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Quantifying diagnostic signal decay in dementia: a national study of Medicare hospitalization data
F. Spoto, Jiazi Tian, Jonas Hügel, Daniel T. Ortega, Christine S. Ritchie, Deborah Blacker, Francesca Dominici, Chirag J. Patel et al.. Alzheimer s & Dementia, 2025-11-01
Topic: Risk, prevention and care in population studies
Non-specific codes were most common. Alzheimer's and vascular dementia codes showed high regional variability. Frequent transitions from specific to non-specific codes indicated diagnostic signal decay. Counties with more rural, Medicaid-eligible, and Black or Hispanic patients had lower alignment with national patterns. Dementia documentation varies widely and systematically across the United States. Much of this reflects inconsistent diagnostic practices, not true disease differences. Signal decay introduces bias into claims-based research and AI. Linking claims to validated cohorts may improve data quality and model fairness. HIGHLIGHTS: Non-specific dementia codes dominate Medicare hospitalization data. Temporal analysis shows diagnostic signal decay over time. Geographic variation is linked to rurality and racial demographics. Signal decay poses bias risks for AI and claims-based research. Model explains 38% of variation in diagnostic pattern similarity.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Spoto, F., Tian, J., Hügel, J., Ortega, D. T., Ritchie, C. S., Blacker, D., et al. (2025). Quantifying diagnostic signal decay in dementia: a national study of Medicare hospitalization data. Alzheimer s & Dementia. https://doi.org/10.1002/alz.70945
Vancouver
Spoto F, Tian J, Hügel J, Ortega DT, Ritchie CS, Blacker D, et al. Quantifying diagnostic signal decay in dementia: a national study of Medicare hospitalization data. Alzheimer s & Dementia. 2025. doi:10.1002/alz.70945. PMID: 41292499.
BibTeX
@article{spoto2025-41292499,
author = {Spoto, F. and Tian, Jiazi and Hügel, Jonas and Ortega, Daniel T. and Ritchie, Christine S. and Blacker, Deborah and Dominici, Francesca and Patel, Chirag J. and others},
title = {{Quantifying diagnostic signal decay in dementia: a national study of Medicare hospitalization data}},
journal = {Alzheimer s \& Dementia},
year = {2025},
doi = {10.1002/alz.70945},
pmid = {41292499},
url = {https://doi.org/10.1002/alz.70945}
}
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Key findings
- Alzheimer's and vascular dementia codes showed high regional variability.
- Frequent transitions from specific to non-specific codes indicated diagnostic signal decay.
- Counties with more rural, Medicaid-eligible, and Black or Hispanic patients had lower alignment with national patterns.
- Dementia documentation varies widely and systematically across the United States.
- Much of this reflects inconsistent diagnostic practices, not true disease differences.
Why it matters
This study of Medicare hospitalization data found that non-specific dementia codes were most common and that documentation often shifted from specific to non-specific codes over time, a pattern the authors call diagnostic signal decay. The authors say much of this variation reflects inconsistent diagnostic practices rather than true disease differences, so it has implications for research data quality, not for treating, curing, or preventing dementia.
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Study details
- Study designcohort study
- Participants2,016
- Evidence strengthModerate
How this study scored 59/100
Published in a peer-reviewed journal, and it is a cohort study following people over time. Scored zero for effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Alzheimer s & Dementia) |
| Journal's citation record | 2 / 4 | Alzheimer s & Dementia: journal h-index 228 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A cohort study following people over time |
| 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 | 3 / 4 | 2,016 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 | 2 / 7 | Cited 7 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 2.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 5.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 3 other studies in this library |
| Still being cited | 1 / 4 | Cited 7 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Hossein Estiri: h-index 27 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | Harvard University: institution h-index 3,235 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41292499) |
| Free to read | 2 / 2 | Free to read |
| Total | 59 / 100 | — |
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Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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