Automated identification of older adults at risk for cognitive decline
337 older primary care patients completed full neuropsychological assessment.Risk modeling used data available in a typical primary care record.The model successfully differentiated patients with/without cognitive impairment.This EHR model offers a passive workflow to identify patients at cognitive risk.
Authors
- Michael B. Rothberg (ORCID: https://orcid.org/0000-0002-2063-1876)
- Olivia Hogue (ORCID: https://orcid.org/0000-0002-3985-3831)
- Alex Milinovich (ORCID: https://orcid.org/0000-0003-0585-1480)
- Darlene Floden (ORCID: https://orcid.org/0000-0002-3131-0058)
- Robert J. Fox (ORCID: https://orcid.org/0000-0002-4263-3717)
- Saket Saxena (ORCID: https://orcid.org/0000-0003-4084-7954)
- Kamini Krishnan (ORCID: https://orcid.org/0000-0001-6741-2905)
- Elizabeth R. Pfoh (ORCID: https://orcid.org/0000-0003-3485-260X)
- Robyn M. Busch (ORCID: https://orcid.org/0000-0002-5442-4912)
- Michael W. Kattan (ORCID: https://orcid.org/0000-0002-3840-4161)
- Anita D. Misra‐Hebert (ORCID: https://orcid.org/0000-0003-3079-7025)
Institutions
- Cleveland Clinic (US)
- Cleveland Clinic Lerner College of Medicine (US)
Publication Details
- Journal
- Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1002/dad2.70136
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute on Aging