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.
