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Identification of cognitively impaired patients at risk for development of Alzheimer’s disease dementia: an analysis of US Medicare claims data
Michele H. Potashman, Benjamin Parcher, Jia Zhou, Qiang Hou, Richard G. Stefanacci. Expert Review of Pharmacoeconomics & Outcomes Research, 2022-02-24
Topic: Risk, prevention and care in population studies
Predictors of an AD dementia diagnosis included age (odds ratio [OR], 1.71) and use of antipsychotics (OR, 2.50) and hypertension medication (OR, 1.25). Medication use for comorbid conditions was a better indicator of risk than comorbidity coding. Diagnosis of CI by a neurologist increased the odds of an AD dementia diagnosis. Possible protective factors for progression included the use of anxiolytics (OR, 0.76), inpatient status at time of diagnosis (OR, 0.49), and a history of stroke (OR, 0.87). None of these factors differentiated AD dementia from all-cause dementia. Identifying patients at risk for AD dementia allows for improved system-level planning to guide policy and optimize economic and clinical outcomes for patients, caregivers, and society.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Potashman, M. H., Parcher, B., Zhou, J., Hou, Q., & Stefanacci, R. G. (2022). Identification of cognitively impaired patients at risk for development of Alzheimer’s disease dementia: an analysis of US Medicare claims data. Expert Review of Pharmacoeconomics & Outcomes Research. https://doi.org/10.1080/14737167.2022.2045956
Vancouver
Potashman MH, Parcher B, Zhou J, Hou Q, Stefanacci RG. Identification of cognitively impaired patients at risk for development of Alzheimer’s disease dementia: an analysis of US Medicare claims data. Expert Review of Pharmacoeconomics & Outcomes Research. 2022. doi:10.1080/14737167.2022.2045956. PMID: 35196953.
BibTeX
@article{potashman2022-35196953,
author = {Potashman, Michele H. and Parcher, Benjamin and Zhou, Jia and Hou, Qiang and Stefanacci, Richard G.},
title = {{Identification of cognitively impaired patients at risk for development of Alzheimer’s disease dementia: an analysis of US Medicare claims data}},
journal = {Expert Review of Pharmacoeconomics \& Outcomes Research},
year = {2022},
doi = {10.1080/14737167.2022.2045956},
pmid = {35196953},
url = {https://doi.org/10.1080/14737167.2022.2045956}
}
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Key findings
- Predictors of an AD dementia diagnosis included age (odds ratio [OR], 1.71) and use of antipsychotics (OR, 2.50) and hypertension medication (OR, 1.25).
- Medication use for comorbid conditions was a better indicator of risk than comorbidity coding.
- Diagnosis of CI by a neurologist increased the odds of an AD dementia diagnosis.
- Possible protective factors for progression included the use of anxiolytics (OR, 0.76), inpatient status at time of diagnosis (OR, 0.49), and a history of stroke (OR, 0.87).
- None of these factors differentiated AD dementia from all-cause dementia.
Why it matters
This study found that older age, use of antipsychotics, and use of hypertension medication predicted an Alzheimer's disease dementia diagnosis, while use of anxiolytics, inpatient status at diagnosis, and a history of stroke were possible protective factors. None of these factors differentiated Alzheimer's disease dementia from all-cause dementia.
Study details
- Evidence strengthLow
How this study scored 32/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Expert Review of Pharmacoeconomics & Outcomes Research) |
| Journal's citation record | 1 / 4 | Expert Review of Pharmacoeconomics & Outcomes Research: journal h-index 80 (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 | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2022 — within 6 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 5 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.8 citations a year over 6 year(s) since 2022 |
| Impact for its field and year | 1 / 6 | Cited 0.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 1 / 4 | Cited 4 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Richard G. Stefanacci: h-index 15 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Thomas Jefferson University: institution h-index 825 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 35196953) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 32 / 100 | — |
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