Implementation science communications最新文献

Background: The demand for homecare is increasing, and reducing low-value care is essential for achieving sustainable healthcare. Low-value care refers to practices that are ineffective, inefficient, unwanted, or potentially harmful to the client. This study aimed to evaluate the effects of a tailored, multifaceted de-implementation strategy in reducing low-value home-based nursing care.

Methods: A prospective, multicenter, convergent parallel mixed method design was employed, including a before-and-after study, using the Reach-Effectiveness-Adoption-Implementation-Maintenance (RE-AIM) framework. The effect of reducing low-value home-based nursing care was assessed from client records, focusing on the number of clients receiving care, minutes of care per week, frequency of visits per week, and clients no longer requiring care. The de-implementation process was evaluated qualitatively through individual interviews with de-implementation ambassadors, registered nurses, and nurse assistants, using Directed Qualitative Content Analysis. This approach served to interpret the effects of the deployment of de-implementation ambassadors and the strategies they implemented.

Results: We observed a reduction in low-value home-based nursing care, with a decrease of 130 h per week in daily showering, bathing and/or dressing; 54 h per week in the assistance with compression stockings; and 8 h per week in changing bandages enabling clients to regain their independence. Important de-implementation strategies included involving clients and relatives in decision making, organizing informational meetings for homecare professionals, and fostering collaboration with other healthcare professionals. Factors that influenced adoption included providing reassurance and using a stepwise approach with clients and relatives. Homecare professionals noted that the de-implementation ambassadors were highly committed to reducing care. De-implementation ambassadors found their role to be intense, challenging, and exciting.

Conclusions: This evaluation found that the deployment of de-implementation ambassadors, paired with additional de-implementation strategies, enhanced the reduction of low-value home-based nursing care. Providing reassurance and involving clients and their relatives were identified as beneficial for the de-implementation process.

Background: Tuberculosis (TB) poses a considerable challenge for people with HIV (PWH), especially in low- and middle-income countries. Even with the availability of effective preventive strategies such as tuberculosis preventive therapy (TPT), the implementation of these measures continues to fall short. Our study explores the perceptions of healthcare workers (HCWs) regarding the barriers and facilitators to TPT implementation in the Philippines and Indonesia.

Methods: We performed 10 focus group discussions and four in-depth interviews with HCWs from June to December 2023. Each discussion and interview lasted between 45 and 120 min. Discussions explored HCWs' perspectives on the policies, logistics, and prescribing practices related to TPT, as well as their personal experiences, concerns, and suggested improvements. Data were coded using MAXQDA24 qualitative software informed by the tenets of constructivist grounded theory. We organized themes using the Consolidated Framework for Implementation Research (CFIR), while contextualizing implementation determinants most pertinent to the local contexts.

Results: Our findings revealed nuanced barriers and facilitators-marked by paradoxes-organized across three CFIR domains: the outer, inner, and individual domains of HIV-TB care. In the outer setting, barriers include limited patient knowledge and drug shortages, while facilitators involved national policies and external pressures from mass media and peer imitation. The inner setting was shaped by structural gaps-such as poor documentation, staff turnover, and procedural challenges in ruling out active TB-that affected patient trust, whereas open communication and role clarity supported TPT implementation. At the individual level, HCWs expressed high motivation but cited limited capacity due to lack of training and information to deliver effective TPT care.

Conclusions: Our findings highlight implementation determinants to TPT implementation across outer, inner, and individual domains of HIV-TB care. Understanding how structural gaps, provider capacity, and patient trust intersect with supportive policies, and peer and mass media influences offer insights into the complex dynamics shaping TPT uptake and integration. Our study insights may inform policy adjustments and guide strategies to better integrate TPT into national health frameworks.

Background: Evidence based practices such as cognitive behavioral therapy (CBT) are often underutilized in community mental health settings. Implementation efforts can be effective in increasing CBT use among clinicians, but not all therapists successfully reach CBT competence at the end of training. Past studies have focused on how clinicians overall acquire CBT skills, rather than examining different learning trajectories that clinicians may follow and predictors of those trajectories; however, understanding of learning trajectories may suggest targets for implementation strategies.

Methods: We used growth mixture models to identity trajectories in CBT skill acquisition among clinicians (n = 812) participating in a large scale CBT training and implementation program, and examined predictors (attitudes towards EBPs, clinician burnout, professional field, educational degree level) of trajectory membership. We assessed model fit using BIC, Vuong likelihood tests, and entropy. We hypothesized that there would be at least two trajectories- one where clinicians increased in skills over time and reach CBT competence, and one with minimal increases in CBT skills that did not result in competence. We hypothesized that presence of a graduate degree, more positive attitudes towards EBPs, and lower burnout would predict more positive trajectories in CBT skill acquisition. We did not have a specific prediction for field of study and CBT skill acquisition.

Results: Clinicians followed either a progressive trajectory with steady increases in CBT skills over time, or a stagnant trajectory with minimal increases in CBT skills. Clinicians with more positive attitudes towards EBPs were 3.51 times more likely to follow a progressive trajectory, while clinicians who were in an 'Other' professional field were 0.46 times less likely to follow a progressive trajectory. Contrary to our hypotheses, educational degree and clinician burnout did not predict CBT trajectories.

Conclusion: Our results indicate that attitudes towards EBPs can be an important intervention point to improve CBT skill acquisition for therapists in training and implementation efforts. More structured support for clinicians who did not receive training in mental health focused fields may also help improve CBT learning.

Background: The overlapping epidemics of opioid use disorder (OUD) and HIV present a critical public health challenge. Although people with OUD frequently engage with healthcare settings, uptake of HIV prevention services such as pre-exposure prophylaxis (PrEP) remains low. Integrating HIV prevention into routine OUD care could reduce new infections, but scalable, evidence-based strategies are lacking. Rhode Island offers a unique opportunity to design and evaluate such strategies using its robust data infrastructure and high OUD burden.

Methods: We will conduct a three-phase, sequential implementation study. In Aim 1, we will use the Rhode Island All-Payer Claims Database and State Emergency Department Database data to identify healthcare engagement patterns and gaps in HIV prevention service delivery among people with OUD, including rates of HIV screening, PrEP use, and medications for OUD uptake, across settings from 2012 to 2022. In Aim 2, we will convene a series of five stakeholder-engaged evidence-based quality improvement panels-including with providers, policymakers, and people with lived experience-to co-develop implementation strategies tailored to each care setting (i.e., primary care, mental health clinics, emergency department, and opioid use treatment centers). Finally, in Aim 3, we will develop an agent-based model (ABM) to simulate the population-level effect of implementation strategies developed for each care setting (as identified in Aim 2). The ABM will project outcomes such as HIV incidence, cases averted, and number needed to treat (NNT) over 5- and 10-year horizons under various scenarios. Model parameters will be based on literature and findings from Aim 1. Outputs from the ABM will be used to prioritize feasible, high-impact strategies for future real-world implementation.

Discussion: This study addresses critical gaps in HIV prevention for people with OUD by combining claims-based analysis, evidence-based quality improvement, and agent-based modeling. By leveraging real-world data and engaging diverse stakeholders, the study aims to generate actionable strategies tailored to clinical settings. Findings will inform future implementation efforts in Rhode Island and other jurisdictions facing overlapping HIV and opioid epidemics.

Trial registration: This study does not meet the World Health Organization's definition of a clinical trial and, therefore, was not registered.

Background: Adverse Childhood Experiences (ACEs) screenings are increasingly being used in primary care clinics to identify toxic stress and potential trauma in children. ACEs are negative life events (e.g., violence exposure) occurring before age 18, that can increase health risks when unaddressed. However, we lack evidence on the impact of ACEs screenings and how they can be feasibly implemented in community-based clinics. We partnered with federally qualified health clinics to test the impact of a multifaceted implementation strategy on ACEs screening reach and mental health referrals for children ages 0-5.

Methods: We conducted a Hybrid Type 2 pilot trial using a stepped-wedge design (2021-2024). Reach data was measured as the proportion of eligible children screened for ACEs, with data collected from Electronic Health Records. We also assessed the percentage of mental health service referrals among all eligible children. Study clinics (n = 3) switched from no ACEs screenings (control) to implementing ACEs screenings supported by the multi-faceted ACE implementation strategy (intervention). The tested strategy comprised personnel training (e.g., trauma-informed care), integrated technology, team-based screening workflows, and ongoing care team implementation support. Additional clinics (n = 2) implemented ACEs screenings as usual without the strategy and served as additional comparison sites for exploratory analyses. Log-binomial and robust Poisson regression models examined differences in screening reach and referrals and were adjusted for site and patient race.

Results: Screening reach rates increased in the intervention period, from 0.0% of patients screened during control to 11.2% screened during intervention. Mental health service referrals increased from 0.4% at control to 7.2% during the intervention, resulting in a risk difference (95% confidence interval) of 6.9% (6.0%, 7.7%). For both the reach and referral outcomes, risk differences were significantly greater for 18-to-60-month-old patients than for patients under 18-months-old.

Discussion: Healthcare policy efforts promoting ACEs screenings in primary care are commendable. We found that a multi-faceted implementation strategy informed by partners and designed to support ACEs screenings in community-based clinics was feasible. However, its impact was attenuated by policy requirements, clinics' capacity to add ACEs screenings to strained workflows, and multiple impactful outer-context events related and unrelated to the COVID-19 pandemic.

Trial registration: Trial # NCT04916587 registered at clinicaltrials.gov on June 4, 2021, https://clinicaltrials.gov/study/NCT04916587.

Background: Despite high post-implementation adherence, clinicians may have unresolved questions or concerns regarding use of a protocol to standardize routine daily coordination of the spontaneous awakening trial (SAT) and spontaneous breathing trial (SBT) on ventilated patients. Unresolved questions or concerns may unwittingly curtail practice normalization, impacting practice sustainment when implementation support is withdrawn. The objective of this study was to identify unresolved questions or concerns that may persist following successful implementation of a coordinated SAT/SBT (C-SAT/SBT) protocol.

Methods: We used an attributed, cross-sectional survey of physicians, advanced practice providers, nurses and respiratory therapists likely to have participated in a C-SAT/SBT in 12 hospitals (15 intensive care units) in Utah and Idaho. We evaluated clinician perceptions of acceptability, including ease of use, usefulness and confidence, along with perceived practice normalization, six months post implementation of a protocol to routinize C-SAT/SBT use.

Results: C-SAT/SBT adherence was 83.1% at the 6th month post implementation. 606 clinicians completed the survey (response rate: 50.0%). Perceived individual usefulness, ease of use, and confidence using the C-SAT/SBT protocol were high [range: 72.1%-88.1% agree/strongly agree], though individuals not performing an SAT or SBT in more than six months and respiratory therapists scored lower. Perceived practice normalization was similar with 82.0% aggregate agreement [agree/strongly agree]. However, when stratifying respondents into four categories based upon respondent percentage agreement with all statements, 71% did not agree with at least one practice normalization statement and 27% agreed with less than 80% of statements, varying by role and site. Sets of observable characteristics or phenotypes regarding the degree of practice normalization begin to emerge by subgroup.

Conclusions: Unresolved questions or concerns may persist regarding implementation of a C-SAT/SBT protocol among certain population subgroups despite current high practice adherence and high levels of perceived acceptability, including ease of use, usefulness and confidence. It is not clear what impact these unresolved questions or concerns may have on practice normalization and multi-year practice sustainment systemwide, including whether targeted late post-implementation strategies are needed to mitigate concerns and promote sustainment when implementation support is withdrawn.

Background: The distinction between efficacy (performance under ideal conditions) and effectiveness (performance in real-world settings) is well established in intervention research. Intervention effectiveness is often used as a proxy for implementation readiness. However, relying on this assumption can lead to overly optimistic expectations about real-world outcomes if the complexities of routine practice settings are not adequately considered.

Main body: This paper introduces the distinction between implementation efficacy (implementation strategy performance under controlled or highly supported conditions) and implementation effectiveness (performance under typical, resource-constrained settings). We argue that the efficacy-effectiveness distinction is as critical for implementation research as it is for intervention research. Recognizing and systematically operationalizing this distinction can sharpen conceptual clarity, strengthen research design and enhance the relevance and generalizability of findings for real-world application. Yet despite its importance, this distinction is rarely made explicit in implementation studies. Research often fails to specify the conditions under which implementation strategies are investigated; studies can vary widely in how closely they reflect routine practice. Compounding this issue, economic evaluations remain uncommon in implementation research. However, without systematic assessment of resource use, it is difficult to determine whether reported implementation outcomes have been achieved through contextually feasible strategies or through intensive supports, such as dedicated staffing, external facilitation, or financial incentives, which are rarely available in everyday practice. To address this gap, we propose adapting the PRECIS-2 (Pragmatic Explanatory Continuum Indicator Summary 2) framework from clinical trials into an "Implementation PRECIS" tool. An adapted version of PRECIS-2 for implementation research could offer a systematic way to describe the extent to which a study reflects idealized conditions versus real-world practice.

Conclusion: Clarifying whether implementation strategies are studied under efficacy-like or effectiveness-like conditions enhances research design, interpretation, and communication with stakeholders. It also supports informed decisions about replication and scale-up. By embracing this distinction, implementation research can temper overly optimistic assumptions, better reflect real-world constraints, and contribute more meaningfully to evidence-based practice. We argue that making this distinction explicit is a necessary step toward a more pragmatic and transparent science of implementation.

Background: Contextual factors, or determinants, are commonly assessed in implementation studies due to their impact on the implementation process. While a substantial number of determinants have been identified, less research has examined the strength of their impact on the implementation process. Identification of key determinants, or those found to play the biggest role in the implementation process more frequently, may assist in guiding implementation of health programs and services. Damschroder & Lowery (2013) developed a rating system to assess which Consolidated Framework for Implementation Research (CFIR) constructs have the strongest impact on implementation. The purpose of this article was to systematically review articles that have utilized this rating system in order to identify key determinants.

Methods: We conducted forward citation searching of articles citing Damschroder & Lowery's (2013) rating criteria in three databases (PubMed, Web of Science, and Google Scholar) in February 2023. Included articles examined the magnitude and valence of factors affecting the implementation process. Quality appraisal was completed using the Mixed Methods Appraisal Tool (MMAT). Articles were included regardless of design, setting, location, or target population. A comprehensive examination of the determinants through numerous graphs and tables was conducted to identify key determinants.

Results: Forty-eight articles were included in the final review. Eight key determinants were identified: Leadership Engagement, Formally Appointed Internal Implementation Leaders, Compatibility, Available Resources, External Change Agents, Champions, Relative Advantage, and Key Stakeholders.

Conclusions: A more systematic approach to guiding implementation efforts will lead to the development of effective implementation strategies that could ultimately improve implementation outcomes. While quantifying qualitative data inherently removes some important nuance, by identifying key determinants, we hope to help researchers and practitioners identify which factors are likely to facilitate success of their implementation efforts.

Trial registration: The protocol for this systematic review was published with PROSPERO (CRD42023416340).

Project Extension for Community Healthcare Outcomes (Project ECHO), a telementoring intervention in which medical specialists share knowledge with medical generalists, has spread to many sites during its 22 years, reaching providers in nearly 200 countries. Based on our familiarity with the ECHO Institute, its practices, and our work with ECHO implementers at many sites, we explain the diffusion of this telehealth intervention in which medical specialists and generalist providers mentor each other in delivering specialty care to patients. We find the diffusion of Project ECHO to be well-accounted for by traditional factors including the perceived attributes of the ECHO model, the status of prominent ECHO adopters, and the inter-organizational environment within which the model arose. We also identify aspects of the ECHO model that have not always figured prominently in studies of diffusion but likely stimulated diffusion in this case. These include charismatic leadership, model elasticity, optional evaluation, and bounded elasticity. The Project ECHO experience can inform the decisions by proponents of other health care innovations to accelerate and broaden diffusion.