Daniel Almirall

Background: Despite the potential for Early Care and Education (ECE) settings to promote healthy habits, a gap exists between current practices and evidence-based practices (EBPs) for obesity prevention in childhood.Methods: We will use an enhanced non-responder trial design to determine the effectiveness and incremental cost-effectiveness of an adaptive implementation strategy for Together, We Inspire Smart Eating (WISE), while examining moderators and mediators of the strategy effect. WISE is a curriculum that aims to increase children’s intake of carotenoid-rich fruits and vegetables through four evidence-based practices in the early care and education setting. In this trial, we will randomize sites that do not respond to low-intensity strategies to either (a) continue receiving low-intensity strategies or (b) receive high-intensity strategies. This design will determine the effect of an adaptive implementation strategy that adds high-intensity versus one that continues with low-intensity among non-responder sites. We will also apply explanatory, sequential mixed methods to provide a nuanced understanding of implementation mechanisms, contextual factors, and characteristics of sites that respond to differing intensities of implementation strategies. Finally, we will conduct a cost effectiveness analysis to estimate the incremental effect of augmenting implementation with high-intensity strategies compared to continuing low-intensity strategies on costs, fidelity, and child health outcomes.Discussion: We expect our study to contribute to an evidence base for structuring implementation support in real-world ECE contexts, ultimately providing a guide for applying the adaptive implementation strategy in ECE for WISE scale-up. Our work will also provide data to guide implementation decisions of other interventions in ECE. Finally, we will provide the first estimate of relative value for different implementation strategies in this setting.Trial registration: NCT05050539; 9/20/21.

Background: Rates of opioid prescribing tripled in the USA between 1999 and 2015 and were associated with significant increases in opioid misuse and overdose death. Roughly half of all opioids are prescribed in primary care. Although clinical guidelines describe recommended opioid prescribing practices, implementing these guidelines in a way that balances safety and effectiveness vs. risk remains a challenge. The literature offers little help about which implementation strategies work best in different clinical settings or how strategies could be tailored to optimize their effectiveness in different contexts. Systems consultation consists of (1) educational/engagement meetings with audit and feedback reports, (2) practice facilitation, and (3) prescriber peer consulting. The study is designed to discover the most cost-effective sequence and combination of strategies for improving opioid prescribing practices in diverse primary care clinics. Methods/design: The study is a hybrid type 3 clustered, sequential, multiple-assignment randomized trial (SMART) that randomizes clinics from two health systems at two points, months 3 and 9, of a 21-month intervention. Clinics are provided one of four sequences of implementation strategies: a condition consisting of educational/engagement meetings and audit and feedback alone (EM/AF), EM/AF plus practice facilitation (PF), EM/AF + prescriber peer consulting (PPC), and EM/AF + PF + PPC. The study’s primary outcome is morphine-milligram equivalent (MME) dose by prescribing clinicians within clinics. The study’s primary aim is the comparison of EM/AF + PF + PPC versus EM/AF alone on change in MME from month 3 to month 21. The secondary aim is to derive cost estimates for each of the four sequences and compare them. The exploratory aim is to examine four tailoring variables that can be used to construct an adaptive implementation strategy to meet the needs of different primary care clinics. Discussion: Systems consultation is a practical blend of implementation strategies used in this case to improve opioid prescribing practices in primary care. The blend offers a range of strategies in sequences from minimally to substantially intensive. The results of this study promise to help us understand how to cost effectively improve the implementation of evidence-based practices. Trial registration: NCT 04044521 (ClinicalTrials.gov). Registered 05 August 2019.

Background Rates of opioid prescribing tripled in the United States between 1999 and 2015 and were associated with significant increases in opioid misuse and overdose death. Roughly half of all opioids are prescribed in primary care. Although clinical guidelines describe recommended opioid prescribing practices, implementing these guidelines in a way that balances safety and effectiveness vs. risk remains a challenge. The literature offers little help about which implementation strategies work best in different clinical settings or how strategies could be tailored to optimize their effectiveness in different contexts. Systems consultation consists of: (1) educational/engagement meetings with audit and feedback reports, (2) practice facilitation, and (3) prescriber peer consulting. The study is designed to discover the most cost-effective sequence and combination of strategies for improving opioid prescribing practices in diverse primary care clinics.Methods/Design The study is a hybrid type 3 clustered, sequential, multiple-assignment randomized trial (SMART) that randomizes clinics from two health systems at two points, months 3 and 9, of a 21-month intervention. Clinics are provided one of four sequences of implementation strategies: a condition consisting of educational/engagement meetings and audit and feedback alone (EM/AF), EM/AF plus practice facilitation (PF), EM/AF + prescriber peer consulting (PPC), and EM/AF + PF + PPC. The study’s primary outcome is morphine-milligram equivalent (MME) dose by prescribing clinicians within clinics. The study’s primary aim is the comparison of EM/AF + PF + PPC versus EM/AF alone on change in MME from month 3 to month 21. The secondary aim is to derive cost estimates for each of the four sequences and compare them. The exploratory aim is to examine four tailoring variables that can be used to construct an adaptive implementation strategy to meet the needs of different primary care clinics.Discussion Systems consultation is a practical blend of implementation strategies used in this case to improve opioid prescribing practices in primary care. The blend offers a range of strategies in sequences from minimally to substantially intensive. The results of this study promise to help us understand how to cost effectively improve the implementation of evidence-based practices.Trial registration NCT 04044521 (ClinicalTrial.gov). Registered 05 August 2019.

Dynamic treatment regimes (DTRs) are sequences of treatment decision rules, in which treatment may be adapted over time in response to the changing course of an individual. Motivated by the substance use disorder (SUD) study, we propose a tree-based reinforcement learning (T-RL) method to directly estimate optimal DTRs in a multi-stage multi-treatment setting. At each stage, T-RL builds an unsupervised decision tree that directly handles the problem of optimization with multiple treatment comparisons, through a purity measure constructed with augmented inverse probability weighted estimators. For the multiple stages, the algorithm is implemented recursively using backward induction. By combining semiparametric regression with flexible tree-based learning, T-RL is robust, efficient and easy to interpret for the identification of optimal DTRs, as shown in the simulation studies. With the proposed method, we identify dynamic SUD treatment regimes for adolescents.

Organizational culture and climate are considered key factors in implementation efforts but have not been examined as moderators of implementation strategy comparative effectiveness. We investigated organizational culture and climate as moderators of comparative effectiveness of two sequences of implementation strategies (Immediate vs. Delayed Enhanced Replicating Effective Programs [REP]) combining Standard REP and REP enhanced with facilitation on implementation of an outreach program for Veterans with serious mental illness lost to care at Veterans Health Administration (VA) facilities nationwide. This study is a secondary analysis of the cluster-randomized Re-Engage implementation trial that assigned 3075 patients at 89 VA facilities to either the Immediate or Delayed Enhanced REP sequences. We hypothesized that sites with stronger entrepreneurial culture, task, or relational climate would benefit more from Enhanced REP than Standard REP. Veteran- and site-level data from the Re-Engage trial were combined with site-aggregated measures of entrepreneurial culture and task and relational climate from the 2012 VA All Employee Survey. Longitudinal mixed-effects logistic models examined whether the comparative effectiveness of the Immediate vs. Delayed Enhanced REP sequences were moderated by culture or climate measures at 6 and 12 months post-randomization. Three Veteran-level outcomes related to the engagement with the VA system were assessed: updated documentation, attempted contact by coordinator, and completed contact. For updated documentation and attempted contact, Veterans at sites with higher entrepreneurial culture and task climate scores benefitted more from Enhanced REP compared to Standard REP than Veterans at sites with lower scores. Few culture or climate moderation effects were detected for the comparative effectiveness of the full sequences of implementation strategies. Implementation strategy effectiveness is highly intertwined with contextual factors, and implementation practitioners may use knowledge of contextual moderation to tailor strategy deployment. We found that facilitation strategies provided with Enhanced REP were more effective at improving uptake of a mental health outreach program at sites with stronger entrepreneurial culture and task climate; Veterans at sites with lower levels of these measures saw more similar improvement under Standard and Enhanced REP. Within resource-constrained systems, practitioners may choose to target more intensive implementation strategies to sites that will most benefit from them. ISRCTN: ISRCTN21059161 . Date registered: April 11, 2013.

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. 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. 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.

Policy is a powerful motivator of clinical change, but implementation success can depend on organizational characteristics. This article used validated measures of organizational resources, culture, and climate to predict uptake of a nationwide Veteran's Health Administration (VA) policy aimed at implementing Re-Engage, a brief care management program that reestablishes contact with veterans with serious mental illness lost to care. Patient care databases were used to identify 2738 veterans lost to care. Local recovery coordinators (LRCs) were to update disposition for 2738 veterans at 158 VA facilities and, as appropriate, facilitate a return to care. Multivariable regression was used to assess organizational culture and climate as predictors of early policy compliance (via LRC presence) and uptake at 6 months. Higher composite climate and culture scores were associated with higher odds of having a designated LRC but were not predictive of higher uptake. Sites with LRCs had significantly higher rates of updated documentation than sites without LRCs.