Evidence map›Paper›PMID 40758352›Full record

ArticleJAMA network open2025

Medicaid Payments and Racial and Ethnic Disparities in Alzheimer Disease Special Care Units.

Huiwen Xu, Shuang Li, John R Bowblis, Monique R Pappadis, Yong-Fang Kuo, James S Goodwin

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Huiwen XuNell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia.
Shuang LiSealy Center on Aging, University of Texas Medical Branch, Galveston.
John R BowblisDepartment of Economics, Farmer School of Business, Miami University, Oxford, Ohio.
Monique R PappadisSealy Center on Aging, University of Texas Medical Branch, Galveston.
Yong-Fang KuoSealy Center on Aging, University of Texas Medical Branch, Galveston.
James S GoodwinSealy Center on Aging, University of Texas Medical Branch, Galveston.

Funding

UTMB OAIC Research Education Component (REC)P30AG024832 · NIA · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI JAMES S. GOODWIN, MD, MELISSA M. MORROW · 2005 to 2026
$26.7M
The effectiveness and consequences of visitation bans in nursing homesR01AG081282 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI Huiwen Xu · 2023 to 2026
$1.5M
Alzheimer's Special Care Units in Nursing Homes: Racial and Ethnic Disparities, Resident Outcomes, and State PoliciesR01AG087296 · NIA · EMORY UNIVERSITY · PI Huiwen Xu · 2024 to 2026
$1.2M
NIA NIH HHS P30 AG024832NIA NIH HHS R01 AG081282NIA NIH HHS R01 AG087296
6 · The paper itself

Abstract

Importance: Alzheimer disease special care units (ASCUs) are associated with improved outcomes for residents with dementia, yet they are unavailable in most nursing homes. Objectives: To examine racial and ethnic disparities in the availability of ASCUs and whether more generous Medicaid payments are associated with reduced disparities. Design, Setting, and Participants: This cohort study used 2009-2019 Certification and Survey Provider Enhanced Reporting data and resident assessments from Medicare- and Medicaid-certified nursing homes in the US, as well as state Medicaid payment-to-cost ratios for 2019. Statistical analysis was performed from September to December 2024. Exposure: The percentages of Black residents and Hispanic residents in a facility and the state mean nursing homes' ratio of Medicaid payment to estimated Medicaid cost of care. Main Outcomes and Measures: The main outcome was whether a nursing home had an ASCU. Multivariable logistic regression was conducted on ASCUs, and then separate logistic regressions were performed for states with different quartiles of Medicaid payment-to-cost ratios. Results: Most of the 13 229 nursing homes in the study were for profit (9561 [72.3%]) and were part of a chain (7775 [58.8%]). The overall mean (SD) Medicaid payment-to-cost ratio among all states was 0.87 (0.13) (range, 0.58-1.29). Each 1% increase in the percentage of Black residents was associated with a 0.1% decrease in the probability of having an ASCU. Compared with facilities with 0% to 0.8% of Black residents, the odds of having an ASCU were 37% lower in nursing homes with 4.3% to 15.2% Black residents (odds ratio [OR], 0.63; 95% CI, 0.53-0.74), and 45% lower in nursing homes with 15.2% or more of Black residents (OR, 0.55; 95% CI, 0.46-0.65). Compared with facilities with no Hispanic residents, the odds of having an ASCU were 27% lower in those with 3.7% or more of Hispanic residents (OR, 0.73; 95% CI, 0.62-0.86). In states with Medicaid payment-to-cost ratios between 0.58 and 0.81, nursing homes with 15.2% or more of Black residents were 68% less likely to have an ASCU (OR, 0.32; 95% CI, 0.21-0.50). This difference decreased to 45% in states with Medicaid payment-to-cost ratios between 0.82 and 0.94 (OR, 0.55; 95% CI, 0.44-0.69) and almost disappeared in states with Medicaid payment-to-cost ratios greater than 0.94 (OR, 0.86; 95% CI, 0.53-1.40). Higher Medicaid payment-to-cost ratios were not associated with reduced disparities among Hispanic residents. Conclusions and Relevance: This cohort study of nursing homes suggests that racial and ethnic disparities in ASCU availability narrowed in states where Medicaid payment rates cover a greater share of costs. Racial disparities in specialized dementia care may be mitigated and even eliminated by more generous Medicaid payments.

Indexed as

Alzheimer DiseaseEthnicityHealthcare DisparitiesMedicaidNursing HomesAgedAged, 80 and overBlack or African AmericanCohort StudiesFemaleHispanic or LatinoHumansMaleUnited StatesWhite

Identifiers

PMID40758352
PMCPMC12322793

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.