A systems science approach for improving continuity of service in substance use disorder treatment

项目总结/文摘

Project Summary/Abstract Increasing access to substance use disorder (SUD) treatment is an important public health priority because substance abuse and dependence is associated with significant morbidity and mortality. While evidence-based treatments are available to care for people with SUDs, only 11% of individuals who need professional treatment receive it. One major service gap in the treatment of SUDs, particularly alcohol and opioid use disorders, is the engagement of patients in treatment or rehabilitation after an initial detoxification (detox). At the point of discharge from detox, patients are at high risk of relapse and therefore vulnerable to system failures. Detox alone increases patients' risk of mortality from overdose if they do not transition to rehabilitation after discharge. To date, research on the problem of continuity of service after detox has focused on patient characteristics and attributes of organizations with no consideration to the dynamic contexts within which SUD treatment occurs. What has not been explored to date is the impact of referral networks between service programs on entry into SUD treatment after detox. The goal of this pilot study is to determine the impact of systems-level predictors such as network structures on continuity of service in the SUD treatment system in Los Angeles County. The central hypothesis will be tested by pursuing three specific aims: 1) Describe the ecology of the publicly-funded SUD treatment system in Los Angeles County using social network analysis, 2) Determine the impact of network structure on continuity of service from detox to SUD treatment using computer simulation models, and 3) Design a protocol for a service implementation network intervention to increase continuity of service after detox. The unique strengths of the study are the experienced research team, theory-driven approach, and application of systems science methodologies such as social network analysis and agent-based modeling. Achieving the study aims will create greater understanding of the interdependency of programs within the treatment systems and demonstrate how partnerships and referral patterns at a system level can impact patient outcomes. The results of the study will be used to plan an R34 study to test the implementation and effectiveness of a service implementation network model for SUD treatment.