Using Consumer Credit Data to Identify Precursors and Consequences of Cognitive Impairment

项目摘要 使用消费者信贷数据识别认知障碍的前兆和后果 老年人口的快速增长加上缺乏有效的医疗手段来扭转或推迟 据估计，阿尔茨海默氏病和相关痴呆症导致超过1200万老年人与 到2050年患痴呆症认知能力下降和痴呆症的最早迹象之一是经济能力受损， 这可能表现为管理金钱和支付账单的困难，或者表现出不稳定和反常的行为， 高风险的财务决策，提高财务欺诈的风险，不适当的资产配置，信用违约 未付账单和其他损失。 认知能力下降的早期预警信号可以通过日常财务行为的变化来观察。 信用局和其他数据聚合器收集了大量高频，实时的消费者信息。 消费信息显示，超过80%的美国人经常使用信贷产品。75%的成年人 50岁及以上的人使用信用卡，39%的人有信用卡余额，60%的房主年龄在50岁及以上。 有抵押贷款债务。这些数据可能有助于确定认知能力下降的具体财务预测因素， 新的信息来源，可以帮助临床诊断，并提醒患者及其家属 需要协助财务决策。到目前为止，消费者的潜在健康用途 金融数据在很大程度上被忽视，特别是老年人的金融数据。这个探索性的项目 考虑来自医疗保健外部的大数据资源的效用;收集的消费者债务特征 信用报告，以预测认知障碍和痴呆症的新病例， 认知受损的病人。 我们有3个研究目标：1-创建连接纽约联邦储备银行/Equifax的数据集 消费者信用小组对国家医疗保险索赔和调查数据，没有直接的患者标识符， 概率匹配; 2-评估消费者债务特征作为认知风险预测因子的效用 下降; 3-评估消费者债务特征作为住院和护理预测因子的效用 老年痴呆症患者的家庭使用。我们将研究估计140万名患者， 跟踪面板数据，以评估信用报告数据中记录的不良信用事件是否可靠地识别 老年人早期或晚期认知障碍的迹象。如果他们这样做，监控程序可能会 旨在警告患者及其家属可能需要筛查和协助管理 钱这种类型的监控工具可以帮助保护老年人免受欺诈和其他金融风险， 帮助远程护理人员了解何时进行干预。除了认知上的潜在好处外， 受损患者及其家属，这项研究将是使用消费者大数据的概念验证， 为临床诊断和患者管理提供信息，这可能对 研究人员和最终受益于未来发现的患者。

PROJECT SUMMARY Using Consumer Credit Data to Identify Precursors and Consequences of Cognitive Impairment Rapid growth in the elderly population combined with a lack of effective medical treatments to reverse or delay Alzheimer's disease and related dementias are estimated to lead to over 12 million older adults living with dementia by 2050. One of the earliest signs of cognitive decline and dementia is impaired financial capacity, which can manifest as difficulties managing money and paying bills or making erratic and uncharacteristically risky financial decisions, heightening risks for financial fraud, inappropriate asset allocation, credit delinquency from unpaid bills and other losses. Earlier warning signs of cognitive decline may be observable through changes in routine financial behavior. Credit bureaus and other data aggregators collect vast quantities of high-frequency, real-time consumer spending information on the more than 80% of Americans regularly using credit products. 75% of adults age 50 and over use credit cards, 39% carry a credit card balance, and 60% of homeowners age 50 and above have mortgage debt. These data may help to identify specific financial predictors of cognitive decline, leading to new information sources that could help with clinical diagnoses and alert patients and their families about the need for assistance with financial decision-making. To date, the potential health uses of consumer financial data have largely been ignored, particularly for the older population. This exploratory project considers the utility of a big data resource from outside healthcare; consumer debt characteristics collected in credit reports, to predict new cases of cognitive impairment and dementia and healthcare utilization of cognitively impaired patients. We have 3 research aims: 1- to create datasets linking the Federal Reserve Bank of New York/Equifax Consumer Credit Panel to national Medicare claims and survey data without direct patient identifiers using probabilistic matching; 2- to assess the utility of consumer debt characteristics as predictors of cognitive decline; 3- to assess the utility of consumer debt characteristics as predictors of hospitalization and nursing home use among patients with dementia. We will study an estimated 1.4 million patients with up to 15 years of panel data follow-up to assess whether adverse credit events captured in credit report data reliably identify signs of early or advanced cognitive impairment among older adults. If they do, monitoring programs could be developed to warn patients and their families of the potential need for screening and assistance managing money. This type of surveillance tool can help to protect older adults from fraud and other financial risks and assist long-distance caregivers to know when to intervene. In addition to the potential benefits for cognitively impaired patients and their families, this study will be a proof-of-concept of the use of consumer big data to inform clinical diagnoses and patient management, which may have a number of important implications for researchers and ultimately the patients who benefit from future discoveries.