Detecting Mild Cognitive Impairment Using Follow-Up Call Speech and Electronic Health Record Data in Home Health Care Settings
Speech collected from routine follow-up calls, when combined with structured clinical data, can enhance early detection of MCI in home health care. This multimodal, low-burden approach leverages existing care coordination workflows and holds promise for scalable cognitive screening in diverse, aging populations.
Authors
- James M. Noble (ORCID: https://orcid.org/0000-0003-0648-6702)
- Sasha Vergez (ORCID: https://orcid.org/0000-0003-4733-7180)
- Nicole Onorato (ORCID: https://orcid.org/0000-0002-0466-6147)
- Grace Flaherty
- Maryam Zolnoori (ORCID: https://orcid.org/0000-0003-4484-2990)
- Margaret V. McDonald (ORCID: https://orcid.org/0000-0003-1045-0956)
- Ali Zolnour (ORCID: https://orcid.org/0009-0007-0668-5169)
- Yasaman Haghbin
- Sina Rashidi
- Ian Spens
- Felix Vasquez
Institutions
- Columbia University Irving Medical Center (US)
- Alzheimer’s Disease Neuroimaging Initiative (US)
Publication Details
- Journal
- Journal of Gerontological Nursing
- Published
- 2025-12-24
- DOI
- https://doi.org/10.3928/00989134-20251208-03
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00