Identifying optimal level-of-care placement decisions for adolescent substance use treatment. (1st July 2020)

• Record Type: Journal Article
• Authors: Agniel, Denis; Almirall, Daniel; Burkhart, Q.; Grant, Sean; Hunter, Sarah B.; Pedersen, Eric R.; Ramchand, Rajeev; Griffin, Beth Ann
• Is Part Of: Drug and alcohol dependence. Volume 212(2020)
• Publication Date: 2020-07-01
• Subjects: LOC level-of-care -- SUD substance use disorder -- GAIN Global Appraisal of Individual Needs -- OP outpatient -- IOP intensive outpatient -- IP inpatient/residential -- NAT no active treatment -- NOM National Outcome Measure -- SFS Substance Frequency Scale -- SPS Substance Problems Scale -- EPS Emotional Problems Scale -- STS Suicidal Thoughts Scale -- CWS Current Withdrawal Scale -- SUDS Substance Use Disorder Scale -- CI confidence interval; Adaptive methods -- Adolescent substance use -- Clinical placement guidelines -- Dynamic treatment regimes -- Observational data; Drug abuse -- Periodicals; Alcoholism -- Periodicals; 616.86
• DOI: 10.1016/j.drugalcdep.2020.107991
• Languages: English
• ISSNs: 0376-8716

Abstract

Highlights: One size does not fit all for adolescent substance use disorder treatment. No empirical basis exists to place adolescents in optimal levels of care over time. We estimate a simple, personalized placement protocol from observational data. We demonstrate the protocol's good performance on independent data. Abstract: Background: Adolescents respond differentially to substance use treatment based on their individual needs and goals. Providers may benefit from guidance (via decision rules) for personalizing aspects of treatment, such as level-of-care (LOC) placements, like choosing between outpatient or inpatient care. The field lacks an empirically-supported foundation to inform the development of an adaptive LOC-placement protocol. This work begins to build the evidence base for adaptive protocols by estimating them from a large observational dataset. Methods: We estimated two-stage LOC-placement protocols adapted to individual adolescent characteristics collected from the Global Appraisal of Individual Needs assessment tool (n = 10, 131 adolescents). We used a modified version of Q-learning, a regression-based method for estimating personalized treatment rules over time, to estimate four protocols, each targeting a potentially distinct treatment goal: one primary outcome (a composite of ten positive treatment outcomes) and three secondary (substance frequency, substance problems, and emotional problems). We compared the adaptive protocols to non-adaptive protocols using an independent dataset. Results: Intensive outpatient was recommended for all adolescents at intake for the primary outcome, while low-risk adolescents were recommended for no further treatment at followup while higher-risk patients were recommended to inpatient. Our adaptive protocols outperformed static protocols by an average of 0.4 standard deviations (95 % confidence interval 0.2−0.6) of the primary outcome. Conclusions: Adaptive protocols provide a simple one-to-one guide between adolescents' needs and recommended treatment which can be used as decision support for clinicians making LOC-placement decisions.