Two decades of evidence support the effectiveness of family navigation (FN) as a care-management approach to reducing disparities in access to health services for disorders; despite substantial promise, widespread dissemination of FN still faces significant challenges. FN is a complex, multi-component intervention that generally incorporates motivational interviewing, problem-solving strategies, patient education, and care coordination. Each of these components can be delivered through a range of strategies including in-person meetings, telehealth, home visits, and/or web-based technologies. Our team?s research strongly supports FN?s effectiveness as a whole; however, three questions remain: 1) what are the most effective delivery strategies for FN; 2) which FN components are the ?active ingredients;? and 3) how can FN be disseminated to a broad population. In the current proposal, FN will be will be delivered by a Family Partner and deployed to improve access to behavioral health services among children ages 3-12 years. Our study will be carried out at a large federally qualified health center within a newly formed Accountable Care Organization. For this project, we propose to optimize FN for dissemination at scale. First, using the Multiphase Optimization Strategy (MOST), which relies on a randomized, multi-factorial design, we will simultaneously test the effectiveness of three novel strategies for delivering FN components: (A) technology-assisted delivery of care coordination using an innovative, web-based platform; (B) community-based; and (C) enhanced symptom tracking using evidence-based screening instruments (compared to standard pediatric surveillance). Second, using path analysis, we will test mediators and moderators of FN outcomes. Third, using a mixed-methods approach, we will study factors that influence implementation. Integration of our three aims will yield a FN model that is optimized for efficiency, effectiveness, and wider implementation.
Our specific aims are: (1) To evaluate the effectiveness of three strategies to deliver FN components. We will use a 2 x 2 x 2 factorial experimental design to test three strategies to deliver FN components. Families (n=304) will be randomized to one of eight conditions. We will estimate main effects of the three experimental factors and the additive effects of combinations of factors on the study?s primary outcome ? engagement in appropriate mental health services. (2) To evaluate mechanisms of FN effectiveness and for whom it is most effective. (3) To Optimize FN for dissemination and evaluate implementation strategies. Following Aarons? scaling-out framework, we will use mixed methods to explore barriers and facilitators to implementation by evaluating fidelity (to intervention and implementation), reach, and cost. Then, working with our team of stakeholders, we will integrate these findings with data from Aim 1 and 2 to optimize FN based on effectiveness, identified mediators and moderators, and implementation success.

Public Health Relevance

Two decades of evidence support the effectiveness of family navigation (FN) as a care-management approach to reducing disparities in access to health services yet widespread dissemination of FN still faces significant challenges. In response to PAR-17-265, we propose to optimize FN for dissemination at scale. Using the Multiphase Optimization Strategy (MOST), which relies on a randomized, multi-factorial design, we will simultaneously test the effectiveness of three novel strategies for delivering FN components; then, we will test mediators and moderators of FN outcomes; and study factors that influence implementation (including fidelity and cost) to yield a FN model that is optimized for efficiency, effectiveness, and wider implementation.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH117123-01
Application #
9578512
Study Section
Mental Health Services Research Committee (SERV)
Program Officer
Pintello, Denise
Project Start
2018-08-01
Project End
2023-05-31
Budget Start
2018-08-01
Budget End
2019-05-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Boston Medical Center
Department
Type
DUNS #
005492160
City
Boston
State
MA
Country
United States
Zip Code