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

采用循证干预措施改善英语水平有限患者的出院流程

• 批准号: 10783353
• 负责人: Kirsten Austad
• 金额: $ 16.19万
• 依托单位: BOSTON MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-23 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10783353
• 关键词: Address; Admission activity; Adverse event; Appointment; Boston; Calendar; Caring; Client satisfaction; Clinical; Clinical Trials Design; Communication; Communication Barriers; Communities; Comprehension; Conduct Clinical Trials; Dangerousness; Data; Disparity; Disparity population; Educational process of instructing; Effectiveness; Engineering; Ensure; Environment; Equity; Ethnic Origin; Evaluation; Evidence based intervention; Exclusion; Face; Failure; Family; Frequencies; Goals; Haitian; Home; Hospital Costs; Hospitalists; Hospitalization; Hospitals; Hybrids; Inequity; Inferior; Instruction; Intervention; Interview; Knowledge; Language; Lead; Limited English Proficiency; Linguistics; Logit Models; Measures; Medical; Medical center; Medication Errors; Mentors; Methodology; Methods; Minority Groups; Modeling; Modification; National Institute on Minority Health and Health Disparities; Nurses; Outcome; Participant; Patient Care; Patient Discharge; Patient Education; Patient Preferences; Patients; Pharmaceutical Preparations; Population; Positioning Attribute; Preparation; Primary Care; Process; Provider; Randomized, Controlled Trials; Reporting; Research; Research Personnel; Review Literature; Safety; Sampling; Science; Series; Site; Structure; Survey Methodology; Symptoms; Testing; Time; Training; Translations; Underserved Population; United States; Work; Writing; acceptability and feasibility; barrier to care; care coordination; care providers; disparity reduction; effectiveness/implementation trial; evidence base; experience; experimental study; feasibility trial; health disparity; health disparity populations; health equity; high risk; hospital readmission; implementation intervention; implementation outcomes; implementation science; improved; improved outcome; insight; medication compliance; multi-component intervention; multidisciplinary; patient safety; person centered; pilot trial; poor health outcome; preference; programs; readmission rates; recruit; response; retention rate; safety net; service coordination; social health determinants; social vulnerability; standardize measure; success; treatment as usual; verbal

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.

项目总结