Reliability of Multidimensional Substance Abuse Treatment Matching

Racial and gender differences in relapse potential and treatment acceptance among rural residents in a substance use disorder treatment program

PURPOSE

To examine racial and gender differences in treatment acceptance and relapse potential among rural residents admitted to a substance use disorder (SUD) treatment program.

METHODS

A cross-sectional study using data collected from a sample of 1850 rural residents admitted to a South Carolina state-run SUD treatment center between the years of 2018 and 2020. Chi-square and t-tests were used to compare treatment acceptance and relapse potential by race and gender. Multivariate logistic regression analyses was conducted to further examine the relationship of race and gender with treatment acceptance and relapse potential after adjusting for potential confounding variables.

FINDINGS

Approximately 50% of participants were classified as being accepting of their treatment and committed to changing their substance use, and there were no racial or gender differences in the bivariate and multivariate analyses. Approximately 25% of participants were classified as having low/no potential risk for relapsing, and there were no racial or gender differences in the bivariate analysis. However, the adjusted odds ratio of relapsing risk were lower among White compared to Black adults [AOR = 0.49 with 95% CI (0.31-0.77)].

CONCLUSION

This study suggests there are no gender or racial differences in treatment acceptance for SUD but that Black adults are at greater risk of relapsing relative to White adults. Additional research is needed to identify factors that increase Black adults' risk for relapse to inform interventions that can improve SUD treatment outcomes in this population.

Thirty Years of TheASAMCriteria: A Report Card

The American Society of Addiction Medicine Criteria (ASAM) Criteria has profoundly influenced addiction treatment and reimbursement, with its growing toolkit of ASAM CONTINUUM software, ASAM-CARF Level of Care Certification Program, educational programs, and publications. A retrospective accounting shows that the field has made considerable strides, but has far to go. Providers and payers still need to (1) improve consistency in their use of standardized, multidimensional patient assessment; (2) improve flexibility in providing and reimbursing person-centered, individualized services; (3) improve measurement in treatment planning for determination of progress; and (4) focus on outcomes and value in the care they deliver.

Identifying optimal level-of-care placement decisions for adolescent substance use treatment

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.

Developing adaptive interventions for adolescent substance use treatment settings: protocol of an observational, mixed-methods project

Background

Over 1.6 million adolescents in the United States meet criteria for substance use disorders (SUDs). While there are promising treatments for SUDs, adolescents respond to these treatments differentially in part based on the setting in which treatments are delivered. One way to address such individualized response to treatment is through the development of adaptive interventions (AIs): sequences of decision rules for altering treatment based on an individual’s needs. This protocol describes a project with the overarching goal of beginning the development of AIs that provide recommendations for altering the setting of an adolescent’s substance use treatment. This project has three discrete aims: (1) explore the views of various stakeholders (parents, providers, policymakers, and researchers) on deciding the setting of substance use treatment for an adolescent based on individualized need, (2) generate hypotheses concerning candidate AIs, and (3) compare the relative effectiveness among candidate AIs and non-adaptive interventions commonly used in everyday practice.

Methods

This project uses a mixed-methods approach. First, we will conduct an iterative stakeholder engagement process, using RAND’s ExpertLens online system, to assess the importance of considering specific individual needs and clinical outcomes when deciding the setting for an adolescent’s substance use treatment. Second, we will use results from the stakeholder engagement process to analyze an observational longitudinal data set of 15,656 adolescents in substance use treatment, supported by the Substance Abuse and Mental Health Services Administration, using the Global Appraisal of Individual Needs questionnaire. We will utilize methods based on Q-learning regression to generate hypotheses about candidate AIs. Third, we will use robust statistical methods that aim to appropriately handle casemix adjustment on a large number of covariates (marginal structural modeling and inverse probability of treatment weights) to compare the relative effectiveness among candidate AIs and non-adaptive decision rules that are commonly used in everyday practice.

Discussion

This project begins filling a major gap in clinical and research efforts for adolescents in substance use treatment. Findings could be used to inform the further development and revision of influential multi-dimensional assessment and treatment planning tools, or lay the foundation for subsequent experiments to further develop or test AIs for treatment planning.

Electronic supplementary material

The online version of this article (10.1186/s13722-017-0099-4) contains supplementary material, which is available to authorized users.

An Argument for Change in Tobacco Treatment Options Guided by the ASAM Criteria for Patient Placement

Tobacco use is a major threat to public health in the United States, and the number one cause of preventable death. Although most smokers try to quit unaided, robust data indicate that pairing behavioral support to US Food Drug Administration-approved cessation medications significantly increase cessation rates. Those who do receive assistance in quitting usually receive very low intensity treatment, regardless of the severity of their dependence or their medical and environmental circumstances. This is in stark contrast to how other substance use disorders are treated, where there are varying levels of care depending on addiction severity and biopsychosocial circumstances. The American Society of Addiction Medicine (ASAM) developed a formal algorithm for assessing substance use disorders and determining the optimal level of care. The ASAM Patient Placement Criteria are regularly used to determine the appropriate level of care for all substance use disorders except tobacco. This paper will review key aspects of the ASAM dimensions of care and placement levels, with emphasis on how they apply to tobacco use and present case examples of typical smokers who would benefit from a higher intensity of tobacco dependence treatment. We also present current barriers to reimbursing healthcare providers for these services. We conclude with a commentary and discussion regarding recommendations for improvements in tobacco dependence treatment care.

Predictive validity of the ASAM Patient Placement Criteria for hospital utilization

We tested the validity of the ASAM Patient Placement Criteria (PPC) using the first complete and reliable computerized implementation of these criteria. Adult U.S. veterans (N = 95) seeking substance abuse treatment were blindly assessed for level of care need according to the PPC but were naturalistically assigned by counselors to residential rehabilitation (Level III) without knowledge of the PPC recommendation. Analyses compared subjects across three levels of recommended care, based on the algorithm, for utilization outcomes of VA hospital admissions and bed days of care. Subjects who were mismatched to lesser level of care than recommended utilized nearly twice as many hospital bed-days over the subsequent year (F (2;92) = 3.88; p < .05); this was unrelated to differential pre-assessment chronicity. The computerized algorithm is a promising new tool for facilitating field trials of the validity of the ASAM Criteria. A comprehensive implementation is an important methodologic requirement. These preliminary results support predictive validity for the ASAM Criteria, in that mismatching may be associated with excessive hospital utilization.

Feasibility of multidimensional substance abuse treatment matching: automating the ASAM Patient Placement Criteria. American Society of Addiction Medicine

The Patient Placement Criteria published by the American Society of Addiction Medicine (ASAM Criteria) established a non-proprietary standard for matching substance use disorder patients to treatment settings.

METHODS

Data from 593 substance dependent adults who were assessed using the first computerized implementation of the ASAM Criteria were analyzed to determine whether the level of care assignments showed significant differences on a variety of clinical measures.

RESULTS

The algorithm showed acceptable discrimination between each of three ASAM Levels of Care across numerous clinical subscales.

CONCLUSIONS

It is feasible to implement complex, multidimensional criteria for substance abuse treatment that may improve reliability and facilitate validity studies.