The Balanced Opioid Initiative: protocol for a clustered, sequential, multiple-assignment randomized trial to construct an adaptive implementation strategy to improve guideline-concordant opioid prescribing in primary care

Quanbeck, Andrew; Almirall, Daniel; Jacobson, Nora; Brown, Randall; Landeck, Jillian; Madden, Lynn M.; Cohen, A. N.; Deyo, Brienna; Robinson, James M.; Johnson, Ryan F.; Schumacher, Nicholas

doi:10.1186/s13012-020-00990-4

Cited by 14 publications

(7 citation statements)

References 35 publications

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“…The study includes four embedded implementation strategies (Table 2), two of which were adaptive based on response to phase 1 strategies [49][50][51]. The primary aim was to test whether the least intensive strategy-REP alone-versus the adaptive implementation strategy in Fig.…”

Section: Primary and Secondary Aims And Hypothesesmentioning

confidence: 99%

“…Given that there is substantial heterogeneity in terms of implementation barriers at schools [48] and in how different schools might respond to different combinations of strategies, there is a need to develop and evaluate effective adaptive implementation strategies [49][50][51]. An adaptive implementation strategy is a sequence of decision rules used to guide implementers in selecting which combination of implementation strategies (e.g., REP, Coaching, Facilitation) to offer and when, including considerations of a school's changing needs.…”

Section: Introductionmentioning

confidence: 99%

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Primary aim results of a clustered SMART for developing a school-level, adaptive implementation strategy to support CBT delivery at high schools in Michigan

et al. 2022

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Background Schools increasingly provide mental health services to students, but often lack access to implementation strategies to support school-based (and school professional [SP]) delivery of evidence-based practices. Given substantial heterogeneity in implementation barriers across schools, development of adaptive implementation strategies that guide which implementation strategies to provide to which schools and when may be necessary to support scale-up. Methods A clustered, sequential, multiple-assignment randomized trial (SMART) of high schools across Michigan was used to inform the development of a school-level adaptive implementation strategy for supporting SP-delivered cognitive behavioral therapy (CBT). All schools were first provided with implementation support informed by Replicating Effective Programs (REP) and then were randomized to add in-person Coaching or not (phase 1). After 8 weeks, schools were assessed for response based on SP-reported frequency of CBT delivered to students and/or barriers reported. Responder schools continued with phase 1 implementation strategies. Slower-responder schools (not providing ≥ 3 CBT components to ≥10 students or >2 organizational barriers identified) were re-randomized to add Facilitation to current support or not (phase 2). The primary aim hypothesis was that SPs at schools receiving the REP + Coaching + Facilitation adaptive implementation strategy would deliver more CBT sessions than SPs at schools receiving REP alone. Secondary aims compared four implementation strategies (Coaching vs no Coaching × Facilitation vs no Facilitation) on CBT sessions delivered, including by type (group, brief and full individual). Analyses used a marginal, weighted least squares approach developed for clustered SMARTs. Results SPs (n = 169) at 94 high schools entered the study. N = 83 schools (88%) were slower-responders after phase 1. Contrary to the primary aim hypothesis, there was no evidence of a significant difference in CBT sessions delivered between REP + Coaching + Facilitation and REP alone (111.4 vs. 121.1 average total CBT sessions; p = 0.63). In secondary analyses, the adaptive strategy that offered REP + Facilitation resulted in the highest average CBT delivery (154.1 sessions) and the non-adaptive strategy offering REP + Coaching the lowest (94.5 sessions). Conclusions The most effective strategy in terms of average SP-reported CBT delivery is the adaptive implementation strategy that (i) begins with REP, (ii) augments with Facilitation for slower-responder schools (schools where SPs identified organizational barriers or struggled to deliver CBT), and (iii) stays the course with REP for responder schools. Trial registration ClinicalTrials.gov, NCT03541317, May 30, 2018.

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Section: Primary and Secondary Aims And Hypothesesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Primary aim results of a clustered SMART for developing a school-level, adaptive implementation strategy to support CBT delivery at high schools in Michigan

et al. 2022

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“…To meet the needs of all clinics, implementers need better guidance from implementation scientists on how to select and “prescribe” the choice of initial strategy(ies) with greater precision. Similarly, implementers could also benefit from guidance on how to monitor the success of strategies early on, and how to subsequently adapt or alter the strategy(ies) being offered depending on such measures of success or failure [ 67 , 68 ]. The findings also begin to point to the importance of building packages of implementation strategies that are successful at engaging clinics [ 27 , 69 , 70 ], or that monitor clinics for early signs of disengagement and then course-correct if needed.…”

Section: Discussionmentioning

confidence: 99%

Expanding access to medications for opioid use disorder in primary care clinics: an evaluation of common implementation strategies and outcomes

Cheng

McGovern

Garneau

et al. 2022

Implement Sci Commun

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Background To combat the opioid epidemic in the USA, unprecedented federal funding has been directed to states and territories to expand access to prevention, overdose rescue, and medications for opioid use disorder (MOUD). Similar to other states, California rapidly allocated these funds to increase reach and adoption of MOUD in safety-net, primary care settings such as Federally Qualified Health Centers. Typical of current real-world implementation endeavors, a package of four implementation strategies was offered to all clinics. The present study examines (i) the pre-post effect of the package of strategies, (ii) whether/how this effect differed between new (start-up) versus more established (scale-up) MOUD practices, and (iii) the effect of clinic engagement with each of the four implementation strategies. Methods Forty-one primary care clinics were offered access to four implementation strategies: (1) Enhanced Monitoring and Feedback, (2) Learning Collaboratives, (3) External Facilitation, and (4) Didactic Webinars. Using linear mixed effects models, RE-AIM guided outcomes of reach, adoption, and implementation quality were assessed at baseline and at 9 months follow-up. Results Of the 41 clinics, 25 (61%) were at MOUD start-up and 16 (39%) were at scale-up phases. Pre-post difference was observed for the primary outcome of percent of patient prescribed MOUD (reach) (βtime = 3.99; 0.73 to 7.26; p = 0.02). The largest magnitude of change occurred in implementation quality (ES = 0.68; 95% CI = 0.66 to 0.70). Baseline MOUD capability moderated the change in reach (start-ups 22.60%, 95% CI = 16.05 to 29.15; scale-ups −4.63%, 95% CI = −7.87 to −1.38). Improvement in adoption and implementation quality were moderately associated with early prescriber engagement in Learning Collaboratives (adoption: ES = 0.61; 95% CI = 0.25 to 0.96; implementation quality: ES = 0.55; 95% CI = 0.41 to 0.69). Improvement in adoption was also associated with early prescriber engagement in Didactic Webinars (adoption: ES = 0.61; 95% CI = 0.20 to 1.05). Conclusions Rather than providing an all-clinics-get-all-components package of implementation strategies, these data suggest that it may be more efficient and effective to tailor the provision of implementation strategies based on the needs of clinic. Future implementation endeavors could benefit from (i) greater precision in the provision of implementation strategies based on contextual determinants, and (ii) the inclusion of strategies targeting engagement.

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“…Findings suggested that the most cost-effective implementation support starts with a less intensive, less costly implementation strategy and increases as needed to enhance EBP uptake [ 22 ]. A SMART design is also being applied to the implementation of clinical guidelines for opioid prescribing in primary care settings, in which clinics are randomized to receive a sequence of implementation strategies that address implementation concerns at the health system, clinic, and provider levels [ 32 ]. This ongoing study aims to identify the most cost-effective sequence and combination of implementation strategies [ 32 ].…”

Section: Methodsmentioning

confidence: 99%

The economics of adaptations to evidence-based practices

Salloum

Midboe

Daniels

et al. 2022

Implement Sci Commun

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Background Evidence-based practices (EBPs) are frequently adapted in response to the dynamic contexts in which they are implemented. Adaptation is defined as the degree to which an EBP is altered to fit the setting or to improve fit to local context and can be planned or unplanned. Although adaptations are common and necessary to maximizing the marginal impact of EBPs, little attention has been given to the economic consequences and how adaptations affect marginal costs. Discussion In assessing the economic consequences of adaptation, one should consider its impact on core components, the planned adaptive periphery, and the unplanned adaptive periphery. Guided by implementation science frameworks, we examine how various economic evaluation approaches accommodate the influence of adaptations and discuss the pros and cons of these approaches. Using the Framework for Reporting Adaptations and Modifications to Evidence-based interventions (FRAME), mixed methods can elucidate the economic reasons driving the adaptations. Micro-costing approaches are applied in research that integrates the adaptation of EBPs at the planning stage using innovative, adaptive study designs. In contrast, evaluation of unplanned adaptation is subject to confounding and requires sensitivity analysis to address unobservable measures and other uncertainties. A case study is presented using the RE-AIM framework to illustrate the costing of adaptations. In addition to empirical approaches to evaluating adaptation, simulation modeling approaches can be used to overcome limited follow-up in implementation studies. Conclusions As implementation science evolves to improve our understanding of the mechanisms and implications of adaptations, it is increasingly important to understand the economic implications of such adaptations, in addition to their impact on clinical effectiveness. Therefore, explicit consideration is warranted of how costs can be evaluated as outcomes of adaptations to the delivery of EBPs.

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The Balanced Opioid Initiative: protocol for a clustered, sequential, multiple-assignment randomized trial to construct an adaptive implementation strategy to improve guideline-concordant opioid prescribing in primary care

Cited by 14 publications

References 35 publications

Primary aim results of a clustered SMART for developing a school-level, adaptive implementation strategy to support CBT delivery at high schools in Michigan

Primary aim results of a clustered SMART for developing a school-level, adaptive implementation strategy to support CBT delivery at high schools in Michigan

Expanding access to medications for opioid use disorder in primary care clinics: an evaluation of common implementation strategies and outcomes

The economics of adaptations to evidence-based practices

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