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Modeling Early Detection and Geographic Variation in Health System Capacity for Alzheimer’s Disease‐Modifying Therapies
Jodi Liu, Lawrence H. Baker, Annie Chen, Jessie J.J. Wang, Federico Girosi. Alzheimer s & Dementia, 2024-12-01
Topic: Amyloid, tau and blood-test diagnosis
Abstract Background The widespread availability of effective disease‐modifying therapies would be a breakthrough in slowing the progression of early Alzheimer’s disease (AD) to later stages of dementia. The purpose of this study is to explore how primary care capacity, variation in patient care‐seeking, and geographic variation in capacity can affect the delivery of AD‐modifying therapies. Method We used a county‐level simulation model to assess patient demand and provider supply for the delivery of AD‐modifying therapies. The model simulates the progression of people aged 50 and older through a clinical pathway and through disease states (normal cognitive, mild cognitive impairment, and Alzheimer’s dementia), and compares patient demand to the health care system capacity for detection, diagnosis, and treatment. We developed an interactive, web‐based tool that allows users to adjust key parameters and explore their effects on results. Result Care models that enable primary care practitioners to diagnose and evaluate patients for treatment eligibility would make the biggest impact on reducing wait times for dementia specialists and increasing the number of people treated from 2025 through 2044. Improved triage of patients using blood‐based biomarker tests in primary care settings could further reduce caseloads for specialists. The estimated wait times and number of patients treated are sensitive to patient uptake of brief cognitive assessments. There is substantial geographic variation in health care system capacity across the US to detect, diagnose, and treat early AD. Estimated average wait times can be three times longer in rural areas compared to urban areas. States with long wait times include Alaska, Arkansas, Idaho, Mississippi, Montana, Nevada, Oklahoma, and Wyoming. Conclusion Widespread delivery of AD‐modifying therapies will require a combination of strategies to communicate the value of detection and treatment to patients, integrate PCPs into the detection and diagnosis pathway, and address capacity disparities across the United States. Further work is needed to evaluate how primary care‐led models of care can widely and effectively evaluate and manage treatment for people with early AD, as well as how technological advancements, such as improved biomarkers and computerized testing, can be integrated into workflows to better serve people living with AD.
Key findings
- We developed an interactive, web‐based tool that allows users to adjust key parameters and explore their effects on results.
- Result Care models that enable primary care practitioners to diagnose and evaluate patients for treatment eligibility would make the biggest impact on reducing wait times for dementia specialists and increasing the number of people treated from 2025 through 2044.
- Estimated average wait times can be three times longer in rural areas compared to urban areas.
Why it matters
This simulation model estimated that letting primary care practitioners diagnose and evaluate patients for Alzheimer's therapies would most reduce wait times for specialists and increase the number treated. It also estimated average wait times could be three times longer in rural than urban areas.
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Study details
- Evidence strengthLow
How this study scored 36/100
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 (Alzheimer s & Dementia) |
| Journal's citation record | 2 / 4 | Alzheimer s & Dementia: journal h-index 228 (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 | 4 / 5 | 2024 — within 3 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 | 1 / 7 | Cited 4 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 4 year(s) since 2024 |
| Impact for its field and year | 2 / 6 | Cited 1.1× 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 | 2 / 4 | Last-listed author Federico Girosi: h-index 48 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | RAND Corporation: institution h-index 492 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Total | 36 / 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).
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. Check the citation against the original before you use it.
APA 7th
Liu, J., Baker, L. H., Chen, A., Wang, J. J., & Girosi, F. (2024). Modeling Early Detection and Geographic Variation in Health System Capacity for Alzheimer’s Disease‐Modifying Therapies. Alzheimer s & Dementia. https://doi.org/10.1002/alz.089739
Vancouver
Liu J, Baker LH, Chen A, Wang JJ, Girosi F. Modeling Early Detection and Geographic Variation in Health System Capacity for Alzheimer’s Disease‐Modifying Therapies. Alzheimer s & Dementia. 2024. doi:10.1002/alz.089739.
BibTeX
@article{liu2024-9ba6d8b3,
author = {Liu, Jodi and Baker, Lawrence H. and Chen, Annie and Wang, Jessie J.J. and Girosi, Federico},
title = {{Modeling Early Detection and Geographic Variation in Health System Capacity for Alzheimer’s Disease‐Modifying Therapies}},
journal = {Alzheimer s \& Dementia},
year = {2024},
doi = {10.1002/alz.089739},
url = {https://doi.org/10.1002/alz.089739}
}
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