# Evaluating Implementation of a Patient Navigator Intervention to Improve Access to Diagnostic and Treatment Services for Children with Autism Spectrum Disorder

> **NIH NIH K23** · BOSTON MEDICAL CENTER · 2020 · $111,352

## Abstract

PROJECT SUMMARY
Significant racial, ethnic, and socioeconomic disparities exist in access to diagnostic and treatment services for
children with autism spectrum disorder (ASD). Because earlier access to ASD services improves long-term
outcomes, delayed engagement with these services can be responsible for substantial morbidity. This pattern
of health service break-down – delay in care, leading to preventable morbidity – exists in many sectors of the
US health care system. One promising solution, which has been studied extensively over the past ten years, is
patient navigation. Patient navigation is a lay-delivered case management strategy designed to reduce health
disparities by helping vulnerable populations overcome psychological and logistical hurdles to care. Navigation
has proven effectiveness in multiple disorders such as cancer and HIV, and early data support its use as a
strategy to promote timely engagement with evidence-based services among children with ASD. However,
despite navigation's substantial effectiveness data, multiple studies demonstrate the attenuation of its impact,
and variable success, when implemented in real-world practice. This “research-practice” gap – whereby
effective clinical innovations fail to be adopted (or practiced with appropriate fidelity) within real-world clinical
practice – is ubiquitous in healthcare; but it is particularly problematic for low-income and minority populations
and the institutions that serve them. Furthermore, despite guidance to the contrary, few clinical trials proactively
collect data on the complex patient, provider, and organizational factors that impact subsequent
implementation of the clinical innovations being tested. As a result of this missed opportunity, implementation
strategies are often arbitrary and prone to failure. Therefore, in this K23 application, I propose to use emerging
techniques in the field of dissemination and implementation science to evaluate key implementation processes
of patient navigation in the context of an ongoing, NIMH-funded, multi-site randomized controlled trial of a
patient navigation system designed to improve access to care for low-income children with ASD
(R01MH104355, Feinberg). The goal of this work is to elucidate factors that can increase the likelihood of rapid
and sustained uptake of patient navigation in diverse, real-world practice settings. My educational objectives
are to gain training and experience in dissemination and implementation science through the following goals: to
learn process mapping and analysis; to learn new qualitative methods; and to learn and apply a new
quantitative technique - multilevel modeling. The research in this proposal builds directly on my prior work,
which focused on using multidisciplinary teams to improve access to services for children with ASD and their
families. I have identified an experienced mentoring team and a supportive research environment, which will
ensure that I attain my immediate and long-t...

## Key facts

- **NIH application ID:** 10002313
- **Project number:** 5K23MH109673-05
- **Recipient organization:** BOSTON MEDICAL CENTER
- **Principal Investigator:** Sarabeth Broder-Fingert
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $111,352
- **Award type:** 5
- **Project period:** 2016-09-26 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10002313

## Citation

> US National Institutes of Health, RePORTER application 10002313, Evaluating Implementation of a Patient Navigator Intervention to Improve Access to Diagnostic and Treatment Services for Children with Autism Spectrum Disorder (5K23MH109673-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10002313. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*