Leveraging Electronic Health Records for Reducing Dementia Screening Disparities in Diverse Communities

利用电子健康记录减少不同社区的痴呆症筛查差异

• 批准号: 10525774
• 负责人: Abraham Aizer Brody
• 金额: $ 84.3万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-21 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10525774
• 关键词: Address; Adoption; Affect; Alzheimer' s Disease; Alzheimer' s disease related dementia; Ambulatory Care; Anti-Cholinergics; Artificial Intelligence; Asian Americans; Black race; Cardiovascular Diseases; Cardiovascular system; Caregiver support; Caregivers; Caring; Clinical; Cognitive; Communities; Complex; Coupled; Dementia; Detection; Diabetes Mellitus; Diagnosis; Disadvantaged minority; Disease; Disparity; Early Diagnosis; Elderly; Electronic Health Record; Enrollment; Ethnic Population; Evaluation; Failure; Family; Future; Goals; Grant; Health; Health Status; High Prevalence; Hypertension; Impaired cognition; Individual; Inequity; Intervention; Latino; Lipids; Machine Learning; Measures; Medicaid; Memory; Methods; Modeling; Modernization; Monitor; Native Americans; Neurologist; Obesity; Outcome; Pathogenesis; Patient-Focused Outcomes; Patients; Persons; Population; Population Heterogeneity; Populations at Risk; Pragmatic clinical trial; Predictive Value; Preventive measure; Primary Care; Qualifying; Race; Risk Factors; Secondary Prevention; Smoking; Specialist; Strategic Planning; Technology; Testing; Therapeutic Agents; Underrepresented Minority; Uninsured; United States; age related; burden of illness; cardiovascular disorder prevention; cardiovascular risk factor; care delivery; clinical decision support; cohort; dementia risk; design; economic disparity; effectiveness evaluation; ethnic minority population; evidence base; health management; human old age (65+); implementation measures; improved; machine learning method; mild cognitive impairment; novel; novel therapeutics; patient engagement; pragmatic trial; preventive intervention; primary care provider; primary care setting; primary outcome; racial diversity; racial minority population; screening; screening disparities; screening program; secondary outcome; socioeconomic disadvantage; socioeconomics; support tools; tool; treatment arm; uptake; usability

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. These risk factors are unequally distributed, with higher prevalence among socioeconomically disadvantaged and racial and ethnic minority groups, and the problem is compounded by lower rates of cognitive screening and diagnosis across these groups – as documented in Black, Latino, Asian, and Native American populations. While referral to qualified memory specialists (geriatricians and/or neurologists) for evaluation and management is considered gold standard, in practice most diagnosis and management of AD/ADRD occurs in non-specialty (primary care) settings, due to shortage of specialists. Novel cognitive screening programs that leverage electronic health records (EHRs) 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 MCI and AD/ADRD, to elevate the quality of cognitive screening and secondary prevention within primary care, with a focus on practices that treat patients from socioeconomically and racially diverse backgrounds. We will design and implement an embedded Pragmatic Clinical Trial (ePCT) that involves engaging patients, families and 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 artificial intelligence (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 on the two NYU Langone Health Brooklyn ambulatory care centers, which include over 70 PCPs and over 10,000 patients age ≥65 years. (With 62% self- identified as non-white). 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 in a predominantly racial and ethnic underrepresented minority cohort. (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 of patient outcomes across different racial/ethnic subgroups for differences 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, particularly those most vulnerable to the disease.

项目概要/摘要： 阿尔茨海默氏病和阿尔茨海默氏病相关痴呆（AD/ADRD）是影响阿尔茨海默氏病的不可逆病症。 超过600万人在美国。虽然AD/ADRD的发病机制复杂， 心血管危险因素参与了其发病机制。这些风险因素分布不均， 在社会经济弱势群体以及少数种族和族裔群体中普遍存在，问题是 这些群体的认知筛查和诊断率较低-正如布莱克所记录的那样， 拉丁美洲人，亚洲人和美洲原住民。虽然转介到合格的记忆专家（老年病学家 和/或神经科医生）的评估和管理被认为是金标准，在实践中，大多数诊断和 由于缺乏专家，AD/ADRD的管理发生在非专业（初级保健）环境中。小说 利用电子健康记录（EHR）的认知筛查项目有可能缩小这一差距 相当大。在这种情况下，我们提出了一个基于利益相关者和技术的多成分框架， 改善MCI和AD/ADRD的早期发现，提高认知筛查和二级筛查的质量 初级保健中的预防，重点是从社会经济和种族角度治疗患者的做法， 不同的背景我们将设计并实施一项嵌入式实用临床试验（ePCT）， 让患者、家属和PCP参与进来，完善PCP应如何提供以下信息的现有做法： 认知筛查、MCI和AD/ADRD诊断及其与心血管疾病的联系。我们将 利用基于回顾性验证的人工智能（AI）的EHR临床决策支持工具 以及用于识别MCI和AD/ADRD的机器学习（ML）方法。ePCT的主要结局将是 认知筛查率和次要结局将包括痴呆的诊断和次要结局。 心血管预防措施。这项ePCT工作将集中在两个纽约大学Langone健康布鲁克林 门诊护理中心，包括70多名PCP和10，000多名年龄≥ 65岁的患者。(With 62%自我- 非白人）。我们的具体目标是（目标1）开展ePCT试点，以优化和评估 可接受性，可用性和采用实施现有的AI/ML工具和PCP决策支持， 主要是代表性不足的种族和族裔少数群体。(Aim 2）监测和监控ePCT 认知筛查的主要结局和MCI、AD/ADRD诊断的次要结局，以及 心血管疾病预防结果。(Aim 3）对患者结局进行子分析， 不同人种/种族亚组在筛查、诊断、继发性心血管疾病 预防性干预。这一试点ePCT将为更大规模的务实试验铺平道路， 老年人，特别是最脆弱人群认知健康管理方面的未满足和迫切需要 对疾病的影响