Abstract

IntroductionSubstance use disorders (SUD) are chronic conditions that often warrant coordinated medical care throughout a relapsing and remitting course. However, SUD treatment is frequently measured as a binary outcome, where individuals either receive or do not receive care following the immediate treatment seeking event. This study aimed to describe longitudinal treatment seeking behaviors by assessing service use patterns among individuals with diagnosed SUDs in a safety net hospital that offers a “no wrong door” care model. This study also examined whether certain patient subgroups were more likely to transition to service use patterns that support recovery or treatment disengagement over time. MethodsThe team conducted a retrospective cohort study using electronic health record data from adult patients diagnosed with SUDs (n = 1157) who regularly accessed services at a safety net hospital over a five-year period. The study used latent class analysis (LCA) and latent profile analysis to empirically identify distinct treatment utilization profiles of individuals with SUDs. We used multinomial logistic regression to evaluate predictors of class membership and transitions over a five-year period. ResultsThe research team identified five distinct service use classes, including patients who disengaged from services (42.4%), or those who predominantly used outpatient substance use services (7.0%), mental health services (13.0%), primary care services (24.7%), or other specialty care services (13.1%). Being female and an older adult were statistically significant predictors for membership in any service use–driven status. Black patients had increased odds for “substance use service” and “primary care” service statuses over time. ConclusionLCA and latent transition analysis (LTA) methods are novel approaches for identifying profiles of patients with higher risk for health services disengagement. SUD treatment engagement strategies are needed to reach males, young adults, and individuals with non-opioid SUDs.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.