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Nursing Home Alzheimer's Special Care Units: Geographic Location Matters

Published:August 16, 2021DOI:https://doi.org/10.1016/j.jamda.2021.07.020

      Abstract

      Objectives

      Limited data suggest nursing home (NH) Alzheimer's special care units (ASCUs) may improve care and outcomes among residents with dementia. Unfortunately, information describing NH characteristics related to presence of ASCUs is lacking, especially whether location and neighborhood resources influence their presence. We examined locations of NHs with ASCUs and assessed whether neighborhood socioeconomic deprivation, region, and levels of rurality were associated with NH ASCUs.

      Design

      Cross-sectional.

      Setting and Participants

      Contiguous United States; we used 2017 LTCfocus and NH Compare data to identify free-standing NHs and obtain addresses (N = 13,207 NHs).

      Methods

      NH ZIP+4 codes were linked to the Area Deprivation Index (ADI) (within-state ranking of neighborhood deprivation). The 9 census-defined regions of the United States and Rural Urban Continuum codes categorized location. Descriptive analyses and binary logistic regression models, adjusting for NH characteristics, examined associations between NH ASCUs and location.

      Results

      Nearly 15% of NHs had ASCUs. In adjusted models, odds of NH ASCUs were 58% to 69% lower in Pacific, Middle Atlantic, and Southern regions compared with the East North Central region (P values <.001). Odds of NH ASCUs increased 25% to 47% as rurality increased relative to NHs in the most metropolitan areas (P < .01); however, odds of NH ASCUs decreased 63% in the most rural areas (P < .001). ADI was not significantly associated with NH ASCUs. For-profit NHs had 42% lower and chain-affiliated NHs 34% higher odds of ASCUs (P < .001). NHs with higher total staffing hours had 29% higher odds of ASCUs; odds of ASCUs were 46% lower in NHs with more RN staffing hours (P < .001).

      Conclusions and Implications

      Using a robust sample, region, rurality, ownership, and nursing hours significantly predicted NH ASCUs whereas ADI did not. Geographically tailored interventions should be considered to promote use of NH-based ASCUs.

      Keywords

      Despite increasing national efforts to prevent or cure Alzheimer's disease and related dementias (ADRDs), 5.8 million Americans aged ≥65 years are currently diagnosed with these degenerative brain diseases, with expected increases to nearly 14 million by 2050.
      2020 Alzheimer's disease facts and figures.
      States located in the Western and Southeastern United States are projected to be especially impacted with ADRD by 2025, as prevalence of these diseases is expected to increase nearly 35% compared to 2020 prevalence estimates.
      2020 Alzheimer's disease facts and figures.
      Although care for persons with ADRD usually begins in communities, use of nursing home (NH) care is commonplace as diseases progress and complex symptoms require advanced medical care provided by NH staff. Each year, approximately 30% of Americans aged ≥65 years (more than 630,000 Americans) spend their last days in NHs and nearly 70% have a diagnosis of ADRD.
      • Li Q.
      • Zheng N.T.
      • Temkin-Greener H.
      Quality of end-of-life care of long-term nursing home residents with and without dementia.
      Quality of NH care is a long-standing concern among families and policy makers and is an essential research area given rapid increases in populations of persons with ADRD transitioning into NHs.
      Limited data suggest that NH Alzheimer's special care units (ASCUs) improve care and resident outcomes,
      • Joyce N.R.
      • McGuire T.G.
      • Bartels S.J.
      • et al.
      The impact of dementia special care units on quality of care: An instrumental variables analysis.
      • Mitchell S.L.
      • Teno J.M.
      • Intrator O.
      • et al.
      Decisions to forgo hospitalization in advanced dementia: A nationwide study.
      • Orth J.
      • Li Y.
      • Simning A.
      • et al.
      End-of-life care among nursing home residents with dementia varies by nursing home and market characteristics.
      but evidence is mixed.
      • Lai C.K.
      • Yeung J.H.
      • Mok V.
      • Chi I.
      Special care units for dementia individuals with behavioural problems.
      ,
      • Gruneir A.
      • Lapane K.L.
      • Miller S.C.
      • Mor V.
      Does the presence of a dementia special care unit improve nursing home quality?.
      Unfortunately, information describing general characteristics of ASCUs as well as structures, processes, and mechanisms of action potentially contributing to beneficial outcomes is lacking. Furthermore, no standard definition of NH ASCUs exists
      • Lai C.K.
      • Yeung J.H.
      • Mok V.
      • Chi I.
      Special care units for dementia individuals with behavioural problems.
      ,
      • Blackburn J.
      • Zheng Q.
      • Grabowski D.C.
      • et al.
      Nursing home chain affiliation and its impact on specialty service designation for Alzheimer disease.
      and reasons why NHs establish ASCUs are unclear; they may be established as an attempt to address resident needs or to increase marketability—or perhaps combinations of both.
      • Joyce N.R.
      • McGuire T.G.
      • Bartels S.J.
      • et al.
      The impact of dementia special care units on quality of care: An instrumental variables analysis.
      ,
      • Gruneir A.
      • Lapane K.L.
      • Miller S.C.
      • Mor V.
      Long-term care market competition and nursing home dementia special care units.
      ,
      • Castle N.G.
      Special care units and their influence on nursing home occupancy characteristics.
      Key limitations in prior studies of NH ASCUs include small samples and failure to meaningfully incorporate geography and neighborhood resources (factors known to impact health and health care utilization).
      • Hu J.
      • Kind A.J.H.
      • Nerenz D.
      Area Deprivation Index predicts readmission risk at an urban teaching hospital.
      • Jung D.
      • Kind A.
      • Robert S.
      • et al.
      Linking neighborhood context and health in community-dwelling older adults in the Medicare Advantage program.
      • Joynt Maddox K.E.
      • Reidhead M.
      • Hu J.
      • et al.
      Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program.
      • Kind A.J.
      • Jencks S.
      • Brock J.
      • et al.
      Neighborhood socioeconomic disadvantage and 30-day rehospitalization: A retrospective cohort study.
      • Kind A.J.H.
      • Buckingham W.R.
      Making neighborhood-disadvantage metrics accessible - The neighborhood atlas.
      • Zuelsdorff M.
      • Larson J.L.
      • Hunt J.F.V.
      • et al.
      The Area Deprivation Index: A novel tool for harmonizable risk assessment in Alzheimer's disease research.
      • Wennberg J.
      • Gittelsohn
      Small area variations in health care delivery.
      NH priorities may differ depending on patient populations, local competition, and neighborhood characteristics. Understanding associations between location, neighborhood resources, and NH ASCUs may provide critical and innovative insights, bringing clarity to currently unknown features of NH care that influence care for residents with ADRD.
      To fill these knowledge gaps, our objectives were 2-fold: (1) examine locations of NHs with ASCUs across the United States, providing first-ever geographic analyses of availability at the national level and (2) assess whether neighborhood resources, region, and levels of rurality are associated with NH ASCUs.

      Methods

       Data Sources and Sample

      We used 2017 LTCfocus
      • Long-term care
      Facts on care in the US. Shaping Long Term Care in America Project at Brown University funded in part by the National Institute on Aging (1P01AG027296).
      and Centers for Medicare & Medicaid Services’ Nursing Home Compare
      • Centers for Medicare and Medicaid Services
      Nursing Home Compare data archive: 2017 data.
      data sets to identify free-standing Medicare- and/or Medicaid-certified NHs and obtain addresses among NHs in the contiguous United States. The LTCfocus data set contains NH characteristics from NH-reported OSCAR/CASPER administrative data, including ASCU presence; the Nursing Home Compare data set contains additional NH characteristics obtained through federally mandated reports and inspections. NH Zip+4 codes were linked with the Area Deprivation Index (ADI).
      • Kind A.J.H.
      • Buckingham W.R.
      Making neighborhood-disadvantage metrics accessible - The neighborhood atlas.
      The most recently available ADI (using 2015 US Census data) includes 17 measures of neighborhood socioeconomic deprivation from 4 domains: education, employment, housing, and poverty; details of its construction are available elsewhere.
      • Kind A.J.
      • Jencks S.
      • Brock J.
      • et al.
      Neighborhood socioeconomic disadvantage and 30-day rehospitalization: A retrospective cohort study.
      We adopted 9 census-defined regions of the United States
      • National Centers for Environmental Information
      US Census divisions.
      and used Rural Urban Continuum (RUC) codes
      • US Department of Agriculture Economic Research Service
      Rural-urban continuum codes.
      to categorize county rurality.
      Of 14,368 NHs matched between LTCfocus and Nursing Home Compare data sets, 155 NHs could not be merged with ADIs (eg, invalid postal address) and 420 did not have ADI values (eg, suppressed data). We excluded 586 hospital-based NHs because their care structures and processes are fundamentally different from free-standing NHs. The resulting study sample included 13,207 NHs.
      This study protocol was approved by University of Maryland's institutional review board.

       Outcome

      We used a binary indicator for whether NHs have beds designated for residents with ADRD as our outcome variable. NHs reporting any beds for ADRD residents are considered as having ASCUs.

       Key Covariates

      Key covariates assessed NH location at 3 levels: census regions, county, and neighborhoods/census tracts. The census regions group states into 9 categories: East North Central (reference), East South Central, Middle Atlantic, Mountain, New England, Pacific, South Atlantic, West North Central, and West South Central. RUC codes group counties into levels of increasing rurality: (1) counties in metro areas of 1 million population or more (reference); (2) counties in metro areas of 250,000 to 1 million population; (3) counties in metro areas of less than 250,000 population; (4) urban population of 20,000 or more, adjacent to metro area; (5) urban population of 20,000 or more, not adjacent to metro area; (6) urban population of 2500 to 19,999, adjacent to metro area; (7) urban population of 2500 to 19,999, not adjacent to metro area; (8) completely rural or less than 2500 urban population, adjacent to metro area; and (9) completely rural or less than 2500 urban population, not adjacent to metro area.
      We included the ADI as a continuous measure: neighborhood scores of socioeconomic deprivation were ranked from lowest to highest within states and divided into deciles (ie, 1 = least disadvantaged, 10 = most disadvantaged neighborhood).

       Other Covariates

      We included common NH-level covariates previously associated with NH performance and care patterns among residents with ADRD.
      • Li Q.
      • Zheng N.T.
      • Temkin-Greener H.
      Quality of end-of-life care of long-term nursing home residents with and without dementia.
      ,
      • Joyce N.R.
      • McGuire T.G.
      • Bartels S.J.
      • et al.
      The impact of dementia special care units on quality of care: An instrumental variables analysis.
      ,
      • Orth J.
      • Li Y.
      • Simning A.
      • et al.
      End-of-life care among nursing home residents with dementia varies by nursing home and market characteristics.
      ,
      • Gruneir A.
      • Lapane K.L.
      • Miller S.C.
      • Mor V.
      Does the presence of a dementia special care unit improve nursing home quality?.
      • Blackburn J.
      • Zheng Q.
      • Grabowski D.C.
      • et al.
      Nursing home chain affiliation and its impact on specialty service designation for Alzheimer disease.
      • Gruneir A.
      • Lapane K.L.
      • Miller S.C.
      • Mor V.
      Long-term care market competition and nursing home dementia special care units.
      • Castle N.G.
      Special care units and their influence on nursing home occupancy characteristics.
      Covariates included ownership (for-profit vs. government owned/nonprofit); chain affiliation (yes/no); number of beds; occupancy; RN hours per resident day (HPRD); total nurse staffing HPRD, % Medicare, Medicaid, female, and white residents; resident age; case-mix acuity (measuring level of NH care need required for given resident populations); and county NH bed competition (Herfindahl-Hirschman Index; score from 0 to 1, with higher values indicating greater competition).

       Statistical Analyses

      We first examined geographic variation in locations of NH ASCUs across the United States through mapping. We then compared descriptive statistics across NHs with or without ASCUs and examined bivariate associations using χ2 and t tests appropriate to respective measures. Finally, we estimated binary logistic regression models for presence of NH ASCUs, adjusting for NH characteristics. Analyses were performed using R, version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Alpha thresholds determining statistical significance were .05 for all analyses.

      Results

      Nearly 15% of NHs had ASCUs in 2017. Within states, Indiana had the highest ASCU prevalence (35.0%) and Tennessee the lowest (1.9%) (Figure 1A). NHs with ASCUs were more prevalent in North Central and Middle Atlantic regions; NH ASCUs varied across the United States from 0.2% (Idaho, Mississippi) to 8.6% (Indiana) (Figure 1B).
      Figure thumbnail gr1
      Fig. 1Geographic distribution of nursing home Alzheimer's special care units (ASCUs). Panel A: % nursing home ASCUs by state (N = 13,207 nursing homes). Panel B: % nursing home ASCUs across the United States (N = 1934 nursing homes). Nursing homes in Alaska, Hawaii, and the District of Columbia were excluded because they could not be matched between LTCfocus and Nursing Home Compare data sets.
      Multiple NH characteristics were associated with the presence of ASCUs (Table 1). ASCUs were more prevalent in NHs that were nonprofit and had more beds, higher occupancy, fewer RN HPRD, fewer Medicare residents, and more female, white, older, and higher-need residents. NHs located in East North Central, Middle Atlantic, Mountain, New England, and West North Central regions were more likely to have ASCUs. Regarding rurality, the most densely populated urban areas and the most rural areas were least likely to have NHs with ASCUs. There was no statistically significant difference in presence of NH ASCUs regarding ADI.
      Table 1Sample Characteristics: Nursing Homes With and Without Alzheimer's Special Care Units
      Sample CharacteristicsASCU (n = 1934; 14.6%)No ASCU (n = 11,273; 85.4%)P Value (χ2 or t Test)
      For-profit, %57.375.7<.001
      Chain affiliation, %58.860.0.35
      Number of beds131.8 ± 62.3104.1 ± 52.3<.001
      Occupancy81.6 ± 13.780.4 ± 14.7<.001
      RN hours per resident day0.7 ± 0.30.8 ± 0.4<.001
      Total nurse staffing hours per resident-day4.1 ± 0.84.1 ± 0.9.85
      % Medicare10.3 ± 7.814.2 ± 12.9<.001
      % Medicaid60.9 ± 20.060.1 ± 23.1.10
      % female67.7 ± 11.465.8 ± 11.9<.001
      % white85.1 ± 18.079.0 ± 22.3<.001
      Average resident age80.8 ± 5.479.0 ± 7.2<.001
      Case-mix acuity12.0 ± 1.012.2 ± 1.4<.001
      County nursing home bed competition (Herfindahl-Hirschman Index)
      Scores from 0 to 1, with higher values indicating greater competition.
      0.8 ± 0.20.8 ± 0.2.30
      State Area Deprivation Index5.8 ± 2.75.8 ± 2.7.42
      Region, %<.001
       East North Central27.319.2
       East South Central4.46.9
       Middle Atlantic12.010.3
       Mountain6.74.5
       New England8.36.1
       Pacific3.811.8
       South Atlantic8.316.0
       West North Central21.111.4
       West South Central8.214.0
      RUC code
      Rural-Urban Continuum code: (1) counties in metro areas of 1 million population or more (reference); (2) counties in metro areas of 250,000 to 1 million population; (3) counties in metro areas of less than 250,000 population; (4) urban population of 20,000 or more, adjacent to a metro area; (5) urban population of 20,000 or more, not adjacent to a metro area; (6) urban population of 2500 to 19,999, adjacent to a metro area; (7) urban population of 2500 to 19,999, not adjacent to a metro area; (8) completely rural or less than 2500 urban population, adjacent to a metro area; and (9) completely rural or less than 2500 urban population, not adjacent to a metro area.
      , %
      <.001
       135.042.4
       220.919.9
       312.59.8
       47.46.0
       52.12.2
       611.08.8
       76.65.3
       81.11.6
       91.02.5
      Unless otherwise noted, values are mean ± standard deviation.
      Scores from 0 to 1, with higher values indicating greater competition.
      Rural-Urban Continuum code: (1) counties in metro areas of 1 million population or more (reference); (2) counties in metro areas of 250,000 to 1 million population; (3) counties in metro areas of less than 250,000 population; (4) urban population of 20,000 or more, adjacent to a metro area; (5) urban population of 20,000 or more, not adjacent to a metro area; (6) urban population of 2500 to 19,999, adjacent to a metro area; (7) urban population of 2500 to 19,999, not adjacent to a metro area; (8) completely rural or less than 2500 urban population, adjacent to a metro area; and (9) completely rural or less than 2500 urban population, not adjacent to a metro area.
      The adjusted logistic regression model was overall significant (P < .001); the c statistic of 0.77 indicates a good model fit. After controlling for NH covariates, for-profit NHs had 42% lower odds of ASCUs; chain-affiliated NHs had 34% higher odds of ASCUs (P < .001) (Table 2). NHs with higher total staffing hours had 29% higher odds of ASCUs, whereas NHs with more RN staffing hours had 46% lower odds of ASCUs (P < .001). NHs with higher percentages of white and older residents were 1% to 5% more likely to have ASCUs (P < .001). NHs located in the Pacific, Middle Atlantic, and Southern regions had 58% to 69% lower odds of ASCUs (P < .001) compared with NHs in the East North Central region. Compared with NHs in the most metropolitan areas, NHs in or near metropolitan counties with fewer than 1 million population had 25% to 47% higher odds of ASCUs (P < .01); NHs in counties with urban population of 2500 to 19,999 adjacent to metro areas had 44% higher odds of ASCUs (P = .002). In the most rural areas, odds of NH ASCUs decreased 63% (P < .001). ADI was not statistically significantly associated with presence of NH ASCUs.
      Table 2Logistic Regression Results for Presence of Nursing Home Alzheimer's Special Care Units
      Odds Ratio (95% Confidence Interval)P Value
      Key covariates
       State Area Deprivation Index1.00 (0.98, 1.02).85
       Region (ref = East North Central):
      East South Central0.42 (0.32, 0.55)<.001
      Middle Atlantic0.42 (0.34, 0.52)<.001
      Mountain1.37 (1.07, 1.74).011
      New England0.81 (0.65, 1.01).06
      Pacific0.31 (0.23, 0.41)<.001
      South Atlantic0.31 (0.24, 0.38)<.001
      West North Central1.31 (1.10, 1.56).003
      West South Central0.40 (0.32, 0.50)<.001
       RUC code (ref = 1)
      Rural-Urban Continuum code: (1) counties in metro areas of 1 million population or more (reference); (2) counties in metro areas of 250,000 to 1 million population; (3) counties in metro areas of less than 250,000 population; (4) urban population of 20,000 or more, adjacent to a metro area; (5) urban population of 20,000 or more, not adjacent to a metro area; (6) urban population of 2500 to 19,999, adjacent to a metro area; (7) urban population of 2500 to 19,999, not adjacent to a metro area; (8) completely rural or less than 2500 urban population, adjacent to a metro area; and (9) completely rural or less than 2500 urban population, not adjacent to a metro area.
      21.25 (1.07, 1.45).004
      31.47 (1.22, 1.78)<.001
      41.39 (1.10, 1.74).005
      51.05 (0.71, 1.52).80
      61.44 (1.15, 1.81).002
      71.23 (0.94, 1.61).14
      80.65 (0.38, 1.09).113
      90.37 (0.21, 0.61)<.001
      Nursing home–level covariates
       For-profit0.58 (0.52, 0.66)<.001
       Chain affiliation1.34 (1.19, 1.51)<.001
       Number of beds1.01 (1.01, 1.01)<.001
       Occupancy1.01 (1.01, 1.02)<.001
       RN hours per resident day0.54 (0.43, 0.68)<.001
       Total nurse staffing hours per resident day1.29 (1.19, 1.40)<.001
       % Medicare0.97 (0.96, 0.97)<.001
       % Medicaid1.00 (1.00, 1.01).09
       % female1.00 (0.99, 1.00).34
       % white1.01 (1.01, 1.01)<.001
       Average resident age1.05 (1.03, 1.06)<.001
       Case mix acuity0.99 (0.94, 1.04).64
       County nursing home bed competition (Herfindahl-Hirschman Index)
      Scores from 0 to 1, with higher values indicating greater competition.
      0.81 (0.58, 1.12).20
       Observations12,343
      c statistic0.77
      χ302<.001
      Rural-Urban Continuum code: (1) counties in metro areas of 1 million population or more (reference); (2) counties in metro areas of 250,000 to 1 million population; (3) counties in metro areas of less than 250,000 population; (4) urban population of 20,000 or more, adjacent to a metro area; (5) urban population of 20,000 or more, not adjacent to a metro area; (6) urban population of 2500 to 19,999, adjacent to a metro area; (7) urban population of 2500 to 19,999, not adjacent to a metro area; (8) completely rural or less than 2500 urban population, adjacent to a metro area; and (9) completely rural or less than 2500 urban population, not adjacent to a metro area.
      Scores from 0 to 1, with higher values indicating greater competition.

      Discussion

      This is a first national study of geographic distributions of NH ASCUs and their characteristics. Despite increasing prevalence of ADRD in the Western and Southern areas of the United States,
      2020 Alzheimer's disease facts and figures.
      NHs with ASCUs are predominately located in North Central and Middle Atlantic regions. NH ASCUs may depend more on geographic region and NH characteristics than local neighborhood resources.
      Regional variations in provider practices have been recognized since the 1970s.
      • Wennberg J.
      • Gittelsohn
      Small area variations in health care delivery.
      Recently, studies are including neighborhood-level resources in examinations of health care utilization using the ADI. Researchers determined that ADI is associated with cognitive function,
      • Zuelsdorff M.
      • Larson J.L.
      • Hunt J.F.V.
      • et al.
      The Area Deprivation Index: A novel tool for harmonizable risk assessment in Alzheimer's disease research.
      30-day rehospitalizations,
      • Hu J.
      • Kind A.J.H.
      • Nerenz D.
      Area Deprivation Index predicts readmission risk at an urban teaching hospital.
      ,
      • Kind A.J.
      • Jencks S.
      • Brock J.
      • et al.
      Neighborhood socioeconomic disadvantage and 30-day rehospitalization: A retrospective cohort study.
      and multiple chronic conditions,
      • Jung D.
      • Kind A.
      • Robert S.
      • et al.
      Linking neighborhood context and health in community-dwelling older adults in the Medicare Advantage program.
      among others. Our study uses the ADI in a first-ever approach, examining neighborhood deprivation and its relation to specialized NH dementia care. Although we did not find statistically significant associations, there are several potential explanations.
      Related to regional practices, NHs appear responsive to local NH competition
      • Gruneir A.
      • Lapane K.L.
      • Miller S.C.
      • Mor V.
      Long-term care market competition and nursing home dementia special care units.
      ; therefore, if ASCUs are not in local markets, NHs may be less motivated to make additional investments. However, county NH bed competition was not statistically significant in our model. Prior studies identify rural-urban differences in care patterns and preferences among dying NH residents with ADRD, supporting our finding of regional variation of ASCUs: more intensive medical measures were less likely preferred and delivered to rural residents.
      • Gessert C.E.
      • Elliott B.A.
      • Peden-McAlpine C.
      Family decision-making for nursing home residents with dementia: rural-urban differences.
      ,
      • Gessert C.E.
      • Haller I.V.
      • Kane R.L.
      • Degenholtz H.
      Rural-urban differences in medical care for nursing home residents with severe dementia at the end of life.
      Further exploration is needed to understand whether geographic variations in NH resources (eg, RN workforce, staff training in dementia care) are associated with resident outcomes. Presence or absence of NH ASCUs does not necessarily indicate the quality of care received by residents with ADRD. Perhaps some NHs are investing more in formal dementia care staff training or following other best practice recommendations
      • Gilster S.D.
      • Boltz M.
      • Dalessandro J.L.
      Long-term care workforce issues: Practice principles for quality dementia care.
      ; others may be investing in culture change practices promoting resident-centered care.
      • Chisholm L.
      • Zhang N.J.
      • Hyer K.
      • et al.
      Culture change in nursing homes: What is the role of nursing home resources?.
      ,
      • Grabowski D.C.
      • Elliot A.
      • Leitzell B.
      • et al.
      Who are the innovators? Nursing homes implementing culture change.
      Although heavily regulated in other areas, there are currently no federal regulations of NH ASCUs. However, assisted living facilities have similar special care units for residents living with ADRD (22%)
      • Carder P.C.
      State regulatory approaches for dementia care in residential care and assisted living.
      that are state regulated. State variations in frequency and stringency of regulations
      • Carder P.C.
      State regulatory approaches for dementia care in residential care and assisted living.
      ,
      • Temkin-Greener H.
      • Mao Y.
      • Ladwig S.
      • et al.
      Variability and potential determinants of assisted living state regulatory stringency.
      impact end-of-life care trajectories among assisted living facility residents.
      • Thomas K.S.
      • Belanger E.
      • Zhang W.
      • Carder P.
      State variability in assisted living residents' end-of-life care trajectories.
      State-level regulation may influence NHs’ willingness to establish ASCUs; therefore, geographically tailored interventions to address uptake of ASCUs may be needed.
      We found NHs that were nonprofit, chain-affiliated, and had higher total staffing hours were more likely to have ASCUs; surprisingly, more RN staffing hours was associated with lower odds of ASCUs. Perhaps ASCUs reduce RN workload burden or RNs are better equipped to care for residents with ADRD without formal ASCUs. Regarding ownership and chain affiliation, our findings suggest motivations for ASCUs may not be profit oriented and may be more need focused. Additionally, we identified potential disparities in access to NH ASCUs: NHs with more white and older residents were more likely to have ASCUs, whereas NHs with more Medicare residents were less likely to have ASCUs. These highlight potential influences of financial resources in implementing ASCUs: specialty dementia care may be more necessary for residents in later stages of the disease when they are more likely long-stay residents and not receiving Medicare-funded skilled nursing facility care.
      We note several limitations. First, our outcome variable does not indicate scope of “units,” only whether ADRD beds are designated. However, that NHs report specialized beds for residents with ADRD suggests attention to resident-centered care. Second, we were unable to incorporate the extent other long-term care options for dementia care (eg, assisted living facilities, home and community-based services) contribute to NHs’ intent for designating ASCUs. Nevertheless, we included local competition for NH beds to offset this concern. Regarding the ADI, our study is limited by shortcomings of Census data, including potential underrepresentation of population groups most in need of NH care.
      • Kind A.J.H.
      • Buckingham W.R.
      Making neighborhood-disadvantage metrics accessible - The neighborhood atlas.

      Conclusions and Implications

      Our findings demonstrate presence of NH ASCUs varies by region, rurality, and NH features including workforce characteristics more so than neighborhood resources. As debates over the value of NH ASCUs continue, our study appears to support notions that ASCUs have been established to address resident needs rather than NH marketability. We demonstrated the feasibility of using the ADI in health services research among long-term care settings and potential for meaningful contributions to policy and intervention development. Future research is needed to examine NH quality and presence of ASCUs through a geographic lens and identify associations with resident outcomes.

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