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Validation of Claims Algorithms to Identify Alzheimer's Disease and Related Dementias
McCarthy EP, Chang CH, Tilton N, Kabeto MU, Langa KM, Bynum JPW.. The journals of gerontology. Series A, Biological sciences and medical sciences, 2022-06-01
Topic: Health services, long-term care and technology
Background Using billing data generated through health care delivery to identify individuals with dementia has become important in research. To inform tradeoffs between approaches, we tested the validity of different Medicare claims-based algorithms. Methods We included 5 784 Medicare-enrolled, Health and Retirement Study participants aged older than 65 years in 2012 clinically assessed for cognitive status over multiple waves and determined performance characteristics of different claims-based algorithms. Results Positive predictive value (PPV) of claims ranged from 53.8% to 70.3% and was highest using a revised algorithm and 1 year of observation. The tradeoff of greater PPV was lower sensitivity; sensitivity could be maximized using 3 years of observation. All algorithms had low sensitivity (31.3%-56.8%) and high specificity (92.3%-98.0%). Algorithm test performance varied by participant characteristics, including age and race. Conclusion Revised algorithms for dementia diagnosis using Medicare administrative data have reasonable accuracy for research purposes, but investigators should be cognizant of the tradeoffs in accuracy among the approaches they consider.
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APA 7th
McCarthy, E. P., Chang, C. H., Tilton, N., Kabeto, M. U., Langa, K. M., & Bynum, J. P. W. (2022). Validation of Claims Algorithms to Identify Alzheimer's Disease and Related Dementias. The journals of gerontology. Series A, Biological sciences and medical sciences. https://doi.org/10.1093/gerona/glab373
Vancouver
McCarthy EP, Chang CH, Tilton N, Kabeto MU, Langa KM, Bynum JPW. Validation of Claims Algorithms to Identify Alzheimer's Disease and Related Dementias. The journals of gerontology. Series A, Biological sciences and medical sciences. 2022. doi:10.1093/gerona/glab373. PMID: 34919686.
BibTeX
@article{mccarthy2022-34919686,
author = {McCarthy, E. P. and Chang, C. H. and Tilton, N. and Kabeto, M. U. and Langa, K. M. and Bynum, J. P. W.},
title = {{Validation of Claims Algorithms to Identify Alzheimer's Disease and Related Dementias}},
journal = {The journals of gerontology. Series A, Biological sciences and medical sciences},
year = {2022},
doi = {10.1093/gerona/glab373},
pmid = {34919686},
url = {https://doi.org/10.1093/gerona/glab373}
}
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Key findings
- Results Positive predictive value (PPV) of claims ranged from 53.8% to 70.3% and was highest using a revised algorithm and 1 year of observation.
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Study details
- Effect size53.8% to 70.3%; 31.3%; 56.8%
- Evidence strengthLow
How this study scored 43/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 25 of the 58 points we could judge it on, which is 43 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (The journals of gerontology. Series A, Biological sciences and medical sciences) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| 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 | 2 / 3 | Effect reported as a number, without an interval or test |
| 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 | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 34919686) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 25 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 25 of the 58 points we could judge it on is 43 out of 100. |
| Total | 43 / 100 | — |
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