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The Proactive Patient: Long-Term Care Insurance Discrimination Risks of Alzheimer's Disease Biomarkers

Overview of attention for article published in The Journal of Law, Medicine & Ethics, January 2021
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Title
The Proactive Patient: Long-Term Care Insurance Discrimination Risks of Alzheimer's Disease Biomarkers
Published in
The Journal of Law, Medicine & Ethics, January 2021
DOI 10.1177/1073110518782955
Pubmed ID
Authors

Jalayne J Arias, Ana M Tyler, Benjamin J Oster, Jason Karlawish

Abstract

Previously diagnosed by symptoms alone, Alzheimer's disease is now also defined by measures of amyloid and tau, referred to as "biomarkers." Biomarkers are detectible up to twenty years before symptoms present and open the door to predicting the risk of Alzheimer's disease. While these biomarkers provide information that can help individuals and families plan for long-term care services and supports, insurers could also use this information to discriminate against those who are more likely to need such services. In this article, we evaluate whether state laws prohibit long-term care insurers from making discriminatory or unfair underwriting and coverage decisions based Alzheimer's disease biomarkers status. We report data demonstrating that current state laws do not provide meaningful protections from discrimination by long-term care insurers based on biomarker information.

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X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 23%
Other 3 14%
Student > Doctoral Student 2 9%
Student > Bachelor 2 9%
Student > Ph. D. Student 1 5%
Other 2 9%
Unknown 7 32%
Readers by discipline Count As %
Medicine and Dentistry 5 23%
Nursing and Health Professions 2 9%
Economics, Econometrics and Finance 2 9%
Psychology 2 9%
Neuroscience 2 9%
Other 2 9%
Unknown 7 32%