Implementation Science最新文献

Background: Implementation strategies are methods or techniques to improve the adoption, implementation, sustainment, and scale-up of evidence-based interventions. Limited guidance exists on feasible processes for selecting and tailoring implementation strategies in community (non-clinical) settings. The Implementation Strategies Applied in Communities (ISAC) compilation includes a pragmatic matching process to accompany the compilation (ISAC Match). This study expands on ISAC Match by providing additional detail and potential approaches to complete the four-step matching process, including a case study from work in a state Cooperative Extension System. IMPLEMENTATION STRATEGIES APPLIED IN COMMUNITIES MATCHING PROCESS (ISAC MATCH): ISAC Match is intended to be applied within integrated research-practice partnerships or similar models. Before beginning the ISAC Match process, participants should have identified a new or existing evidence-based intervention they are interested in integrating (or improving the integration of) and have the power and scope to influence implementation. ISAC Match includes four steps: 1) reviewing available information on evidence-based intervention integration and conducting contextual inquiry, if needed, to understand barriers and facilitators; 2) identifying existing implementation strategies used in the implementing organization, 3) using recommended guidance tools to select relevant implementation strategies to overcome barriers and capitalize on facilitators; and 4) tailoring strategies to fit within the setting they will be used in. These steps are completed with health equity considerations in mind to ensure that implementation strategies are designed to improve adoption, implementation, and maintenance in ways that seek to narrow existing health disparities. To illustrate the use of ISAC Match, this study applied the four-step ISAC Match process to select and tailor implementation strategies to increase Montana State University Extension Agents' adoption of built environment approaches that facilitate physical activity.

Conclusions: The ISAC match process was developed to apply to community settings because of a lack of guidance on rapid, relevant methods for selecting and tailoring implementation strategies to overcome barriers and capitalize on facilitators. Future work is needed to determine whether the ISAC match process is more efficient and whether results are more impactful than other matching processes that are less specific to community settings.

Background: Implementation costs-the combined costs of delivering expert support and participating in an implementation endeavor-are often omitted from economic evaluations. When included, delivery and participation costs are usually combined, even though these may be covered by different funders. We propose a pragmatic micro-costing approach that separates the delivery and participation costs as well as outlines practical considerations for measuring implementation costs.

Methods: Sixty-four specialty addiction treatment programs and primary care clinics participated in a stepped sequence of implementation strategies focused on improving access to buprenorphine and naltrexone for persons with opioid use disorder. The implementation strategies deployed were: audit and feedback (A&F), a two-day workshop, internal facilitation, and external facilitation. Our micro-costing approach separately measured the cost to deliver and participate in implementation strategies, as demonstrated through the A&F case example, which was the first of four implementation strategies deployed. We applied the following practical considerations to maximize the precision and accuracy of cost data: 1) Balance the frequency and length of cost survey, 2) Cost tracking training, 3) Regular survey reminders, 4) Tailor cost surveys, 5) Perform frequent cost data validation, 6) Iterative evaluation and refinement.

Results: In A&F, the implementation setup cost was $32,266, and the annual recurring costs were $4,231 per clinic. While the majority of the setup cost (99%) can be attributed to A&F delivery, over half of the annual recurring costs (63%) were attributed to clinic participation in A&F.

Conclusions: This micro-costing approach appears both pragmatic and meaningful. By understanding the total cost implications of implementation, decision-makers can better select the most suitable strategy based on the context, goals, and budget constraints to efficiently optimize the pace and desired outcome of an implementation endeavor.

Trial registration: The trial protocol is registered with ClinicalTrials.gov (NCT05343793).

Background: In the U.S., racial and ethnic disparities in hypertension control contribute to disparities in cardiovascular mortality. Evidence-based practices (EBPs) for improving hypertension control have not been consistently applied across patient subgroups, especially in safety-net settings, contributing to observed disparities. The Los Angeles County Department of Health Services serves racially and ethnically diverse, low-income patients with hypertension and represents a valuable setting for research to reduce disparities. We designed a hybrid Type 3 effectiveness-implementation study using a three-arm, crossover randomized controlled trial to compare the effects of patient- and provider-focused strategies and usual implementation strategy on key implementation and clinical outcomes.

Methods: We will enroll 27 primary care clinics. Patient-focused implementation strategies aim to increase patient access to culturally and linguistically tailored educational materials on hypertension and improve patient engagement in hypertension care. Provider-focused strategies include training in culturally tailored hypertension care and activities to strengthen clinic workflows for home blood pressure monitoring, medication titration, referral to nurse-directed blood pressure clinics, and social needs screening and referral. Implementation facilitators provide support for these EBPs. The primary implementation outcome is provider EBP adoption clustered at the clinic level, based on a scoring system using medical records, clinic observation, and webinar participation. The primary health-related outcome is the proportion of patients in a clinic with controlled hypertension by race and ethnicity. We will use the constrained generalized Poisson mixed-effects model to compare changes in event rate of provider EBP adoption between usual implementation strategy and either provider- or patient-focused strategies. We will use constrained logistic mixed-effects models to assess the effect on change in blood pressure control. We will record implementation progress using the Stages of Implementation Completion tool and identify costs and resource use using the Cost of Implementing New Strategies tool.

Discussion: Our study contributes to the implementation science literature on cardiovascular health equity by examining alternative implementation strategies to increase use of culturally and linguistically tailored hypertension EBPs and social needs screening and intervention. Findings from our study will build evidence for implementation of hypertension EBPs in safety-net and other health systems serving racial and ethnic minority patients.

Trial registration: Clinicaltrials.gov NCT06359691, registered April 10, 2024.

Background: Implementation scientists increasingly recognize the value of multiple strategies to improve the adoption, fidelity, and scale up of an evidence-based intervention (EBI). However, with this recognition comes the need for alternative and innovative methods to ensure that the package of implementation strategies work well within constraints imposed by the need for affordability, scalability, and/or efficiency. The aim of this article is to illustrate that this can be accomplished by integrating principles of intervention optimization into implementation science.

Method: We use a hypothetical example to illustrate the application of the multiphase optimization strategy (MOST) to develop and optimize a package of implementation strategies designed to improve clinic-level adoption of an EBI for smoking cessation.

Results: We describe the steps an investigative team would take using MOST for an implementation science study. For each of the three phases of MOST (preparation, optimization, and evaluation), we describe the selection, optimization, and evaluation of four candidate implementation strategies (e.g., training, treatment guide, workflow redesign, and supervision). We provide practical considerations and discuss key methodological points.

Conclusion: Our intention in this methodological article is to inspire implementation scientists to integrate principles of intervention optimization in their studies, and to encourage the continued advancement of this integration.

Background: Despite substance use disorders (SUD) being a leading cause of preventable death in the US, most people who visit primary care in the US are not screened for SUD. There are multiple barriers to screening for, identifying, and managing SUD in primary care. However, there are also promising strategies available to address these barriers, including practice facilitation (PF), learning collaboratives (LC), and performance incentives (PI).

Methods: This study is a 48-site cluster-randomized 2 × 2 factorial implementation trial that aims to compare the effectiveness of several strategies for implementing evidence-based screening and interventions for SUDs in primary care. Practices will be randomized to one of four implementation strategies: (1) PF only, (2) PF + LC, (3) PF + PI, or (4) all three strategies. An estimated 144 participants from 48 primary care practices will be enrolled. All participants will receive PF to guide them in making changes to implement screening for SUD, focusing on a defined change package and associated tools. PF includes quality improvement (QI) coaching, as well as electronic health record (EHR) support, training, and expert consultation. LC includes monthly virtual education sessions led by content experts to support practice improvement and innovation with didactics on key topics as well as facilitating participant interactions to share experiences. PI includes financial incentives for performance. Primary care practices will be the unit of analysis for both the primary outcome (rate of SUD screening) and secondary outcomes (rates of evidence-based interventions for SUD). Assessments will be conducted during a 12-month implementation phase and 12-month sustainment phase.

Discussion: This study will produce evidence regarding the comparative effectiveness of several strategies on implementation and sustainment of evidence-based screening and interventions for SUD within primary care. It will also generate knowledge about mechanisms of change in primary care settings. The results are expected to have a positive impact by providing a nuanced understanding of the incremental benefits of LC and/or PI to inform primary care practices, health systems, policymakers, and payers about optimal implementation strategies for SUD screening and evidence-based interventions.

Trial registration: ClinicalTrials.gov NCT06524232. July 23, 2024 -registered.

Background: The Consolidated Framework for Implementation Research (CFIR) is a determinant framework that includes constructs from many implementation theories, models, and frameworks; it is used to predict or explain barriers and facilitators to implementation success. CFIR is among the most widely applied implementation science frameworks, and after 15 years of use in the field, the framework was updated based on user feedback obtained via literature review and survey. Dissemination of the updated CFIR and accompanying outcomes addendum resulted in hundreds of requests from users for further guidance in applying the framework. In addition, observations of potential and actual misuse of CFIR in grant reviews and published manuscripts were the catalyst for the development of this user guide. As a result, the objective of this article is to provide a user guide and essential tools and templates for using CFIR in implementation research.

Methods: This user guide was generated from the combined wisdom and experience of the CFIR Leadership Team, which includes the lead developers of the original and updated CFIR (LJD, CMR), and has collectively used CFIR in more than 50 projects. The five steps as well as the tools and templates were finalized via consensus discussions.

Results: The five steps below guide users through an entire research project using CFIR and include 1) Study Design; 2) Data Collection; 3) Data Analysis; 4) Data Interpretation; and 5) Knowledge Dissemination. In addition, the article provides a Frequently Asked Questions (FAQs) section based on user queries and six tools and templates: 1) CFIR Construct Example Questions; 2) CFIR Construct Coding Guidelines; 3) Inner Setting Memo Template; 4) CFIR Construct Rating Guidelines; 5) CFIR Construct x Inner Setting Matrix Template; and 6) CFIR Implementation Research Worksheet.

Conclusion: This user guide details how to use CFIR in implementation research, from the design of the study through dissemination of findings, answers frequently asked questions, and offers essential tools and templates. We hope this guidance will facilitate appropriate and consistent application of the framework as well as generate feedback and critique to advance the field.

Background: Screening for gastrointestinal (GI) cancers, specifically colorectal cancer (CRC) and hepatocellular carcinoma (HCC), is often inadequately and inequitably implemented, leading to preventable morbidity and mortality. This protocol paper describes a study designed to compare the effectiveness of external facilitation with patient navigation across hospitals in the Veterans Health Administration (VA).

Methods: Two hybrid type 3, cluster-randomized trials will compare the effectiveness of patient navigation versus external facilitation for supporting HCC and CRC screening completion. Twenty-four sites will be included in the HCC trial and 32 in the CRC trial, cluster-randomizing Veterans by their site of primary care. The primary outcome of reach of cancer screening completion will be measured after intervention and during sustainment. Multi-level implementation determinants (i.e., barriers and facilitators), preconditions, and moderators will be evaluated pre- and post-intervention, using Consolidated Framework for Implementation Research (CFIR)-mapped surveys and interviews of Veteran participants and provider participants.

Discussion: Comparing findings in the two trials will allow researchers to understand how implementation barriers and strategies operate differently for a one-time screening in a relatively healthy population (CRC) vs. repeated screening in a more medically complex population (HCC).

Trial registration: This project was registered at ClinicalTrials.Gov (NCT06458998) on 6/13/24.

Background: Community-engaged research (CER) leverages knowledge, insights, and expertise of researchers and communities to address complex public health challenges and improve community well-being. CER fosters collaboration throughout all research phases, from problem identification and implementation to evaluation. Artificial Intelligence (AI) could enhance the collaborative process by improving data collection, analysis, insight, and engagement, while preserving research ethics. By integrating AI into CER, researchers could enhance their capacity to work collaboratively with communities, making research more efficient, inclusive, and impactful. However, careful consideration must be given to the ethical and social implications of AI to ensure that it supports the goals of CER. This paper introduces the PRISM-Capabilities model for AI to promote a human-centered approach that emphasizes collaboration, transparency, and inclusivity when using AI within CER.

Methods: The PRISM-Capabilities model for AI includes six components to ensure that ethical concerns are addressed, trust and transparency are maintained, and communities are equipped to use and understand AI technology. This conceptual model is specifically tailored for community-engaged implementation science research, facilitating close collaboration between researchers and community partners to guide the use of AI throughout. This paper also proposes next steps to validate the model using the HEALing Communities Study (HCS), the largest community-engaged research study to date, which aimed to reduce fatal overdose deaths in 67 highly impacted communities in the United States.

Case study: The PRISM-Capabilities model consists of six components: Optimizing engagement of implementers, settings, and recipients; characteristics of intervention implementers, settings, and recipients; equity assessment and risk management; implementation and sustainability infrastructure; external environment; and ethical assessment and evaluation. Although AI was not initially used during the HCS, we highlight how AI will be leveraged to complete post-hoc analyses of each of the six components and validate the PRISM-Capabilities model.

Conclusion: The application of AI to CER relies on human-centered principles that prioritize human-AI collaboration, allowing for the operationalization of responsible AI practices. The PRISM-Capabilities model provides a framework to account for the complexities of real-world social science problems and explicitly positions AI tools at bottlenecks experienced with conventional approaches.

Background: Incomplete or delayed implementation of Guidelines can lead to potentially avoidable medication-related harm. All Australian residential aged care facilities (RACFs) are recommended to have access to a multidisciplinary medication advisory committee (MAC) to provide clinical governance of medication management. The objective of this trial is to evaluate the effectiveness and relative net benefit of using knowledge brokers, supported by a national quality improvement collaborative, to implement Australia's new Guiding Principles for Medication Management in Residential Aged Care Facilities (Guiding Principles).

Methods: The Maximising Embedded Pharmacists in AGed CAre Medication Advisory Committees (MEGA-MAC) trial will be conducted in partnership with RACFs operated by three aged care provider organizations across four states of Australia. The intervention will involve knowledge broker dyads (pharmacist plus a MAC representative [e.g. nurse]) developing, implementing and evaluating RACF-specific local action plans to implement the Guiding Principles in up to 15 RACFs. Knowledge broker dyads will be supported by a national quality improvement collaborative (MEGA-MAC collaborative) comprising clinical experts, implementation scientists and resident and caregiver representatives. An interrupted time series design will be used to assess change over time with three pre-intervention (-6, -3 and 0 months) and three post-intervention assessment time points (+ 3, + 6, + 9 months). The primary outcome will be change in pre/post RACF-level concordance with the Guiding Principles measured using quality indicators (score 0 to 28, higher scores = greater concordance). A net benefit analysis will be conducted to examine the relative costs and benefits of implementing the intervention.

Discussion: The MEGA-MAC trial investigates a novel multifactorial knowledge translation strategy to improve the uptake of guidelines and support safe and appropriate use of medication in RACFs. We anticipate that the findings will provide new information on the role of healthcare professionals as knowledge brokers, MACs, and quality improvement collaboratives for effective guideline implementation in RACFs.

Ethics and dissemination: Ethics approval obtained from Monash University and Grampians Health Human Research Ethics Committees. Findings will be disseminated through professional and lay media, conference presentations and peer-reviewed publications. TRIAL REGISTRATION : Australian New Zealand Clinical Trial Registry (ANZCTR): ACTRN12624000894594. Registered 22nd July 2024 - Prospectively registered. https://www.anzctr.org.au/ACTRN12624000894594.aspx.

Background: As implementation science evolves, it is essential to expand training capacity to build intellectual capital continually. The demand for training in implementation science far outstrips the current supply. This paper presents the methods and findings from the Institute for Implementation Science Scholars (IS-2) national training program (2020-2024).

Methods: The IS-2 was a US-based, two-year training program that provided mentored training for early- and mid-career researchers interested in applying implementation science principles to reduce the burden of chronic disease disparities. Scholars attended two annual, 2.5-day intensive training sessions, received ongoing remote and in-person mentoring, and were supported by other activities (e.g., pilot funding, networking events, mock grant reviews). A quasi-experimental (pre/post) design evaluated IS-2 on skill building, mentoring, and networking. We used descriptive and inferential statistics to characterize the sample and analyzed primary outcomes and networks.

Results: A majority of the 59 scholars were female (86%), white (61%), and assistant professors (61%). Forty-three implementation science competencies were assessed; all skill categories increased from baseline to 10 months and from 10 to 22 months post-enrollment. The relative change was largest for advanced competencies. Scholars rated their assigned mentors as highly competent across all mentoring competencies. A vibrant mentoring network was established, with the highest number of network ties in 2023, facilitating manuscript publication and joint research. Under-represented scholars (n = 21) had similar skill gains relative to scholars not-under represented, yet were less likely to hold network ties in 2024. After accounting for other predictors, sharing a mentoring relationship within the previous two years was a strong positive predictor of forming collaboration ties between network members in 2024 (odds ratio = 9.66; 95% confidence interval = 6.34-14.74). IS-2 showed multiple impacts of practice and societal relevance (e.g., improving intervention reach, building cost data in patient decision aids).

Conclusions: The approaches used in IS-2 effectively helped mentees gain skills in implementation science, experience mentorship for career development, and establish collaborative networks. The results demonstrate how the field can develop and utilize a mentoring program to reach diverse scholars, incorporate equity into curricula, and conduct high-quality mentoring to address critical implementation science topics.