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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Prevalence and predictors of diagnosed mild cognitive impairment among Medicare beneficiaries
Elyse Couch1, Munachimso Ugoh1, Lauren Thomas1
1Department of Health Services, Policy and Practice Brown University School of Public Health Providence Rhode Island USA.
Introduction:
Mild cognitive impairment (MCI) is a known risk factor for dementia and presents an opportunity for early engagement in preventative strategies, treatment, and advanced planning. However, little is known about MCI diagnosis rates among Medicare beneficiaries.
Methods:
Using data from the 2014 to 2022 rounds of the National Health and Aging Trends Study (NHATS) linked with Medicare claims data, we identified the proportion of beneficiaries with symptoms of MCI, as defined by an NHATS algorithm, who received a diagnosis according to International Classification of Diseases codes. Univariate and multivariate logistic regressions were used to identify predictors of diagnosed MCI.
Results:
Of beneficiaries identified by the NHATS algorithm, 10.6% had a recorded diagnosis of MCI. Odds of diagnosis were higher among women and beneficiaries with a bachelor's degree or higher, and lower among beneficiaries who attended doctor visits alone.
Discussion:
Targeted initiatives are needed to increase MCI diagnosis rates, particularly in the era of novel diagnostic tests and therapies.
Highlights:
We linked National Health and Aging Trends Study data to Medicare claims to identify the prevalence of diagnosed mild cognitive impairment (MCI).We identified 10.6% of Medicare beneficiaries with symptoms of MCI who have a diagnosis.Women and people with a bachelor's degree were more likely to have an MCI diagnosis.People who visited the doctor alone were less likely to have an MCI diagnosis.
Insights
Only 10.6% of Medicare beneficiaries with mild cognitive impairment (MCI) symptoms receive a diagnosis. Women and those with higher education were more likely to be diagnosed, highlighting a need for improved MCI detection rates.
Area of Science:
- Gerontology
- Neurology
- Public Health
Background:
- Mild cognitive impairment (MCI) is a significant risk factor for dementia.
- Early diagnosis of MCI allows for timely intervention and planning.
- MCI diagnosis rates among Medicare beneficiaries remain largely unknown.
Purpose of the Study:
- To determine the prevalence of diagnosed MCI among Medicare beneficiaries.
- To identify factors associated with MCI diagnosis in this population.
Main Methods:
- Utilized data from the National Health and Aging Trends Study (NHATS) linked with Medicare claims (2014-2022).
- Defined MCI using an NHATS algorithm and identified diagnoses via ICD codes.
- Employed logistic regression to analyze predictors of MCI diagnosis.
Main Results:
- 10.6% of Medicare beneficiaries with MCI symptoms had a recorded MCI diagnosis.
- Higher odds of diagnosis were observed in women and those with a bachelor's degree or higher.
- Lower odds of diagnosis were associated with attending doctor visits alone.
Conclusions:
- Current MCI diagnosis rates among Medicare beneficiaries are low.
- Targeted strategies are essential to enhance MCI detection.
- Improved diagnosis is critical given advancements in MCI therapies and diagnostics.
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