Curation and validation of electronic medical record-based dementia diagnoses in the VA Million Veteran Program
We found that our MVP-developed ICD-based algorithms had good performance in chart review and generated strong genetic signals, especially after inclusion of medication-identified cases. Ultimately, our MVP-derived algorithms are likely to have good performance in the broader VA, and their performance may also be suitable for use in other large-scale EMR-based biobanks in the absence of definitive biomarkers such as amyloid-PET and cerebrospinal fluid biomarkers.
Authors
- Victoria C. Merritt (ORCID: https://orcid.org/0000-0001-5683-4168)
- Monica T. Ly (ORCID: https://orcid.org/0000-0002-4842-9047)
- Mark W. Logue (ORCID: https://orcid.org/0000-0001-9347-7892)
- Debby W. Tsuang (ORCID: https://orcid.org/0000-0002-4716-1894)
- Richard L. Hauger (ORCID: https://orcid.org/0000-0003-1509-1868)
- David E. Marra (ORCID: https://orcid.org/0000-0002-7392-6555)
- Matthew S. Panizzon (ORCID: https://orcid.org/0000-0002-6449-2097)
- Richard Sherva (ORCID: https://orcid.org/0000-0003-2133-1493)
- Rui Zhang (ORCID: https://orcid.org/0000-0002-8664-6915)
Institutions
- Boston University (US)
- University of Washington (US)
- VA Boston Healthcare System (US)
- University of California San Diego (US)
- VA Puget Sound Health Care System (US)
- VA San Diego Healthcare System (US)
- National Center for PTSD (US)
- Geriatric Research Education and Clinical Center (US)
- Seattle University (US)
Publication Details
- Journal
- Journal of Alzheimer s Disease
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1177/13872877241299130
- Citations
- 4
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 1.54
Funders
- U.S. Department of Veterans Affairs
- Center of Excellence for Stress and Mental Health
- National Institute on Aging