The DOI matches its Crossref record; 39 of the 41 references it cites were found in a registry or an index.
Assessment of Racial/Ethnic Disparities in Timeliness and Comprehensiveness of Dementia Diagnosis in California
Open accessAbstract
Importance: The US aging population is rapidly becoming more racially and ethnically diverse. Early diagnosis of dementia is a health care priority. Objective: To examine the associations between race/ethnicity and timeliness of dementia diagnosis and comprehensiveness of diagnostic evaluation. Design, Setting, and Participants: This retrospective cross-sectional study used 2013-2015 California Medicare fee-for-service data to examine the associations of race/ethnicity, individual factors, and contextual factors with the timeliness and comprehensiveness of dementia diagnosis. Data from 10 472 unique beneficiaries were analyzed. The sample was selected on the basis of the following criteria: presence of 1 or more claims; no diagnoses of dementia or mild cognitive impairment in 2013 to 2014; continuous enrollment in Medicare Parts A and B; Asian, Black, Hispanic, or White race/ethnicity; and incident diagnoses of dementia or mild cognitive impairment in January through June 2015. Data analyses were conducted from November 1, 2019, through November 10, 2020. Main Outcomes and Measures: Timeliness of diagnosis, defined as incident diagnosis of mild cognitive impairment vs dementia, and comprehensiveness of diagnostic evaluation, defined as presence of the following services in claims within 6 months before or after the incident diagnosis date: specialist evaluation, laboratory testing, and neuroimaging studies. Results: The sample comprised 10 472 unique Medicare beneficiaries with incident diagnoses of dementia or mild cognitive impairment (6504 women [62.1%]; mean [SD] age, 82.9 [8.0] years) and included 993 individuals who identified as Asian (9.5%), 407 as Black (3.9%), 1255 as Hispanic (12.0%), and 7817 as White (74.6%). Compared with White beneficiaries, those who identified as Asian (odds ratio, 0.46; 95% CI, 0.38-0.56), Black (odds ratio, 0.73; 95% CI, 0.56-0.94), or Hispanic (odds ratio, 0.62; 95% CI, 0.52-0.72) were less likely to receive a timely diagnosis. Asian beneficiaries (incidence rate ratio, 0.81; 95% CI, 0.74-0.87) also received fewer diagnostic evaluation elements. These associations remained significant after adjusting for age, sex, comorbidity burden, neighborhood disadvantage, and rurality. Conclusions and Relevance: These findings highlight substantial disparities in the timeliness and comprehensiveness of dementia diagnosis. Public health interventions are needed to achieve equitable care for people living with dementia across all racial/ethnic groups.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“with greater delays among individuals from racial and ethnic minority groups.”
From 2024 Alzheimer's disease facts and figures (2024) · cites this paper as [709]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Comorbidity measures for use with administrative data.
Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998) · Medical Care · doi:10.1097/00005650-199801000-00004 · Cited by 9,921
Making Neighborhood-Disadvantage Metrics Accessible — The Neighborhood Atlas
Kind, A. J. H., & Buckingham, W. R. (2018) · New England Journal of Medicine · doi:10.1056/nejmp1802313 · Cited by 3,310
Self-citation(2015) · HAL · Cited by 2,238
Diagnosis and Management of Dementia: Review
Arvanitakis, Z., Shah, R. C., & Bennett, D. A. (2019) · JAMA · doi:10.1001/jama.2019.4782 · Cited by 1,561
The Diagnosis and Management of Mild Cognitive Impairment: A Clinical Review
Langa, K. M., & Levine, D. A. (2014) · JAMA · doi:10.1001/jama.2014.13806 · Cited by 1,337
Matthews, K. A., Xu, W., Gaglioti, A. H., Holt, J. B., Croft, J. B., Mack, D., & McGuire, L. C. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.06.3063 · Cited by 1,124
Inequalities in dementia incidence between six racial and ethnic groups over 14 years
Mayeda, E. R., Glymour, M. M., Quesenberry, C. P., & Whitmer, R. A. (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.12.007 · Cited by 883
Cordell, C. B., Soo Borson, B., Boustani, M. A., Chodosh, J., Reuben, D. B., Verghese, J., Thies, W. H., Fried, L. B., & Workgroup, M. D. O. C. I. (2012) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2012.09.011 · Cited by 581
Timely Diagnosis for Alzheimer’s Disease: A Literature Review on Benefits and Challenges
Dubois, B., Padovani, A., Scheltens, P., Rossi, A., & Dell’Agnello, G. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150692 · Cited by 565
Cited by
Sorted by citations
2024 Alzheimer's disease facts and figures
(2024) · Alzheimer's & Dementia · doi:10.1002/alz.13809 · Cited by 2,536
2025 Alzheimer's disease facts and figures
(2025) · Alzheimer s & Dementia · doi:10.1002/alz.70235 · Cited by 642
Disparities by Race and Ethnicity Among Adults Recruited for a Preclinical Alzheimer Disease Trial
Raman, R., Quiroz, Y. T., Langford, O., Choi, J., Ritchie, M., Baumgartner, M., Rentz, D. M., Aggarwal, N. T., Aisen, P. S. S., Sperling, R. A., et al. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.14364 · Cited by 172
Antiamyloid Monoclonal Antibody Therapy for Alzheimer Disease
Ramanan, V. K., Armstrong, M. J., Choudhury, P., Coerver, K. A., Hamilton, R. H., Klein, B. C., Wolk, D. A., Wessels, S. R., & Jones, L. K. (2023) · Neurology · doi:10.1212/wnl.0000000000207757 · Cited by 120
Kalaria, R. N., Maestre, G. E., Mahinrad, S., Acosta, D. M., Akinyemi, R., Alladi, S., Allegri, R., Arshad, F., Babalola, D. O., Baiyewu, O., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13836 · Cited by 110
Self-citation
Metadata
- Authors
- Tsoy, E., Kiekhofer, R. E., Guterman, E. L., Tee, B. L., Windon, C. C., Dorsman, K. A., Lanata, S. C., Rabinovici, G. D., Miller, B. L., Kind, A. J. H., & Possin, K. L.
- Affiliations
- University of California, San Francisco (US)
- The University of Texas Southwestern Medical Center (US)
- University of Wisconsin–Madison (US)
- Corresponding author
- Possin, Katherine L.
- ORCID
- Venue
- JAMA Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2021-06-01
- Volume
- 78
- Issue
- 6
- Pages
- 657
- ISSN
- 2168-6149 (ISSN-L)
- PMC
- PMC8008426
- OpenAlex
- W3146388672
- Cited by
- 182
- References
- 41
- Citations by year
- 2026: 38 · 2025: 44 · 2024: 50 · 2023: 25 · 2022: 20 · 2021: 5
- FWCI
- 17.94
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Neurology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute on Aging (R01AG037639, R01AG056715, P01AG019724, P30AG062422, R35AG072362, P30AG062715, R01AG070883, T32AG023481)
- National Institute of Neurological Disorders and Stroke (UH3NS105557)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Health › Health disparities and outcomes
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Keywords
- racial and ethnic disparities, dementia diagnosis, diagnostic timeliness, mild cognitive impairment, Medicare beneficiaries, Asian Americans, African Americans, Hispanic Americans, neuroimaging, laboratory testing, health care access, California, population aging, health equity, health care costs, quality of care
- MeSH terms
- Aged, Aged, 80 and over, California, Cross-Sectional Studies, Dementia, Ethnicity, Female, Medicare, Humans, Male, Retrospective Studies, United States, Fee-for-Service Plans, Racial Groups, Healthcare Disparities, Delayed Diagnosis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
