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The benefits of expanding funding for Medicaid long-term care home and community-based services (HCBS) relative to institutional care are often taken as self-evident. However, little is known about the outcomes of these services, especially for racial and ethnic minority groups, whose members tend to use the services more than whites do, and for people with dementia who may need high-intensity care. Using national Medicaid claims data on older adults enrolled in both Medicare and Medicaid, we found that overall hospitalization rates were similar for HCBS and nursing facility users, although nursing facility users were generally sicker as reflected in their claims history. Among HCBS users, blacks were more likely to be hospitalized than non-Hispanic whites were, and the gap widened among blacks and whites with dementia. Also, conditional on receiving HCBS, Medicaid HCBS spending was higher for whites than for nonwhites, and higher Medicare and Medicaid hospital spending for blacks and Hispanics did not offset this difference. Our findings suggest that home and community-based services need to be carefully targeted to avoid adverse outcomes and that the racial/ethnic disparities in access to high-quality institutional long-term care are also present in HCBS. Policy makers should consider the full costs and benefits of shifting care from nursing facilities to home and community settings and the potential implications for equity.

It is important to understand differences in coronavirus disease 2019 (COVID-19) deaths by nursing home racial composition and the potential reasons for these differences so that limited resources can be distributed equitably. To describe differences in the number of COVID-19 deaths by nursing home racial composition and examine the factors associated with these differences. This cross-sectional study of 13 312 nursing homes in the US used the Nursing Home COVID-19 Public File from the Centers for Medicare and Medicaid Services, which contains COVID-19 cases and deaths among nursing home residents as self-reported by nursing homes beginning between January 1, 2020, and May 24, 2020, and ending on September 13, 2020. Data were analyzed from July 28 to December 18, 2020. Confirmed or suspected COVID-19 infection. Confirmed cases were defined as COVID-19 infection confirmed by a diagnostic laboratory test. Suspected cases were defined as signs and/or symptoms of COVID-19 infection or patient-specific transmission-based precautions for COVID-19 infection. Deaths associated with COVID-19 among nursing home residents. Death counts were compared by nursing home racial composition, which was measured as the proportion of White residents. Among 13 312 nursing homes included in the study, the overall mean (SD) age of residents was 79.5 (6.7) years. A total of 51 606 COVID-19-associated deaths among residents were reported, with a mean (SD) of 3.9 (8.0) deaths per facility. The mean (SD) number of deaths in nursing homes with the lowest proportion of White residents (quintile 1) vs nursing homes with the highest proportions of White residents (quintile 5) were 5.6 (9.2) and 1.7 (4.8), respectively. Facilities in quintile 1 experienced a mean (SE) of 3.9 (0.2) more deaths than those in quintile 5, representing a 3.3-fold higher number of deaths in quintile 1 compared with quintile 5. Adjustment for the number of certified beds reduced the mean (SE) difference between these 2 nursing home groups to 2.2 (0.2) deaths. Controlling for case mix measures and other nursing home characteristics did not modify this association. Adjustment for county-level COVID-19 prevalence further reduced the mean (SE) difference to 1.0 (0.2) death. In this study, nursing homes with the highest proportions of non-White residents experienced COVID-19 death counts that were 3.3-fold higher than those of facilities with the highest proportions of White residents. These differences were associated with factors such as larger nursing home size and higher infection burden in counties in which nursing homes with high proportions of non-White residents were located. Focusing limited available resources on facilities with high proportions of non-White residents is needed to support nursing homes during potential future outbreaks.

In December 2008 the Centers for Medicare and Medicaid Services (CMS) launched a five-star rating system of nursing homes as part of Nursing Home Compare, a web-based report card detailing quality of care at all CMS-certified nursing homes. Questions remain, however, as to how well consumers use this rating system as well as other sources of information in choosing nursing home placement. We used a qualitative assessment of how consumers select nursing homes and of the role of information about quality, using semistructured interviews of people who recently placed a family member or friend in a nursing home. We found that consumers were receptive to using Internet-based information about quality as one source of information but that choice was limited by the need for specialized services, proximity to family or health care providers, and availability of Medicaid beds. Consumers had a positive reaction when shown Nursing Home Compare; however, its use appeared to be limited by lack of awareness and, to some extent, initial lack of trust of the data. Our findings suggest that efforts to expand the use of Nursing Home Compare should focus on awareness and trust. Useful additions to Nursing Home Compare might include measures of the availability of activities, information about cost, and consumer satisfaction.

Market-based reforms in health care, such as public reporting of quality, may inadvertently exacerbate disparities. We examined how the Centers for Medicare and Medicare Services' five-star rating system for nursing homes has affected residents who are dually enrolled in Medicare and Medicaid (\"dual eligibles\"), a particularly vulnerable and disadvantaged population. Specifically, we assessed the extent to which dual eligibles and non-dual eligibles avoided the lowest-rated nursing homes and chose the highest-rated homes once the five-star rating system began, in late 2008. We found that both populations resided in better-quality homes over time but that by 2010 the increased likelihood of choosing the highest-rated homes was substantially smaller for dual eligibles than for non-dual eligibles. Thus, the gap in quality, as measured by a nursing home's star rating, grew over time. Furthermore, we found that the benefit of the five-star system to dual eligibles was largely due to providers' improving their ratings, not to consumers' choosing different providers. We present evidence suggesting that supply constraints play a role in limiting dual eligibles' responses to quality ratings, since high-quality providers tend to be located close to relatively affluent areas. Increases in Medicaid payment rates for nursing home services may be the only long-term solution.

Recent work suggests that instability in nursing home staffing levels may be an important marker of nursing home quality. Whether that association holds when controlling for average staffing levels is unknown. To examine whether staffing instability, defined as the percentage of days below average staffing levels, is associated with nursing home quality when controlling for average staffing levels. This quality improvement study of 14 717 nursing homes used the merged Centers for Medicare & Medicaid Services Payroll Based Journal, Minimum Data Set, Nursing Home Care Compare, and Long-Term-Care Focus data for fiscal years 2017 to 2019. Statistical analysis was performed from February 8 to November 14, 2022. Linear, random-effect models with state fixed effects and robust SEs were estimated for 12 quality indicators as dependent variables, percentage of below-average staffing days as independent variables, controlling for average staffing hours per resident-day for registered nurses, licensed practical nurses, and certified nurse aides. Below-average staffing days were defined as those 20% below the facility average, by staffing type. Quality indicators included deficiency citations; long-stay residents receiving an antipsychotic; percentage of high-risk long-stay residents with pressure ulcers (2 different measures for pressure ulcers were used); and percentage of long-stay residents with activities of daily living decline, mobility decline, emergency department visits, and hospitalizations; and short-stay residents with new antipsychotic medication, mobility decline, emergency department visits, and rehospitalizations. For the 14 717 nursing homes in this study, the mean (SD) percentage of days with below-average staffing was 30.2% (12.0%) for registered nurses, 16.4% (11.3%) for licensed practical nurses, and 5.1% (5.3%) for certified nurse aides. Mean (SD) staffing hours per resident-day were 0.44 (0.40) for registered nurses, 0.80 (0.32) for licensed practical nurses, and 2.20 (0.50) for certified nurse aides. In regression models that included average staffing, a higher percentage of below-average staffing days was significantly associated with worse quality for licensed practical nurses in 10 of 12 models, with the largest association for decline of activities of daily living among long-stay residents (regression coefficient, 0.020; P < .001). A higher percentage of below-average staffing days was significantly associated with worse quality for certified nurse aides in 9 of 12 models, with the largest association for short-stay functioning (regression coefficient, 0.030; P = .01). This study suggests that holding average staffing levels constant, day-to-day staffing stability, especially avoiding days with low staffing of licensed practical nurses and certified nurse aides, is a marker of better quality of nursing homes. Future research should investigate the causes and potential solutions for instability in staffing in all facilities, including those that may appear well-staffed on average.

More than 30 years after the Nursing Home Reform Act, the United States still fails to protect nursing home residents and provide them with high-quality care. The Covid-19 pandemic’s devastating effect on nursing homes reminds us that further reforms are sorely needed.

Policy Points In the preexpansion period, federally qualified health centers (FQHCs) in Medicaid expansion states were significantly different from those in nonexpansion states. This gap widened as revenues in expansion states continued to grow at a faster rate after the expansion. If Medicaid expansion had occurred nationwide, FQHCs’ revenue and capacity could have increased substantially. Over time, Medicaid could play a bigger role as it becomes a more stable funding source to allow for capital investments. Section 330 grants appear to have a larger impact on access to care. Given the varying levels of reliance on Medicaid, investing through federal grants might be more effective and equitable. Context The Health Resources and Services Administration's Health Center Program (HCP) plays a critical role as the national ambulatory safety net, delivering services to patients in medically underserved areas, regardless of their ability to pay. As the program has grown, health policy initiatives may have altered access to care for the underserved population. Understanding how federally qualified health centers (FQHCs) have been affected by past policies is important for anticipating the effects of future policies. Methods By analyzing a national data set from the Uniform Data System, we examined, using two sets of random effects regressions, the potential impact of alternative policy actions affecting FQHCs. Our primary equation models the number of full‐time equivalent staff, of patients served, and of visits provided in the subsequent year as a function of Medicaid revenues, Section 330 grants, and other revenues. Our secondary equation is a difference‐in‐differences analysis that models Medicaid revenues as a function of the states’ status of Medicaid expansion. Findings The expansion of Medicaid in nonexpansion states could have increased Medicaid revenues by 138%, staffing by 25%, and patients’ visits by 24% in 2017. Compared to the impact of a “repeal” of Medicaid expansion, the percentage of reductions in staffing would be similar to those predicted by a 50% cut in Medicaid revenues or in Section 330 grants. On a dollar‐for‐dollar basis, the effects of one dollar of Section 330 grants were more than double that of one dollar of Medicaid revenue. Conclusions Both Medicaid eligibility and Section 330 funding support are important to the HCP, and Section 330 grants are particularly closely related to staffing and the provision of services. States’ decisions not to participate in or to repeal Medicaid expansion, to reduce Medicaid payment rates, and federal funding cuts all could have a negative impact on FQHCs, resulting in thousands of low‐income patients losing access to primary care.

It is important to understand the association between staff vaccination rates and adverse COVID-19 outcomes in nursing homes. To assess the extent to which staff vaccination was associated with preventing COVID-19 cases and deaths among residents and staff in nursing homes. This longitudinal cohort study used data on COVID-19 outcomes in Medicare- and Medicaid-certified nursing homes in the US between May 30, 2021, and January 30, 2022. Participants included the residents of 15 042 US nursing homes that reported COVID-19 data to the Centers for Disease Control and Prevention and passed Centers for Medicare & Medicaid Services data quality checks in the National Healthcare Safety Network. Weekly staff vaccination rates. Main outcomes are weekly COVID-19 cases and deaths among residents and weekly COVID-19 cases among staff. The treatment variable is the primary 2-dose staff vaccination rate in each facility each week. In the primary analysis of 15 042 nursing homes before the Omicron variant wave (May 30 to December 5, 2021) using fixed effects of facility and week, increasing weekly staff vaccination rates by 10 percentage points was associated with 0.13 (95% CI, -0.20 to -0.10) fewer weekly COVID-19 cases per 1000 residents, 0.02 (95% CI, -0.03 to -0.01) fewer weekly COVID-19 deaths per 1000 residents, and 0.03 (95% CI, -0.04 to -0.02) fewer weekly COVID-19 staff cases. In the secondary analysis of the Omicron wave (December 5, 2021, to January 30, 2022), increasing staff vaccination rates were not associated with lower rates of adverse COVID-19 outcomes in nursing homes. The findings of this cohort study suggest that before the Omicron variant wave, increasing staff vaccination rates was associated with lower incidence of COVID-19 cases and deaths among residents and staff in US nursing homes. However, as newer, more infectious and transmissible variants of the virus emerged, the original 2-dose regimen of the COVID-19 vaccine as recommended in December 2020 was no longer associated with lower rates of adverse COVID-19 outcomes in nursing homes. Policy makers may want to consider longer-term policy options to increase the uptake of booster doses among staff in nursing homes.

Average staffing measures are a focus of nursing homes' quality assessments and reporting. They may, however, mask daily variation in staffing, additional information that could be important for understanding nursing home quality and relative ranking. To examine daily variation in staffing, its association with quality, and whether daily variation provides information regarding quality ranking of nursing homes over and above the information provided by average staffing levels. This quality improvement study included registered nurses (RNs) and certified nurse aide (CNAs) at 13 339 certified nursing homes throughout the United States during 2017 to 2018. Retrospective analyses of the Payroll-Based Journal, Medicare Cost Reports, and Nursing Home Care Compare were conducted. Data were analyzed from January 2017 to December 2018. Three measures of daily variation, ie, coefficient of variation (COV), total outlier days (TOD), and low outlier days (LOD), were calculated for RNs and CNAs. The association between these measures and quality rankings and other facility characteristics were evaluated. A total of 13 339 nursing homes were included in this study, with 9476 (71%) for-profit facilities. The mean (SD) hours-per-resident-day were 0.41 (0.29) for RNs and 2.16 (0.49) for CNAs, and a mean (SD) 55% (26%) of residents were Medicaid beneficiaries. Outcome measures were as follows: mean (SD) COV, 0.5 (0.6) for RNs and 0.1 (0.1) for CNAs; mean (SD) TOD, 220 (69) for RNs and 44 (45) for CNAs; and mean (SD) LOD, 116 (45) for RNs and 22 (24) for CNAs. All 3 variation measures, for both RNs and CNAs, were significantly associated with both the 5-Star Quality Measures (COV among RNs, -0.014 [95% CI, -0.021 to -0.007]; P < .001; COV among CNAs: -0.004 [95% CI, -0.006 to -0.003]; P < .001; TOD among RNs, -3.79 [95% CI, -4.59 to -2.99]; P < .001; TOD among CNAs, -2.52 [95% CI, -3.08 to -1.96]; P < .001; LOD among RNs, -2.46 [95% CI, -3.03 to -1.88]; P < .001; LOD among CNAs, -1.29 [95% CI, -1.58 to -0.99]; P < .001) and the 5-Star Survey rankings (COV among RNs,-0.026 [95% CI, -0.033 to -0.019]; P < .001; COV among CNAs: -0.006 [95% CI, -0.007 to -0.004]; P < .001; TOD among RNs, -5.10 [95% CI, -5.97 to -4.23]; P < .001; TOD among CNAs, -4.16 [95% CI, -4.77 to -3.55]; P < .001; LOD among RNs, -3.04 [95% CI, -3.65 to -2.44]; P < .001; LOD among CNAs, -1.97 [95% CI, -2.29 to -1.65]; P < .001) published in Nursing Home Care Compare. Low κ values, ranging from 0.23 to 0.63, indicated that the variation measures add information about ranking to the information provided by average staffing measure. These findings highlight the importance of reporting daily variation in staffing to improve understanding of the relationship between staffing and quality. They suggest that 2 facilities with the same average staffing achieve different quality of resident care and survey ratings in association with on the day-to-day variation in staffing. Measures of daily staffing may enhance the value of Nursing Home Care Compare for nursing homes and others engaged in quality improvement and consumers searching for high quality nursing homes.