Using Machine Learning to Find Older Adults with Undiagnosed Dementia
Author Information
Author(s): Barnes Deborah, Benjamin Cynthia, Mannen Delia, Boscardin John
Primary Institution: University of California San Francisco
Hypothesis
Can machine learning methods effectively identify older adults with undiagnosed dementia using Medicare claims data?
Conclusion
Machine learning can accurately identify older adults at risk of undiagnosed dementia using Medicare claims data.
Supporting Evidence
- Approximately half of people living with Alzheimer’s disease and related dementias are undiagnosed.
- On average, 24,410 (2.9%) of Medicare beneficiaries were diagnosed with incident dementia each year.
- Model accuracy for detecting undiagnosed dementia ranged from 0.77 to 0.81.
Takeaway
Researchers used computer programs to look at health records and found ways to spot older people who might have dementia but don't know it.
Methodology
A retrospective cohort study using the 5% Medicare claims sample to identify predictors of undiagnosed dementia.
Limitations
The study is retrospective and may not account for all variables affecting dementia diagnosis.
Participant Demographics
Beneficiaries aged 65 years or older.
Digital Object Identifier (DOI)
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