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. Author manuscript; available in PMC: 2024 May 1.
Published in final edited form as: J Am Med Dir Assoc. 2023 Mar 1;24(5):712–717. doi: 10.1016/j.jamda.2023.01.017

Quality of Nursing Homes Among ADRD Residents Newly Admitted From the Community: Does Race Matter?

Shubing Cai a,*, Di Yan a, Sijiu Wang b, Helena Temkin-Greener a
PMCID: PMC10182813  NIHMSID: NIHMS1871655  PMID: 36870366

Abstract

Objective:

To examine racial differences in admissions to high-quality nursing homes (NHs) among residents with Alzheimer disease and related dementias (ADRD), and whether such racial differences can be influenced by dementia-related state Medicaid add-on policies.

Design:

Retrospective cross-sectional study.

Setting and Participants:

The study included 786,096 Medicare beneficiaries with ADRD newly admitted from the community to NHs between January 1, 2011 and December 31, 2017.

Methods:

2010–2017 Minimum Data Set 3.0, Medicare Beneficiary Summary File, Medicare Provider Analysis and Review, and Nursing Home Compare data were linked. For each individual, we constructed a “choice” set of NHs based on the distance between the NH and an individual residential zip code. McFadden’s choice models were estimated to examine the relationship between admission into a high-quality (4- or 5-star) NH and individual characteristics, specifically race, and state Medicaid dementia-related add-on policies.

Results:

Among the identified residents, 89% were White, and 11% were Black. Overall, 50% of White and 35% of Black individuals were admitted to high-quality NHs. Black individuals were more likely to be Medicare-Medicaid dually eligible. Results from McFadden’s model suggested that Black individuals were less likely to be admitted to a high-quality NH than White individuals (OR = 0.615, P < .01), and such differences were partially explained by some individual characteristics. Furthermore, we found that the racial difference was reduced in states with dementia-related add-on policies, compared with states without these policies (OR = 1.16, P < .01).

Conclusions and Implications:

Black individuals with ADRD were less likely to be admitted to high-quality NHs than White individuals. Such difference was partially related to individuals’ health conditions, social-economic status, and state Medicaid add-on policies. Policies to reduce barriers to high-quality NHs among Black individuals are necessary to mitigate health inequity in this vulnerable population.

Keywords: ADRD, racial differences, nursing home admission, quality

The US population living with Alzheimer disease and related dementia (ADRD) is expected to reach nearly 14 million by 2050.1 The prevalence of ADRD is reported to be higher among Black individuals than White individuals. For example, among those aged 75 to 84, the prevalence of ADRD is estimated to be 20% for Black individuals and 11% for White individuals, increasing to 59% for Black individuals and 30% for White individuals among those aged 85 and older.2 During the course of illness, older adults with ADRD gradually lose their functional and cognitive independence, and many develop behavioral and psychiatric symptoms of dementia (BPSD), such as psychosis, physical or verbal aggression, or agitation.3–5 Because of the increased care needs, many older adults with ADRD eventually turn to nursing home (NH) care.6–9 The need for NH care may be higher for Black individuals, as they have a higher prevalence of ADRD, experience greater levels of cognitive impairment, and are more likely to develop BPSD than their White counterparts.4,10,11

There has been a long-standing concern that Black individuals receive a lower quality of NH care than White individuals. One reason for this difference is that Black individuals are more likely to reside in lower-quality NHs.12–14 Such racial differences in access to high-quality NHs may be exacerbated among older adults with ADRD because of the potentially higher care needs and a greater burden of care among Black individuals.4,15,16 Accommodating higher care needs and providing appropriate care, such as proper management of disruptive behaviors, can be resource-intensive (eg, requiring staff time and training) and costly, and place higher burden and stress on NH staff.3,17–30 However, not providing proper dementia care may lead to worse health outcomes for residents with ADRD and affect the quality of life for other residents.31–33 Thus, NHs, especially those with a high quality, which generally experience higher demand, may have lower incentives to admit Black individuals with ADRD because of their potentially higher burden of care. To date, there is limited empirical evidence on the extent to which Black residents with ADRD, who have unique care needs, experience access barriers to high-quality NHs.

Considering the higher costs associated with providing care to residents with cognitive impairment or behavioral symptoms, some states offer an add-on payment to their state Medicaid NH reimbursement rates for residents with mental health issues, cognitive impairment, or dementia.34 For example, New York State adopted such an add-on approach paying an additional $8 per resident per day for residents with these conditions.34,35 Between 2011 and 2017, 18 states (Colorado, Delaware, Georgia, Idaho, Indiana, Maine, Massachusetts, Michigan, Mississippi, Missouri, Nevada, New Jersey, New York, Ohio, Oregon, South Carolina, South Dakota, Utah) adopted add-on payments for cognitive impairment or mental health issues.34 These policies may influence a NH’s decision to admit such residents and thus reduce potential barriers to accessing higher-quality NHs. However, there is no empirical evidence on whether and how state Medicaid add-on policies affect residents’ access to high-quality NHs, especially among Black individuals.

Motivated by current literature gaps, this study’s main objectives were to examine racial differences in admission to high-quality NHs among residents with ADRD, and whether and how they may be influenced by individual characteristics and state Medicaid add-on policies. We focused on residents admitted to NHs from the community, as their care needs differed from those admitted to NHs after a hospitalization event (ie, post-acute residents). Factors influencing admission into a certain NH could also differ between these 2 populations. We hypothesize that Black individuals with ADRD were less likely to be admitted to high-quality NHs, and such differences may be reduced with Medicaid cognitive impairment/mental health add-on payment.

Methods

This study is based on secondary data analysis from existing national data.

Data Sources

We linked 2010–2017 national Minimum Data Set (MDS 3.0), Medicare Master Beneficiary Summary File (MBSF), and Medicare Provider Analysis and Review (MedPAR). The MDS includes information on individual health conditions, such as the diagnosis of ADRD, aggressive behavior, and cognitive performance, at admission, at least quarterly after if a resident remains in a NH, and at discharge. MBSF contains information on residents’ socio-demographic characteristics, such as race, gender, and Medicare-Medicaid dual-eligibility status. The MedPAR file has information on hospitalization, such as admission and discharge dates.

We further linked the preceding individual-level data with NH-, community-, and state-level data. NH-level data included Nursing Home Compare (NHC) and Long-term Care Focus data (https://ltcfocus.org/). These data contain information on NH quality measures (ie, the 5-star rating) and other characteristics, such as ownership and number of beds. We also obtained the 2015 national Area Deprivation Index (ADI) from the University of Wisconsin Neighborhood Atlas website (https://www.neighborhoodatlas.medicine.wisc.edu/). ADI captures the socio-economic status of a neighborhood, with a higher ranking indicating a more economically deprived community. ADI was linked with individual-level data at the zip code level. Last, we collected information on Medicaid payment add-on policies for behavioral problems or cognitive impairment from the American Health Care Association reports, state government websites, and the Medicaid and CHIP Payment and Access Commission (MACPAC).34–36

Study Sample and “Choice Set”

We included White and Black residents with ADRD newly admitted to NHs from the community between January 2011 and December 2017. The diagnosis of ADRD was based on the checkbox of “Alzheimer disease” and “dementia,” as well as on the International Classification of Diseases (ICD)-9 and (ICD)-10-CM codes from the MDS 3.0. We considered a NH admission from the community if there were no hospitalizations or NH stay 30 days before the index NH admission date. Hospitalizations were identified based on MedPAR data. To ensure the identification of hospitalizations, we further restricted the analyses to those enrolled in Medicare fee-for-service at least 30 days before the NH admission. If a resident had multiple qualified “new” admissions, we only counted the first NH admission to avoid within-person correlation.

For each individual with eligible NH admission, we obtained the zip code of their residence and defined a choice set of NHs. More specifically, we considered a NH as within an individual’s “choice set” if the NH’s zip code was within 15 miles (in non-rural areas) or 20 miles (in rural areas) radius of the individual’s zip code of residence.37,38 We excluded individuals with only one NH in their choice sets, and they did not have a “choice.” The final analytical sample included 786,096 individuals and 15,755 NHs.

Measures

Dependent variable

The dependent variable was whether a NH within a choice set was “chosen” by an individual or not, with a value of 1 for a NH that admitted the resident and 0 for all other NHs within the choice set.

Key independent variables

The key independent variables included individual race, quality of NH, and state Medicaid add-on policies. Race was defined as non-Hispanic White or Black, based on Research Triangle Institute race code in the MBSF.39 NH quality was determined based on the overall 5-star rating in the NHC. The overall star rating is based on the ratings of staffing, quality measures, and health inspection, with 5 indicating much above average quality and 1 as much below average quality (https://www.cms.gov/medicare/provider-enrollment-and-certification/certificationandcomplianc/fsqrs). We dichotomized a NH as high quality (ie, 4- or 5-star rating) vs all others (ie, 1–3 stars). We used a star rating of 3 as the cutoff point for high- vs low-quality NHs, because the average star rating of NHs is 3. State Medicaid add-on policy was dichotomized as 1 if the state had a behavioral/mental health or cognitive impairment add-on payment policy in the year when a resident was admitted and 0 otherwise.

Covariates

We also accounted for a set of covariates that might affect an individual’s NH “choice.” Covariates included individual demographic characteristics (age, gender, marital status), socio-economic characteristics (Medicare-Medicaid dual-eligibility status and residence in a disadvantaged neighborhood), presence of aggressive behavior and cognitive impairment at the time of NH admission, and driving distance from an individual’s residence to each NH in the choice set. Aggressive behavior was measured by the aggressive behavior scale (ABS) at NH admission, based on the MDS. The scale40 ranges from 0 to 12, with a higher score indicating more severe behavioral problems. We considered those with ABS greater than 1 as having any behavioral issues.41 Individual cognitive impairment was measured by the cognitive function scale (CFS) at NH admission based on the MDS. Following prior studies, we categorized residents as having severe impairment vs not.42 We linked the MBSF data with Neighborhood Atlas data at the zip code level and used ADI as a proxy for the individual socio-economic status. Based on the distribution of the ADI in our study sample, we categorized a community as whether the ADI was at/above or below the score of 41 (ie, the average value of ADI in the sample).

Facility-level characteristics included ownership, the total number of beds, occupancy rates, and the percent of Medicare and Medicaid residents in an NH, based on the NHC and the LTC Focus datasets. We also accounted for state Medicaid NH reimbursement, as it may affect an NH’s consideration for admitting high-risk residents.43

Statistical Analysis

We first described the distribution of NH star ratings for Black and White individuals within their choice sets. We then compared individual characteristics at NH admission and the attributes of NHs to which Black and White individuals were admitted.

Similar to prior studies,44–46 we used McFadden’s choice (conditional logit) model to examine the relationship among race, state policy, and the likelihood of entering high-quality NHs. The estimation of this model requires the specification of a choice set of NHs that residents may enter when seeking NH care, as defined previously. The “choice” of an NH may reflect both an individual’s choice of NHs and an NH’s decision to admit a resident. To examine the relationship between individual characteristics, especially race, and the likelihood of entering high-quality NHs, we interacted individual characteristics (eg, race, ABS, and CFS) with NH quality.47

We estimated a set of models to explore potential racial differences in entering high-quality NHs and factors related to such differences. We started with a model with only the interaction between NH quality and race, which captured the overall racial differences in entering high-quality NHs, and then sequentially added interactions between high-quality NHs and other individual variables, such as race and ABS and CFS, to explore how much other individual characteristics could explain the racial difference. Last, we added some 3-way interactions, such as between race, quality of NHs, and state Medicaid policies, to examine whether state policies can modify racial differences in entering high-quality NHs. All analyses were performed using SAS 9.4 (SAS Institute Inc.) and STATA 17 (StataCorp LLC). This study has been approved by the institutional review board at University of Rochester.

Results

On average, approximately 11% of those admitted to NHs were Black, and 89% were White. The average number of NHs in the choice sets was 54 for Black individuals vs 29 for White individuals with ADRD. Table 1 compares the distribution of the quality of (ie, star ratings) of the NHs in the choice sets for White and Black individuals with ADRD. On average, 51% vs 48% of NHs in the choice sets were high-quality NHs (4 or 5 stars) for White and Black individuals, respectively.

Table 1.

Distribution of Star Ratings of NHs in the Choice Sets for White and Black Individuals With ADRD

Choice Set for White Individuals Choice Set for Black Individuals
Star rating % Distance to NHs Star Rating % Distance to NHs
1 11.0 8.74 1 12.3 8.55
2 19.4 8.85 2 20.8 8.62
3 18.4 8.88 3 18.4 8.78
4 24.7 8.88 4 22.8 8.90
5 26.4 8.96 5 25.5 8.97
Total 100.0 8.88 Total 100.0 8.79
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Table 2 compares individual characteristics and characteristics of NHs to which Black individuals and White individuals were admitted. Compared with White individuals with ADRD who were newly admitted to NHs, Black individuals were younger (26% vs 48% older than 85, with average age 76.11 for Black individuals and 82.19 for White individuals), less likely to be married, more likely to have a severe cognitive impairment, more likely to be Medicare-Medicaid dually eligible, and more likely to live in socio-economically deprived communities. NHs to which Black individuals with ADRD were admitted were less likely to have 4 or 5 stars (34% for Black individuals vs 50% for White individuals) and had a higher percentage of Medicaid residents.

Table 2.

Comparison of Individual Characteristics and Characteristics of Admission NHs Between Black and White Individuals With ADRD

White Black Total
702,591 (89.38%) 83,505 (10.62%) 786,096
Number of NHs in choice set 29.35 (37.46) 54.37 (52.77) 32.06 (40.17)
Characteristics of admission NHs
 Overall rating of admission NH
  1 12.13 19.56 12.93
  2 18.88 26.19 19.67
  3 19.14 19.67 19.19
  4 26.53 20.53 25.88
  5 23.23 13.95 22.23
 Ownership (for-profit) 66.58 82.29 68.28
 Percent of residents paid by Medicaid 54.27% (22.94) 65.42% (20.78) 55.47% (22.98)
 Percent of residents paid by Medicare 17.61 (14.84) 16.40 (13.57) 17.48 (14.72)
 NH occupancy rate 83.07% (13.23) 83.43% (12.87) 83.11% (13.19)
 Resident has NO high-quality NH in choice set 4.98 3.69 4.84
Individual characteristics
 Marital
 Married 32.27 21.43 31.10
 Male 37.80 46.50 38.74
 Age ≥85 48.12 26.20 44.14
 Cognitive Performance Scale: Severe 6.80 9.62 7.11
 Any aggressive behavior 16.63 14.81 16.43
 Reside in socio-economically deprived community 65.89 77.14 67.11
 Medicare and Medicaid duals 28.21 55.17 31.14
 Distance from the chosen NH to resident’s zip 4.13 (4.60) 4.36 (4.13) 4.15 (4.55)
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Numbers in the cell are percentages for categorical variables and mean (SD) for continuous variables.

The results from the 3 choice models are presented in Table 3. Model 1 captured the overall relationship between race and the likelihood of entering high-quality NHs. The odds of “choosing” a high-quality (the “choice” may reflect both individual and NH roles) was 38% lower (OR = 0.615, P < .01) for Black individuals with ADRD as compared with White individuals. After accounting for additional individual-level characteristics, racial differences in the likelihood of “choosing” high-quality NHs declined: the odds of “choosing” a high-quality NHs was 24% lower (OR = 0.762, P <.01) for Black individuals compared with White individuals (Model 2). This reduction was statistically different (ie, 0.762 in Model 2 vs 0.615 in Model 1, P < .01). Findings from Model 2 also suggested that residents with a higher level of cognitive impairment and aggressive behaviors were less likely to enter high-quality NHs (OR = 0.902 and 0.935, respectively, P < .01). Residents who were dually eligible (OR = 0.624, P < .01) and resided in a poor neighborhood (OR = 0.888, P < .01) were less likely to enter high-quality NHs. On the other hand, married residents were more likely than others to be admitted to high-quality NHs.

Table 3.

Regression Results: Factors Associated With Admission to High-Quality NHs Among Residents With ADRD From the Community, 2011–2017

Model 1 Odds Ratio Model 2 Odds Ratio Model 3 Odds Ratio
High-quality NHs (4–5 star) 1.058* 1.231* 1.233*
High-quality NHs × Black 0.615* 0.762* 0.741*
High-quality NHs × Age 85+ 1.274* 1.274*
High-quality NHs × Male 0.852* 0.852*
High-quality NHs × Married 1.099* 1.100*
High-quality NHs × CFS 0.902* 0.901*
High-quality NHs × ABS 0.935* 0.936*
High-quality NHs × ADI poor zip 0.888* 0.889*
High-quality NHs × Duals 0.624* 0.611*
High-quality NHs × ADRD add-on 0.993
High-quality NHs × Black × ADRD add-on 1.162*
High-quality NHs × Duals × ADRD add-on 1.050*
High-quality NHs × High per diem rate States 0.990
High-quality NHs × Black × High Rate 0.957†
High-quality NHs × Duals × High Rate 1.007
For-profit NHs 1.075* 1.066* 1.059*
Occupancy rate 1.008* 1.009* 1.009*
Bed number 1.004* 1.004* 1.004*
Medicare, % 1.000 1.001* 1.001*
Medicaid, % 0.990* 0.991* 0.991*
Distance to NH (mile) 0.771* 0.770* 0.767*
Number of individuals 786,096 786,096 740,145
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Results from McFadden’s choice models; numbers in the cell are odds ratios with SEs in parentheses.

*

P < .01.

†

P < .05.

Last, we examined whether state add-on policy could modify racial differences in entering high-quality NHs by adding race, high-quality NHs, and add-on policies in the model (Model 3). The add-on policy increased the likelihood of entering high-quality NHs for Black individuals (OR = 1.162, P < .01) and for duals (OR = 1.050, P < .01).

Discussion

We examined racial differences in admission to high-quality NHs among residents with ADRD from the community, and the association with individual characteristics and state-level policies. Consistent with the prior literature among the general population,12–14 we found that Black individuals with ADRD were less likely to enter high-quality NHs than their White counterparts. Our findings further suggested that such racial differences could be partially explained by individual characteristics and modified by state Medicaid NH policies.

We found that some individual characteristics, such as socioeconomic status and health conditions, may contribute to racial differences in admissions to high-quality NHs, as racial differences diminished after accounting for these characteristics. Although we were not able to determine the exact reasons for these relationships, some are more likely to be related to individual choices, whereas others are more likely to reflect an NH’s decisions. For example, we found that Black individuals were less likely to be married, and those who were not married were less likely to be admitted to high-quality NHs. It is not very likely that marital status would affect an NH’s choice of residents, but married residents were likely to have more support and assistance in choosing a high-quality NH.

On the other hand, we found that Black individuals were more likely to be Medicare-Medicaid dual eligible, and Medicare-Medicaid dual status was associated with a lower likelihood of admission to high-quality NHs, which is consistent with prior studies.37,48 In addition, we found that Black individuals were more likely to have a higher level of cognitive impairment, and those with a higher level of cognitive impairment were less likely to be admitted to high-quality NHs. These relationships may reflect an NH’s role in admitting a resident. For example, dual-eligible residents rely on Medicaid to pay for their NH stays that are not considered post-acute. Medicaid reimbursement rate for NHs is generally lower than for private-pay residents, and Medicaid risk-adjustment payment for NHs may not adequately capture the costs of appropriate care for persons with ADRD who have high care needs.19 This especially could be a concern when residents have more complex conditions, such as a higher level of cognitive impairment, that increase the potential costs of care. As high-quality NHs generally have a higher demand, they may have fewer incentives to offer admission priority to these patients.

Moreover, we found that Medicaid mental health/cognitive impairment add-on policy increased the likelihood of entering high-quality NHs for Black individuals. The policy may reduce the perceived higher costs for NHs to provide care to individuals with potentially higher care needs, reducing barriers to admissions to high-quality NHs among Black individuals. As the Medicaid state policy is not likely to influence an individual’s choice, the finding further suggests NHs’ role in admission decisions, and financial incentives may be associated with NHs’ decisions to admit residents.

Despite these findings, racial differences in admission to high-quality NHs cannot be completely explained. It is possible that there were racial differences in the availability of high-quality NHs in their “choice” sets. Indeed, we found that Black individuals had slightly fewer high-quality NHs (ie, a 3 percentage-point difference) in their “choice” sets compared with White individuals. Although this difference appears to be small, it is also possible that high-quality NHs were less accessible to Black individuals, even within the defined “choice” sets. For example, Black individuals may have barriers in transportation, and thus family members may not prefer NHs that are farther away from their place of residence, even if they are high-quality NHs.

There are several limitations of this study. First, although we have accounted for the relationship between some individual characteristics and the likelihood of access to high-quality NHs, there can be other unobserved individual characteristics, such as individual cultural background, contributing to the racial differences in high-quality NH admission. Nevertheless, our findings suggested the racial differences in access to high-quality NHs among residents with ADRD and the potential roles of individuals and NHs. Second, this study only focused on residents admitted to NHs from the community and did not involve post-acute care residents admitted to NHs after an acute inpatient event. Although a high proportion of post-acute residents became long-stayers, the factors that affected the choice of an NH after an inpatient could be very different from those who were directly admitted from the community. For example, the distance between the hospital and NH (ie, a skilled nursing facility for post-acute residents), the relationship between the NH and a hospital, and the hospital discharge planner may influence the admission into a certain NH. Last, this study excluded residents with only one NH available in their choice sets. Although these residents did not have a “choice,” they may have faced additional geographic barriers in access to high-quality care.

Reducing health inequity is one of the top priorities in public health. Access to high-quality NHs is key to reducing health inequity in this vulnerable population. As NHs may play a role in the admission decision, appropriate financial incentives may motivate NHs to provide care to individuals with higher care needs but with lower payment rates (ie, duals). On the other hand, the limited availability of high-quality providers has been commonly cited as one of the reasons for the lower quality of care received among racial minorities.12,49,50 Improving the quality of NHs serving a high proportion of minorities may help to reduce health inequity. However, NHs serving a large minority population are likely to be resource-deprived and may not have the capability to improve the quality of care. Therefore, policies may need to focus on improving resources in these facilities while monitoring the quality of care.

Conclusions and Implications

We found that Black individuals with ADRD were less likely to be admitted to high-quality NHs than White individuals. Such difference was partially explained by some individuals’ characteristics and could be modified by state Medicaid add-on policies. To mitigate health inequity in quality of NH care among this vulnerable population, policies may be needed to improve access to high-quality NHs among Black individuals.

Acknowledgments

This study was supported by NIH/NIA RF1AG063811 and RF1AG073052. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the funder.

Footnotes

The authors declare no conflicts of interest.

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