Leveraging Electronic Health Records and artificial IntelligeNce to improve Dementia Screening and early Detection in primary care (LEARN-DSD)
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Project Summary/Abstract: Alzheimer’s Disease and Alzheimer's Disease related dementias (AD/ADRD) are irreversible conditions affecting over 6 million people in the United States. While the pathogenesis of AD/ADRD is complex, modifiable cardiovascular risk factors contribute to its pathogenesis. The problem is compounded by lower rates of cognitive screening and diagnosis. Novel cognitive screening programs that leverage electronic health records (EHRs) and artificial intelligence (AI) have the potential to close this gap considerably. In this context, we propose a multicomponent stakeholder- and technology-based framework to improve early detection of mild cognitive impairment (MCI) and AD/ADRD, to elevate the quality of cognitive screening and secondary prevention within primary care. We will design and implement an embedded Pragmatic Clinical Trial (ePCT) that involves engaging patients, families and primary care providers (PCPs) to refine existing practices on how PCPs should present information on cognitive screening, MCI and AD/ADRD diagnosis, and their linkage with cardiovascular disease. We will leverage an EHR-based clinical decision support tool based on retrospectively validated AI and machine learning (ML) methods for identifying MCI and AD/ADRD. Primary outcome for the ePCT will be the rate of cognitive screening, and secondary outcomes will include diagnosis of dementia, and secondary cardiovascular preventive measures. This ePCT effort will focus at the NYU Langone Family Health Center, a Federally Qualified Health Center, which include over 200 PCPs and over 10,000 patients age ≥65 years, and NYU Langone Ambulatory West Side. Our Specific Aims are to (Aim 1) Conduct a pilot ePCT to optimize and evaluate the acceptability, usability and adoption of implementing an existing AI/ML tool and PCP decision support. (Aim 2) Validate and monitor the ePCT primary outcome of cognitive screening, and secondary outcomes of diagnosis of MCI, AD/ADRD, and cardiovascular disease prevention outcomes. (Aim 3) Perform a sub-analysis for heterogeneity of treatment effects in uptake of screening, diagnosis, secondary cardiovascular preventative interventions. This pilot ePCT will pave the way for larger scale pragmatic trials that will address an unmet and urgent need in cognitive health management of elderly population.
