Executive Summary

The COVID-19 pandemic has disproportionately affected residents and staff in nursing homes and other long-term care facilities (LTCFs). While this group is in the top priority group for vaccine distribution in all states, some may remain at risk as the pandemic continues to spread across the country, particularly LTCF staff for whom vaccination rates have been low. In addition, the pandemic may have exposed vulnerabilities in LTCFs that can inform future efforts to address infectious disease outbreaks.

This brief summarizes the findings of 30 studies between April 2020 and January 2021 that examined potential factors associated with COVID-19 cases and/or deaths in LTCFs. Key takeaways include:

• The prevalence of COVID-19 cases in the community is consistently associated with COVID-19 cases and/or deaths in long-term care facilities.
• Staff infections appear to be a link between cases in the community and long-term care facilities, although it is unclear if the staff infections were the result of community spread or pre-existing cases in LTCFs.
• Long-term care facilities that are for-profit or have higher shares of residents who are people of color (or are located in communities with a large share of people from communities of color) were more likely to have COVID-19 cases and deaths. Urban location and large bed size are also associated with cases and deaths, which may reflect other factors such as community spread or association between bed side and case count.
• Among studies that examine the association between CMS overall quality ratings and infection control deficiencies in nursing facilities, most find no clear association with COVID-19 cases or deaths, but a small number of studies do.
• Nursing homes with higher staffing levels, including those with higher CMS 5-star quality ratings for staffing are associated with fewer cases or deaths in the facility.

It should be noted that many of these studies were conducted in real time, as the pandemic was gaining force and shifting geographically; it is possible that results from studies conducted in the earlier months may not reflect changes that have occurred over the course of the year. Further, we did not identify research that examines the role of PPE shortages, staff shortages, or state or facility policy on cases or deaths in LTCFs. While a successful vaccination effort should mitigate the future risk of serious illness and deaths due to COVID-19, this analysis identifies factors that may make residents and staff of nursing homes and other LTCFs vulnerable if sufficient numbers are not vaccinated, or if they are exposed to other highly contagious and dangerous infections in the future.

Introduction

The COVID-19 pandemic has disproportionately affected residents and staff in nursing homes and other long-term care facilities (LTCFs), accounting for 6% of all cases and 38% of all COVID-19 deaths nationwide. In response, the Centers for Disease Control (CDC) recommended that LTCFs have the highest priority when it comes to vaccinations. Since the initial high-profile outbreak of the virus at the Life Care Center of Kirkland, Washington, many facilities have implemented measures to contain the spread of coronavirus in LTCFs, including universal testing, widespread use of personal protective equipment (PPE), and visitor restrictions. The federal government also responded to pandemic by refocusing early routine nursing home inspections on infection control and convening a panel of experts to provide evidence-based recommendations on how to address the pandemic in nursing homes (Coronavirus Commission for Safety and Quality in Nursing Homes). Additionally, federal legislation allocated some funds to help cover the expense of PPE and testing.

Despite these measures, deaths and infections among long-term care facility residents and staff have continued to increase throughout the pandemic, largely following the national trend, underscoring the need to better understand factors that are associated with increased COVID-19 cases and deaths in LTCFs. Early data also suggests that initial vaccine distribution has been slower than anticipated, and that staff vaccination rates are relatively low due to concerns about vaccine safety, which could lead to the continued spread of the virus in LTCFs.  According to a recent survey conducted by KFF, nearly three in ten (29%) people who work in health care settings said they would definitely or probably not get vaccinated. Additionally, 35% of Black adults (a group that has borne a disproportionate burden of the pandemic and makes up over a quarter of the long-term care work force) say they definitely or probably would not get vaccinated. This review of studies informs ongoing efforts to limit preventable infections and deaths in long-term care settings, and may help to identify characteristics of facilities most at risk that could be prioritized for vaccine distribution, staff education and oversight.

This issue brief summarizes the findings of 30 studies that have examined potential factors associated with COVID-19 cases and/or deaths in LTCFs. We group those factors into categories of community spread, including staff-to-patient transmission and patient transfers; facility quality and infection control; staffing levels; and other facility-level characteristics, such as ownership, location, payer mix, and the racial/ethnic composition of residents. An overview of the methods used in identifying studies included is provided in the Methods box at the end of the brief.

Key Findings

Community Spread

The prevalence of COVID-19 in the community is consistently associated with COVID-19 cases and/or deaths in long-term care facilities. In total, all nine studies that looked at community transmission found an association between community (typically county) case rates and likelihood or severity of outbreaks or deaths in LTCFs. All studies found that communities with high coronavirus case rates had more cases and deaths in its long-term care facilities than communities with low case rates. These studies used data from time periods ranging from early in the pandemic (end of May) to mid-September 2020, but most were using data from late Spring through Summer 2020. Only two used national or 50-state data^1 ,2  while four studies used state-reported data for a subset of states^{3 ,4 ,5 ,6} , and three used other samples or a single state.^7 ,8 ,9  Only one of these studies adjusted for the possible endogeneity between community cases and LTCF cases (that is, high cases or deaths in LTCFs contributing to high COVID-19 rates within the county), though it still found a significant relationship between community rates and cases and deaths in LTCFs.¹⁰ 

Some studies identify staff infections as a likely link between community cases and cases in long-term care facilities. Three studies explicitly looked at the role of staff in LTCF outbreaks, and all found a relationship between community spread, staff infections, and resident infections. In a NY state report from summer 2020, researchers found that staff infections correlated with the timing of peak nursing home resident mortality across the state and were typically centralized in communities with high case rates.¹¹  Another analysis using geolocation data from 50 million smartphones and data from 22 states found that overlapping staff networks between nursing homes were significantly associated with coronavirus infections.¹²  The third study, using data from one large academic LTCF, found that facilities with a high burden of disease were more likely to have staff members that lived in communities with high rates of COVID-19 infection.¹³  It is unclear from existing research whether these findings are generalizable nationwide or whether staff infections themselves were a result of community transmission or pre-existing cases within the facility.

The evidence is mixed on the effect of patient transfers on COVID-19 cases and deaths in long-term care facilities.  Following reports in the media about transfers from hospitals and other health care settings leading to new infections in LTCFs, three state-based analyses (from New York, Michigan, and Maryland) examined the potential role of patient transfers to other health care facilities in COVID-19 outbreaks in LTCFs. Neither the New York nor Michigan state report found a consistent relationship between hospital transfers and increased COVID-19 case load or deaths among nursing home residents, though both relied on descriptive analysis of timing and number of cases.^14 ,15  In contrast, a third study from Maryland found that nursing home residents that were transferred to receive dialysis treatment were more likely to contract the virus than those who were not transferred.¹⁶  The generalizability of findings from the three state-based studies may not be generalizable nationwide. In addition, we did not identify research evaluating outcomes of residents that were transferred within long-term care facilities.

Quality and Infection Control

Among the twelve studies that analyzed whether lower quality ratings under the CMS 5-Star Quality Rating System were associated with COVID-19 cases or deaths, the evidence is mixed:  eight studies found that overall quality ratings were not associated with the likelihood of a COVID-19 cases and deaths while four states identified a link between quality ratings and cases or deaths. The CMS star-rating system is one of the most cited measures of nursing home quality and accounts for a nursing home’s performance in the following domains: health inspection ratings, quality measure ratings, and staffing ratings. Early in the pandemic, there was speculation that nursing home quality was associated with virus outbreaks. This theory gained additional traction when early analysis by CMS  found that nursing homes with a one-star quality star rating were more likely to have more COVID-19 cases than facilities with a five-star quality rating. Since that report, 12 studies have investigated star ratings and COVID-19 among skilled nursing facilities, using data from time periods ranging from early in the pandemic (end of May) to the summer (June-July).  Only one study used national or 50-state data, while five studies used state-reported data for a subset of states and six used single state data.

Among these 12 studies, eight studies, including 1 national study, 5 studies based on a subset of states, and 2 single-state studies, found that CMS overall quality ratings were not associated with the likelihood of having a reported COVID-19 case,^17 ,18  the number of COVID-19 cases,^{19 ,20 ,21 ,22 ,23}  or mortality rates ²⁴ . Among the remaining four studies, which were all based on single-state data, all found some link between overall star rating and either likelihood of having COVID-19 cases or deaths^25 ,26  or severity of outbreaks among facilities with cases.^27 ,28  Additional studies have examined star ratings on staffing and COVID-19 and found significant associations between those ratings and cases or deaths, as summarized in the staffing section below.

Most of the limited number of studies that examine nursing home infection control and COVID-19 find no association between nursing home infection control deficiencies and COVID-19 cases and deaths. Recent analysis by the Government Accountability Office found that most nursing homes had infection control deficiencies even prior to the COVID-19 pandemic. During the pandemic, facilities, states, and the federal government have undertaken several measures to strengthen infection control practices in nursing homes, including through CMS’ National Training Program.

Four out of five studies that have evaluated whether infection control practices or deficiencies, separately from overall health deficiencies and/or CMS overall star rating, are associated with COVID-19 outcomes in nursing homes, found no association with COVID-19 burden. Among the four studies that found no association, one study used national data and found no relationship between the number of deficiencies related to infection control and COVID-19 outbreak,²⁹  two used data from a subset of states and  found no association between prior infection violations and probability of having at least one COVID-19 case,^30 ,31  and one implemented the same infection control procedures across all long-term care facility units in a single long-term care facility in Boston but still found that the prevalence of COVID-19 cases and deaths varied widely.³²  In contrast, one of the five studies found that 91% of nursing homes that reported at least one COVID-19 case had a prior infection control violation compared to 81% of nursing homes without any reported cases.³³   Other studies looked at broader measures of deficiencies not limited to infection control and found that nursing homes with higher health rates of deficiencies were more likely to report at least COVID-19^34 ,35  but nursing homes that received a fine for deficiencies had lower case rates than those that did not.³⁶ 

Staffing Levels

Findings suggest that higher staffing levels may play a protective role in containing COVID-19 cases and deaths in nursing homes, particularly in containing outbreaks once they enter the facility, though some research finds a link between LPN hours and cases or deaths.  Prior to the pandemic, research suggested that majority of nursing homes did not have adequate staffing levels, raising questions as to whether lower staffing levels are linked to COVID-19 cases and deaths in LTCFs. Seven studies examined the relationship between staffing levels and COVID-19 outcomes in nursing homes, with some variation in conclusions:

• Quality ratings on staffing: Four studies examined whether nursing homes’ star rating on nurse staffing were associated with COVID-19 cases or deaths, including one that used national data, one that used data from a subset of states, and two that used data from a single state. Three of the four studies found that nursing homes with high quality ratings on nurse staffing were less likely to have more than 30 COVID-19 cases or deaths (controlling for bed size and other factors),³⁷  had fewer cases and deaths per bed,³⁸  and lower probability of having a resident with COVID-19.³⁹  However, the remaining study, based on national data, did not find a statistically significant association between lower staffing ratings and COVID-19 cases.
• Nursing and aide hours: Five studies examined whether staffing levels, separate from staffing quality ratings, are associated with COVID-19 cases and/or deaths, including two national studies and three state- based analyses. Three studies found an association between higher staffing and fewer cases, deaths, and/or lower likelihood of experiencing an outbreak. Specifically, the first study, based on national data, found that while nursing homes with a higher number of registered nurse (RN) hours per resident per day were more likely to experience at least one COVID-19 case, higher nurse aide hours and total nursing hours were associated with fewer deaths and lower likelihood of an outbreak among facilities with at least one COVID-19 case.⁴⁰  The second study, also based on national data, found that higher total staffing was associated with no COVID-19 cases.⁴¹  The third study based on California data, found that early in the pandemic, nursing homes with lower total nurse staffing (RN, LVN, and CNA) had higher case rates, but as the pandemic progressed to August, nursing homes with higher RN staffing had lower case rates.⁴²  Of note, these three studies included both staff and resident cases in their analyses, with two studies finding that county-level rates of COVID-19 were associated with COVID-19 transmission in nursing homes.^43 ,44 
  • The remaining two studies, based on single-state data of cases among residents only, found either an inverse relationship between staffing and cases, where low RN hours per resident were associated with higher odds of a nursing home having COVID-19 cases,⁴⁵  or found no association between RN staffing and likelihood of having one or more COVID-19 cases or deaths but rather, among facilities with at least one case or death, an increase in RN staffing was associated with fewer cases and deaths.⁴⁶ 
  • Additionally, among the five studies, two national studies examined the role of licensed practical nurses (LPNs) and found a positive association between LPN hours and COVID-19 cases and/or deaths. The first study found that low LPN hours were associated with fewer deaths but not the probability of an outbreak,⁴⁷  and the second study found that higher LPN staffing rates were associated with more COVID-19 cases, a difference that could be partially attributed to the fact that LPNs, unlike RNs, tend to interact with more residents while completing tasks such as wound care or dressing changes.⁴⁸ 

Additional research has examined factors associated with staffing shortages during the pandemic and found that shortages are associated with factors that are also associated with COVID-19 cases and deaths. Data from the federal government shows that approximately one in five nursing homes have reported a staffing shortage at some point in time during the pandemic. However, we were unable to identify analyses that examined whether and to what extent these shortages contributed to outbreaks or severity of outbreaks in LTCFs.⁴⁹  Not surprisingly, staffing shortages as an outcome measure in research are linked to the same factors associated with cases and deaths, such as community spread, since shortages are logically related to COVID-19 outbreaks among staff.

Five studies evaluated the most likely factors associated with staffing shortages in nursing homes during the pandemic, finding that higher COVID-19 cases in the surrounding community or within the facility,^50 ,51 ,52  lower CMS star rating,^53 ,54 ,55  government ownership,^56 ,57  and a higher share of residents covered by Medicaid^58 ,59  were associated with staff shortages. One study found that high concentrations of Black residents and facility location in a less urban county were associated with reported staffing shortages.⁶⁰  One study identified several factors associated with a lower likelihood of reporting a staffing shortage, including having at least a one week supply of PPE, higher occupancy rates, or a higher share of Medicare residents.⁶¹  Again, it is unclear from existing research if these staffing shortages in turn contribute to higher COVID-19 cases or deaths.

Other Facility-Level Characteristics

Long-term care facilities that are for-profit, have a higher share of residents who are people of color, located in urban areas, and have more beds are more likely to have COVID-19 cases and deaths. Seventeen studies analyzed a range of facility-level characteristics associated with COVID-19 cases and/or deaths in long-term care facilities, including characteristics such as location, facility size (as measured by number of beds), share of residents with Medicaid as their primary payer, racial composition of residents, ownership, and labor union presence.^{62 ,63 ,64 ,65 ,66 ,67 ,68 ,69 ,70 ,71 ,72 ,73 ,74 ,75 ,76 ,77 ,78}  These studies used data from various time periods, including eleven studies with data collected early in the pandemic (end of May), four studies as of June and July, and one study as of October. One study collected data from two time periods: May and August 2020. Among these seventeen studies, only four studies used national or 50-state data, while seven studies used state-reported data for a subset of states and six used single state data.

• For-profit nursing facilities are at higher risk for COVID-19 cases and deaths, while nursing facilities with labor unions are less likely to have COVID-19 deaths: Six studies evaluated whether for-profit versus non-profit status was associated with COVID-19 outcomes.^{79 ,80 ,81 ,82 ,83 ,84}  Three studies collected data as of early in the pandemic (end of May), two studies had study collection periods during the summer, and one study used data from both May and August. Four studies obtained data from a subset of states whereas two studies obtained data from single states. All six studies found that for-profit nursing homes were associated with higher COVID-19 case and/or death counts..One study that focused more specifically on private-equity owned nursing homes, using national data from early summer, found that private equity-owned nursing homes did not have higher COVID-19 case rates or death rates than non-profit or for-profit nursing homes, though they did have higher case rates than government-owned facilities.⁸⁵  Two examined chain status, with mixed results: a Connecticut study found that nursing facilities that were part of a chain were more likely to have at least one COVID-19 case, while the second study, based on a subset of states, found that non-chain status was associated with the likelihood of having at least one COVID-19 case.^{86 , 87} .One study using data as of May found that nursing facilities in New York with labor unions were associated with lower COVID-19 death rates compared to facilities without these unions.⁸⁸ 

• Long-term care facilities with higher shares of residents who are people of color are more likely to experience COVID-19 cases and/or deaths: Ten studies examined racial/ethnic composition of LTCF residents as potential factors associated with COVID-19 cases and/or deaths. Among these 10 studies, nine studies found that LTCFs with higher shares of people of color, especially Black or Hispanic residents, were more likely to have a greater likelihood of having at least one COVID-19 case^{89 , 90 ,91}  or at least one COVID-19 death,⁹²  a higher number of new COVID-19 cases and deaths,⁹³  a higher number of cases,^94 ,95  higher case rates,⁹⁶  and higher case and death counts.⁹⁷  The remaining study found that the concentration of residents who are people of color was not associated with the likelihood of having one or more COVID-19 case or deaths in the facility; however, among facilities with at least one case, nursing homes with a greater share of people of color had higher counts of COVID-19 cases.⁹⁸  One study examined whether the concentration of African-Americans at the county-level was associated with cases in nursing homes.⁹⁹  This study found that county-level population of African-Americans was associated with COVID-19 cases in nursing homes.
• Urban location may be associated with cases in long-term care facilities: Two studies examined the role of location using data collected in May from a subset of states.^100 ,101  Both studies found that nursing facilities located in urban locations were associated with an increased probability of having at least one COVID-19 case or a higher likelihood of more COVID-19 cases.   As the pandemic has spread across the country and affected more rural areas, it is possible that distinctions in location are no longer associated with LTCF outbreaks.
• Facilities with more beds and higher occupancy rates are more likely to have COVID-19 cases and/or deaths: Nine studies evaluated the relationship between COVID-19 burden and the size of long-term care facilities, as measured by the number of beds, among a subset of states or from single states using data ranging from early in the pandemic (end of May) to August.^{102 ,103 ,104 ,105 ,106 ,107 ,108 ,109 ,110}  These nine studies found that long-term care facilities with more beds were associated with increased probability of having at least one COVID-19 case ^111 ,112  higher case counts,¹¹³  higher mortality rates,¹¹⁴  higher case and death counts, ^{115 ,116 ,117}  and severity of outbreak.¹¹⁸  Two additional studies also found that LTCFs with higher occupancy rates were associated with increased likelihood of experiencing at least one COVID-19 case but not necessarily a higher count of cases,¹¹⁹  and a higher count of COVID-19 cases and deaths.¹²⁰  The relationship between COVID-19 cases and facility size likely reflects the fact that larger facilities accept more residents and have more staff, potentially increasing the risk of community spread through movements of residents and staff to and from the facility.
• There is some association between the share of residents covered by Medicaid as a primary payer and COVID-19 burden: Five studies evaluated whether nursing homes with a greater share of residents for whom Medicaid was primary payer had more COVID-19 cases and deaths, with mixed results.^{121 ,122 ,123 ,124 ,125}  Two studies, one multi-state study using data from Spring 2020 and one based on Spring 2020 data from Connecticut, found that facilities with a relatively high share of residents covered by Medicaid did not have higher likelihood of one or more cases or deaths; however, the Connecticut-based study found that among facilities with at least one case, nursing homes with relatively high share of Medicaid-insured residents had more COVID-19 cases (controlling for other facility characteristics including size and resident race/ethnicity). Two multi-state studies found that facilities with a higher share of residents on Medicaid were associated with more COVID-19 cases or deaths. Additionally, one study found that facilities that reported at least one COVID-19 case had a greater share of Medicaid-insured residents than facilities that did not report any cases.
• Few studies have examined the association between COVID-19 cases and deaths and facility-level characteristics in Assisted Living Facilities separately from nursing facilities: One study, using data from a subset of seven states, examined the association between assisted living characteristics and COVID-19 cases and deaths in the facility. Consistent with other studies on nursing homes, this study found that assisted living facilities with a high share of residents who are people of color have high case rates. Additionally, this study found that larger ALFs are more likely to experience at least one COVID-19 case. We were unable to find other studies that analyzed the relationship between assisted living characteristics and COVID-19 outcomes.

Discussion

The coronavirus pandemic has had an outsized impact on older adults generally and long-term care facility residents and staff more specifically, prompting a wave of studies that have looked at factors associated with COVID-19 cases and deaths.  Our analysis of the studies published 9 months into the pandemic finds that community transmission was found to be consistently associated with cases and deaths.  In addition, the data indicate that certain facility characteristics are associated with COVID-19 cases and deaths, including having a relatively large share of Black or Hispanic residents, for-profit status, a relatively large number of beds, and being located in urban areas. There also appears to be evidence that nursing homes with higher staffing levels, including higher CMS 5-star quality ratings for staffing, have a lower likelihood of cases or deaths.

However, there are other areas where the evidence so far is less clear.  Studies have mixed results on the relationship between overall nursing home quality ratings and COVID-19 cases and deaths. Results are also less clear on important questions of transmission patterns, such as whether patient transfers contribute to the spread of the virus. In addition, we could find no studies that look at whether shortages of PPE, testing and staff are associated with cases or deaths, nor whether certain practices (e.g., setting up separate COVID-19 facilities) or policies (e.g., relaxing or restricting visitation) directly affected the spread of infection across LTCFs.  Further, we were able to identify only one pertaining to assisted living, group homes, and other residential facilities, separate from nursing facility studies, which are home to nearly one million people who are unable to live independently.

While the pandemic took hold in March of 2020, nursing facilities were not required to begin reporting coronavirus cases and deaths to the federal government until May 8, 2020, which means that many of the studies were limited to state-reported data, if available, or missing the early months when nursing homes in some states were hit hard by infections. Even with the federal reporting requirements imposed by CMS, there are gaps in data that would help further pinpoint which residents, staff and facilities were most at risk.  For example, current requirements do not include cases or deaths from long-term care facilities that are not certified by Medicare or Medicaid, which excludes virtually all assisted living and residential care facilities. Further, nursing facilities are not required to report the race or ethnicity, age, or comorbidities of the staff and residents who have become seriously ill or died due to COVID-19.

As the new Administration takes the helm in managing the pandemic and putting in place safeguards to protect residents and staff from future outbreaks, this analysis informs efforts that may be used to help strengthen safety and quality protections in long-term care settings and inform efforts to maximize resident and staff vaccinations.

 

1. Rebecca Gorges, “Staffing Levels and COVID-19 Cases and Outbreaks in U.S Nursing Homes,” Journal of the American Geriatrics Society 68 no. 11 (November 2020): 2462-2466, https://doi.org/10.1111/jgs.16787 ↩︎
2. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
3. Helena Temkin-Greener, Wenhan Guo, Yunjiao Mao, Xueya Cai, and Yue Li, “COVID‐19 Pandemic in Assisted Living Communities: Results from Seven States,” Journal of the American Geriatrics Society 68, no. 12 (December 2020): 2727-2734, https://doi.org/10.1111/jgs.16850 ↩︎
4. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al., “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
5. Priya Chidambaram, Rising Cases in Long-term Care Facilities Are Cause for Concern (Washington, DC: Kaiser Family Foundation, July 2020), https://modern.kff.org/coronavirus-covid-19/issue-brief/rising-cases-in-long-term-care-facilities-are-cause-for-concern/ ↩︎
6. Paul Chatterjee, Sheila Kelly, Mingyu Qi, and Rachel Werner, “Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19),” JAMA Network Open 3, no. 7 (July 2020): e2016930, doi:10.1001/jamanetworkopen.2020.16930 ↩︎
7. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
8. Craig Richmond, Arick Sabin, “SARS-CoV-2 sequencing reveals rapid transmission from college student clusters resulting in morbidity and deaths in vulnerable populations” MedRxiv (October 2020), https://doi.org/10.1101/2020.10.12.20210294 ↩︎
9. [9] David P. Bui, Isaac See, Elisabeth M. Hesse et al., “Association Between CMS Quality Ratings and COVID-19 Outbreaks in Nursing Homes – West Virginia, March 17-June 11, 2020,” MMWR. Morbidity and mortality weekly report, 69 no. 37 (September 2020): 1300–1304. https://doi.org/10.15585/mmwr.mm6937a5 ↩︎
10. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
11. New York State Department of Health, Factors Associated with Nursing Home Infections and Fatalities in New York State During the COVID-19 Global Health Crisis, (New York, NY: New York State Department of Health, July 2020), https://www.health.ny.gov/press/releases/2020/docs/nh_factors_report.pdf ↩︎
12. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
13. Sandra M. Shi, Innokentiy Bakaev, Helen Chen, Thomas G. Travison, and Sarah D. Berry, “Risk Factors, Presentation, and Course of Coronavirus Disease 2019 in a Large, Academic Long-Term Care Facility”  JAMDA, 21 no.10 (August 2020), https://doi.org/10.1016/j.jamda.2020.08.027 ↩︎
14. New York State Department of Health, Factors Associated with Nursing Home Infections and Fatalities in New York State During the COVID-19 Global Health Crisis (New York, NY: New York State Department of Health, July 2020), https://www.health.ny.gov/press/releases/2020/docs/nh_factors_report.pdf ↩︎
15. Center for Health and Research Transformation, Keeping nursing home residents safe and advancing health in light of COVID-19 (Center for Health and Research Transformation, September 2020), https://chrt.org/wp-content/uploads/2020/09/KeepingNursingHomeResidentsSafe_SummaryReport_9-8-2020.pdf ↩︎
16. Bigelow BF, Tang O, Toci GR, et al., “Transmission of SARS-CoV-2 Involving Residents Receiving Dialysis in a Nursing Home — Maryland, April 2020,” MMWR Morb Mortal Wkly 69 no. 32 (August 2020): 1089-1094, http://dx.doi.org/10.15585/mmwr.mm6932e4 ↩︎
17. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
18. Paul Chatterjee, Sheila Kelly, Mingyu Qi, and Rachel Werner, “Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19),” JAMA Network Open 3, no. 7 (July 2020): e2016930, doi:10.1001/jamanetworkopen.2020.16930 ↩︎
19. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
20. Jose F. Figueroa, Rishi K. Wadhera, Irene Papanicolas et al., “Association of Nursing Home Ratings on Health Inspections, Quality of Care, and Nurse Staffing With COVID-19 Cases,” JAMA 324, no. 11 (August 2020): 1103-1105, doi:10.1001/jama.2020.14709 ↩︎
21. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
22. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al., “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
23. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
24. New York State Department of Health, Factors Associated with Nursing Home Infections and Fatalities in New York State During the COVID-19 Global Health Crisis (New York, NY: New York State Department of Health, July 2020), https://www.health.ny.gov/press/releases/2020/docs/nh_factors_report.pdf ↩︎
25. David P. Bui, Isaac See, Elisabeth M. Hesse et al., “Association Between CMS Quality Ratings and COVID-19 Outbreaks in Nursing Homes – West Virginia, March 17-June 11, 2020,” MMWR. Morbidity and mortality weekly report, 69 no. 37 (September 2020): 1300–1304. https://doi.org/10.15585/mmwr.mm6937a5 ↩︎
26. Jordan Rau and Anna Almendrala, “COVID-Plagued California Nursing Homes Often Had Problems in Past,” Kaiser Health News (May 2020), https://kffhealthnews.org/news/covid-plagued-california-nursing-homes-often-had-problems-in-past/ ↩︎
27. Yue Li, Helena Temkin‐Greener, Gao Shan, and Xueya Cai, “COVID‐19 Infections and Deaths among Connecticut Nursing Home Residents: Facility Correlates,” Journal of the American Medical Directors Association, 68 no. 9 (September 2020): 1899-1906, https://doi.org/10.1111/jgs.16689 ↩︎
28. Mengying He, Yumeng Li, and Fang Fang, “Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities,” Journal of the American Medical Directors Association 21, no. 7 (July 2020): 905–908, https://doi.org/10.1016/j.jamda.2020.06.016 ↩︎
29. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
30. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
31. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al., “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
32. Sandra M. Shi, Innokentiy Bakaev, Helen Chen, Thomas G. Travison, and Sarah D. Berry, “Risk Factors, Presentation, and Course of Coronavirus Disease 2019 in a Large, Academic Long-Term Care Facility”  JAMDA, 21 no.10 (August 2020), https://doi.org/10.1016/j.jamda.2020.08.027 ↩︎
33. Jordan Rau and Anna Almendrala, “COVID-Plagued California Nursing Homes Often Had Problems in Past,” Kaiser Health News (May 2020), https://kffhealthnews.org/news/covid-plagued-california-nursing-homes-often-had-problems-in-past/ ↩︎
34. Charlene Harrington, Leslie Ross, Susan Chapman, et al., “Nurse Staffing and Coronavirus Infections in California Nursing Homes.” Policy, Politics, & Nursing Practice 21, no. 3 (August 2020): 174–86, https://doi.org/10.1177%2F1527154420938707 ↩︎
35. Paul Chatterjee, Sheila Kelly, Mingyu Qi, and Rachel Werner, “Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19),” JAMA Network Open 3, no. 7 (July 2020): e2016930, doi:10.1001/jamanetworkopen.2020.16930 ↩︎
36. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths (California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
37. Jose F. Figueroa, Rishi K. Wadhera, Irene Papanicolas et al., “Association of Nursing Home Ratings on Health Inspections, Quality of Care, and Nurse Staffing With COVID-19 Cases,” JAMA 324, no. 11 (August 2020): 1103-1105, doi:10.1001/jama.2020.14709 ↩︎
38. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
39. Charlene Harrington, Leslie Ross, Susan Chapman, et al., “Nurse Staffing and Coronavirus Infections in California Nursing Homes.” Policy, Politics, & Nursing Practice 21, no. 3 (August 2020): 174–86, https://doi.org/10.1177%2F1527154420938707 ↩︎
40. Rebecca Gorges, “Staffing Levels and COVID-19 Cases and Outbreaks in U.S Nursing Homes,” Journal of the American Geriatrics Society 68 no. 11 (November 2020): 2462-2466, https://doi.org/10.1111/jgs.16787 ↩︎
41. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
42. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths ( California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
43. Rebecca Gorges, “Staffing Levels and COVID-19 Cases and Outbreaks in U.S Nursing Homes,” Journal of the American Geriatrics Society 68 no. 11 (November 2020): 2462-2466, https://doi.org/10.1111/jgs.16787 ↩︎
44. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
45. Charlene Harrington, Leslie Ross, Susan Chapman, et al., “Nurse Staffing and Coronavirus Infections in California Nursing Homes.” Policy, Politics, & Nursing Practice 21, no. 3 (August 2020): 174–86, https://doi.org/10.1177%2F1527154420938707 ↩︎
46. Yue Li, Helena Temkin‐Greener, Gao Shan, and Xueya Cai, “COVID‐19 Infections and Deaths among Connecticut Nursing Home Residents: Facility Correlates,” Journal of the American Medical Directors Association, 68 no. 9 (September 2020): 1899-1906, https://doi.org/10.1111/jgs.16689 ↩︎
47. Rebecca Gorges, “Staffing Levels and COVID-19 Cases and Outbreaks in U.S Nursing Homes,” Journal of the American Geriatrics Society 68 no. 11 (November 2020): 2462-2466, https://doi.org/10.1111/jgs.16787 ↩︎
48. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
49. Priya Chidambaram, Rising Cases in Long-term Care Facilities Are Cause for Concern (Washington, DC: Kaiser Family Foundation, July 2020), https://modern.kff.org/coronavirus-covid-19/issue-brief/rising-cases-in-long-term-care-facilities-are-cause-for-concern/ ↩︎
50. Brian E. McGarry, David C. Grabowski, and Michael L. Barnett, “Severe Staffing And Personal Protective Equipment Shortages Faced By Nursing Homes During The COVID-19 Pandemic” Health Affairs 39, no. 10 (August 2020), https://doi.org/10.1377/hlthaff.2020.01269 ↩︎
51. Huiwen Xu, Orna Intrator, John R. Bowblis “Shortages of Staff in Nursing Homes During the COVID-19 Pandemic: What are the Driving Factors?” Journal of the American Medical Directors 21, no. 10 (October 2020): 1371-1377, https://doi.org/10.1016/j.jamda.2020.08.002 ↩︎
52. Diane Gibson and Jessica Greene, “State Actions and Shortages of PPE and Staff in U.S Nursing Homes” Journal of the American Geriatrics Society 68, no. 12 (October 2020): 2721: 2726, https://doi.org/10.1111/jgs.16883 ↩︎
53. Diane Gibson and Jessica Greene, “State Actions and Shortages of PPE and Staff in U.S Nursing Homes” Journal of the American Geriatrics Society 68, no. 12 (October 2020): 2721: 2726, https://doi.org/10.1111/jgs.16883 ↩︎
54. Brian E. McGarry, David C. Grabowski, and Michael L. Barnett, “Severe Staffing And Personal Protective Equipment Shortages Faced By Nursing Homes During The COVID-19 Pandemic” Health Affairs 39, no. 10 (August 2020), https://doi.org/10.1377/hlthaff.2020.01269 ↩︎
55. Huiwen Xu, Orna Intrator, John R. Bowblis “Shortages of Staff in Nursing Homes During the COVID-19 Pandemic: What are the Driving Factors?” Journal of the American Medical Directors 21, no. 10 (October 2020): 1371-1377, https://doi.org/10.1016/j.jamda.2020.08.002 ↩︎
56. Brian E. McGarry, David C. Grabowski, and Michael L. Barnett, “Severe Staffing And Personal Protective Equipment Shortages Faced By Nursing Homes During The COVID-19 Pandemic” Health Affairs 39, no. 10 (August 2020), https://doi.org/10.1377/hlthaff.2020.01269 ↩︎
57. Robert Tyler Braun, Hyunkyung Yun, Lawrence P. Casalino et al., “Comparative Performance of Private Equity–Owned US Nursing Homes During the COVID-19 Pandemic,” JAMA Network Open 3, no 10 (October 2020): e2026702, doi:10.1001/jamanetworkopen.2020.26702 ↩︎
58. Diane Gibson and Jessica Greene, “State Actions and Shortages of PPE and Staff in U.S Nursing Homes” Journal of the American Geriatrics Society 68, no. 12 (October 2020): 2721: 2726, https://doi.org/10.1111/jgs.16883 ↩︎
59. Brian E. McGarry, David C. Grabowski, and Michael L. Barnett, “Severe Staffing And Personal Protective Equipment Shortages Faced By Nursing Homes During The COVID-19 Pandemic” Health Affairs 39, no. 10 (August 2020), https://doi.org/10.1377/hlthaff.2020.01269 ↩︎
60. Diane Gibson and Jessica Greene, “State Actions and Shortages of PPE and Staff in U.S Nursing Homes” Journal of the American Geriatrics Society 68, no. 12 (October 2020): 2721: 2726, https://doi.org/10.1111/jgs.16883 ↩︎
61. Huiwen Xu, Orna Intrator, John R. Bowblis “Shortages of Staff in Nursing Homes During the COVID-19 Pandemic: What are the Driving Factors?” Journal of the American Medical Directors 21, no. 10 (October 2020): 1371-1377,  https://doi.org/10.1016/j.jamda.2020.08.002 ↩︎
62. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
63. Paul Chatterjee, Sheila Kelly, Mingyu Qi, and Rachel Werner, “Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19),” JAMA Network Open 3, no. 7 (July 2020): e2016930, doi:10.1001/jamanetworkopen.2020.16930 ↩︎
64. Helena Temkin-Greener, Wenhan Guo, Yunjiao Mao, Xueya Cai, and Yue Li, “COVID‐19 Pandemic in Assisted Living Communities: Results from Seven States,” Journal of the American Geriatrics Society 68, no. 12 (December 2020): 2727-2734, https://doi.org/10.1111/jgs.16850   ↩︎
65. Robert Tyler Braun, Hyunkyung Yun, Lawrence P. Casalino et al., “Comparative Performance of Private Equity–Owned US Nursing Homes During the COVID-19 Pandemic,” JAMA Network Open 3, no. 10 (October 2020): e2026702, doi:10.1001/jamanetworkopen.2020.26702 ↩︎
66. Mengying He, Yumeng Li, and Fang Fang, “Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities,” Journal of the American Medical Directors Association 21, no. 7 (July 2020): 905–908, https://doi.org/10.1016/j.jamda.2020.06.016 ↩︎
67. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al.,, “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
68. Mark Aaron Unruh, Hyunkyung Yun, Yongkang Zhang, et al., “ Nursing Home Characteristics Associated With COVID-19 Deaths in Connecticut, New Jersey, and New York,” Journal of the American Medical Directors Association, 21 no. 7 (July 2020): 1001–1003, https://doi.org/10.1016/j.jamda.2020.06.019 ↩︎
69. Adam Dean, Atheendar Venkataramani, and Simeon Kimmel, “Mortality Rates From COVID-19 Are Lower In Unionized Nursing Homes,” Health Affairs, 39 no.11 (September 2020): https://doi.org/10.1377/hlthaff.2020.01011 ↩︎
70. Charlene Harrington, Leslie Ross, Susan Chapman, et al., “Nurse Staffing and Coronavirus Infections in California Nursing Homes.” Policy, Politics, & Nursing Practice 21, no. 3 (August 2020): 174–86, https://doi.org/10.1177%2F1527154420938707 ↩︎
71. Yue Li, Helena Temkin‐Greener, Gao Shan, and Xueya Cai, “COVID‐19 Infections and Deaths among Connecticut Nursing Home Residents: Facility Correlates,” Journal of the American Medical Directors Association, 68 no. 9 (September 2020): 1899-1906, https://doi.org/10.1111/jgs.16689 ↩︎
72. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
73. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
74. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths ( California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
75. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
76. Priya Chidambaram, Tricia Neuman, and Rachel Garfield, Racial and Ethnic Disparities in COVID-19 Cases and Deaths in Nursing Homes (Washington, DC: Kaiser Family Foundation, October 2020), https://modern.kff.org/coronavirus-covid-19/issue-brief/racial-and-ethnic-disparities-in-covid-19-cases-and-deaths-in-nursing-homes/ ↩︎
77. The New York Times, “The Striking Racial Divide in How Covid-19 Has Hit Nursing Homes”, The New York Times (September 2020), https://www.nytimes.com/article/coronavirus-nursing-homes-racial-disparity.html?action=click&module=Well&pgtype=Homepage&section=US%20News ↩︎
78. Yue Li, Xi Cen, Xueya Cai, and Helena Temkin-Greener, “Racial and Ethnic Disparities in COVID‐19 Infections and Deaths Across U.S. Nursing Homes,” Journal of the American Geriatrics Society 68, no. 11 (November 2020): 2454-2461, https://doi.org/10.1111/jgs.16847 ↩︎
79. Paul Chatterjee, Sheila Kelly, Mingyu Qi, and Rachel Werner, “Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19),” JAMA Network Open 3, no. 7 (July 2020): e2016930, doi:10.1001/jamanetworkopen.2020.16930 ↩︎
80. Mengying He, Yumeng Li, and Fang Fang, “Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities,” Journal of the American Medical Directors Association 21, no. 7 (July 2020): 905–908, https://doi.org/10.1016/j.jamda.2020.06.016 ↩︎
81. Mark Aaron Unruh, Hyunkyung Yun, Yongkang Zhang, et al., “ Nursing Home Characteristics Associated With COVID-19 Deaths in Connecticut, New Jersey, and New York,” Journal of the American Medical Directors Association, 21 no. 7 (July 2020): 1001–1003, https://doi.org/10.1016/j.jamda.2020.06.019 ↩︎
82. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
83. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
84. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths ( California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
85. Robert Tyler Braun, Hyunkyung Yun, Lawrence P. Casalino et al., “Comparative Performance of Private Equity–Owned US Nursing Homes During the COVID-19 Pandemic,” JAMA Network Open 3, no. 10 (October 2020): e2026702, doi:10.1001/jamanetworkopen.2020.26702 ↩︎
86. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
87. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
88. Adam Dean, Atheendar Venkataramani, and Simeon Kimmel, “Mortality Rates From COVID-19 Are Lower In Unionized Nursing Homes,” Health Affairs, 39 no.11 (September 2020): https://doi.org/10.1377/hlthaff.2020.01011 ↩︎
89. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
90. Priya Chidambaram, Tricia Neuman, and Rachel Garfield, Racial and Ethnic Disparities in COVID-19 Cases and Deaths in Nursing Homes (Washington, DC: Kaiser Family Foundation, October 2020), https://modern.kff.org/coronavirus-covid-19/issue-brief/racial-and-ethnic-disparities-in-covid-19-cases-and-deaths-in-nursing-homes/ ↩︎
91. The New York Times, “The Striking Racial Divide in How Covid-19 Has Hit Nursing Homes”, The New York Times (September 2020), https://www.nytimes.com/article/coronavirus-nursing-homes-racial-disparity.html?action=click&module=Well&pgtype=Homepage&section=US%20News ↩︎
92. Priya Chidambaram, Tricia Neuman, and Rachel Garfield, Racial and Ethnic Disparities in COVID-19 Cases and Deaths in Nursing Homes (Washington, DC: Kaiser Family Foundation, October 2020), https://modern.kff.org/coronavirus-covid-19/issue-brief/racial-and-ethnic-disparities-in-covid-19-cases-and-deaths-in-nursing-homes/ ↩︎
93. Yue Li, Xi Cen, Xueya Cai, and Helena Temkin-Greener, “Racial and Ethnic Disparities in COVID‐19 Infections and Deaths Across U.S. Nursing Homes,” Journal of the American Geriatrics Society 68, no. 11 (November 2020): 2454-2461, https://doi.org/10.1111/jgs.16847 ↩︎
94. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
95. Helena Temkin-Greener, Wenhan Guo, Yunjiao Mao, Xueya Cai, and Yue Li, “COVID‐19 Pandemic in Assisted Living Communities: Results from Seven States,” Journal of the American Geriatrics Society 68, no. 12 (December 2020): 2727-2734, https://doi.org/10.1111/jgs.16850 ↩︎
96. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths ( California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
97. Mengying He, Yumeng Li, and Fang Fang, “Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities,” Journal of the American Medical Directors Association 21, no. 7 (July 2020): 905–908, https://doi.org/10.1016/j.jamda.2020.06.016 ↩︎
98. Yue Li, Helena Temkin‐Greener, Gao Shan, and Xueya Cai, “COVID‐19 Infections and Deaths among Connecticut Nursing Home Residents: Facility Correlates,” Journal of the American Medical Directors Association, 68 no. 9 (September 2020): 1899-1906, https://doi.org/10.1111/jgs.16689 ↩︎
99. Margaret M. Sugg, Trent J. Spaulding, Sandi J. Lane et al, “Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach,” Science of the Total Environment 752, no. 15 (January 2021):141946,  https://doi.org/10.1016/j.scitotenv.2020.141946 ↩︎
100. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
101. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
102. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
103. Helena Temkin-Greener, Wenhan Guo, Yunjiao Mao, Xueya Cai, and Yue Li, “COVID‐19 Pandemic in Assisted Living Communities: Results from Seven States,” Journal of the American Geriatrics Society 68, no. 12 (December 2020): 2727-2734, https://doi.org/10.1111/jgs.16850 ↩︎
104. Mengying He, Yumeng Li, and Fang Fang, “Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities,” Journal of the American Medical Directors Association 21, no. 7 (July 2020): 905–908, https://doi.org/10.1016/j.jamda.2020.06.016 ↩︎
105. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al., “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
106. Mark Aaron Unruh, Hyunkyung Yun, Yongkang Zhang, et al., “ Nursing Home Characteristics Associated With COVID-19 Deaths in Connecticut, New Jersey, and New York,” Journal of the American Medical Directors Association, 21 no. 7 (July 2020): 1001–1003, https://doi.org/10.1016/j.jamda.2020.06.019 ↩︎
107. Charlene Harrington, Leslie Ross, Susan Chapman, et al., “Nurse Staffing and Coronavirus Infections in California Nursing Homes.” Policy, Politics, & Nursing Practice 21, no. 3 (August 2020): 174–86, https://doi.org/10.1177%2F1527154420938707 ↩︎
108. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
109. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
110. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths ( California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
111. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
112. Charlene Harrington, Leslie Ross, Susan Chapman, et al., “Nurse Staffing and Coronavirus Infections in California Nursing Homes.” Policy, Politics, & Nursing Practice 21, no. 3 (August 2020): 174–86, https://doi.org/10.1177%2F1527154420938707 ↩︎
113. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎
114. Mark Aaron Unruh, Hyunkyung Yun, Yongkang Zhang, et al., “ Nursing Home Characteristics Associated With COVID-19 Deaths in Connecticut, New Jersey, and New York,” Journal of the American Medical Directors Association, 21 no. 7 (July 2020): 1001–1003, https://doi.org/10.1016/j.jamda.2020.06.019 ↩︎
115. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al., “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
116. Patricia Rowan, Reena Gupta, Rebecca Lester et al., A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities (Princeton, NJ: Mathematica, Inc., September 2020), https://www.mathematica.org/our-publications-and-findings/publications/fr-a-study-of-the-covid-19-outbreak-and-response-in-connecticut-long-term-care-facilities ↩︎
117. Bruce Spurlock, Alex Stack, Charlene Harrington, COVID-19 in California’s Nursing Homes: Factors Associated with Cases and Deaths ( California Health Care Foundation, December 2020), https://www.chcf.org/publication/covid-19-californias-nursing-homes-factors-cases-deaths/#recommendations ↩︎
118. Elizabeth M. White, Cyrus M. Kosar, Richard A.Feifer et al., “Variation in SARS‐CoV‐2 Prevalence in U.S. Skilled Nursing Facilities,” Journal of the American Geriatrics Society 68, no. 10 (October 2020): 2167-2173, https://doi.org/10.1111/jgs.16752 ↩︎
119. Helena Temkin-Greener, Wenhan Guo, Yunjiao Mao, Xueya Cai, and Yue Li, “COVID‐19 Pandemic in Assisted Living Communities: Results from Seven States,” Journal of the American Geriatrics Society 68, no. 12 (December 2020): 2727-2734, https://doi.org/10.1111/jgs.16850 ↩︎
120. Mengying He, Yumeng Li, and Fang Fang, “Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities,” Journal of the American Medical Directors Association 21, no. 7 (July 2020): 905–908, https://doi.org/10.1016/j.jamda.2020.06.016 ↩︎
121. Hannah R. Abrams, Lacey Loomer, Ashvin Gandhi, and David Grabowski, “Characteristics of U.S. Nursing Homes with COVID‐19 Cases,” Journal of the American Geriatrics Society 68, no. 8 (August 2020): 1653-1656, https://doi.org/10.1111/jgs.16661 ↩︎
122. Paul Chatterjee, Sheila Kelly, Mingyu Qi, and Rachel Werner, “Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19),” JAMA Network Open 3, no. 7 (July 2020): e2016930, doi:10.1001/jamanetworkopen.2020.16930 ↩︎
123. Mark Aaron Unruh, Hyunkyung Yun, Yongkang Zhang, et al., “ Nursing Home Characteristics Associated With COVID-19 Deaths in Connecticut, New Jersey, and New York,” Journal of the American Medical Directors Association, 21 no. 7 (July 2020): 1001–1003, https://doi.org/10.1016/j.jamda.2020.06.019 ↩︎
124. Yue Li, Helena Temkin‐Greener, Gao Shan, and Xueya Cai, “COVID‐19 Infections and Deaths among Connecticut Nursing Home Residents: Facility Correlates,” Journal of the American Medical Directors Association, 68 no. 9 (September 2020): 1899-1906, https://doi.org/10.1111/jgs.16689 ↩︎
125. M Keith Chen, Judith A. Chevalier, and Elisa F. Long, Nursing Home Staff Networks and COVID-19, (National Bureau of Economic Research, Working Paper Series no. 27608, July 2020), https://www.nber.org/papers/w27608 ↩︎

In the recent months, the US has experienced record-breaking highs of new coronavirus cases and deaths in nearly every state across the country, and new overall cases and deaths have been higher in January 2021 than at any other point in the pandemic. Research suggests that increased community-level cases are associated with increased long-term care cases. A rise in cases in LTC facilities (LTCFs) is particularly concerning, given that those who live in LTCFs are more vulnerable to severe illness and death from the virus than the general population. In recognition of their high-risk status, LTCF residents and staff have been prioritized for vaccine distribution. However, initial reports indicate slower-than-anticipated rollout, with some reports of high levels of vaccine hesitancy among LTCF staff members. These delays will likely mean additional deaths due to COVID-19 in LTCFs.

This analysis assesses when new LTCF cases and deaths were highest in states across the country, as well as how national trends in LTCF COVID-19 cases/deaths compare to national trends in overall COVID-19 cases/deaths. This piece is limited to data from 2020 since a full month of 2021 data was not available at the time of analysis. Thus, the findings in this data note reflect only when LTCF cases and deaths were highest in 2020. It is likely that many states will hit peak new cases and deaths in LTCFs in early 2021, surpassing the 2020 highs. This analysis finds that, mirroring total COVID-19 cases and deaths trends, LTCF cases were highest in December 2020 and LTCF deaths were highest in April 2020. However, there is a great deal of state variation in these findings, with many states reporting highest new LTCF deaths in December 2020. Our analysis builds on other research examining recent surges in LTCF cases and deaths by providing state-level data, including data through the end of 2020, and comparing LTCF trends to overall trends.

This analysis draws on state-reported data from 42 states to examine patterns in LTCF COVID-19 cases and deaths across the country, including 38 states that report trend-able data on cases and 39 states that report trend-able data on deaths. Detailed state-level data on average weekly new cases and deaths from April – December 2020 is available in Tables 1 and 2. Data reported in this paper is as of the week of December 27^th. See Methods box for more details. For a closer look at long-term care trends prior to September, see Key Questions About the Impact of Coronavirus on Long-Term Care Facilities Over Time.

When Did States Report Highest New COVID-19 Cases and Deaths in Long-Term Care Facilities in 2020?

Cases

Approximately three-quarters of reporting states with trend-able data (28 of 38) experienced their highest average weekly number of new coronavirus cases in long-term care facilities in November or December 2020 (Table 1). Among the 38 states that reported at least four months of trend-able data on LTCF cases since April 2020, four states reported highest average weekly new cases in November 2020, and 24 states reported their highest average weekly new cases in December 2020. This pattern aligns with timing of when many states experienced their highest state-wide new cases and deaths.

A small number of states, concentrated in the Northeast and Southeast, saw highest new cases in LTCFs earlier in the year (Figure 1 and Table 1). Six states experienced their highest average weekly new LTCF cases in Spring of 2020, defined as April or May 2020 (CT, DC, GA, MA, NJ, and RI), with 5 of these 6 states experiencing highest new cases in April 2020 (Table 1). New York, whose early LTCF outbreaks were comparable to those in NJ or CT, does not report data on cases in long-term care facilities. Another four states experienced their highest new LTCF cases in Summer 2020, defined as June, July, or August 2020 (AL, DE, LA, and SC). All other states experienced highest new LTCF cases in the last two months of 2020, coinciding with the recent community-level surges.

Deaths

Over half of reporting states (21 of 39 states) reported their highest average weekly new COVID-19 deaths in long-term care facilities in the last two months of 2020, mostly in December (Table 2). 39 states have reported at least four months of trend-able data on LTCF deaths since April 2020. Of these states, three reported highest average weekly new deaths in November, while nearly half (18 states) reported highest new deaths in December 2020.

States that had reported highest new COVID-19 LTCF deaths in the Spring of 2020 were clustered in the Northeast region of the country, while most of the states that reported highest new LTCF deaths in December 2020 were in the West and the Midwest (Figure 2). States in the Northeast were most likely to experience highest new LTCF deaths sometime in Spring 2020 (April or May) while states in the Southeast were more likely to experience highest new LTCF deaths in Summer 2020 (June- August). Three of the 39 states included in this trend analysis for deaths experienced highest new deaths in November 2020, two of which were Mountain-area states (MT and ND). The remaining 18 states, primarily in the Midwest, West coast, and a few states in the South, experienced their highest new LTCF deaths due to COVID-19 in December 2020.

National Patterns in Long-Term Care Cases and Deaths

Mirroring overall COVID-19 cases and deaths, new LTCF cases were highest nationally in December 2020, while new LTCF deaths were highest nationally in April 2020. (Figure 3). Overall cases are defined as total coronavirus cases in the US population. New overall cases nationally were the lowest at the start of the pandemic, which can be partially attributed to the relatively low testing availability early in the pandemic. In comparison, new LTCF cases dropped from between the spring and summer and were the lowest in summer months before rising again in later in the year. The drop in new cases over the summer may be attributed to the measures that LTCFs put in place to mitigate spread.

National data shows that both total overall and LTCF cases and deaths have been on the rise since September. Based on early state-level trend data, it appears that this trend will continue through early 2021, suggesting that the peak in deaths in LTCFs is yet to come, and could occur in early 2021.

Looking Ahead

Overall, trends in long-term care facilities to some extent mirror trends in community outbreaks, although LTCF cases and deaths may be affected by measures that have been put in place to mitigate the impact of the pandemic on residents and staff. This analysis finds wide variation across states in the timing of highest new cases and deaths due to COVID-19, with some regions of the country experiencing its worst LTCF outbreaks very recently. These outbreaks are happening at the same time that vaccines are making their way to long-term care facility residents and staff. Early data suggests that initial vaccine distribution has been slower than anticipated and that staff vaccination rates are relatively low due, in part due to vaccine hesitancy, which could lead to the continued spread of the virus in long-term care facilities. Based on recent trends, it is likely that we will see a continued rise in new cases in the early months of 2021. Given that the peaks in cases and deaths tend to overlap, it is likely that spread of the virus will mean additional deaths, possibly making the coming months the deadliest of the pandemic for long-term care residents and staff.

 

Introduction

The coronavirus pandemic has generated both a public health crisis and an economic crisis, with major implications for Medicaid enrollment, particularly among the expansion population. Many people who lose their jobs and health coverage during the pandemic will qualify for Medicaid if their income falls below eligibility limits, and low-income adults living in states which have expanded Medicaid under the ACA will have more coverage options than those in states that have not expanded. These states provide coverage to the Medicaid expansion group, which includes adults under age 65 with incomes at or below 138% of the federal poverty level (FPL). (Medicaid enrollees who do not qualify for coverage under the expansion are referred to as the “traditional Medicaid” group throughout this brief; see Box 1 for more details.) Medicaid enrollment has increased by more than five million individuals during the pandemic from February to August 2020. Data from a subset of states suggests that enrollment through the expansion has outpaced growth overall since the start of the pandemic.

Increased Medicaid enrollment has implications for both federal and state spending. For traditional Medicaid enrollees, states receive their regular match rate (“FMAP”) plus additional federal support through a 6.2 percentage point increase in the federal Medicaid match rate for traditional Medicaid spending. The federal government continues to pay a larger share (90%) of the costs for those already or newly enrolled in the expansion group. New expansion group enrollment is likely to compose a large share of increased overall Medicaid enrollment during the pandemic; however, the 6.2 percentage point FMAP increase does not apply to spending for the expansion group.

This issue brief analyzes pre-pandemic trends for enrollment in and spending on the expansion group and examines potential consequences of recent enrollment increases during the pandemic. Enrollment and expenditure data are from the Medicaid Budget and Expenditure System (MBES). As of writing, enrollment data for the fourth quarter of FY 2019 have not been released, and our FY 2019 enrollment figures are drawn from annualized enrollment totals from the data available. Additionally, two states, Maine and Virginia, implemented Medicaid expansion later in FY 2019, so expansion spending in these two states reflect only the months that the expansion has been in effect. States which have or plan to implement the expansion after FY 2019 (Idaho, Utah, Nebraska, Oklahoma, and Missouri) are considered non-expansion states for all years of this analysis. Enrollment and expenditure data for New York have been adjusted due to what appear to be reporting anomalies for the traditional Medicaid group and expansion group, which affected national totals. We did not make adjustments for any other states. See the Methods section for more information.

Medicaid Expansion Enrollment

In FY 2019, the expansion group represented 20% of all Medicaid enrollment and 28% of enrollment in expansion states (Figure 1, Appendix Table 1). In total, Medicaid enrollment for FY 2019 was 75.2 million individuals across all 50 states and DC, with 15.3 million adults enrolled in the expansion group. Within the expansion group, most (81%, 12.5 million) were newly eligible enrollees covered through Medicaid expansion, while a smaller share (19%, 2.9 million) were not newly eligible enrollees (childless adults who were enrolled through state waivers prior to passage of the ACA). The majority of Medicaid enrollment overall (80%, 59.8 million) was within the traditional Medicaid group, which is composed of several different eligibility groups (see Box 1 above for more information). These groups are subject to varying eligibility levels across states, with children and pregnant women generally covered at much higher eligibility levels compared to non-expansion parents and seniors and people with disabilities.

The share of Medicaid enrollment represented by the expansion group varies across expansion states in FY 2019 (Figure 2). Expansion enrollment ranged from a high of 48% of total enrollment in Oregon to a low of 11% in Maine, which implemented Medicaid expansion coverage in the second quarter of FY 2019 (January 2019), although Maine allowed for retroactive enrollment as early as July 2018. The variation across expansion states likely reflects several factors, including different poverty distributions and economic conditions across states (particularly, the state share of the population with income at or below 138% of the FPL) as well as variation in state Medicaid eligibility levels for expansion and traditional groups. For example, the District of Columbia covers expansion adults above the minimum threshold of 138% FPL, with a threshold of 221% FPL for parents and 215% FPL for other adults.

Expansion group enrollment peaked in FY 2017 and FY 2018 but declined in FY 2019, despite two states (Maine and Virginia) that newly implemented Medicaid expansion that year (Figure 3). Expansion enrollment grew from 13.6 million enrollees in FY 2015 (the first full fiscal year of Medicaid expansion following its implementation beginning January 2014), when 30 states had implemented expansion, and peaked at roughly 15.6 million expansion enrollees in FY 2017 and FY 2018, when 32 states had implemented expansion. Expansion enrollment declined to 15.3 million in FY 2019, despite the addition of two more states implementing expansion that year (34 in all). Traditional Medicaid enrollment showed a different trend, declining from a high of 63.2 million in FY 2015 to 59.8 million in FY 2019, with annual declines in all years except FY 2018. Trends in overall (traditional plus expansion) Medicaid enrollment were similar to those for traditional Medicaid enrollment, with annual declines in every year except for FY 2018. Several factors could have contributed to recent declining enrollment for expansion and traditional enrollees, such as improving economic conditions, barriers to maintaining or renewing coverage, and federal funding cuts to outreach and enrollment programs that assist eligible individuals enrolling in Medicaid or marketplace coverage.

Medicaid Expansion Spending

In FY 2019, spending on the expansion group represented 16% of all Medicaid spending and 21% of spending in expansion states (Figure 4, Appendix Table 2). Medicaid spending totaled $594.6 billion across all 50 states and DC. Across the 34 states that implemented expansion before or during FY 2019, spending on the expansion group totaled $93.8 billion that year. Spending on the traditional Medicaid population was much higher: $347.6 billion in expansion states (79% of total spending) and $500.8 billion across all states (84% of total spending). This difference in spending is partially explained by the greater number of traditional enrollees compared to expansion enrollees. Further, the traditional Medicaid group is composed of many different eligibility groups, including groups with smaller enrollment levels but higher per-enrollee spending such as seniors and people with disabilities (for more details, see Per Capita Spending section below). Thus, the proportion of spending represented by the expansion group is lower than its share of enrollment (21% vs. 28% in expansion states).

The share of Medicaid spending represented by expansion spending varied across expansion states in FY 2019 and was less than 40% of total spending in all these states (Figure 5). The share of spending on the expansion group ranged from 4% in Maine to 39% in Montana. (Virginia and Maine implemented expansion in the second quarter of FY 2019 and do not represent a full year of spending.) Much like enrollment, several factors likely contribute to this variation. These include demographic differences across states (such as age and income level of the population), variation in benefit packages and payment levels, and state variation in eligibility limits for other, non-expansion groups (such as seniors and people with disabilities and parents with income at or below pre-ACA eligibility limits).

Medicaid expansion spending is primarily federal funds, with state spending on the expansion group representing just 1% of overall Medicaid spending in FY 2019 (Figure 6). The ACA initially provided 100% federal financing for expansion costs in 2014; this match rate gradually fell to 93% in 2019 then to 90% in 2020 and beyond.¹  In FY 2019, expansion spending totaled $93.8 million, $84.9 billion of which was paid for by the federal government with the remaining $8.9 billion paid for by states. In contrast, states contributed a larger proportion of traditional Medicaid spending, attributable to the lower federal match rate for the traditional population, which in FY 2019 ranged from 50% to 76% based on a statutory formula that accounts for each state’s average per capita income relative to the national average.

As total Medicaid spending has increased in the years since FY 2015, the share of spending represented by the expansion group has remained nearly constant (Figure 7). The share of Medicaid spending on the expansion group has remained between 20% and 22% of total Medicaid spending in expansion states for every year from FY 2015 through FY 2019, suggesting that increases in total Medicaid spending over these years have been proportionately driven by the expansion and traditional populations. The share of total spending represented by expansion spending has remained similarly constant across all states as well (between 14% and 16%). Notably, while total spending increased in FY 2019 for both the expansion and traditional Medicaid groups, enrollment declined that year. Not accounting for the initial increase in spending immediately following implementation, expansion states and non-expansion states experienced similar total spending growth from FY 2015 to FY 2019: 12% growth for both the 30 states that expanded Medicaid by FY 2015 (excluding Louisiana, Maine, Montana, and Virginia, which implemented expansion between FY 2015 and FY 2019) as well as for the 17 non-expansion states. Several factors may explain growing Medicaid costs aside from enrollment, including changes to the makeup of the Medicaid population, service utilization, and rising costs. In FY 2019, states identified increasing costs for prescription drugs, provider rate increases, pressures from an aging population, and a higher acuity case-mix as key upward pressures on total Medicaid spending.

Per Capita Spending

Medicaid spending per enrollee is lower for the expansion group than for other groups (Figure 8, Appendix Table 3). While overall spending per enrollee was $7,910 in FY 2019, spending per expansion enrollee was just $6,110 and spending per traditional enrollee was $8,370 (spending per expansion enrollee may be slightly underreported due to Maine and Virginia implementing expansion later in this fiscal year). This difference is in line with earlier data finding lower spending per enrollee for adults and children as compared to other groups. In contrast, the elderly and beneficiaries with disabilities account for a disproportionate share of Medicaid spending, largely attributable to greater need for acute care and long-term care.

Spending per expansion enrollee varies across expansion states (Figure 9). In FY 2019, spending per expansion enrollee ranged from $3,950 in Vermont to $12,330 in North Dakota (Virginia and Maine implemented expansion in the second quarter of FY 2019, so spending per expansion enrollee may be slightly underreported in these figures). Spending per expansion enrollee was lower than per capita spending for other groups in nearly all expansion states, and states with higher total spending per enrollee generally also had higher spending per expansion enrollee. Factors that may contribute to variation in per capita spending across states include differences in health care costs and utilization and the relative health status of the underlying populations.

Looking Ahead

Medicaid expansion enrollment has grown at a fast rate during the pandemic. In a reversal of prior trends, recent data shows that total enrollment is increasing during the pandemic, reflecting changes in the economy (as more people experience income and job loss and become eligible and enroll in Medicaid coverage) and provisions in the Families First Coronavirus Response Act (FFCRA) that require states to ensure continuous coverage for current Medicaid enrollees and meet other maintenance of eligibility (MOE) conditions to access a temporary increase in the Medicaid federal match rate. Current Medicaid and CHIP enrollment data show that total enrollment increased by over 5 million (7.4%) from February to August 2020, with non-expansion states experiencing slightly faster growth over this time period as compared to expansion states (8.4% growth vs. 7.1% growth). However, enrollment data collected from a subset of state websites for specific eligibility groups show that Medicaid expansion enrollment is growing at a faster rate than enrollment overall, which would lead to a commensurate increase in expansion spending. Non-expansion states are more likely to see increases in the uninsured population as adults who lose employer-sponsored insurance during the pandemic have fewer coverage options in these states.

Although federal dollars will pay for the majority of increased Medicaid spending during the pandemic, states still face economic pressure and may look to cost cutting measures. The federal government pays 90% of costs for the expansion group, which is substantially higher than the regular match rate in all states. Additionally, research showing positive economic outcomes from the Medicaid expansion suggests that expansion states could be better positioned to cope with the economic fallout of the pandemic. The federal government also continues to contribute a higher portion of non-expansion spending to offset costs during the pandemic: under the FFCRA, states that meet MOE conditions receive an additional 6.2 percentage point increase in the federal match rate for traditional spending through the quarter in which the national public health emergency declaration ends. Despite substantial increases in federal dollars going to states for Medicaid during the pandemic, budgetary pressures may cause some states to look to Medicaid program cuts. Because of the federal match for Medicaid spending, programmatic cuts must be substantial to generate state savings, especially for the expansion population. For example, a $100 reduction in expansion spending would yield only $10 in state savings.

Looking ahead, uncertainty remains regarding the future course of the pandemic, the scope and length of federal fiscal relief efforts, and potential state and federal policy actions to expand coverage. As people continue to lose jobs and income during the pandemic, non-expansion states may consider adopting Medicaid expansion to increase coverage. While any new adoption of expansion would increase federal dollars going to states due to the 90% federal match, states may have difficulty covering the remaining 10% of expansion spending amid adverse state budgetary impacts during the pandemic. At the federal level, President-elect Joe Biden has supported a new federal public health insurance option which would be available to individuals in non-expansion states who would otherwise be eligible had their states adopted Medicaid expansion; however, this plan may face challenges to passage in a closely divided Senate. Policymakers may consider more narrow options, such as proposals to make 100% federal financing available to states that newly expand. Additionally, President-elect Joe Biden could implement a number of administrative actions that could increase Medicaid coverage in expansion and non-expansion states

1. The match rate for the expansion group in FY 2019 was 93%; however, the data analyzed in this brief show that the federal government contributed about 90.5% of expansion spending in that year. This discrepancy is because the ACA initially provided the enhanced match rate only for beneficiaries made newly eligible for Medicaid under the law (these beneficiaries composed 89% of the expansion group in FY 2019). The ACA also provided additional federal funding for not newly eligible expansion enrollees, with match rates for this population increasing to 90% in CY 2020 and onward (the same year that the match rate for newly eligible expansion enrollees decreased to 90%). (For more details, see Understanding How States Access the ACA Enhanced Medicaid Match Rates.) Accounting corrections in the MBES data (where states corrected for over or under charging the federal government for Medicaid in prior years) may also contribute to the discrepancy in the federal share. ↩︎