Adapting an Evidence-Based Intervention to Improve the Hospital Discharge Process for Patients with Limited English Proficiency - PROJECT SUMMMARY 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 who face communication obstacles, including those with other language preference (OLP)—a growing demographic in the United States—are the most likely to be negatively impacted by these gaps in quality and safety. Patients with OLP are more likely to have poor comprehension of discharge instructions, face challenges to obtaining medications, report new or worsening symptoms once home, and suffer post-discharge adverse events. Further supports to improve communication could improve health outcomes. While multiple care transition interventions have been shown to improve these outcomes, they have excluded patients with OLP. ReEngineered Discharge (RED) is a multi-component discharge intervention that was shown to reduce reutilization by 32% and improve patient experience. To improve outcomes relating to hospital discharge, care transition programs such as RED must be adapted to meet the needs of those with OLP, addressing communication, access limitations, and consideration of personal preferences relevant at the time of discharge. Intervention adaptation is a proven strategy to improve health outcomes by ensuring intervention fit, and thus effectiveness. The goal of this application is to adapt RED for patients with OLP, 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 OLP value different discharge supports. In Aim 2, I will apply the ADAPT methodology, an evidence-based approach that harnesses wisdom from a team of stakeholders, to determine the specific adaptations to RED. In Aim 3, I will test the adapted intervention (RED-OLP) in a low resource hospital 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. This research builds on my prior work and my clinical expertise as a hospitalist. My training aims—along with my multi-disciplinary mentor/advisor team with experience in outcomes research, implementation science, and patient-provider communication—will facilitate my transition to research independence and position me to test the RED-OLP model in a multi-site hybrid type II effectiveness-implementation trial.
