Implementation science to scale and sustain tobacco treatment leveraging point of care paradigm and health information technology

About This Grant

We propose to evaluate scale-up and sustainment strategies to promote tobacco use treatment (TUT) in cancer survivors. In a landmark study of 28 cancer centers, we learned that scale-up success is a function of both implementation strategies and clinical context. Clinic selection of implementation strategies varies, and the same strategies do not yield consistent outcomes across variable contexts. We need a rigorous comparison of commonly used strategies, knowledge on how context (and context-strategy fit) impacts scale-up and sustainment, and how to enhance scale-up and sustainment with additional strategies. In the UG3 phase, we will leverage the Practical, Robust Implementation and Sustainability Model (PRISM), a context-based extension of the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework, to adapt/refine strategies, harmonize outcomes, and establish trial feasibility across a range of clinic settings. UG3 Phase: Aim 1: Engage clinics using multilevel PRISM to identify contextual needs, core functions, and forms of strategies to scale-up and sustain TUT in a common protocol for use in the UH3. Aim 2: Establish the feasibility of a multi-stage RCT by demonstrating fidelity of strategy components, harmonized outcome availability, and refined thresholds for the successful reach of TUT. Go/no-go Threshold: To proceed to the UH3 phase, we must achieve >80% strategy fidelity, >80% outcome availability, and >15% TUT reach (based on empirical C3I data). UH3 Phase: Using a Type 3 effectiveness-implementation hybrid design, we will test strategies in a 2-stage cluster-randomized SMART trial of 72 clinics across 4 regional hubs. Stage 1 is a 4-arm cluster RCT to assess scale-up strategies. In Stage 2, non-responder clinics will proceed to a 2-arm cluster RCT to compare scale enhancement strategies. Responder clinics will undergo a 2-arm cluster RCT to compare sustainment strategies. Aim 3: Assess the effect of scale-up strategies on TUT reach and effectiveness. We hypothesize that Referral to Specialist, Point of Care, and combination will result in higher reach and effectiveness, compared to usual care. In a sub-aim, we will evaluate scale enhancement in non-responder clinics and hypothesize Precision Implementation (PI)+Biological Precision Treatment (BPT) will result in higher TUT reach, compared to PI alone. Aim 4: Test the effect of sustainment strategies on the maintenance of strategy component delivery, TUT reach, and effectiveness. We hypothesize that a clinic data-driven facilitation strategy (Precision Facilitation) will result in higher maintenance outcomes than General Facilitation. Aim 5. Examine implementation outcomes and determinants associated with comparative strategies. This proposal will develop a contextually-informed algorithm for cancer clinics in selecting optimal implementation strategies for TUT and advance implementation science in refining the strategy-context fit and metrics to inform precision efforts to scale-up and sustain TUT for cancer survivors.