average for these enrollees and they would pay an average of $800 per year more if enrolled for the full year.

Premiums or deductibles would increase most steeply for the lowest-income Marketplace enrollees

People with incomes between 1 and 1.5 times the poverty level currently represent 42% of enrollees, and, with the ARPA subsidies, now pay nothing or next to nothing for their monthly premium. Before the ARPA, these individuals had to contribute more than 2% of their income toward the benchmark silver plan premium. These lowest-income enrollees would therefore see the steepest percent increases if ARPA subsidies expire.

Because of these premium increases, some low-income people may move from very generous silver plans with deductibles under $200, to bronze plans with deductibles of about $7,000 – more than 30 times higher. HHS reports that the median deductible in the federal marketplace decreased by more than 90%, from $750 in 2020 to $50 in 2021, because some low-income enrollees moved from bronze to silver plans.

Millions of middle-income people would lose subsidy eligibility

Middle income individuals and families also buy coverage in the marketplace when they don’t have access to job-based group plan coverage. These include people who work for small businesses that don’t offer group health benefits, gig and other self-employed workers, and people who retire early, before the age of Medicare eligibility. We estimate that 3.7 million people (most with incomes between 4 and 6 times poverty) gained subsidy eligibility with the ARPA.

Under the ARPA, the vast majority of people buying their own health insurance coverage can be sheltered from premium increases by taking advantage of the subsidies offered in the ACA marketplace. If these subsidies expire, though, middle and upper-middle income people who lose subsidy eligibility will not only have to make up the difference in the subsidy; they will also be on the hook for any increase in the “sticker price” of the premium between now and January 1, 2023.

Although these individuals earn a living wage, it is often not enough to afford full-priced insurance. A 48-year-old making $60,000 per year would see their monthly premium payments increase by 36% if they lost subsidy eligibility, and that doesn’t account for any additional increase in the sticker price of premiums. Families and older enrollees would see even larger premium increases.

Without a subsidy, a 60-year-old’s health insurance premium currently averages more than $11,000 per year. If that 60-year-old has an income just above $51,000 – over four times the poverty level – their ARPA subsidy covers more than half of their monthly costs. Without the ARPA, their premium would increase 165%.

The timing of potential premium increases could have political implications

In the event ARPA subsidies are allowed to expire, the timing of the resulting impact on insurance affordability could become an election issue. The ARPA premium subsidy enhancements are set to expire at the end of 2022. Open enrollment begins on November 1, just one week before the midterm election is held on November 8, 2022.

What Does the CPS Tell Us About Health Insurance Coverage in 2020?

Authors: Jennifer Tolbert, Kendal Orgera, and Anthony Damico
Published: Sep 23, 2021

Data Note

As job and income losses mounted during 2020, many experts feared the economic upheaval caused by the COVID-19 pandemic would lead to disruptions in health coverage and increases in the number of people without health insurance. Yet, due to delays or data quality problems in federal surveys typically used to measure health coverage in the US, there has been limited comprehensive data to measure what happened to the number of uninsured people during 2020. The recent release of the Census Bureau’s Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) provides data on changes to health coverage during 2020. The data show that the number of people who were uninsured and the uninsured rate held steady in 2020.

This data note provides additional context and analysis to understand the 2020 CPS findings. It describes trends in health coverage prior to and during the pandemic and examines the characteristics of the uninsured population in 2020. We focus on nonelderly people, since there is virtually universal coverage among those age 65 and over because of Medicare. Due to known data quality issues with the 2019 CPS ASEC data, which was collected in March 2020 just at the onset of the pandemic and experienced low response rates, we use 2018 for comparisons to pre-pandemic coverage. We also discuss possible reasons for the stability in coverage shown in the recent data, including ongoing challenges with measuring coverage during the pandemic.

What happened to health coverage in 2020?

  • In 2020, 27.4 million nonelderly people were uninsured, and the uninsured rates was 10.2%. The uninsured rate was unchanged from 2018 but was higher than the uninsured rate in 2016 (9.1%) (Appendix Table A). The number of people who were uninsured in 2020 grew by more than 2.5 million from 2016 (Figure 1).
Uninsured Rates Among the Nonelderly Population, 2016-2020
  • Coverage declines in recent years reverse a trend that began following enactment of the ACA in 2010, when coverage for young adults below age 26 and early Medicaid expansion went into effect, and the number of uninsured people and the uninsured rate began to drop. When the major ACA coverage provisions went into effect in 2014, the number of uninsured and uninsured rate dropped dramatically and continued to fall through 2016.
  • For the nonelderly population, health coverage type remained surprisingly constant in 2020 compared to 2018. Similar to 2018, 58.7% of the nonelderly population was covered by employer-sponsored insurance, 6.4% purchased non-group coverage, 20.2% had Medicaid, and 4.5% had Medicare or military coverage in 2020 (Figure 2, Appendix Table A).
Health Insurance Coverage Among the Nonelderly Population, 2018-2020
  • For most demographic groups, changes in the uninsured rates from 2018 to 2020 were not significantly different. However, the uninsured rate among nonelderly non-Hispanic Black people increased from 10.5% in 2018 to 11.7% in 2020 while the rate for Asian people decreased from 7.7% in 2018 to 6.4% in 2020 (Figure 3).
Nonelderly Uninsured Rates By Race/Ethnicity, 2018-2020
  • Having a full-time, full-year job in 2020 reduced the risk of becoming uninsured. Among nonelderly adults working less than full-time full-year, the uninsured rate increased to 16.4% in 2020, up from 14.6% in 2018. In contrast, the uninsured rate for full-time full-year nonelderly adult workers was 8.4% in 2020, a decline of 1.1 percentage points from 2018 (Figure 4).
Uninsured Rates By Work Status Among Nonelderly Adults, 2018-2020

Who remained uninsured in 2020?

  • Most (84.3%) of the nonelderly uninsured are nonelderly adults. The uninsured rate among children was 5.6% in 2020, less than half the rate among nonelderly adults (11.9%), largely due to broader availability of Medicaid and CHIP coverage for children than for adults (Appendix Table B).
  • In 2020, over three quarters of uninsured individuals (76.1%) had at least one full-time worker in their family and an additional 11.2% had a part-time worker in their family (Figure 5).
Characteristics of the Nonelderly Uninsured, 2020
  • Individuals with income below 200% of the Federal Poverty Level (FPL; the federal poverty level was $20,852 for a family of two adults and a child in 2020) are at the highest risk of being uninsured. In total, more than eight in ten (82.6%) uninsured people were in families with incomes below 400% of poverty in 2020 (Figure 5).
  • People of color make up 43.6% of the nonelderly population, but account for over six in ten (62.8%) of the uninsured population in 2020. Hispanic people comprised the largest share of the uninsured (40.1%) while 37.2% of the uninsured are non-Hispanic White people (Figure 5). In general, people of color are at higher risk of being uninsured than White people. Hispanic, Black, and American Indian/Alaska Native people all have significantly higher uninsured rates than White people (6.7%) (Figure 3).

Discussion

Despite a public health crisis that caused significant economic turmoil, the CPS data indicate that health coverage during 2020 was relatively stable compared to before the pandemic. According to the data, the uninsured rate did not increase, and the share of people with private coverage through an employer and purchased directly in the individual market as well as those with Medicaid coverage did not change compared to 2018. While coverage overall was steady, certain groups experienced a greater risk of becoming uninsured in 2020, including nonelderly Black individuals and nonelderly adults who worked less than full-time.

The survey findings are consistent with other analyses of health coverage changes during 2020 that suggest job losses were higher than declines in employer-sponsored coverage. These analyses conclude that job losses occurred primarily among lower income workers who were less likely to obtain health coverage through their employer. Consequently, these individuals did not lose employment-based coverage when they lost their jobs. They may have already been uninsured or had coverage through another source, such as Medicaid or the ACA Marketplace. Also, some people who lost their jobs were placed on temporary furlough, and employers may have continued their health benefits. Additionally recent increases in Marketplace coverage, driven in part by more generous subsidies made available by the American Rescue Plan Act, occurred during 2021 and would not be captured in the 2020 data. However, administrative data suggests declines in employer coverage were somewhat larger than suggested by the CPS.

However, the survey findings are somewhat less consistent with administrative data showing large increases in Medicaid enrollment during the pandemic. Following implementation of the ACA’s Medicaid expansion, enrollment in Medicaid increased as many low-income working adults who did not have coverage through their jobs became eligible for Medicaid. While enrollment dropped in 2019, administrative data indicate Medicaid enrollment has grown by nearly 15% since the start of the pandemic. From 2018 to 2020, average monthly Medicaid enrollment increased by 4% according to administrative data, an increase not mirrored in the CPS. Provisions in the Families First Coronavirus Response Act (FFCRA) that require states to ensure continuous coverage for those enrolled in Medicaid as of March 18, 2020 to be eligible for enhanced federal Medicaid matching funds during the COVID-19 public health emergency (PHE) contributed to the enrollment growth.

Some of the discrepancies noted above may be related to the way in which the survey counts uninsured people or to ongoing challenges with response rates. The CPS counts people as uninsured if they lack coverage for the full year and thus does not capture those who may have lost insurance during the year. Other analyses of monthly data on health coverage from the CPS ASEC shows that a higher share of adults were uninsured for part of the year in 2020 compared to 2018, indicating that adults may have been more likely to lose coverage in 2020 than in 2018 (rates of part-year coverage for children were the same in 2018 and 2020). Also, KFF analysis of the March 2021 point-in-time coverage estimates shows a higher uninsured rate (10.8% as March 2021 versus 10.2% for full-year 2020), further indicating some loss of coverage due to the pandemic. In addition, though the Census Bureau made adjustments in the 2020 data collection to account for ongoing issues with response rates, there is evidence suggesting that the nonresponse bias persists with the 2020 data, especially among lower income individuals. The CPS also relies on respondents self-reporting their health coverage, which may not match administrative data.

As the US moves forward from the pandemic, continuing economic challenges and the unwinding of the PHE could lead to coverage disruptions in the coming year. Although the economy is rebounding, not all of the new jobs provide health coverage. Additionally, when the continuous coverage requirements in Medicaid end, states will need to redetermine eligibility for current enrollees, a process that can lead to loss of coverage even among those who remain eligible. Continued efforts will be important to ensure people who may be at risk of losing coverage are aware of and connected to potential alternative coverage options.

Appendix

 

Appendix Table A: Change in Selected Characteristics of the Nonelderly Uninsured, 2016, 2018, and 2020

 

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Housing Affordability, Adequacy, and Access to the Internet in Homes of Medicaid Enrollees

Author: Bradley Corallo
Published: Sep 22, 2021

Issue Brief

Executive Summary

The COVID-19 pandemic and the ensuing economic disruption have drawn more attention to longstanding issues related to housing and internet access and how these issues can impact health. As the primary source of health insurance for low-income populations, Medicaid covers a considerable share of people living in homes that are unaffordable, inadequate, or have limited access to the internet. This brief examines housing adequacy, affordability, and internet access within the homes of Medicaid enrollees using data from the 2019 American Community Survey (prior to the COVID-19 pandemic) and assesses the limited role that Medicaid can play in helping to address these challenges. Key findings include the following:

  • Prior to the pandemic, in 2019, the majority (57%) of Medicaid enrollees lived in a home that was inadequate (defined as lacking complete plumbing or kitchen facilities or being overcrowded) or unaffordable (defined as costing more than 30% of household income), representing more than one-third (36%) of all individuals in such homes nationally.
  • We estimate that 13% of Medicaid enrollees did not have internet access in their home prior to the pandemic, either through a computer or cell phone, and an additional 13% have internet but with limited computer access in their homes (i.e., a smartphone was the only computer device in the home or no computer device).
  • The likelihood of Medicaid enrollees living in inadequate or unaffordable homes were especially high for Native Hawaiian/Other Pacific Islander enrollees (70%) and Hispanic enrollees (67%), as well as enrollees ages 18 and under (63%) and enrollees in metro areas (59%). Limited internet and computer access was highest among American Indian/Alaska Native enrollees (43%), enrollees ages 65 and older (41%), and enrollees in non-metro areas (31%).
  • Housing problems can negatively impact health, but Medicaid plays a narrow role in addressing these impacts. Medicaid has traditionally been able to cover certain non-clinical services (including housing-supports) through home and community-based services (HCBS) programs that support seniors and people with disabilities. Beyond HCBS programs, states have limited ways to leverage Medicaid for supporting access to some housing supports, though Medicaid generally cannot pay the direct costs of non-medical services like rent and food.

While housing insecurity and other “social determinants” can affect health, policies and programs outside of Medicaid – and the health care sector generally – have the greatest impact on housing issues among the broader Medicaid population. Recent legislation has created or extended funding for several federal housing programs, which likely helped to stabilize housing for many people during the pandemic. Additionally. one of the key priorities in the proposed infrastructure bill, the Infrastructure Investment and Jobs Act, would address some issues related to broadband access in rural and low-income communities if signed into law. The Centers for Disease Control and Prevention also implemented a temporary eviction moratorium that likely contributed to greater housing stability for people behind on rent; however, the Supreme Court ended the moratorium in August 2021, requiring that Congress authorize the moratorium to continue.

Why is housing important for health and the COVID-19 pandemic?

Housing can impact health in several ways. For example, housing adequacy may have a direct link to health through its effect on access to clean water, ability to store food or medications, prepare healthy meals, or maintain personal hygiene. Problems with housing affordability (typically defined as spending more than 30% of household income on housing) can lead to housing instability, overcrowding, and potentially homelessness, all of which have been associated with a range of physical and mental conditions. The causes of housing adequacy and affordability issues are extremely complex vary greatly by locality, with differences often reflecting state and local policy decisions, local economic conditions, availability of federal housing assistance, and historical and ongoing practices of housing discrimination.

Households with lower incomes generally have higher rates of living in unaffordable housing and having serious housing deficiencies or limited internet access. As the primary source of health insurance coverage for low-income populations, Medicaid covers many enrollees who are likely experiencing housing issues such as these. While Medicaid has traditionally been able to cover certain non-clinical services (including housing-supports) through home and community-based services (HCBS) programs that support seniors and people with disabilities, Medicaid generally cannot pay the direct costs of non-medical services like housing and food. However, there are more narrow ways in which Medicaid can be leveraged to help support access to some housing supports. Other programs outside of Medicaid – and the health care sector – are designed to address housing issues for low-income populations. At the federal level, for example, programs such as the Low-Income Housing Tax Credit Program, Housing Choice (Section 8) Voucher Program, and public housing are designed to improve access to affordable housing, although these programs have historically faced a range of unique challenges, including underfunding, long wait lists to receive benefits, and challenges locating housing units in desirable neighborhoods.

The COVID-19 pandemic has drawn more attention to housing issues related to affordability, quality, and internet access at home. For example, data from the Census Bureau’s Household Pulse Survey estimate that, between September 1 and September 13, 2021 (the latest data available), 14.6 million adults lived in households that were behind on rent or mortgage payments, and 4.5 million of these adults reported that they were “very likely” or “somewhat likely” to be evicted or experience foreclosure in the next two months. Moreover, as people spend more time in and around their homes during the pandemic, living in safe, adequate housing with complete amenities has also become increasingly important for personal health and social distancing. For example, living in a crowded household can potentially increase transmission of the coronavirus to other member of the household and limit their ability to effectively quarantine. Similarly, having internet access in the home has become a common way to receive health care and attend school, as well as to work from home where possible, while following social distancing guidelines during much of the pandemic.

What do the data say about housing affordability, adequacy, and access to internet for Medicaid enrollees prior to the pandemic?

In this brief, we follow the definitions for incomplete plumbing facilities, incomplete kitchen facilities, overcrowding, and unaffordable housing as defined by the U.S. Census Bureau’s ACS 2019 Subject Definitions. Notably, this brief’s definition of “inadequate housing” (defined below) differs from the U.S. Department of Housing and Urban Development’s (HUD’s) definition captured through the American Housing Survey (AHS). We did not use AHS data because the survey does not capture health insurance information for respondents.

Inadequate housing is either (1) a housing unit lacking complete plumbing and/or kitchen facilities as reported in the ACS or (2) “overcrowded” housing units. In the ACS, complete plumbing and kitchen facilities include hot and cold running water, a shower or bathtub, a sink with a faucet, a stovetop or range, and a refrigerator. Overcrowded housing units are those with more than 1 occupant per room (not counting bathrooms, porches, balconies, hallways, or unfinished basements, etc.).

Unaffordable housing is defined as paying more than 30% of household income on either (1) gross rent (contract rent plus most utilities) or (2) owner costs (mortgage payments, most utilities, real estate taxes, some insurance coverage, condominium fees, deeds of trust, and contracts to purchase). Housing units with zero or negative income are considered to live in unaffordable housing, while housing units who do not pay cash rent are assumed to live in affordable housing.

Internet access includes individuals living in homes that receive internet services through internet service providers or through a cell phone company, whether or not the household pays for internet services.

Limited computer access includes individuals living in homes that either (1) do not have a computer or (2) the only means to access the internet is with a smartphone (versus having a desktop, laptop, tablet, or another computer device available in the home, sometimes called “smartphone dependent”). We only report limited computer access for housing units with internet.

Even before the pandemic, the majority of Medicaid enrollees (57%) lived in inadequate or unaffordable housing, greatly exceeding the rate of the U.S. population overall (31%). In 2019, prior to the pandemic, nearly half (47%) of Medicaid enrollees lived in housing that was unaffordable, and 17% lived in crowded housing, both of which exceeded the national average (26% and 7%, respectively). Few Medicaid enrollees (1%) live in homes with incomplete plumbing or kitchen facilities, similar to the national average. Roughly one in 13 (8%) Medicaid enrollees live in a home that has two or all three of these conditions, exceeding the national rate of 3%. Overall, there are roughly 99 million people that live in inadequate or unaffordable housing across the U.S., and more than one-third (36% or 36 million) are enrolled in Medicaid. Although these data show national rates, other research shows that the share of people living in unaffordable housing varies greatly across localities.

The Majority of Medicaid Enrollees Live in Inadequate or Unaffordable Housing

The share of Medicaid enrollees living in homes that are inadequate or unaffordable varied across race/ethnicity in 2019. For example, seven in ten (70%) Native Hawaiian/Other Pacific Islander (NHOPI) enrollees live in a home with at least one of the selected housing conditions for inadequate or unaffordable housing, and two in ten (20%) live in homes with two or all three of the selected housing conditions. Additionally, American Indian and Alaska Native (AIAN) enrollees have the highest rates of incomplete plumbing or kitchen facilities, and AIAN enrollees were among the only demographic group we examined to exceed 2% on this measure. Generally, the shares of people of color enrolled in Medicaid exceeded the rates among White enrollees living in overcrowded and unaffordable housing.

Among different age groups, children enrolled in Medicaid (or CHIP) were the most likely to live in inadequate or unaffordable housing (63%). This pattern may reflect having multiple children (relative to the number of adults) within an inadequate or unaffordable housing unit. Enrollees in metro areas also experienced higher rates of inadequate or unaffordable housing compared to enrollees in non-metro areas, and the difference was especially large for unaffordable housing (49% vs. 38%). When looking at sex, although the differences were statistically significant at the p < .05 level (Appendix Table 1), rates of unaffordable housing were generally similar for males and females across all measures. For example, 56% of male enrollees and 58% of female enrollees lived in a home with any condition related to inadequate or affordable housing.

Percent of the U.S. Population and Medicaid Enrollees Living in Homes with Selected Housing Conditions by Race/Ethnicity, 2019

In 2019, roughly one in four Medicaid enrollees lived in a home without internet or with limited computer access. An estimated 13% of Medicaid enrollees have no internet access in their home, either through a computer or a cell phone. A similar share (13%) of Medicaid enrollees have internet access, but they either lack any type of computer device (1%) or the only computer in the home is a smartphone (12%), limiting the amount of tasks and activities that can be completed online. Previous KFF research showed Medicaid enrollees made up 32% of people across the U.S. without internet access in their home. When considering internet access in conjunction with limited computer access, Medicaid enrollees make up a slightly larger share. Of the 47 million individuals living in homes without internet or with limited computer access, 16 million (34%) are enrolled in Medicaid.

One in four Medicaid Enrollees Lives in a Home with Limited Internet or Computer Access.

Leading up to the pandemic, internet access and the availability of computers in the homes of Medicaid enrollees varies by race/ethnicity, age, sex, and metro/non-metro areas in 2019. More than four in ten (43%) AIAN enrollees had limited internet or computer access, including 27% who had no internet access in their homes. Black people also had among the highest rates of limited internet or computer access (34%), including 16% with no internet access in their homes. Enrollees who are ages 65 and older also had high rates, with 41% facing internet or computer limitations, with nearly one-third (30%) lacking internet in their homes. Non-metro areas also had high rates of internet or computer limitations (31%), with 17% of enrollees lacking access to the internet in their homes. Conversely, there was little difference between male and female enrollees, with 25% and 26% of enrollees reporting limited internet or computer access, respectively, although differences were statistically significant at the p < .05 level (Appendix Table 2).

The Share of Medicaid Enrollees Living in a Home with Internet and Computer Access by Selected Demographic Characteristics, 2019

What are the policy levers for Medicaid to address housing challenges?

State Medicaid programs can add certain non-clinical services, including housing supports, into home and community-based services (HCBS) programs to support seniors and people with disabilities. CMS released guidance in January 2021 to highlight opportunities to address SDOH in Medicaid and CHIP. That guidance specified that federal Medicaid matching funds are available for certain housing-related services and supports that promote health and community integration. These services are generally available for children with special health care needs, adults with disabilities, or seniors. Housing-related services in HCBS programs might include: home accessibility modifications (such as wheelchair ramps or grab bars in the shower); one-time community transition costs (such as payment of a security deposit, utility activation fees, and essential household furnishings); and housing and tenancy supports (such as help with a housing search, identifying adequacy of public transit, and assisting in arranging for and supporting move-in); and tenancy sustaining services (education or training on the role, rights, and responsibilities of the tenant and landlord).

Beyond HCBS authorities, Medicaid has limited ability to address housing related challenges for most enrollees. Primarily, Medicaid can help to finance many health and behavioral health services that can be critical in helping people obtain and maintain housing. Medicaid can play an important role in coordinating medical and non-medical services and act as a bridge to social services (e.g., case management). States can also require managed care organizations to screen for and provide referrals for social services. States and plans can also build partnerships across sectors to meet basic needs for enrollees – including building linkages with supportive housing programs. Plans may also have additional flexibilities to provide certain non-medical services outside of contractually-covered services (through what are known as “in-lieu-of” and “value-added” services), although state Medicaid agencies must approve which services can be counted toward the capitation rate paid to the plans. While there are examples of health plans and provider systems investing in affordable housing programs (e.g., community investment or reinvestment requirements), these programs are often hard to scale or replicate broadly given issues with housing costs and supply. Further, screening and referral may not help to address housing challenges for Medicaid enrollees. While Medicaid is an entitlement, affordable housing/rental assistance programs are generally capped and not available to all who qualify and need assistance.

Some states have used or are seeking approval to use Medicaid waivers to address housing issues for high need populations. For example, in October 2018, CMS approved North Carolina’s Section 1115 waiver which provides financing for a new pilot program, called “Healthy Opportunities Pilots,” to cover non-medical services that may include housing modifications (such as carpet replacement and air conditioner repair to improve a child’s uncontrolled asthma control). To be eligible, enrollees must have at least one physical or behavioral health risk factor and at least one social risk factor (including homelessness or housing insecurity). Pilot services in North Carolina are expected to begin in the Spring of 2022.

Arizona is currently requesting Section 1115 waiver approval to enhance and expand housing services and supports for enrollees who are homeless or at risk of becoming homeless and also have another high-risk condition. Services could include short-term, transitional housing (up to 18 months) for individuals leaving homelessness or institutional settings; community transitional services to provide financial assistance for non-recurring move-in expenses to assist members in obtaining housing; eviction prevention services, which may include payment of back rent, utility bills; home modification services or pre-tenancy and tenancy support services. The waiver application is still pending but, if approved, will be authorized in the fall of 2021.

In 2016, California began its “Whole Person Care” (WPC) pilot program authorized under Section 1115 waiver authority. This program operates in certain counties and targets high-risk, high-utilizing populations including individuals experiencing or at risk of homelessness. Common services offered by WPC pilots include housing-related services such as housing navigation, tenancy support, and landlord incentives. In June 2021, California requested CMS approval to sunset Section 1115 authority for the WPC pilot program, indicating plans to instead expand the WPC approach statewide via the state’s managed care delivery system (with the introduction of enhanced care management statewide and a new menu of state-approved in-lieu-of services). This Section 1115 request also included federal funding to support capacity building for this expanded initiative, called “California Advancing and Innovating Medi-Cal” (CalAIM). California intends to implement CalAIM in January 2022.

In addition to stable and adequate housing, lack of internet and computers have implications to receive Medicaid services via telehealth. Prior to the pandemic, state coverage of telehealth in Medicaid varied widely. States took many factors into consideration when establishing temporary policies during the pandemic to increase telehealth coverage and access, including budget limitations, patient and provider acceptance, scope of practice laws, operational/technology challenges and costs for providers and patients, evidence of quality and effectiveness for services delivered via telehealth, and concerns involving potential for fraud and abuse, among others. Although state coverage of telehealth in Medicaid still varies widely, many states vastly expanded the use of telehealth in response to the COVID-19 crisis. However, telehealth requires technology and internet access that is a challenge for many Medicaid enrollees. While state Medicaid programs can expand the use of telehealth, Medicaid funds cannot address broader issues of internet and computer access.

Looking Ahead

A growing body of literature shows that improving housing quality, affordability, and internet access is fundamental step to improving individual and population health. As the primary source of health insurance for low-income Americans, Medicaid covers a considerable share of people living in homes that are inadequate, unaffordable, or have limited access to the internet. Although Medicaid has a limited role in helping to address these issues for the broader Medicaid population, states have some existing policy levers and can use partnerships to provide some access to housing services and supports for narrow subsets of enrollees.

In response to the pandemic, the federal government has taken several steps to stabilize housing for low-income households during the pandemic. For example, The American Rescue Plan Act created or increased funding for several federal housing programs, including an increase in funding for the Emergency Rental Assistance (ERA) program to over $45 billion, which is a program administered through the states to help renters pay late rent and utilities. It is unclear whether ERA funds will be enough to cover low-income renters’ late rent and utilities, as estimates of need vary widely. Additionally, data from the Census Bureau’s Household Pulse Survey estimate that only 2.8 million of the 8.2 million adults behind on rent had applied for rental assistance through the state or local government, and the majority were still awaiting a response (1.4 million) or were denied (900,000) as of late August. The  current infrastructure proposal being debated in Congress also contains provisions to expand broadband internet access for rural and low-income communities, as well as funds for digital literacy training so that individuals can use the internet effectively for daily tasks. Moreover, the proposed infrastructure bill includes increased funding for replacing lead service lines, in additional to other steps, to improve access to safe drinking water. Earlier in the pandemic, the Centers for Disease Control and Prevention (CDC) issued a temporary eviction moratorium that prevented landlords from evicting tenants due to unpaid rent (although it did not stop rent, fees, penalties, or interest from accruing). However, the Supreme Court ended the eviction moratorium in August 2021, before it was set to expire, requiring that Congress authorize the moratorium to continue. Housing and internet issues pose major challenges to Medicaid enrollees and low-income populations generally – and these issues generally worsened during the pandemic. The breadth and scope of federal housing programs and supports will ultimately have implications for Medicaid enrollees’ home lives and associated health risks during the pandemic.

Methods

This brief analyzes data from the 2019 American Community Survey (ACS) 1-year file. The unit of analysis in this brief is the individual, rather than households or the housing unit, and we use the person weights in the ACS data file. Household characteristics, such as household income, housing costs, and internet access, are the same for all members of the household. However, individual characteristics, such race, age, and sex, are reported differently for each member of the household. For example, children and adults in the household may be reported separately in our findings, as well as individuals in a household comprised of people identifying with different race/ethnicities or sexes. Our findings will differ from other studies where the unit of analysis is the housing unit, which often report demographics based on the householder (rather than individuals in the house) and use housing unit weights in the ACS data file. All differences between Medicaid enrollees that are mentioned in the brief are significant at the p < .05 level, which are also shown in appendix tables.

Our analysis excluded people living in noninstitutional group quarters such as college dormitories and residential treatment centers because the ACS does not collect data on plumbing, kitchen facilities, or internet access for in these housing units. Notably, however, our analysis included both renters and owners.

As noted in the definitions box in the brief, the definitions for incomplete plumbing facilities, incomplete kitchen facilities, overcrowding, and unaffordable housing are defined by the U.S. Census Bureau’s ACS 2019 Subject Definitions. For unaffordable housing, we assumed that people with zero or negative income lived in unaffordable housing, and those who do not pay cash rent (but have positive household income) are assumed to live in affordable housing.

Metro and non-metro classifications are not part of the ACS microdata files. Metro and non-metro areas are defined by the USDA Economic Research Service. For this analysis, metro areas were defined as public use microdata areas (PUMAs) where more than 50% of the 2010 population lived in metro areas, and the remaining PUMAs were defined as non-metro areas. We received a crosswalk of metro/non-metro populations for each PUMA from a personal communication with USDA staff (June 17, 2021), which we joined with the ACS data. Our analysis used the same methods described further in a another Peterson-KFF Health System Tracker brief.

Appendix

Appendix Table 1: Percent of Medicaid Enrollees Living in Homes with Selected Housing Conditions by Race/Ethnicity, Age, Sex, and Metro/Non-Metro Status, 2019
Appendix Table 2: Percent of Medicaid Enrollees with No Internet or Limited Computer Access in their Home by Race/Ethnicity, Age, Sex, and Metro/Non-Metro Status, 2019

Tracking U.S. COVID-19 Vaccine Donations

Published: Sep 22, 2021

For the latest data on U.S. COVID-19 vaccine donations visit our tracker.

There remains a significant gap in vaccine access across the world, with only 2% of the population in low-income countries (LICs) receiving at least one vaccine dose, compared to 30% in lower-middle-income countries (LMICs), 54% in upper-middle-income countries (UMICs), and nearly two-thirds in high-income countries (HICs). One way to address this gap is for countries that have vaccines to donate them to countries in need, either via the multilateral COVAX mechanism or directly to countries and/or regions via bilateral donations. For its part, the U.S. government has pledged to donate at least 1.1 billion doses of COVID-19 vaccine for global use by 2022 and has been delivering doses to countries around the world since June.1  To understand more about these donated doses and where they have been directed, we analyzed data from the U.S. State Department, COVAX, and other sources. We find that, as of September 20, 2021:

  • The U.S. has donated approximately 140 million doses2  to at least 93 countries (see Table 1 and Figure 1). The ten countries receiving the most doses include: Pakistan (15.8 million), Bangladesh (6.5 million), Philippines (6.4 million), Colombia (6.0 million), South Africa (5.7 million), Vietnam (5.0 million), Indonesia (4.5 million), Guatemala (4.5 million), Uzbekistan (4.2 million), and Nigeria (4.0 million).
Recipients of U.S. COVID-19 Vaccine Donation Deliveries by Total Doses Received
  • Looking by country income, more than half of U.S. doses have been donated to LMICs (see Figure 2). Of the 140 million doses delivered to date, approximately 77 million (55%) have been provided to LMICs, followed by UMICs (36 million, 26%), LICs (10 million, 7%), and HICs (5 million, 4%). When standardized by population, LMICs still account for the largest amount received (24.9 thousand doses per million population), while UMICs and LICs have received smaller amounts (13.5 thousand and 13.3 thousand doses per million population), and HICs receiving the smallest amount with 4.4 thousand doses per million population.
Total Doses Received of U.S. COVID-19 Vaccine Donation Deliveries by Income
  • Countries in the Western Hemisphere have received the most U.S. doses (both in total and when standardized by population size; see Figure 3). Forty million doses (28%) have been provided to countries in the Western Hemisphere, followed by South and Central Asia (35 million, 25%), Sub-Saharan Africa (29 million, 21%), East Asia and the Pacific (29 million, 20%), Middle East and North Africa (4 million, 3%), and Europe and Eurasia (4 million, 3%). When standardized based on population size, the number of doses received by countries in the Western Hemisphere (50.1 thousand per million) is more than double the next largest region (Sub-Saharan Africa; 22.7 thousand doses per million population).
Total Doses Received of U.S. COVID-19 Vaccine Donation Deliveries by Region
  • The Moderna vaccine accounts for the largest share of U.S. donated doses (see Figure 4). Of the 140 million doses provided to date, 42% are Moderna, followed by Pfizer (25%), and Johnson & Johnson (19%).
U.S. COVID-19 Vaccine Donation Doses Delivered by Vaccine Product
  • The majority of U.S. donated doses have been provided through COVAX (see Figure 5). Approximately 53% of doses (74.7 million) have been provided through COVAX with 38% (54.0 million doses) provided directly to the recipient country.
U.S. COVID-19 Vaccine Donation Doses Delivered by Delivery Mechanism
  • The bulk of U.S. COVID-19 vaccine donations occurred in July 2021. By number of deliveries, most occurred in July (64 deliveries or 50%), followed by August (36 deliveries, 28%), June (7 deliveries, 6%), and through September 20 (17 deliveries, 13%). By number of doses delivered, most doses were still delivered in July (82.4 million doses, or 59%), followed by August (17.6 million doses, 13%), through September 20 (14.4 million doses, 10%), and June (12.3 million doses, 9%).

President Biden has said the U.S. will be the “arsenal of vaccines” for the globe, and the 140 million doses donated by the U.S. to date represent one component of the U.S. effort to expand access to Covid-19 vaccines. While the doses provided so far make the U.S. the single largest donor of vaccines worldwide, these donations remain a fraction of what the U.S. has promised to provide by the end of this year and into next and are far from sufficient to meet global needs. Continued monitoring of U.S. donations will help gauge progress toward meeting its global vaccination goals.

Table 1: U.S. COVID-19 Vaccine Donation Deliveries by Recipient Country
  1. The U.S. announced in June that it would donate 500 million doses of the Pfizer vaccine, and announced an additional 500 million dose donation of Pfizer vaccine in September; the U.S. plans to supply these Pfizer doses via COVAX. An additional number of Moderna and Johnson & Johnson vaccine doses are part of the 1.1. billion total pledge. The U.S. has stated that all of these doses are to be donated in 2021 and 2022. ↩︎
  2. While the U.S. reports that it had shipped over 160 million doses as of September 21, it also reports that it has delivered approximately 140 million doses to country recipients. ↩︎

Tracking Global COVID-19 Vaccine Equity: An Update

Published: Sep 22, 2021

Prompted by the global COVID-19 Summit, called on by President Biden on September 22 held in conjunction with the United Nations General Assembly (UNGA), we provide updated estimates of global COVID-19 vaccine access and equity (our prior analysis from July is here). We examine access by country income level and region, and also estimate progress toward global vaccination goals. These goals include reaching 40% vaccination coverage in all countries by the end of 2021 and 70% by mid-2022, called for by the World Health Organization and others.1  In addition, President Biden has called for reaching 70% fully vaccinated in all countries by fall 2022, ahead of next year’s UNGA meeting. For this analysis, we estimate the share of population within each grouping (income and region) expected to receive at least one dose against these targets in order to provide a best-case scenario (since reaching full vaccination would actually require more than one dose for many COVID-19 vaccines).

In our updated analysis we find that, as of September 9, there continue to be wide disparities in access and at current rates, most low-income countries (LICs) and most countries in Africa will not reach global vaccination targets. We also find that, compared to July, the rate at which vaccination would have to increase for LICs to meet global targets is even greater now, due to more ambitious goals and continued low rates of dose administration in these countries.

COVID-19 Vaccinations by Country Income

There are large differences in the share of the population that has received at least one vaccine dose by country income, with low-income countries lagging significantly behind. As of September 9, only 2% of the population in LICs had received at least one vaccine dose, compared to 30% in lower-middle-income countries (LMICs), 54% in upper-middle-income countries (UMICs), and nearly two-thirds (65%) in high-income countries (HICs). In 6 LICs (25%), fewer than 1% had received at least one vaccine dose. By contrast, in 6 HICs (8%), more than 80% of the population had (see Figure 1 and Figure 2).

Share of Population That Has Received At Least One Dose by Income
Share of Population That Has Received At Least One Dose by Country and Income

See Table 1 for the full list of countries in each income group by share of population that has received at least one dose.

Similarly, there is also a large gulf in the rate at which vaccines are being administered by country income. While the daily rate of first doses administered varies by country (see Figure 3), in late August, LMICs surpassed HICs and UMICs, due to both an increase in first doses being administered in LMICs and a decrease in rates among HICs and UMICs. However, all three income groups are vaccinating at a rate ranging from 19-29 times higher than LICs. See Table 2 for a breakdown of countries in each income group by coverage and daily administration rates.

Daily Rate of First Doses Administered per One Million People by Country and Income

If current trends continue, these disparities are likely to grow, and LICs are unlikely to meet vaccination targets. Based on current vaccination rates (using rates of first doses administered), HICs, UMICs, and LMICs are on track to have 40% or more of their populations having received at least one dose by the end of the year, whereas LICs would need to increase their daily rate by nearly 35 times in order to meet the same goal. HICs, UMICs, and LMICs are also on track to have 70% or more of their populations having received at least one dose by mid-2022, while LICs would need to increase their daily rate by 24 times (see Figure 4). As of September 9, almost all HICs (68 countries or 96%) had already met one or both of the WHO targets, as had just over a third of UMICs (18 or 35%). Less than a fifth of LMICs (9 or 17%) and no LICs had met these targets. In order to reach 70% of the population with at least one dose by next year’s UNGA meeting, LICs would need to increase their daily rate by 19 times.

Projected Share of Population That Has Received At Least One Dose by Income Using Global Targets

COVID-19 Vaccinations by Region

As with country income, there are large differences in the share of the population that has received at least one vaccine dose by region, with the highest coverage in the Western Pacific and smallest in Africa. As of September 9, the region with the highest coverage is the Western Pacific (67%) followed by the Americas (56%) and Europe (52%); Africa has the lowest coverage (4%) (see Figure 5 and Figure 6).

Share of Population That Has Received At Least One Dose by Region
Share of Population That Has Received At Least One Dose by Country and Region

See Table 3 for a breakdown of top countries in each region by coverage and daily administration rates.

The rate of vaccine administration is highest in South-East Asia and lowest in Africa. While rates of first doses administered vary by country (see Figure 7), South-East Asia currently has the highest rate of daily doses administered. This region is vaccinating at a rate 1.2 times that of the Western Pacific, 1.4 times that of Eastern Mediterranean nearly 2 times the rate of the Americas, 2.7 times that of Europe, and   6 times higher that of Africa. See Table 4 for a breakdown of countries in each region by coverage and daily administration rates.

Daily Rate of First Doses Administered per One Million People by Country and Region

These disparities are likely to grow based on current vaccination trends. Western Pacific, Europe, the Americas, and South-East Asia, and Eastern Mediterranean are all ahead of schedule toward reaching 40% by the end of 2021 while Africa would need to increase its rate of daily first doses administered by more than 6 times the current rate. They are also ahead of schedule to reach 70% by mid-2022, while Africa would need to increase its rate of daily first doses administered by approximately 5 times the current rate (see Figure 8). Certain countries, primarily those in Europe, have already met some of these vaccination targets. As of September 9, 35 European countries (66%) have met one or both of these targets, and more than half of countries in the Americas (54%) and the Western Pacific (52%) have met one or both of these targets. On the other hand, only 7% of countries in Africa (3 countries) have met either of these targets. In order to reach 70% of the population with at least one dose by next year’s UNGA meeting, the African region would need to increase its daily rate by nearly 4 times.

Projected Share of Population That Has Received At Least One Dose by Region Using Global Targets

Implications

These findings underscore an ongoing equity gap in access to COVID-19 vaccinations around the world, particularly for those living in the poorest countries and in countries in Africa. Furthermore, they suggest that if current rates continue, some of these disparities may grow and many low-income countries will not meet global targets. Increasing vaccine supply and stepping up the pace of vaccinations in those countries lagging furthest behind can narrow the equity gap and help all countries achieve COVID-19 vaccination coverage goals.

Tables

Table 1: Countries by Share of Population that Has Received at Least One Dose

Table 2: Countries by Daily Rate of First COVID-19 Vaccine Doses Administered per 1,000,000 People

Table 3: Countries by Share of Population that Has Received at Least One Dose

Table 4: Countries by Daily Rate of First Doses Administered by Region

Methodology

Vaccination Data: We used country-level vaccination data on doses administered, provided by Our World in Data (OWID), to assess global vaccination trends at the income and regional level. Totals for some entities were combined (Taiwan, Hong Kong, and Macao included as part of China, and Jersey and Guernsey were combined and reported as the Channel Islands). Where missing data in the daily doses provided existed between two dates for a country, we estimated the number of doses administered each day between the two reported dates assuming a linear distribution. For countries that have stopped reporting data, we assumed no change in new doses administered. For countries that report total doses administered but not share of population that has received at least one dose, we use OWID’s suggested methodology and calculated a lower-bound estimate. As a result, our estimates are conservative and the actual share of the population receiving one dose is likely higher. For data on daily administration of first doses, we calculated the rolling 7-day average in daily change of the number of people who have received at least one dose. For projecting increased rate needed for groupings to reach certain benchmarks (40% by end of 2021, 70% by July 1, 2022, and 70% by September 13, 2022), we calculated the rate needed to reach these benchmarks for each grouping, based on number of first doses already administered and population, and calculated the percentage change from the current daily rate in first doses being administered to the increased rate needed to reach these targets. Lastly, for all data, to account for any lag in country reporting, we use data up to one week prior (September 9, 2021).

Population Data: Population data were obtained from the United Nations World Population Prospects using 2020 estimates for total population (and the CIA World Factbook for Serbia and Kosovo). Totals for some entities were combined (Taiwan, Hong Kong, and Macao included as part of China), while others were separated (separating Kosovo from Serbia).

Income Data: Income classifications were obtained using World Bank data. Entities lacking an income classification were excluded from the income-level analysis.

Regional Data: Region classifications were obtained using World Health Organization data. Entities lacking a region classification were excluded from the region-level analysis.

  1. While the coverage goals seek to reach 40% and 60% coverage, it is not clear whether this refers to partial coverage (share of population that has received at least one dose) or full coverage (share of population that is fully vaccinated). For our analysis, we focus on share of population that has received at least one dose. Additionally, while these goals aim to vaccinate the global population, we look at populations by income-level and region. ↩︎
News Release

Many Medicare Beneficiaries Face High Out-of-Pocket Costs for Dental and Hearing Care, Whether in Traditional Medicare or Medicare Advantage

Analysis Provides Context About Existing Coverage and Costs as Congress Considers Adding Dental, Hearing and Vision Coverage to Medicare

Published: Sep 21, 2021

Many Medicare beneficiaries face high annual out-of-pocket costs for dental and hearing care — services that generally aren’t covered in traditional Medicare, but typically are covered by Medicare Advantage plans though the scope and value of these benefits vary, finds a new KFF analysis.

The analysis shows that, among beneficiaries who used each type of service, average annual out-of-pocket spending was $914 for hearing care and $874 for dental care in 2018, but considerably less ($230) for vision care. Among those who were in the top 10 percent in terms of their out-of-pocket costs for such services, 2.7 million beneficiaries spent $2,136 or more on their dental care, while 360,000 beneficiaries spent $3,600 or more on hearing services.

Beneficiaries can face high out-of-pocket costs whether they are in traditional Medicare or privately-run Medicare Advantage plans, the analysis finds. Among users of dental services, for instance, average out-of-pocket spending was $766 among beneficiaries in Medicare Advantage and $992 among those in traditional Medicare in 2018.

The analysis also finds that people on Medicare in communities of color, with disabilities, or with low incomes are disproportionately likely to have difficulty getting these services. About 16 percent of all Medicare beneficiaries reported in 2019 that there was a time in the last year that they could not get dental, hearing, or vision care, but this was reported by a greater percentage of beneficiaries under age 65 with long-term disabilities (35%); those enrolled in both Medicare and Medicaid (35%); with low incomes (e.g., 31% for those with income under $10,000); and Black and Hispanic beneficiaries (25% and 22%, respectively).

The new analysis also provides an overview of coverage of dental, hearing, and vision services in Medicare Advantage plans. While most plans offer coverage for these services, the extent of coverage varies and has limits.

  • Nearly all Medicare Advantage enrollees with access to dental coverage have preventive care benefits, and most have access to more extensive dental benefits. Cost sharing for more extensive dental services is typically 50 percent for in-network care, and typically is subject to an annual dollar cap on plan payments.
  • Similarly, almost all Medicare Advantage enrollees have access to hearing exams and hearing aid coverage. The coverage generally is subject to either a maximum annual dollar cap and/or frequency limits on how often plans cover the service.
  • Virtually all Medicare Advantage enrollees have access to vision exams and eyewear coverage, typically subject to maximum annual limits averaging about $160 per year.

The findings come as policymakers in Congress are considering adding dental, hearing, and vision benefits to Medicare as part of the budget reconciliation bill, one of several competing spending priorities in the debate. It would be the largest expansion of Medicare benefits since the Part D drug benefit was launched in 2006. (A similar 2019 proposal would have increased Medicare spending by more than $300 billion over 10 years according to the Congressional Budget Office.)

For the full analysis and other KFF data and analyses about Medicare, including the recent Medicare and Dental Coverage: A Closer Look, visit kff.org

Dental, Hearing, and Vision Costs and Coverage Among Medicare Beneficiaries in Traditional Medicare and Medicare Advantage

Published: Sep 21, 2021

Notably missing among covered benefits for older adults and people with long-term disabilities who have Medicare coverage are dental, hearing, and vision services, except under limited circumstances. Results from a recent KFF poll indicate that 90% of the public says expanding Medicare to include dental, hearing, vision is a “top” or “important” priority for Congress. Policymakers are proposing to add coverage for these services as part of budget reconciliation legislation, and a provision to add these benefits to traditional Medicare was included in the version of H.R. 3 that passed the House of Representatives in the 116th Congress.

The Biden Administration endorsed improving access to these benefits for Medicare beneficiaries in the FY2022 budget. Addressing these gaps in Medicare benefits is grounded in a substantial body of research showing that untreated dental, vision, and hearing problems can have negative physical and mental health consequences. Adding these benefits to Medicare would increase federal spending, and they will be competing against other priorities in the budget reconciliation debate.

Dental, hearing, and vision services are typically offered by Medicare Advantage plans, but the extent of that coverage and the value of these benefits varies. Some beneficiaries in traditional Medicare may have private coverage or coverage through Medicaid for these services, but many do not. As a result, beneficiaries who need dental, vision, or hearing care may forego getting the care or treatment they need or face out-of-pocket costs that can run into the hundreds and even thousands of dollars for expensive dental treatment, hearing aids, or corrective eyewear.

In a separate KFF analysis, we analyzed dental coverage, use, and out-of-pocket spending among Medicare beneficiaries and provided an in-depth look at coverage of dental services in Medicare Advantage plans. In this brief, we build on our prior work by analyzing hearing and vision use, out-of-pocket spending and cost-related barriers to care among beneficiaries in traditional Medicare and Medicare Advantage, incorporating top-level findings from our analysis of dental services to provide a comprehensive profile of dental, hearing, and vision benefits in Medicare Advantage plans. The analysis of spending, use, and cost-related barriers to care is based on self-reported data by beneficiaries in both traditional Medicare and Medicare Advantage from the 2018 and 2019 Medicare Current Beneficiary Survey, and analysis of Medicare Advantage plan benefits is based on the 2021 Medicare Advantage Enrollment and Benefit files for data on individual Medicare Advantage plans (see Methods for details).

Findings

Dental, Hearing, and Vision Use and Spending

  • Difficulty with hearing and vision is relatively common among Medicare beneficiaries, with close to half (44%, or 25.9 million) of beneficiaries reporting difficulty hearing and more than one third (35% or 20.2 million beneficiaries) reporting difficulty seeing in 2019. These percentages may understate the share of beneficiaries who have problems with hearing or vision in that some beneficiaries who wear corrective eyewear or hearing aids do not report having difficulties. For example, among the 83% of Medicare beneficiaries who report wearing eyeglasses or contact lenses, only 32% say they have vision difficulties, while of the 14% of beneficiaries who report using a hearing aid, 65% say they have hearing difficulties. The lower overall rate of hearing aid use, relative to the rate of reported hearing difficulties, may be a function of affordability, considering the relatively high cost of hearing aids and limited availability of lower-cost options for hearing technology.
  • A larger share of Medicare beneficiaries used dental services than either hearing or vision services in 2018. In 2018, 53% (31.3 million) of beneficiaries reported having a dental visit within the past year, 35% (20.3 million) used vision services, and 8% (4.6 million) used hearing services (Figure 1).
  • On average, out-of-pocket spending on hearing and dental care by Medicare beneficiaries who used these services in 2018 was higher than spending on vision care by beneficiaries who used vision services that year. Among beneficiaries who used each type of service, average spending was $914 for hearing care, $874 for dental care, and $230 for vision care (Figure 1).
On Average, Medicare Beneficiaries' Out-of-Pocket Costs Were Higher for Hearing and Dental Care than Vision Care in 2018
  • The distribution of out-of-pocket spending on dental and hearing services is highly skewed, with a small share of users incurring significant out-of-pocket costs (likely associated with the purchase of costly equipment such as hearing aids, or expensive dental procedures, such as implants). For example, in 2018, among beneficiaries who used dental services, beneficiaries in the top 10% in terms of their out-of-pocket costs (2.7 million beneficiaries) spent $2,136 or more on their dental care, while among beneficiaries who used hearing services, beneficiaries in the top 10% in terms of out-of-pocket costs (0.4 million beneficiaries) spent $3,600 or more on these services (Figure 2). Conversely, half of beneficiaries who used dental services had out-of-pocket spending below $244 for their dental care; half of those who used vision services had out-of-pocket spending below $130 for their vision care; and half of those who used hearing services had out-of-pocket spending below $60 for their hearing care.
 Small Share of Medicare Beneficiaries Incurred High Out-of-Pocket Costs for Hearing and Dental Care in 2018
  • Among users of these services, beneficiaries enrolled in Medicare Advantage plans spent less out of pocket for dental and vision care than beneficiaries in traditional Medicare in 2018, but there was no difference between the two groups in spending on hearing care. Both groups spent substantially more for dental and hearing services than vision services. For dental services, average out-of-pocket spending was $766 among beneficiaries in Medicare Advantage and $992 among beneficiaries in traditional Medicare (Figure 3). For vision services, average out-of-pocket spending was $194 among beneficiaries in Medicare Advantage and $242 among beneficiaries in traditional Medicare. Most Medicare Advantage enrollees had coverage for some dental, vision and hearing benefits, as described below, but still incurred out-of-pocket costs for these services.
    • Lower average out-of-pocket spending among Medicare Advantage enrollees for dental and vision care is likely due to several factors. Most Medicare Advantage enrollees have coverage for dental, hearing, and vision services through their plan (as described below), which helps to improve the affordability of these services. Lower out-of-pocket spending among Medicare Advantage enrollees may also be related to lower overall income levels among these beneficiaries. Previous KFF analysis showed that average out-of-pocket spending on dental care rises with income because higher income beneficiaries are more able to afford such expenses, not because they have greater dental needs. It is possible that some traditional Medicare beneficiaries used more, or more expensive, types of dental and vision care than those in Medicare Advantage, contributing to their higher average out-of-pocket costs for these services. Due to data limitations, it is not possible to assess how utilization of dental, vision, or hearing care differed between Medicare Advantage and traditional Medicare enrollees.
Among Beneficiaries Who Used Services, Medicare Advantage Enrollees Spent Less Out of Pocket on Average for Dental and Vision Care than Beneficiaries in Traditional Medicare in 2018
  • About one in six Medicare beneficiaries reported in 2019 that there was a time in the last year that they could not get dental, hearing, or vision care, and among those who reported access problems, cost was a major barrier.
    • Overall, in 2019, 16% of Medicare beneficiaries, or 9.5 million, reported that there was a time in the last year that they could not get dental, hearing, or vision care. This includes 12% of Medicare beneficiaries who said they could not get dental care, 6% who couldn’t get vision care, and 3% who couldn’t get hearing care (Figure 4).
    • Similar shares of beneficiaries in both traditional Medicare and Medicare Advantage reported access problems in the last year for dental, hearing, or vision services (16% and 17%, respectively).
    • Among the 20.2 million beneficiaries who reported difficulty seeing, 11% (2.1 million beneficiaries) said there was a time in the last year they could not get vision care, and among the 25.9 million beneficiaries who reported difficulty hearing, 7% (1.8 million beneficiaries) said there was a time in the last year they could not get hearing care.
    • Medicare beneficiaries more likely to report difficulty getting dental, hearing, or vision care include beneficiaries under age 65 with long-term disabilities (35%); with low incomes (e.g., 31% for those with income under $10,000); in fair or poor health (30%); enrolled in both Medicare and Medicaid (35%); Black and Hispanic beneficiaries (25% and 22%, respectively); and residing in rural areas (20%) (Figure 5).
Cost was a Barrier to Care for Medicare Beneficiaries who Reported in 2019 They Couldn't Get Dental, Vision, or Hearing Care in the Last Year
The Share of Medicare Beneficiaries Saying They Couldn't Get Dental, Hearing, or Vision Care in the Last Year Was Highest Among Those under Age 65, with Low Incomes, in Poor Health, and in Communities of Color
  • Among the 16% of beneficiaries who said that there was a time in the last year that they could not get dental, hearing, or vision care, a majority (70%) said that it was due to cost (Figure 4). This includes 75% of those who couldn’t get hearing care, 71% of those who couldn’t get dental care, and 66% of those who couldn’t get vision care.
    • Among beneficiaries in traditional Medicare and Medicare Advantage who reported access problems in the last year for dental, hearing, or vision care, roughly 7 in 10 beneficiaries in both groups said that cost was a barrier to getting these services (72% and 70%, respectively).
    • Beneficiaries more likely to report cost as a barrier to dental, hearing, or vision care include those under age 65 with long-term disabilities (76%); with low incomes (e.g., 72% for those with incomes under $10,000); and in fair/poor health (75%).

What Dental, Hearing, and Vision Benefits Are Offered by Medicare Advantage Plans?

Most Medicare Advantage plans provide some coverage of routine dental, vision, and hearing benefits, unlike traditional Medicare. Plans can use rebate dollars – a portion of the difference between their bid to cover Medicare Parts A and B services and the benchmark – to provide supplemental benefits, such as dental, hearing, and vision benefits. Plans also use rebate dollars to lower enrollee cost sharing and reduce premiums, and for administrative expenses and profit. According to MedPAC, about 21% of rebate dollars in 2021, or $29 per enrollee per month, were used to cover supplemental benefits not covered by traditional Medicare.

Dental Benefits

In 2021, 94% of Medicare Advantage enrollees or 16.6 million people, are in a plan that offers access to some dental coverage. Virtually all Medicare Advantage enrollees have access to preventive dental benefits and most have access to more extensive dental benefits, according to a prior KFF analysis. Most enrollees with access to more extensive benefits are typically subject to annual dollar limits on coverage, which averages $1,300.

Among Medicare Advantage enrollees with access to dental coverage:

  • Most (86%) of these enrollees are offered both preventive and more extensive dental benefits.
  • More than three in four (78%) Medicare Advantage enrollees who are offered more extensive coverage are in plans with annual dollar limits on dental coverage, with an average limit of $1,300 in 2021. More than half (59%) of these enrollees are in a plan with a maximum dental benefit of $1,000 or less.
  • Nearly two-thirds of Medicare Advantage enrollees (64%) with access to preventive benefits, such as oral exams, cleanings, and/or x-rays, pay no cost sharing for these services, though their coverage is typically subject to an annual dollar cap. The most common coinsurance for more extensive dental services, such as fillings, extractions, and root canals, is 50%.
  • About 10% of Medicare Advantage beneficiaries are required to pay a separate premium to access any dental benefits. For additional and more detailed information about dental benefits offered by Medicare Advantage plans, see “Medicare and Dental Coverage: A Closer Look.”

Hearing Benefits

In 2021, 97% of Medicare Advantage enrollees or 17.1 million people, have access to a hearing benefit. Among these enrollees, virtually all (95%) are in plans that provide access to both hearing exams and hearing aids (either outer ear, inner ear, or over the ear). Hearing aid coverage is typically subject to annual dollar limits on coverage or frequency limits, with an average dollar limit of $960 and the most common frequency limit of one set of aids per year.

Among Medicare Advantage enrollees who have access to hearing coverage:

  • Virtually everyone with hearing aid coverage is subject to either annual dollar limits on coverage, frequency limits on covered services, or both (Figure 6).
    • Nearly a third (32%) of Medicare Advantage enrollees are in plans with a maximum dollar limit the plan will pay annually toward hearing aid coverage as well as frequency limits on hearing aid coverage; about 8% are in plans with maximum dollar limits, but do not have frequency limits. For those in plans with maximum annual dollar limits, the average limit is $960 in 2021, ranging from $66 up to $4,000.
    • Nearly 6 in 10 enrollees (59%) are in plans that do not have maximum dollar limits on hearing aid coverage but do have a frequency limit on how often hearing aids are covered; 1% of enrollees have neither a maximum annual dollar limit nor a frequency limit on hearing aids.
About 40% of Medicare Advantage enrollees are in plans with annual dollar limits on hearing aids; nearly all remaining enrollees have a frequency limit on hearing aids that are covered during a given period
  • Medicare Advantage enrollees are often subject to limits in the frequency of obtaining certain covered hearing-related services.
    • Among enrollees with access to hearing exams, virtually all enrollees (98%) are in plans that limit the number of hearing exams, with the most common limit being no more than once per year.
    • Of the 69% of enrollees with access to fitting and evaluation for hearing aids, about 88% are in plans that have frequency limits on those services, with the most common limit being no more than once per year.
    • Most enrollees (91%) are in plans with frequency limits on the number of hearing aids they can receive in a given period. The most common limit is one set (one for each ear) per year (58%), followed by one set every two years (28%), and one set every three years (14%).
  • Hearing exams are often covered without cost sharing, but hearing aids are typically subject to cost-sharing requirements, and enrollees who do not face cost sharing for hearing aids are usually subject to annual dollar limits.
    • Nearly three quarters of all enrollees (74%) are in plans that do not require cost sharing for hearing exams, while 11% of enrollees are in plans that report cost sharing for hearing exams, with the majority being copays, which range from $15 to $50. Data on cost sharing is missing for plans that cover the remaining 15% of enrollees (see Methods for more information).
    • Of those enrollees with access to fitting and evaluations of hearing aids as part of their plan, more than half (61%) of enrollees are in plans that do not require cost sharing for these services. About 5% of enrollees are in plans that require cost sharing for fittings and evaluations, nearly all copays, which range from $15 to $50.
    • About 60% of enrollees are in plans that require cost sharing for hearing aids, which can range from $5 up to $3,355. Nearly one quarter of enrollees (22%) pay no cost sharing for any type of hearing aid, but virtually all these enrollees are in plans with a maximum annual limit.

Vision Benefits

In 2021, 99% of Medicare Advantage enrollees or 17.5 million people, have access to some vision coverage. Among these enrollees, virtually all (93%) are in plans that provide access to both eye exams and eyewear (contacts and/or eyeglasses). Most enrollees do not pay cost sharing for eyewear, but nearly all vision coverage is subject to annual dollar limits on coverage, averaging $160.

Among Medicare Advantage enrollees who have access to vision coverage:

  • Virtually all (99%) Medicare Advantage enrollees offered both eye exams and eyewear coverage are in plans with annual dollar limits on vision coverage, with an average limit of $160 in 2021. Nearly half (45%) of these enrollees are in a plan with a maximum vision care benefit of $100 or less (Figure 7).
Virtually all Medicare Advantage plans that offer vision have an annual dollar limit on the benefit; nearly half of enrollees in these plans have a limit of $100 or less in 2021
  • For vision benefits, Medicare Advantage enrollees are often limited in terms of the frequency of obtaining certain covered services.
    • Among enrollees with access to eye exams, nearly all enrollees (94%) are in plans that limit the number of covered eye exams, with the most common limit being no more than once per year.
    • More than half of enrollees (58%) in plans that cover eyeglasses are limited in how often they can get a new pair. Among those with a limit on eyeglasses, the most common limit is one pair per year (52%), followed by one pair every two years (47%).
    • Among plans that cover contact lenses, one third of enrollees (33%) are in plans that have frequency limits on contact lenses, typically once per year.
    • Virtually all enrollees in plans without quantity limits on eyeglasses or contact lenses are limited by an annual dollar cap, as noted above.
  • Vision exams are often covered without cost sharing, and eyewear is also often covered without cost sharing but is always subject to annual dollar limits.
    • Most enrollees (71%) pay no cost sharing for eye exams, while about 14% of enrollees are in plans that report cost sharing for eye exams, with virtually all requiring copays, ranging from $5 to $20. Data on cost sharing is missing for plans that cover the remaining 15% of enrollees.
    • Around two-thirds of Medicare Advantage enrollees pay no cost sharing for eyeglasses or contact lenses (66% and 64% respectively), but all these enrollees are in plans that have an annual maximum dollar limit on coverage. About 2% of enrollees are in plans that require cost sharing for either eyeglasses or contacts, with nearly all requiring copays; these enrollees are also subject to an annual dollar cap.

In conducting this analysis of Medicare Advantage benefits, we found that plans do not use standard language when defining their benefits and include varying levels of detail, making it challenging for consumers or researchers to compare the scope of covered benefits across plans. Our analyses take into account benefits, as described in the Medicare Advantage Plan Benefit files, which includes annual limits on plan benefits, frequency limits on obtaining covered services, and cost-sharing requirements, but does not take into account plan restrictions that may affect access, such as type or model of hearing aids covered, type of eyeglasses or lenses covered (e.g. bifocals, graduated lenses), the extent to which prior authorization rules are imposed, or network restrictions on suppliers.

Discussion

While some Medicare beneficiaries have insurance that helps cover some dental, hearing, and vision expenses (such as Medicare Advantage plans), the scope of that coverage is often limited, leading many on Medicare to pay out-of-pocket or forego the help they need due to costs. Traditional Medicare generally does not cover routine dental, hearing, or vision services, and coverage for these services under Medicare Advantage varies.

Based on self-reported data, use of dental, hearing, and vision services ranges widely among Medicare beneficiaries overall, with just over half of all beneficiaries reporting that they used dental services in 2018, roughly one-third using vision services, and fewer than one in 10 using hearing services. While it is not the case that use of these services is indicated or required annually for everyone on Medicare, our analysis shows that vision and hearing difficulty is not uncommon among Medicare beneficiaries and cost prevented many beneficiaries in both traditional Medicare and Medicare Advantage plans who sought dental, hearing, or vision care from getting it in 2019.

Medicare Advantage plans are the leading source of dental coverage for people with Medicare, and a main source of coverage for hearing and vision. According to our analysis of plan benefit data, most Medicare Advantage plans provide access to these benefits; only 6% of enrollees are in plans that do not cover dental benefits, 3% are in plans that do not cover hearing exams and/or aids, and 1% are in plans that do not cover eye exams/glasses. While the scope of coverage varies across Medicare Advantage plans, there are some common features within each category. Nearly all Medicare Advantage enrollees with access to dental coverage have preventive benefits, and most have access to more extensive dental benefits, though cost sharing for more extensive services is typically 50% for in-network care, and subject to an annual cap on plan payments. Almost all Medicare Advantage enrollees have access to both hearing exams and hearing aid coverage; hearing aid coverage is subject to either a maximum annual dollar cap and/or frequency limits on how often plans cover the service. Virtually all Medicare Advantage enrollees have access to both vision exams and eyewear coverage, and this coverage is typically subject to maximum annual limits, averaging about $160 per year.

Policymakers are considering adding dental, hearing, and vision benefits to Medicare as part of the budget reconciliation bill – a change that would be the largest expansion of Medicare benefits since the Part D drug benefit was launched in 2006. These program improvements would lead to higher federal spending of $358 billion over 10 years (2020-2029), including $238 billion for dental and oral health care, $89 billion for hearing care, and $30.1 billion for vision care, according to a Congressional Budget Office estimate of the version of H.R.3 passed by the House in 2019. Additionally, in a July 2021 executive order, President Biden called for the Secretary of Health and Human Services to issue a proposed rule that would allow hearing aids to be sold over-the-counter, as allowed under the FDA Reauthorization Act of 2017 – a move that could help make hearing aids more affordable for people with hearing difficulties who may be foregoing purchasing them due to cost. Expanding Medicare coverage for dental, hearing, and vision services and making lower-cost hearing aids available would address significant gaps in coverage and could alleviate cost concerns related to these services for people on Medicare.

This work was supported in part by the AARP Public Policy Institute. We value our funders. KFF maintains full editorial control over all of its policy analysis, polling, and journalism activities.

Methods

Our analysis of dental, hearing, and vision out-of-pocket spending and cost-related barriers to care is based on data from the 2018 and 2019 Medicare Current Beneficiary Survey (MCBS). For the analysis of problems getting care due to cost, we relied on the 2019 MCBS Survey File topical segment “Access to Care, Medical Appointments” (ACCSSMED) to identify community-dwelling beneficiaries who reported that they couldn’t get dental, hearing, or vision care in the last year because of cost. This analysis was weighted to represent the ever-enrolled population, using the ACCSSMED topical segment weight ‘ACSEWT’.

Respondents were coded as having hearing difficulty if they reported having “a little trouble hearing”, “a lot of trouble hearing”, or deafness/serious difficulty hearing.

Respondents were coded as having vision difficulty if they reported having “a little trouble seeing”, “a lot of trouble seeing”, blindness, or blindness/difficulty seeing even with glasses. This analysis was weighted to represent the ever-enrolled population, using the weight ‘EEYRSWGT’.

For the analysis of out-of-pocket spending on dental, hearing, and vision services, we relied on the 2018 MCBS Cost Supplement data, which includes survey-reported events for these services since they are generally not Medicare-covered services and therefore there are no Medicare claims. We identified dental events based on the Dental segment, and vision and hearing events using the Medical Provider Events (MPE) segment. We subset the file to beneficiaries with hearing events, which were identified as medical provider specialty events for an audiologist or hearing therapist or where the type of event was for a hearing or speech device or a hearing aid, and beneficiaries with vision events, which were identified as medical provider specialty events for an optometrist or where the type of event was for eyeglasses. We analyzed out-of-pocket spending on dental, hearing, and vision services (separately) among community-dwelling beneficiaries overall, and among the subset of community-dwelling beneficiaries who were coded as having a dental, vision, or hearing event. This analysis was weighted to represent the ever-enrolled population, using the Cost Supplement weight ‘CSEVRWGT’. We also analyzed out-of-pocket spending among community-dwelling beneficiaries who reported having difficulty hearing or difficulty seeing.

The Medicare Advantage Enrollment and Benefit files for 2021 were used to look at dental, hearing, and vision coverage for beneficiaries enrolled in individual Medicare Advantage plans (e.g., excludes Special Needs Plans, employer-group health plans, and Medicare-Medicaid Plans (MMPs)). This analysis includes enrollees in the 50 states, Washington D.C., and Puerto Rico. Plans with enrollment of 10 or fewer people were also excluded because we are unable to obtain accurate enrollment numbers. For cost-sharing amounts for dental, vision, and hearing coverage, many plans do not report these figures, and in cases where enrollee cost sharing does not add up to 100%, it is due to plans not reporting this data. Due to data limitations, we examine benefits offered, but are unable to analyze the extent to which enrollees in Medicare Advantage plans use supplemental benefits specifically offered by their plan, such as dental, hearing and vision, because encounter data for these benefits are not available. It is also unclear from the plan Benefit files the extent to which plans limit the type of eyeglasses or hearing aids, impose network restrictions or prior authorization.

Medicaid and State Financing: Key Indicators to Watch Through Pandemic and Recovery

Authors: Elizabeth Williams, Robin Rudowitz, Rachel Garfield, and Elizabeth Hinton
Published: Sep 20, 2021

The health and economic effects of the pandemic have significant implications for Medicaid.  Medicaid, which provides coverage of health and long-term care for low-income residents, is administered by states within broad federal rules and jointly funded by states and the federal government. Medicaid is a counter-cyclical program, meaning that more people become eligible and enroll during economic downturns; at the same time, states may face declines in revenues that make it difficult to fund the state share of funding for the program. As in past economic downturns, the federal government has provided additional financial assistance to states during the current pandemic to help them maintain their Medicaid programs at a time of growing need.  This brief presents the most current data for key indicators to help understand how various economic factors that could affect Medicaid enrollment and spending are changing in light of the pandemic as well as efforts to address the pandemic and the start of economic recovery.  An overview of the methods is in the Methods Box at the end of the brief, and a companion brief provides an overview of Medicaid Financing Basics.

What factors could affect Medicaid enrollment?

Medicaid enrollment is typically the primary driver of spending.  Administrative data for Medicaid show that after declines in enrollment from 2017 through 2019, total enrollment nationwide began to grow after February 2020, right before the pandemic began. Between February 2020 and April 2021, enrollment steadily increased to 82.3 million, an increase of 11.1 million, or 15.5%, from actual enrollment in February 2020. These trends in enrollment likely reflect changes in the economy as more people experience income and job loss and become eligible and enroll in Medicaid coverage as well as “maintenance of eligibility” (MOE) provisions in the Families First Coronavirus Response Act (FFCRA) that require states to ensure continuous coverage to current Medicaid enrollees to access a temporary increase in the federal Medicaid match rate.

Key economic indicators that could signal changes to Medicaid enrollment include those showing job and income loss such as the unemployment rate, unemployment insurance claims, and the employment-to-population ratio.  Unemployment rates and unemployment insurance filings capture people who are actively looking for or have recently lost employment, respectively, and may be affected by people who opt to leave the workforce altogether.  Employment-to-population ratios capture what share of the population is working overall.  All measures capture some aspect of income loss, which could make more people eligible for Medicaid. However, Medicaid enrollment changes may lag behind changes in broader economic metrics.  For example, when unemployment rises, increases in Medicaid enrollment may follow, but improvements in unemployment may not immediately translate to slower Medicaid growth. This effect was observed following the end of the Great Recession in 2009 when Medicaid spending and enrollment continued to grow in 2010 and 2011 and is due in part by MOE provisions that prevent states that accept additional federal funding from disenrolling Medicaid beneficiaries.

National data show sharp increases in the average unemployment rate and unemployment claims following the onset of the pandemic in March 2020, but they have moderated in more recent months.  Indicators of employment-to-population ratios also show precipitous declines at the start of the pandemic, unmatched by trends since 2008. While changes in indicators related to employment and jobs have moderated in more recent months, they are still not at pre-pandemic levels. For example, July 2021 saw a national unemployment rate of 5.4% across all states including DC, below the peak of 14.8% in April 2020 but still above 3.5% in February 2020, right before the pandemic.  Similarly, total unemployment claims peaked in May 2020 and have been steadily declining, but total claims in July 2021 were greater than February 2020.  Finally, the employment-to-population ratio dropped to a low of 51.3% in April 2020; the 58.4% ratio in July 2021 is below the February 2020 level of 61.1%.  Unemployment rates and unemployment claims were higher, and the employment-to-population ratios were lower relative to the Great Recession that started in December 2007.

Monthly Unemployment Rate

For each employment indicator there was wide variation across states in the average over the most recent 12-month period compared to a year earlier.  Looking at the average for the most recent 12-month period (August 2020 to July 2021) compared to the same period in the prior year, the national unemployment rate decreased by 1%; however, growth across states varied significantly, from more than a 30% increase in Hawaii and Connecticut to a 33% decrease in New Hampshire. Measures continue to improve, with over half of states seeing declines in their average unemployment rate and number of unemployment claims and a quarter of states seeing growth in their average employment-to-population ratio when comparing the most recent 12-month average to the year prior. South Dakota was in the top 5 states with the most improvement in its 12-month average for at least two of the three indicators, and Connecticut, D.C., Hawaii, and Maryland were hardest hit, being in the top 5 with the largest changes in their 12-month averages for at least two of the three indicators.

Employment-related economic consequences are directly related to the proportion of jobs a state has in more impacted sectors. States, like Hawaii and Nevada, which rely heavily on more exposed sectors (restaurants and bars, travel and transportation, entertainment, etc.), saw larger changes in job-related indicators throughout the pandemic. On the other hand, states more reliant on less exposed sectors, like agriculture in the Midwestern states, fared better. The leisure and hospitality industries experienced the highest unemployment rates at the start of the pandemic, but other industries also reliant on in-person work, like mining, are now seeing higher rates of unemployment. Many individuals enrolled in Medicaid even before the pandemic are employed in exposed sectors (such as food and other service industries) and are particularly at risk for income or job loss. Additionally, state issued stay-at-home orders and personal social-distancing behaviors varied across states and also contributed decreased economic activity.

Percent Change in Unemployment Rate by State

What factors could affect states’ ability to finance Medicaid?

States generally fund their share of Medicaid costs through general revenue collected from residents, businesses, and sales taxes. States must adopt balanced budgets, so during economic downturns when demand for services and programs like Medicaid increases, state revenues typically decline, putting pressure on state budgets.  To provide broad fiscal relief to states and to help support increases in Medicaid enrollment, the Families First Coronavirus Response Act (FFCRA) authorized a 6.2 percentage point increase in the federal match rate (“FMAP”) for states that meet certain “maintenance of eligibility” (MOE) requirements. The additional funds were retroactively available to states beginning January 1, 2020 and continue through the quarter in which the PHE period ends. While the current PHE declaration expires 90 days from July 20, 2021, the Biden Administration has notified states that the PHE will likely remain in place throughout CY 2021 and that states will receive 60 days-notice before the end of the PHE.

Measures of changes in state revenue can provide insight into states’ ability to finance the state share of Medicaid. State revenues are largely dependent on revenue from personal income taxes, corporate income taxes and sales taxes. The share of revenue coming from each of these sources varies, and 9 states have no personal income tax at all. In addition, each type of tax may be affected differently by changes in economic conditions.

State revenues overall have increased sharply in recent months, with unadjusted 12-month rolling averages for revenue now surpassing pre-pandemic averages. For the most recent 12-month rolling average (ending June 2021) compared to the 12-month average from February 2020, before the pandemic, average monthly total revenues are 13.4% higher. This is much improved from the 12-month period ending June 2020, the lowest point during the pandemic, which saw a 8.0% drop from the 12-month average from February 2020. Overall, states have not experienced revenue declines as large as original projections. While the data show steep revenue declines early in the pandemic, overall unadjusted revenues have rebounded in recent months, though some of the sharp increases in the recent 12-month rolling averages can be attributed to delayed income tax filing deadlines. Revenues appear to have surpassed pre-pandemic levels; however, there is variation across states, and the data pre-dates the Delta variant and is volatile due to changing income tax deadlines. States adapted to the changing outlook, adopting conservative FY 2021 budgets and then adopting FY 2022 budgets with increases in state spending and revenue after ending FY 2021 with surpluses.

State revenue changes vary across revenue sources, with personal income taxes faring better than sales taxes during the pandemic. Corporate income tax revenues are volatile and can fluctuate considerably from month to month. For the most recent 12-month rolling average (ending June 2021) compared to February 2020, before the pandemic, average monthly personal income taxes increased by 19.5%, corporate income taxes grew by 40.4%, and sales taxes grew by 6.3%. Most states pushed back their 2020 income tax filing deadline from April 15th to July 15th and their 2021 deadline to May 17th, delaying income tax revenue and causing the 12-month averages for May and June 2021 to contain two income tax collection months for many states. US total data is preliminary for April, May, and June 2021, due to delays by some states to report revenues as they close out the 2021 fiscal year.

12-Month Rolling Average Tax Revenue

There is considerable variation across states with regard to changes in revenues. Almost all states are now seeing an increase in average monthly total tax revenue for the most recent 12-month period (ending June 2021) compared to the prior year, with only 2 states experiencing declines. Changes in overall average monthly tax collections ranged from a decline of 18% in Alaska to growth of 53% in California for the most recent 12-month period compared to the prior year, and there was also variation by revenue source. Since the pandemic has disproportionately affected low income workers in the service industry, most states experienced smaller declines in personal income tax revenue than expected, especially for states with progressive income tax structures, where people with higher incomes pay a higher share of income tax.  In addition, income tax withholdings on the supplemental federal unemployment benefits may have also sustained state income tax revenues.

States that issued stay-at-home orders saw reduced sales tax revenues, and states that rely heavily on tourism, like Hawaii, Florida, and Nevada, or oil and gas, like Alaska and North Dakota, experienced larger revenue declinesSales tax revenues were bolstered by $600 weekly federal unemployment benefits under the CARES Act that allowed consumers to continue spending, the 2018 Supreme Court decision that authorized states to collect sales tax on online purchases, and increased spending on goods instead of services, which most states do not tax. While sales taxes on groceries have been shown to worsen income and racial inequalities, states that tax groceries saw smaller declines in sales tax revenue during the pandemic. Sales tax revenues are recovering more slowly than personal income and corporate income tax revenues, and states that rely more heavily on sales tax revenues and do not have an income tax experienced steeper declines in total tax revenues.

Percent Change in Total Tax Revenue by State

Looking Ahead

The ongoing health and economic effects of the pandemic will continue to have implications for Medicaid enrollment and financing. While revenues and employment indicators have improved, employment indicators have not yet returned to pre-pandemic levels and there remains a lot of variation across states. In addition, while indicators are improving on average across states, it is unclear how quickly and how much jobs and revenue in certain sectors of the economy will improve.  As the economy improves, what happens in certain sectors could greatly affect Medicaid as there have been disproportionate effects on low-wage workers who could be eligible for Medicaid.

Almost all states have adopted budgets for state fiscal year 2022 (which started July 1 for most states), and revenue and spending projections incorporated improvements in revenue tied to COVID-19 vaccination efforts and eased restrictions, assumptions about the duration of the PHE (which has implications for the temporary fiscal relief and continuous coverage requirements for Medicaid), and federal stimulus funds that were part of the American Rescue Plan. However, the spread of the Delta variant and the recent surge in COVID-19 cases and deaths casts more uncertainty about state economic conditions and the duration of the PHE.

Methods Overview

The data in this analysis draws on a range of sources, including the Bureau of Labor Statistics, Department of Labor, and State and Local Finance Initiative at Urban Institute.  We draw on the most current data available for each specific indicator. For most indicators, we examined both national and state-by-state changes over time. To avoid major fluctuations using monthly data, we calculate 12-month rolling averages and percent changes in 12-month rolling averages compared to the prior year period.

  • At the state level, we calculate the percent change in the most recent 12-month average compared to the prior year by taking the average of the measure (revenue, unemployment rate, etc.) for the most recent 12-month period and comparing to the same 12-month period the prior year. For example, the percent change calculation for June 2021 compares the average tax revenue from July 2020-June 2021 to the average tax revenue from July 2019-June 2020. When the most recent month’s revenue is not available for a state, we shift the 12-month comparison back to the most recent 12-months available and add a note to the figure. For example, total tax revenue for Nevada is not available for June 2021 so the most recent 12-month average is calculated using June 2020-May 2021 and compared to June 2019-May 2020.
  • Monthly unemployment claims are calculated by combining reported initial and continued unemployment claims for each week, and then aggregating into months using the date in which the filing week ended.
  • For the state level revenue data, state data is removed if there is one revenue outlier that heavily skews the average calculations for that state. When this occurs, a note is added to the figure.
  • All other data is pulled directly from sources and no additional adjustments are made. Revenue data is not adjusted for inflation.