Identifying Risk and Improving Care for Elder Abuse among Veterans

背景虐待老人是指身体、性或心理虐待、经济剥削或忽视 年龄≥ 60岁的成年人。在美国，十分之一的老年人每年都会经历EA，其中许多人 多种类型。退伍军人是在特别高的风险，由于高流行率的EA危险因素，在这一点上， 人口经历EA与抑郁症，受伤，增加医疗保健使用和死亡率有关，但尽管如此， 由于艾滋病的流行和发病率，只有不到5%的病例被发现，限制了干预的机会。而 筛查是改善类似疾病检测的常用方法，但EA的筛查工具还没有 被广泛研究或验证。此外，EA筛查可能会错过重要的高危人群， 例如痴呆症患者，需要开发额外的检测策略， 筛选本研究旨在通过评估和优化当前EA来改善VA中的EA风险检测 筛选方法，并利用VA医疗保健数据来识别临床怀疑EA的退伍军人 他们可能会从进一步的评估中受益。意义/影响。随着老年人口的增长， 美国和超过1000万年龄≥ 60岁的美国退伍军人，改善EA的检测和干预是一个 国家和VA公共卫生优先事项。通过更好地了解情况的筛查和 新的数据驱动的工具，这项研究符合VA HSR & D的优先事项，以改善我们国家的老龄化护理 退伍军人和他们的照顾者。创新这项研究整合了虐待老人和实施科学 概念框架，以开发新的方法来改善EA检测。这项研究将评估测试 使用独特的VA数据元素的第一个EA怀疑数据标记的特征，并将采用 创新的数据信息学方法，如自然语言处理（NLP），以解决复杂的 对健康有重大影响的社会问题。具体目标。目标1是对当前的 VA医疗中心（VAMC）EA筛查实践的概况和设施的定量评估 与筛选相关的水平因素。目标2是一项定量研究，将确定最佳的EA VA数据中的管理标记（AM）。目标3是一项定性研究，将阐明机会， 促进者和障碍，以实施基于医疗保健的EA检测程序在VA。方法论 在密切合作与护理管理和社会工作的VA办公室，目标1将进行全国性的 VAMC调查，以评估EA筛查和检测的当前实践; VA机构级数据将 用于评估与筛查相关的结构特征。目标2将研究三种潜在的EA 怀疑AM，并通过与多组分参比标准品进行比较，选择性能最佳的 包括：a）简化的基于规则的NLP进度记录内容，以及B）评估 通过有针对性的医疗记录审查来实现AM和NLP。在目标3中，早期、近期和非EA筛选站点 根据目标2中选择的AM，目标1中确定的EA病例量不同，将招募入组 深入定性访谈，阐明EA检测计划的机会、促进因素和障碍 在弗吉尼亚州。执行/后续步骤。从这项研究的结果将被用来推导和验证一个新的EA 可疑工具（EAST）在弗吉尼亚州，然后开发和实施一种检测方法，提高效率， 通过将改进的EA筛查与针对那些 最高风险候选人莉娜·马卡伦博士是退伍军人事务部健康中心的老年病学家和核心研究员 公平研究和促进。该CDA的目标是获得培训和研究经验， 通过以下方面的深入培训在老年退伍军人中进行EA检测：（1）真实世界EA评估和干预 程序;（2）实施科学;（3）框架指导的定性方法;（4）预测分析。 该CDA将支持Makaroun博士的长期职业目标，即成为一名独立的VA健康服务人员 研究人员专注于改善护理服务，干预，并最终预防老年人的EA。

Background. Elder abuse (EA) is the physical, sexual or psychological abuse, financial exploitation or neglect of an adult age ≥60 years. One in 10 older adults experience EA annually in the US, with many experiencing multiple types. Veterans are at particularly high risk due to the high prevalence of EA risk factors in this population. Experiencing EA is linked to depression, injury, increased healthcare use and mortality, but despite its prevalence and morbidity, fewer than 5% of cases are detected, limiting opportunities for intervention. While screening is a common approach to improving detection of similar conditions, screening tools for EA have not been well validated or widely studied. Furthermore, EA screening may miss important high-risk populations, such as those with dementia, necessitating the development of additional detection strategies that complement screening. This research aims to improve EA risk detection in VA by both evaluating and optimizing current EA screening approaches and by leveraging VA healthcare data to identify Veterans with clinical suspicion of EA who may benefit from further assessment. Significance/Impact. With the growing population of older adults in the US and over 10 million US Veterans age ≥60 years, improving detection of and interventions for EA is a national and VA public health priority. By improving detection of EA via both better-informed screening and novel data-driven tools, this research aligns with VA HSR&D’s priority to improve care for our nation’s aging Veterans and their caregivers. Innovation. This research integrates elder abuse and implementation science conceptual frameworks to develop new approaches to improving EA detection. This study will evaluate the test characteristics of the first-ever data marker for EA suspicion using unique VA data elements and will employ innovative data informatics approaches, such as natural language processing (NLP), to address a complex social problem with large health impacts. Specific Aims. Aim 1 is a national assessment of the current landscape of EA screening practices in VA medical centers (VAMCs) and a quantitative evaluation of facility level factors associated with screening. Aim 2 is a quantitative study that will identify the best performing EA administrative marker (AM) in VA data. Aim 3 is a qualitative study that will elucidate opportunities for, facilitators of and barriers to implementation of healthcare-based EA detection programs in VA. Methodology. In close partnership with the VA Office of Care Management and Social Work, Aim 1 will conduct a national survey of VAMCs to assess current practices around EA screening and detection; VA facility-level data will be used to assess structural characteristics associated with screening. Aim 2 will examine three potential EA suspicion AMs and select the best performing via comparison to a multi-component reference standard consisting of: a) simplified rule-based NLP of progress note content, and b) evaluation of discordance between AMs and NLP through targeted medical record review. In Aim 3, early-, recent-, and non-EA screener sites identified in Aim 1 varying in EA case volume according to the AM selected in Aim 2 will be recruited for in- depth qualitative interviews to elucidate opportunities for, facilitators of, and barriers to EA detection programs in VA. Implementation/Next steps. Findings from this research will be used to derive and validate a novel EA Suspicion Tool (EAST) in VA, then develop and implement a detection approach that improves efficiency and impact by combining improved EA screening with comprehensive EA assessments targeted towards those at highest risk. Candidate. Dr. Lena Makaroun is a geriatrician and Core Investigator at the VA Center for Health Equity Research and Promotion. The goal of this CDA is to gain training and research experience in improving EA detection among older Veterans through in-depth training in: (1) real-world EA evaluation and intervention programs; (2) implementation science; (3) framework-guided qualitative methods; and (4) prediction analytics. This CDA will support Dr. Makaroun’s long-term career goal of becoming an independent VA health services researcher focused on improving care delivery, intervention and, ultimately, prevention of EA in older adults.