Abstract

Introduction:Appropriate and personalized pharmacologic management of behavioral and psychologic symptoms in dementia (BPSD) is among the most complex clinical challenges in dementia care. Use of antipsychotics and mood stabilizers is common but accompanied by risk, including high likelihood of adverse effects that can lead to hospitalization or institutionalization. Information to support decision-making in these scenarios is typically obtained from self-report/caregiver report. This presentation will focus on demonstrating how data obtained through digital phenotyping may augment clinical decision making.Methods:This presentation will include information from 3 completed or ongoing studies. The first looks at radio wave based sensing as a way of passively monitoring behavior and dementia. The second uses wearables to track the impact of psychopharmacologic changes in dementia. The third study focuses on incorporating data from electronic media (e-mail, text messages) impact psychotherapy in early and late lifeResults and Discussion:Preliminary results indicate that passive sensing is able to accurately identify patterns of behavior as well as circumscribed clinical events with a precision that exceeds the current standard of care. Data and insights gained from these three ongoing studies are helping develop best practice models that can impact clinical outcomes.Conclusions:Collectively, the data in this presentation will demonstrate to clinicians a range of approaches towards developing precision care for older adults with dementia and psychiatric diagnosis. These approaches share the common theme of emphasizing the human element in care, while augmenting it with a range of data that provide objective collateral information to guide more precise decision making. The session will also discuss issues that will impact precision care, including the potential for creating inequities, translation to low income settings and countries as well as the matter of data privacy and security.

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