Examining the Outcomes of Repeated Client Referrals Based on the Trajectories of Care
Abstract
In the United States, individuals routinely need to be referred from one organization to another to receive necessary services. Referral networks are systems of relationships among organizations that allow them to direct people (e.g., clients) to the appropriate services that are not available at their own facility (Gibbons & Samaddar, 2009, p. 352). Recently, referral networks have arisen to integrate health and social services into unified systems to address the social determinants of health (SDH). ÒSDH are the non-medical factors that influence health outcomesÓ (WHO, nd) Research examining the outcomes of referral systems relies on time-intensive, cross-sectional surveys (e.g., Provan & Milward, 1995) or efficiency metrics (i.e., the average time to close cases; Saitgalina & Council, 2020). These metrics provide little help to referrers in determining which set of referrals or referral processes would lead to the highest quality of care for individual clients, especially when client needs are complex and varied. They fail to examine how a set of referrals over time produces better or worse outcomes for clients. This research aims to address these deficiencies. This field-based research will introduce and validate a system-derived measure of the quality of client outcomes based upon trajectories of care. Partnering with the AmericaServes and Combined Arms, the team will use mixed methods to develop trajectories of care metrics for veterans and transitioning service members. First, using interviews and surveys, the team will develop a program categorization toolkit designed to measure the level of need programs and services address. A score will be given to each client with multiple service episodes by combining program rankings with systems data. The team will validate the scores by comparing them to the results of client record audits and a survey-based measure of client well-being. This research makes two critical contributions to network science. First, this research advances the study of network performance. Previous research on network effectiveness involves a costly examination of multifaceted client outcomes (e.g., Loran et al., 2017) or examines service episode outcomes (e.g., Saitgalina & Council, 2020). This research takes a new tact, defining network performance as the longitudinal improvement of client well-being across service episodes. This definition is a radical departure from previous research. Still, it fulfills the promise of research on SDH by demonstrating how the combination of services over time produces (or fails to produce) better client outcomes. In doing so, it opens up new questions such as: What is the effectiveness of different pathways in the network over time? Which referrals should be made first? Which providers are most effective at each stage of the trajectory of care? Second, this research builds upon previous advances in relational event modeling (Butts, 2008; Butts & Marcum, 2017) to create relational event measures of network outcomes. In short, it addresses a fundamental limitation of network science research on relational events: the ability to evaluate whether a sequence of relational events performed better than others. Finally, because this proposal focuses on the wellbeing of transitioning service members, veterans, and military families, it allows the Army to fulfill its commitment to those who serve. The SDH are strongly related to many high priority concerns for the military community, especially transitioning service member and veteran mental health and suicide. This research promises to develop a system-derived metric for the success of referral networks in promoting veteran wellbeing.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 11, 2022
- Source ID
- W911NF2210180
Entities
People
- Michelle Shumate
Organizations
- Army Contracting Command
- Northwestern University
- United States Army