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A Data-Driven Approach to Identifying Patients with AAD

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On November 4, Avalere experts presented “Development of a Claims-Based Algorithm to Identify Patients with Agitation in Alzheimer’s Dementia” at the Gerontological Society of America Annual Scientific Meeting.

Agitation is common in patients with Alzheimer’s disease and dementia, yet until recently the lack of a consensus definition has limited our understanding of the prevalence, patient profile, and added healthcare burden of agitation in Alzheimer’s disease and dementia (AAD). In 2015, the International Psychogeriatric Association (IPA) developed a provisional consensus definition of agitation in cognitive disorders. While the IPA consensus definition allows us to better understand agitation as a discrete syndrome in cognitive disorders, the application of the consensus definition against real-world data has not yet been completed.

The objective of this study was to develop a claims-based algorithm, based on the IPA definition of agitation, to enable identification of patients with AAD compared to patients without agitation. The algorithm was developed and tested using an in-house 100% sample of Medicare fee-for-service administrative claims from 2010 to 2017, accessed through a research-focused data use agreement with the Centers for Medicare & Medicaid Services.  The first step to understanding the AAD population is being able to identify the patients. The new algorithm can be applied to health plan claims data to help providers identify patients with agitation for targeted interventions designed to prevent adverse outcomes and to predict which AD patients are at high risk for agitation for early intervention.

The research found Alzheimer’s disease patients with agitation were more likely to be younger, male, and dual eligible for Medicare and Medicaid (a proxy for low-income status), and they were more likely to be treated with antipsychotics, antidepressants, and dementia medications. The AAD patients were 2 times more likely to be using antipsychotics such as quetiapine and risperidone, which have been shown to be harmful in this population and carry a Food & Drug Administration black-box warning due to high risk of mortality, stroke, and other complications.

Read “Development of a Claims-Based Algorithm to Identify Patients with Agitation in Alzheimer’s Dementia.”

Disclosure: This research was funded by Avanir Pharmaceuticals.

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