Implementation Science最新文献

Background: Providing healthcare providers (HCPs) feedback on their practice patterns and achieved outcomes is a mild to moderately effective strategy for improving healthcare quality. Best practices for providing feedback have been proposed. However, it is unknown how these strategies are implemented in practice and what their real-world effectiveness is. This scoping review addresses this gap by examining the use and reported impact of feedback reporting practices in various clinical fields.

Methods: A systematic review of the literature was conducted, and electronic databases were searched for publications in English between 2010-June 2024. We included studies that utilized and evaluated feedback reporting to change HCP behaviours and enhance outcomes, using either qualitative or quantitative designs. Two researchers reviewed and extracted data from full texts of eligible studies, including information on study objectives, types of quality indicators, sources of data, types of feedback reporting practices, and co-interventions implemented.

Results: In 279 included studies we found that most studies implemented best practices in reporting feedback, including peer comparisons (66%), active delivery of feedback (65%), timely feedback (56%), feedback specific to HCPs' practice (37%), and reporting feedback in group settings (27%). The majority (68%) combined feedback with co-interventions, such as education, post-feedback consultations, reminders, action toolboxes, social influence, and incentives. 81% showed improvement in quality indicators associated with feedback interventions. Interventions targeting outcome measures were reported as less successful than those targeting process measures, or both. Feedback interventions appeared to be more successful when supplemented with post-feedback consultations, reminders, education, and action toolboxes.

Conclusion: This review provides a comprehensive overview of strategies used to implement feedback interventions in a wide range of practice settings. Targeting process measures or combining them with outcome measures results in more positive outcomes. Additionally, feedback interventions may be slightly more effective when combined with other interventions designed to facilitate behaviour change. These findings can provide valuable insights for others wishing to implement similar interventions.

Registration: Open Science Framework, https://doi.org/10.17605/OSF.IO/GAJVS .

Background: It is important to determine the relative value of health innovations when allocating limited healthcare resources. Implementation strategies require and consume healthcare resources yet are often excluded from published economic evaluations. This paper reports on the development of a pragmatic implementation costing instrument to assist with the planning, delivery, and evaluation of digital health implementation strategies.

Methods: A modified e-Delphi process was adopted to develop an implementation costing instrument. Purposive sampling was used to recruit a panel of experts in implementation science, health economic evaluations and/or digital health from the academic, government, clinical or health service sectors. In each round, participants were sent an electronic questionnaire and a prototype of the implementation costing instrument. The prototype in the initial round was informed from a literature review and qualitative interview findings. The prototype was updated iteratively between rounds in response to the panel's feedback. In subsequent rounds, participants also received the anonymous results of items that did not reach consensus in the previous round. Termination occurred once consensus was reached on integral questions (those pertaining specifically to the instrument design) or when three rounds were completed, to prevent sample fatigue. Consensus was defined as at least 75% of experts in agreement for any item.

Results: Consensus was reached on the core components and design of the instrument from a panel of twelve experts in implementation science, health economic evaluations and/or digital health. Areas where consensus was not reached included users' level of implementation science knowledge, specificity of the tool to digital health and accessibility via digital formats.

Conclusions: Cost-IS is a pragmatic data collection instrument designed to estimate the costs of implementation strategies for digital health solutions. Further piloting of Cost-IS is required to establish its feasibility and generalisability.

Background: Approximately half of all antimicrobial prescriptions in intensive care units (ICUs) may be inappropriate, including those prescribed when not needed, in unnecessary combinations or for longer durations than needed. Inappropriate prescribing is costly, exposes patients to unnecessary side-effects and drives population-level antimicrobial resistance, the prevalence and consequences of which are greatest in low- and middle-income countries. However, the implementation of interventions to improve the appropriateness of antimicrobial prescribing has been variable and requires further study.

Methods: We propose a type III hybrid implementation/effectiveness interventional cohort trial in 35 ICUs in up to 11 low- and middle- income countries. The study intervention is a structured review of antimicrobial prescriptions as recommended by the World Health Organisation. Strategies to support stakeholder-led implementation include development of local protocols, registry-enabled audit and feedback, and education. Evaluation of implementation, and the determinants of its success, is informed by the RE-AIM framework and the Consolidated Framework for Implementation Research respectively. The primary outcome is a composite measure of fidelity, reach and adoption. Secondary outcomes describe the effectiveness of the intervention on improving antimicrobial prescribing. Qualitative interviews will assess relevant implementation acceptability, adaptations and maintenance. A baseline survey will investigate ICU-level antimicrobial stewardship structures and processes.

Discussion: This study addresses global policy priorities by supporting implementation research of antimicrobial stewardship, and strengthening associated healthcare professional competencies. It does this in a setting where improvement is sorely needed: low- and middle- income country ICUs. The study will also describe the influence of pre-existing antimicrobial stewardship structures and processes on implementation and improve understanding about the efficacy of strategies to overcome barriers to implementation in these settings.

Trial registration: This study protocol has been registered with ClinicalTrials.gov (ref NCT06666738) on 31 Oct 2004. https://clinicaltrials.gov/study/NCT06666738?term=NCT06666738&rank=1 .

Background: Rollout designs, which include stepped wedge designs, are defined by staggered implementation of new or alternative programs or services. Critiques of stepped wedge and other rollout designs have raised concerns regarding the confounding of true implementation or program effects with unrelated, global changes in service delivery, with some recommending they only be used when traditional parallel-group designs are not practicable. However, rollout designs may sometimes be more suitable than traditional parallel group designs for ethical, scientific, or practical reasons.

Results: As investigators involved in several recent rollout trials, we define and provide rationale for and examples of stepped wedge and the larger class of rollout designs, in which all participating units receive a new program or service implementation. Staged implementation in a rollout design may be necessary when denying, rather than delaying, implementation of a known effective service is ethically unacceptable. Scientifically, stepped wedge has increased statistical power relative to an equivalent parallel group design, and some rollout designs have the capability to compare different phases of implementation and sustainment. A rollout design may be practically necessary either because of limited resources and other logistical challenges or community requirements that no site serve as a control. Examples of completed and ongoing rollout trials illustrate how these ethical, scientific, and practical considerations influenced trial designs.

Conclusions: Stepped wedge and other rollout trial designs may be well suited to evaluation of implementation strategies or policy changes. In implementation trials, rollout designs may be necessary for practical reasons, may be required for ethical reasons, and may be preferred for scientific reasons. We summarize when such rollout designs have advantages and drawbacks.

Background: Implementing evidence-based parenting programs often involves navigating fidelity-adaptation decisions. While research has explored various aspects of this dilemma, little is known about how practitioners' outcome preferences influence their decisions in real-world scenarios.

Methods: This study employed a discrete choice experiment (DCE) to investigate the relative importance of five outcomes (Relationship Quality, Satisfaction, Workload Strain, Value Conflict, and Reach) in fidelity-adaptation decisions among 209 practitioners delivering evidence-based parenting programs in Sweden. The DCE presented 25 choice sets across five contextual scenarios, analyzed using Bayesian hierarchical logistic regression.

Results: All five outcomes significantly influenced practitioners' choices, with Relationship Quality emerging as the most impactful (log-odds: 4.56, 95% CI [4.16, 4.91]). Satisfaction and minimizing Value Conflict showed similar importance (log odds: 2.45 and -2.40, respectively), while Workload Strain and Reach had slightly less impact (log odds: -2.10 and 1.96, respectively).

Conclusions: This study offers a novel perspective on the role of outcome preference in navigating fidelity-adaptation decisions. The strong preference for improving parent-child relationships aligns with core parenting program goals, while consideration of other outcomes reflects practitioners' holistic approach to implementation. These findings can inform the design of interventions and implementation strategies that balance effectiveness with real-world constraints, potentially enhancing parenting programs' adoption, sustainability, and impact.

Background: This Sequential Multiple Assignment Randomized Trial (SMART) was conducted to determine minimum implementation support needed for agencies serving pregnant people on public assistance to adopt and sustain the ROSE (Reach Out, Stay Strong, Essentials for mothers of newborns) postpartum depression (PPD) prevention program.

Methods: Enrolled prenatal agencies (N=98) received thorough initial implementation support (initial training + written sustainment planning). Agencies were identified as at risk for non-sustainment within the first 15 months (N=56) were randomized to: (1) no additional implementation support (N=12), or (2) quarterly implementation support (coaching and feedback; N=44). If agencies receiving quarterly implementation supports were still at risk and within the first 15 months (N=29), they were randomized to: (1) continued quarterly support (N=14), or (2) monthly implementation support (N=15). No implementation support occurred after 18 months. Follow-ups occurred quarterly and then at 18, 24, and 30 months. Outcomes included sustainment of core program elements, agency PPD rates, reach, and costs/cost-effectiveness of each sustainment step.

Results: Twice as many agencies as expected (41 of 98; 42%) delivered ROSE with fidelity for 15+ months after receiving thorough initial implementation support only. For agencies at risk for non-sustainment, no effects of adding quarterly implementation supports were observed. However, adding monthly supports (versus quarterly) for agencies still at risk resulted in higher monthly percent of core ROSE elements sustained and more months ROSE was sustained with fidelity with large (Cohen's d = 0.73 and 0.80) effect sizes, and improved reach over 30 months. Many agencies did not consistently collect PPD rates, making results difficult to interpret. Mean implementation costs (including implementation support and agency staff time) per agency were $1,849 (SD $1,429) for agencies receiving initial implementation support only, $2,699 (SD $1,837) for those receiving initial and quarterly implementation support, and $4,059 (SD $1,763) for those receiving initial, quarterly, and ultimately monthly implementation support.

Conclusions: The cost of agency-wide ROSE implementation is far less than the cost of a single untreated case of PPD ($33,484). We suggest implementing ROSE through thorough training and written sustainment planning. For agencies not sustaining, adding monthly support can promote sustainment and improve reach.

Trial registration: Registered June 14, 2018 at clinicaltrials.gov, NCT03267563 ( https://clinicaltrials.gov/study/NCT03267563 ).

Background: Translating research into clinical practice is challenging. One implementation intervention that supports translation is employment of a change champion. It is important to understand how individuals are prepared for the change champion role. This rapid systematic review aimed to identify the education, training, and support provided to individuals in change champion roles within implementation trials.

Method: Rapid review approach. We searched the Scopus database to identify systematic reviews on champions, knowledge brokers, facilitators, and implementation support practitioners. The most recent reviews on each topic were screened to find eligible studies. To identify studies published after these reviews, we searched Medline, PsycINFO, OVID, CINAHL, ProQuest, SCOPUS, and EBSCO. We included randomised and cluster randomised controlled trials that reported on implementation interventions in healthcare settings involving a local change champion.

Results: Fifteen cluster randomised controlled trials were included. Specific champion training was provided in 12 studies (80%), but none reported incorporating adult learning principles into their education program. Some form of post-training support was reported in 11 studies (73%). Only two studies included content on behaviour or organizational change in the champion preparation program. Most programs were not individualized, and details of training and support were poorly reported.

Conclusions: Training needs and educational outcomes of change champions are poorly reported in implementation trials. Training tends not to align with adult learning. More rigorous development and reporting of programs to prepare change champions to support implementation of evidence in healthcare is recommended.

Registration: PROSPERO registration number CRD42022368276.

Background: For nearly two decades, it has been widely recognized that individuals in jail settings have a high prevalence of opioid use disorders (OUD) and are highly susceptible to fatal overdose upon their release. This setting provides a public health opportunity to address OUD with Medication for Opioid Use Disorders (MOUDs). Yet, 56% of jails do not provide MOUD, creating a pressing need for better implementation approaches in jail and the hand-off to the community. Two successful implementation strategies, NIATx external coaching and the Extension for Community Healthcare Outcomes (ECHO) case management telementoring model, were compared to address this persistent treatment gap.

Methods: This 2 × 2 design compared high (n = 12) and low (n = 4) dose coaching with and without ECHO in a 12-month intervention and 12 M sustainability period. The national trial included 25 jails and 13 community-based partners. MOUD trends for buprenorphine, methadone, injectable naltrexone, and combined MOUD between the study arms were assessed.

Results: Jail sizes ranged from 24% with < 100 and 24% with > 500 daily population, and community-based treatment providers ranged from 63% with < 50 and 7% with > 500 average monthly OUD intakes. New patient counts were found to significantly increase across the intervention phase for buprenorphine (p < .01) and combined MOUD (p < .01). Injectable naltrexone and methadone showed no consistent, significant gains. For sites with low coaching without ECHO, new patient counts for combined MOUD were predicted to increase by 47.44% during the intervention phase and 7.30% during the sustainability phase. ECHO demonstrated that MOUD use did not significantly increase compared to coaching across MOUDs in the intervention phase (p = .517). High- and low-dose coaching showed no significant differences in MOUD use during the intervention phase (p = .124).

Conclusions: Coaching emerged as a more effective implementation strategy than ECHO for increasing buprenorphine use in jail settings. In practice, ECHO sessions offered considerable overlap with coaching strategies. While high-dose coaching had greater gains for MOUDs overall than low-dose coaching, those gains were statistically insignificant, suggesting low-dose coaching to be more economical. To increase MOUD use in jail settings, jurisdictions should focus on new MOUDs so all three MOUDs are available and enhance the post-incarceration continuum of care.

Trial registration: Name of registry: ClinicalTrials.gov.

Trial registration number: NCT04363320. Date of registration: 2020-07-30. URL of trial registry record: https://clinicaltrials.gov/study/NCT04363320?term=molfenter&rank=7 .

Background: While key to interpreting findings and assessing generalizability, implementation fidelity is underreported in mobile health (mHealth) literature. We evaluated implementation fidelity of an opt-in, hybrid, two-way texting (2wT) intervention previously demonstrated to improve 12-month retention on antiretroviral therapy (ART) among people living with HIV (PLHIV) in a quasi-experimental study in Lilongwe, Malawi.

Methods: Short message service (SMS) data and ART refill visit records were used to evaluate adherence to 2wT content, frequency and duration through the lens of the Conceptual Framework for Implementation Fidelity. Message delivery and 2wT participant interactions were considered across four core 2wT components: 1) weekly motivational SMS messages; 2) proactive SMS appointment reminders; 3) SMS reminders after missed appointments; and 4) interactive messaging with 2wT staff about transfers and appointment rescheduling. Using mixed-effects logistic regression models adjusted for participant demographics, we examined the effect of core 2wT component fidelity on a) on-time appointment attendance and b) timely return to care after a missed appointment, presenting adjusted odds ratios (aORs) and 95% confidence intervals (CIs).

Results: The 468 2wT participants had a median of 52 study weeks (interquartile range [IQR] 34 - 52) with 6 ART appointments (IQR 4-7) of which 2 (IQR 1 - 3) were missed. On average, participants received a motivation message for 75% (IQR 56%-83%) of enrolled weeks, a reminder before 83% (IQR 67%-100%) of appointments, and after 67% (IQR 0%-100%) of missed appointments. Participants reported 9 transfers and rescheduled 46 appointments through 2wT prompts; 196 appointments were changed via unprompted interaction. Participants with 10% higher expected motivation message delivery were more likely to attend clinic appointments on time (aOR: 1.08; 95%CI: 1.01 - 1.16, p = 0.03). Receiving and responding to an appointment reminder in any way were also associated with increased on-time appointment attendance (aOR: 1.35; 95%CI: 1.03 - 1.79, p = 0.03 and aOR: 1.47, 95%CI: 1.16 - 1.87, p = 0.001, respectively). No associations were found for 2wT messages and timely return to care following a missed appointment.

Conclusion: Greater 2wT implementation fidelity was associated with improved care outcomes. Although implementation fidelity monitoring of mHealth interventions is complex, it should be integrated into study design.

Background: Public health nutrition interventions, including school-based programs, are a recommended approach to improve child dietary behaviours. However, the adoption of effective school-based nutrition programs face numerous challenges, including the limited evidence on effective strategies to maximise implementation and adoption of such programs. This study aimed to address this evidence gap by employing a novel collaborative network trial design to evaluate a series of implementation strategies employed by three NSW Local Health Districts, to improve school adoption of an effective school-based nutrition program ('SWAP IT').

Methods: Three independent, two arm parallel group randomised controlled trials were conducted simultaneously to examine the potential effectiveness of implementation strategies on school adoption of SWAP IT. Schools were randomised to either a high intensity (various implementation strategies), or a business as usual (minimal support) group. Measures and data collection processes were harmonised across the three trials to provide individual school-level data for planned pooled analyses. The primary outcome was school adoption of SWAP IT, objectively measured via electronic registration records. Logistic regression analyses were used to assess school adoption of SWAP IT for each trial. Meta-analyses were also conducted to pool the effects of the three trials and allow the comparison of the potential relative effects of the different strategies.

Results: A total of 287 schools were included in the study: Trial 1 (n = 164), Trial 2 (n = 64) and Trial 3 (n = 59). Relative to control, we found increased odds of adoption in Trial 1 that employed a combination of the educational materials and local facilitation strategies (OR 8.78; 95%CI 2.90, 26.56; p < 0.001), but no significant differences in adoption in Trial 2 or 3 that employed solely the educational materials strategy. Pooled data suggests the combination of educational materials and local facilitation has a greater effect on adoption compared to educational materials alone (OR 4.18; 95%CI 1.60, 10.04; n = 3 studies; indirect effect).

Conclusion: Findings of this study indicate that local facilitation is an important strategy to increase school adoption of SWAP IT, and potentially other health promotion programs.

Trial registration: The trials were prospectively registered with Australia New Zealand Clinical Trials Register: ANZCTR, ACTRN12622000257763, Registered 11/2/2022, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383515&isReview=true ANZCTR, ACTRN12622000406707, Registered 9/3/2022 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383701&isReview=true ANZCTR, ACTRN12622000252718, Registered on 11/2/2022, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383513&isReview=true.