Grant Details
Grant Number: |
5R01CA271303-02 Interpret this number |
Primary Investigator: |
Chu, Daniel |
Organization: |
University Of Alabama At Birmingham |
Project Title: |
Adapting Enhanced Recovery Programs (ERPS) Through Health Literacy to Eliminate Surgical Disparities |
Fiscal Year: |
2024 |
Abstract
PROJECT SUMMARY
Rationale: Low health literacy affects over a third of surgical populations and is associated with significantly
worse outcomes in surgery. Interventions that reduce disparities in this large population are urgently needed.
Our team has previously shown that enhanced recovery programs (ERPs) mitigate racial disparities in surgical
outcomes and offer a pragmatic way to address surgical disparities. Existing ERPs, however, work poorly for
patients with low health literacy who still experience worse outcomes. This gap arises from the lack of fit between
current ERPs and the needs of low health literacy patients. Through a K23, our team assessed these needs and
developed a novel multilevel strategy to improve fit: engage patients with VISuAl aids, Coach providers in
communication, and Train organizations in health literacy (VISACT). An opportunity now exists to deliver and
test the VISACT using a theory-based adaptation framework. Successful adaptations would transform existing
ERPs and broaden its disparity-reducing impact to low health literacy populations. Objectives: Our long-term
objective is to eliminate disparities and improve outcomes for low health literacy populations in surgery through
context-driven adaptations of existing ERPs. We hypothesize that VISACT will improve fidelity to ERP’s
components for low health literacy patients and thereby surgical outcomes. To achieve our objective, we aim to:
(SA1) identify the health literacy-sensitive components of ERPs to augment with VISACT, (SA2) assess the
health literacy needs of providers and organizational units on ERP teams, and (SA3) deliver and pilot test the
VISACT implementation strategy on existing ERPs. Methods: Guided by the Dynamics Adaptation Process
framework, we will first use machine learning on a large ERP database (n>7,000) to identify the health literacy-
sensitive components of ERPs to augment with VISACT (SA1). Second, we will use a convergent mixed-
methods integrative approach to identify gaps in health literacy knowledge, best practices, and preparedness to
adapt on ERP implementation teams through three interrelated methods: in vivo observations of ERPs in-action
at 4 Alabama facilities, extended semi-structured interviews of 120 stakeholders, and surveys measuring health
literacy knowledge and organizational preparedness to adapt. Third, we will deliver the VISACT to two sites in
Alabama (urban and rural) through a novel interactive response platform in a pilot study and assess for
feasibility/acceptability through a RE-AIM framework of reach, efficacy, adoption, implementation, and
maintenance measures. Acquired data will inform design of a multi-institutional stepped-wedge trial of the
VISACT in the Deep South. Significance: This study will advance the NIH/NIMHD mission to eliminate surgical
disparities and responds directly to the NIMHD Science Visioning Research Strategies by removing health
literacy barriers (#24) and building the science of adapting interventions to different contexts (#30). Our team will
furthermore (i) deliver the first health literate intervention in surgery, (ii) establish a novel implementation strategy
(VISACT) to address surgical disparities and (iii) advance the science of interventions through adaptations.
Publications
None