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Classifying Dementia Diagnoses in the Baltimore Experience Corps Trial Using Medicare and Maryland’s Health Data
Vishaldeep Sekhon, Qian‐Li Xue, Kyle Moored, Halima Amjad, Emily Richards, Eric P. Slade, George Rebok, Michelle C. Carlson. Innovation in Aging, 2025-12-01
Topic: Risk, prevention and care in population studies
Abstract Centers for Medicare and Medicaid Services (CMS) administrative data are among the most practical sources for understanding the incidence of dementia over time in older populations, but have yet to be widely used in intervention studies. Through the National Institute of Aging’s LINKAGE program, the Baltimore Experience Corps Trial (2006-2022) is one of the first intervention studies to leverage Maryland’s state-level Health Information Exchange (HIE) (2013-2022) data, along with CMS administrative data (2008-2022) to sensitively capture participants’ healthcare utilization. After evaluating multiple established dementia classification algorithms, we used the Bynum evaluation and management (Bynum-EM) algorithm to identify dementia using International Classification of Diseases (ICD-9,10) codes from CMS Fee-for-Service, Medicare Advantage, and HIE data. We further adjudicated dementia diagnosis by its subtypes (Alzheimer’s, mixed/vascular) and incorporated dementia-free mortality. Of 702 participants, 520 were successfully linked with CMS/HIE administrative data. These linked participants were predominantly female (84%), Black (95%), with an average age of 68±6 years and an average of two comorbidities. Over the 14-year follow-up, 26% (n = 135) of the BECT cohort developed dementia, with 8% (n = 32) of them diagnosed with vascular or mixed dementia. About 44% (n = 230) of participants died over time, with 27% having dementia-free mortality. Our study demonstrated the value of both CMS Medicare and state-level HIE data in classifying incident dementia and its subtypes among older adults, providing a useful approach to evaluating long-term intervention effects on dementia risk without requiring in-person follow-up.
Key findings
- Our study demonstrated the value of both CMS Medicare and state-level HIE data in classifying incident dementia and its subtypes among older adults, providing a useful approach to evaluating long-term intervention effects on dementia risk without requiring in-person follow-up.
Why it matters
Using CMS and Maryland health information exchange data, 26% of 520 linked trial participants developed dementia over 14 years, showing that administrative data can classify incident dementia and its subtypes without in-person follow-up. This is a methods finding about tracking dementia in intervention studies, not a treatment, cure or prevention result.
Study details
- Participants135
- Evidence strengthModerate
How this study scored 37/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Innovation in Aging) |
| Journal's citation record | 0 / 4 | Innovation in Aging: journal h-index 48 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 2 / 4 | 135 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 0 / 7 | Cited 0 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 0 / 6 | Cited 0.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 0 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Michelle C. Carlson: h-index 59 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Johns Hopkins University: institution h-index 2,306 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Total | 37 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 8 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Sekhon, V., Xue, Q., Moored, K., Amjad, H., Richards, E., Slade, E. P., et al. (2025). Classifying Dementia Diagnoses in the Baltimore Experience Corps Trial Using Medicare and Maryland’s Health Data. Innovation in Aging. https://doi.org/10.1093/geroni/igaf122.3560
Vancouver
Sekhon V, Xue Q, Moored K, Amjad H, Richards E, Slade EP, et al. Classifying Dementia Diagnoses in the Baltimore Experience Corps Trial Using Medicare and Maryland’s Health Data. Innovation in Aging. 2025. doi:10.1093/geroni/igaf122.3560.
BibTeX
@article{sekhon2025-e26227ab,
author = {Sekhon, Vishaldeep and Xue, Qian‐Li and Moored, Kyle and Amjad, Halima and Richards, Emily and Slade, Eric P. and Rebok, George and Carlson, Michelle C.},
title = {{Classifying Dementia Diagnoses in the Baltimore Experience Corps Trial Using Medicare and Maryland’s Health Data}},
journal = {Innovation in Aging},
year = {2025},
doi = {10.1093/geroni/igaf122.3560},
url = {https://doi.org/10.1093/geroni/igaf122.3560}
}