Predicting longitudinal service use for individuals with substance use disorders: A latent profile analysis
Journal of Substance Abuse Treatment, ISSN: 0740-5472, Vol: 132, Page: 108632
2022
- 12Citations
- 57Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations12
- Citation Indexes12
- 12
- Captures57
- Readers57
- 57
- Mentions1
- News Mentions1
- 1
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Article Description
Substance 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. The 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. The 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. LCA 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.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0740547221003585; http://dx.doi.org/10.1016/j.jsat.2021.108632; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85116396826&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/34607732; https://linkinghub.elsevier.com/retrieve/pii/S0740547221003585; https://dx.doi.org/10.1016/j.jsat.2021.108632
Elsevier BV
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