Adapting an Evidence-Based Intervention to Improve the Hospital Discharge Process for Patients with Limited English Proficiency

项目摘要 医院出院是一个高风险的时间，因为沟通错误、用药错误和 服务提供者中断，导致危险和昂贵的再次住院治疗。有限的患者 英语熟练程度(LEP)--美国日益增长的人口结构--最有可能是负面的 受到这些质量和安全差距的影响，因为语言不协调造成了沟通障碍 护理和他们额外的社会脆弱性。患有LEP的患者更有可能对 出院指示，药物治疗面临障碍，回家后报告新的或恶化的症状， 并遭受出院后的不良事件。这种不平等导致了糟糕的结果，从而推动了健康 差距。虽然多种护理过渡干预措施已被证明可以改善这些结果， 他们排除了LEP患者。重组放电(红色)是一种多组分的放电 干预措施显示可降低32%的再利用率，并改善患者体验。增进健康 在与出院相关的结果方面的公平，必须调整RED等护理过渡方案以适应 满足LEP患者的需求，解决语言障碍、文化因素和社会决定因素 出院时的健康状况。适应是一种行之有效的战略，通过确保 干预措施适用于健康差距人群，因此也是有效的。此应用程序的目标是 根据有关患者偏好和多学科的新数据，为LEP患者调整RED 利用关键利益攸关方的适应过程，并在试点试验中进行测试。在目标1中，我将进行一个离散的选择 实验(DCE)，一种改进的调查方法，通过隐含的权衡来量化偏好 选择，以了解患有LEP的人如何重视不同的放电支持。在目标2中，我将应用 方法论，一种基于证据的方法，利用不同利益相关者团队的智慧，以 确定对红色的具体适应。在目标3中，我将测试适应性干预(RED-LEP) 通过试点随机对照试验实现不同的安全网LEP人群，目的是评估关键 实施结果(保真度、可接受性和可行性)以及收集以下数据的可行性 临床结果。拟议的研究将为我提供以下领域的经验，即 解决我迄今在实施科学方面的培训中的具体缺陷：量化方法 了解利益相关者偏好、干预适应以及与参与者一起进行的临床试验 使用LEP。这项研究建立在我之前对全球少数民族和语言少数群体所做工作的基础上 在不同的安全网环境中，我作为一名医院医生的临床专业知识。我的培训目标-以及 我的多学科导师/顾问团队，在卫生公平研究、实施科学、 和关心的语言障碍-将促进我向研究独立性的过渡，并使我能够测试 多点混合II型有效性实施试验中的RED-LEP模型。

Project Summary Hospital discharge is a high-risk time due to the frequency of miscommunication, medication errors, and discontinuity of providers which lead to dangerous and costly hospital readmissions. Patients with limited English proficiency (LEP)—a growing demographic in the United States—are the most likely to be negatively impacted by these gaps in quality and safety given the communication barriers created by language discordant care and their additional social vulnerabilities. Patients with LEP are more likely to have poor comprehension of discharge instructions, face barriers to obtaining medications, report new or worsening symptoms once home, and suffer post-discharge adverse events. Such inequities lead to poor outcomes, which drive health disparities. While multiple care transition interventions have been shown to improve these outcomes, they have excluded patients with LEP. ReEngineered Discharge (RED) is a multi-component discharge intervention that was shown to reduce reutilization by 32% and improve patient experience. To improve health equity in outcomes relating to hospital discharge, care transition programs such as RED must be adapted to meet the needs of those with LEP, addressing language barriers, cultural factors, and social determinants of health salient at the time of discharge. Adaptation is a proven strategy to reduce disparities by ensuring intervention fit, and thus effectiveness, in health disparity populations. The goal of this application is to adapt RED for patients with LEP, informed by new data on patient preferences and a multidisciplinary adaptation process utilizing key stakeholders, and test it in a pilot trial. In Aim 1, I will conduct a discrete choice experiment (DCE), a modified survey methodology to quantify preferences through implicit trade-offs in choices, to understand how those with LEP value different discharge supports. In Aim 2, I will apply the ADAPT methodology, an evidence-based approach that harnesses wisdom from a diverse team of stakeholders, to determine the specific adaptations to RED. In Aim 3, I will test the adapted intervention (RED-LEP) in a diverse safety net LEP population through a pilot randomized controlled trial with the goal to assess key implementation outcomes (fidelity, acceptability, and feasibility) as well as the feasibility collecting data on clinical outcomes. The proposed research will provide me with experience in the following domains, which address specific deficits in my training in implementation science to date: quantitative approaches to understanding stakeholder preference, intervention adaptation, and conduct of clinical trials with participants with LEP. This research builds on my prior work with ethnic and linguistic minority populations in the global setting and my clinical expertise as a hospitalist in a diverse safety net setting. My training aims—along with my multi-disciplinary mentor/advisor team with experience in health equity research, implementation science, and linguistic barriers to care—will facilitate my transition to research independence and position me to test the RED-LEP model in a multi-site hybrid type II effectiveness-implementation trial.