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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
System changes to empower primary care in Alzheimer's disease detection and care
Sharon Phares1, Ian Kremer2, J K Wall3
1Tufts Medical Center, Institute for Clinical Research and Health Policy Studies, Center for Biomedical System Design & NEWDIGS, Tufts University School of Medicine, Boston, USA.
Abstract:
Despite advances in disease-modifying treatments, significant barriers in the evaluation and clinical management of people with early Alzheimer's disease (AD) remain. These barriers have been documented in scientific literature and increasingly call for primary care to play a larger role in the detection, diagnosis, treatment, and monitoring of AD. Drawing upon the work of a multistakeholder consortium, this article identifies systemic and structural barriers that hinder primary care professionals in the United States from playing a larger role. We propose solutions to these barriers and call for evolution of the U.S. healthcare system to ensure it is prepared to adapt to the rapidly progressing scientific and societal landscape and meet the growing needs of people affected by the early stages of AD.
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