Screening for Cognitive Impairment Following Critical Illness: Designing and Testing an Implementation Program to Support High Risk Older Adults

帕拉克沙帕 1K23AG073529-01 危重病导致许多老年人发生轻度认知障碍（MCI）或阿尔茨海默病及相关痴呆（ADRD）。在美国，每年约有250万老年人入住重症监护室（ICU）;其中，1/4的老年人在ICU住院12个月后，其严重程度与轻度ADRD相似。在危重疾病后识别MCI或ADRD对于将患者及其护理人员与支持联系起来至关重要，提供已知可减少MCI进展为阿尔茨海默病（AD）的护理建议，并最终提高我们对导致这种并发症的可改变风险因素的理解。因此，跨学科专家建议在高危患者的危重疾病后筛查MCI或AD;然而，这尚未被广泛采用。该指导职业发展奖的总体目标是获得认知评估和实施科学方面的额外培训，并使用混合方法来开发和试点测试实施计划，以支持筛查老年人重症疾病后的MCI或ADRD事件。目标1将使用医疗保险索赔数据开发和测试重大疾病后的MCI或AD事件预测模型，然后重新校准该模型用于电子健康记录（EHR），提供将预测建模与EHR数据集成的经验学习。在目标2中，我将学习使用定性数据，通过识别在ICU后人群中实施认知筛查的促进者和障碍来为实施提供信息。在目标3中，我将获得设计和进行试点实施试验的经验，并确定预测痴呆症和提供治疗（ADAPT）的可行性和潜在影响，ADAPT是一项旨在支持在我们的卫生系统中筛查危重疾病后MCI或ADRD的实施计划。我将充分利用维克森林医学院出色的研究环境，以及一个非常合格的导师团队（威廉姆森博士，休斯顿，汉彻特，伯肯，文件，迈耶）的支持和指导。通过教学课程，专门的指导和实践经验，我将获得必要的培训，将预测建模与EHR数据相结合，使用定性数据为实施提供信息，以及设计和进行试点实施试验。我还将继续在认知评估方法和老年医学原则的额外培训，建立一个专业领域连接危重病，衰老和认知，以及实施科学。这种指导以患者为导向的研究K23将促进我们对如何最好地识别和支持危重病后MCI或ADRD的老年人的理解，它将帮助我实现我的长期目标，成为一名独立的医生-科学家，致力于改善我们在危重病期间和之后为老年人提供的护理。

Palakshappa 1K23AG073529-01 Critical illness leads to incident mild cognitive impairment (MCI) or Alzheimer’s disease and related dementias (ADRD) in many older adults. Roughly 2.5 million older adults are admitted to intensive care units (ICUs) annually in the United States; of those, 1 in 4 have a degree of impairment similar in severity to mild ADRD 12 months after their ICU stay. Recognizing MCI or ADRD following critical illness is crucial for connecting patients and their caregivers with support, providing care recommendations known to decrease the progression of MCI to Alzheimer’s disease (AD), and ultimately improving our understanding of modifiable risk factors that lead to this complication. As such, experts across disciplines recommend screening for MCI or AD following critical illness in high-risk patients; however, this has not been widely adopted. The overall objective of this mentored career development award is to obtain additional training in cognitive assessment and implementation science and use a mixed-methods approach to develop and pilot-test an implementation program to support screening for incident MCI or ADRD following critical illness in older adults. Aim 1 will develop and test a prediction model for incident MCI or AD following critical illness using Medicare claims data and then re-calibrate that model for use in the electronic health record (EHR), providing experiential learning in integrating prediction modeling with EHR data. In Aim 2, I will learn to use qualitative data to inform implementation by identifying facilitators and barriers to implementing cognitive screening specifically in the post-ICU population. In Aim 3, I will gain experience with the design and conduct of a pilot implementation trial and determine the feasibility and potential impact of Anticipating Dementia and Providing Therapy (ADAPT), an implementation program designed to support screening for MCI or ADRD following critical illness in our health system. I will capitalize on the outstanding research environment at Wake Forest School of Medicine as well as the support and guidance of an exceptionally qualified mentorship team (Drs. Williamson, Houston, Hanchate, Birken, Files, Meyer). Through didactic coursework, dedicated mentorship, and hands-on experience, I will obtain the necessary training in the integration of prediction modeling with EHR data, the use of qualitative data to inform implementation, and the design and conduct of a pilot implementation trial. I will also pursue additional training in cognitive assessment methods and geriatric principles, establishing an area of expertise linking critical illness, aging and cognition, and implementation science. This Mentored Patient-Oriented Research K23 will advance our understanding of how best to identify and support older adults with MCI or ADRD after critical illness and it will help me to achieve my long-term goal of becoming an independent physician-scientist dedicated to improving the care we deliver to older adults during and after critical illness.