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Comparing a standard and tailored approach to scaling up an evidence-based intervention for antiretroviral therapy for people who inject drugs in Vietnam: study protocol for a cluster randomized hybrid type III trial

Abstract

Background

People who inject drugs (PWID) bear a disproportionate burden of HIV infection and experience poor outcomes. A randomized trial demonstrated the efficacy of an integrated System Navigation and Psychosocial Counseling (SNaP) intervention in improving HIV outcomes, including antiretroviral therapy (ART) and medications for opioid use disorder (MOUD) uptake, viral suppression, and mortality. There is limited evidence about how to effectively scale such intervention. This protocol presents a hybrid type III effectiveness-implementation trial comparing two approaches for scaling-up SNaP. We will evaluate the effectiveness of SNaP implementation approaches as well as cost and the characteristics of HIV testing sites achieving successful or unsuccessful implementation of SNaP in Vietnam.

Methods

Design: In this cluster randomized controlled trial, two approaches to scaling-up SNaP for PWID in Vietnam will be compared. HIV testing sites (n = 42) were randomized 1:1 to the standard approach or the tailored approach. Intervention mapping was used to develop implementation strategies for both arms. The standard arm will receive a uniform package of these strategies, while implementation strategies for the tailored arm will be designed to address site-specific needs.

Participants: HIV-positive PWID participants (n = 6200) will be recruited for medical record assessment at baseline; of those, 1500 will be enrolled for detailed assessments at baseline, 12, and 24 months. Site directors and staff at each of the 42 HIV testing sites will complete surveys at baseline, 12, and 24 months.

Outcomes: Implementation outcomes (fidelity, penetration, acceptability) and effectiveness outcomes (ART, MOUD uptake, viral suppression) will be compared between the arms. To measure incremental costs, we will conduct an empirical costing study of each arm and the actual process of implementation from a societal perspective. Qualitative and quantitative site-level data will be used to explore key characteristics of HIV testing sites that successfully or unsuccessfully implement the intervention for each arm.

Discussion

Scaling up evidence-based interventions poses substantial challenges. The proposed trial contributes to the field of implementation science by applying a systematic approach to designing and tailoring implementation strategies, conducting a rigorous comparison of two promising implementation approaches, and assessing their incremental costs. Our study will provide critical guidance to Ministries of Health worldwide regarding the most effective, cost-efficient approach to SNaP implementation.

Trial registration

NCT03952520 on Clinialtrials.gov. Registered 16 May 2019.

Background

People who inject drugs (PWID) bear a disproportionate burden of HIV infection. Globally, approximately 1.4 million PWID live with HIV, and the prevalence of HIV among PWID has been estimated to be 12.7% [1]. PWID with HIV have high mortality rates compared with their non-drug using counterparts [2]. The mortality difference is largely driven by delayed diagnosis, low uptake, and adherence to antiretroviral therapy (ART) [3]. Most PWID have not been tested for HIV; in some geographic areas, less than 2% of PWID have been tested [4]. In countries with available data, ART coverage among HIV-positive PWID is only 5–67% of PWID living with HIV [1]. PWID lack access to HIV care, medications for opioid use disorder (MOUD), and harm reduction services and limited skills to navigate complex health care systems [4,5,6,7,8]. They also face persistent social barriers, such as stigma and punitive legal systems [5].

Vietnam is a prime country example of an HIV epidemic that has been primarily driven by injection drug use. Vietnam has over 271,000 PWID in the country [9] with an HIV prevalence among PWID in different provinces ranging from 17 to 25% [10,11,12]. In 2014, the 90-90-90 targets were launched by the Joint United Nations Programme on HIV/AIDS: 90% of all people living with HIV will know their HIV status; 90% of all people with diagnosed HIV infection will receive sustained antiretroviral therapy, and 90% of all people receiving antiretroviral therapy will have viral suppression [13]. Vietnam was the first Asian country to commit to the World Health Organization’s 90-90-90 targets [14], but reaching these targets will require significant efforts to prevent and treat HIV among PWID. Moreover, since funding from international donors for HIV research has dramatically decreased within the last few years [15, 16], it is even more critical for the Vietnamese government to implement effective and cost-efficient HIV interventions.

From 2015 to 2018, we conducted the HIV Prevention Network Trial 074 (HPTN074)—a multi-site study to evaluate the feasibility and efficacy of an integrated systems navigation and psychosocial counseling (SNaP) intervention for HIV-positive PWID on ART use, viral suppression, and MOUD use in Vietnam, Indonesia, and Ukraine [17]. Among PWID with HIV, SNaP led to marked improvements in ART uptake and use, viral suppression, MOUD uptake and use, and mortality [17]. SNaP has potential to curb the epidemic among PWID, but first it needs to be scaled-up to reach a broader population.

Scaling-up evidence-based interventions (EBIs) is often impeded by barriers at different levels, such as constrained budgets, lack of support policies, lack of qualified leaders, and staff as well as cultural resistance to new practice [18, 19]. In reality, EBIs such as SNaP often languish on a shelf or are implemented without careful consideration of barriers in routine care settings [20]. Many countries have recently scaled-up HIV testing and counseling and ART throughout their countries [4, 6] using national level decrees [5, 7]. This top-down, one-size-fits-all decree approach successfully reached many people with HIV [21,22,23] but has failed to reach PWID [4, 21,22,23]. The limited success among PWID may be because the national implementation strategy does not address key country-wide barriers or because the implementation approach failed to consider variation by risk groups and clinics. For example, despite the well-documented effectiveness of EBIs such as needle/syringe programs and opioid substitution treatment, the coverage of these EBIs still remained very low among PWID in many parts of the world [4]. This is partly due to policing practices and laws criminalizing drug use and possession implemented by local authorities, which could vary by country, state, or even city [24].

There is a need to identify and evaluate systematic approaches to scaling-up and sustaining EBIs such as SNaP [19, 25, 26], as the best approach to implementing and scaling up such efficacious interventions for PWID in real-world settings is unclear [4, 20]. Scaling-up EBIs will likely require the use of multiple implementation strategies that effectively address multi-level determinants (i.e., barriers and facilitators) of implementation and scale-up [27,28,29]. Implementation strategies are “methods or techniques used to enhance the adoption, implementation, sustainment, or scale-up of interventions” [28]. The lack of systematic approaches to developing implementation strategies can lead to failed implementation efforts and make them difficult to replicate in other settings [30, 31]. A number of approaches that integrate theory, evidence, and relevant stakeholder perspectives to systematically design and tailor implementation strategies have been identified [32, 33], including intervention mapping (IM) [34,35,36]. Recent guidance clarifies IM’s role in implementation science by describing how it can be used to adapt interventions and develop implementation strategies [34], and a study underway is examining its potential utility as a method for tailoring implementation strategies at the organizational level [25].

IM applied at the national level may suffice to produce an appropriate national implementation package for SNaP scale up. But implementation determinants at specific HIV testing sites may impede this approach. Thus, it may be useful to apply methods that will help to tailor implementation approaches to address site-specific needs. Tailoring strategies to address contextual needs has face validity [37] and has been shown to be effective at improving health practices [38], but rigorous evaluations that test methods for tailoring strategies and compare tailored and standard multifaceted strategies are needed [28, 32, 38, 39]. Moreover, since the scale up of interventions might be costly and various interventions usually compete for resources and attention from stakeholders [40], evidence of the costs in conjunction with effectiveness of implementation approaches is also required, especially in settings where resources are limited. However, the quantity and quality of economic evaluations of implementation studies remain inadequate [40, 41]. In a systematic review and critical appraisal of health economic methods in implementation research, only 3 (10%) among all studies included were conducted in low- and middle-income countries [40].

To close these gaps, this cluster randomized trial will compare a standard multifaceted approach to implementation to a tailored approach that involves the identification of site-specific determinants combined with implementation facilitation that will help sites identify and apply appropriate implementation strategies. We hypothesize that, compared to the standard approach, the tailored approach will (a) increase site fidelity to SNaP, (b) increase ART uptake among PWID, and (c) be cost-effective. Our specific aims are the following:

  1. 1.

    To compare the standard approach with the tailored approach for scaling-up the integrated intervention, SNaP, for PWID in HIV testing sites in Vietnam.

  2. 2.

    To measure the incremental costs of the standard approach compared with the tailored approach for SNaP implementation in Vietnam.

  3. 3.

    To explore the key characteristics of high- and low-performing HIV testing sites for SNaP implementation in each study arm.

In this protocol paper, we present the conceptual framework, study design, and randomization scheme of the study. We also describe the participants, intervention approaches, outcomes, data collection, and analysis. Finally, we discuss the strengths and weaknesses of the trial, as well as the priorities in the field of implementation science that it addresses. We followed the STARi checklist for implementation intervention [42] and the CONSORT checklist for cluster randomized controlled trial [43] (Additional file 1).

Methods

Guiding conceptual frameworks

As specified in the conceptual framework (Fig. 1), both standard and tailored implementation approaches are expected to have an effect on SNaP implementation. High acceptability, fidelity, penetration of SNaP implementation will lead to better effectiveness outcomes such as ART uptake, MOUD uptake, and viral suppression. The study is guided by conceptual frameworks to inform implementation processes (intervention apping) [36], identify implementation barriers, and facilitators (Consolidated Framework for Implementation Research; CFIR) [45], and assess implementation outcomes [44, 46]. IM provides a systematic process to yield standard and tailored approaches to implementation. CFIR is a comprehensive framework that identifies 39 different factors in five domains that influence implementation outcomes. In this study, we focus primarily on one of the five CFIR domains, the “inner setting,” defined as the clinic or organizational context in which the intervention will exist [47]. We will measure the inner setting characteristics that influence implementation of SNaP and are likely to vary across sites. These include the age and size of the test site; norms of the test site; organizational readiness to change; implementation leadership, and implementation climate [45, 48,49,50,51]. We hypothesize that tailoring implementation strategies to address test site context will improve test site context and lead to better implementation and effectiveness outcomes. The implementation outcomes framework [44] guides our assessment of key implementation outcomes: acceptability, fidelity, penetration, and cost. The effectiveness of SNaP scale-up will be assessed by the implementation processes as operationalized through both arms. As depicted in the conceptual framework (Fig. 1), these implementation outcomes are in relation to both implementation approaches and SNaP itself. First, the two implementation approaches must be acceptable to stakeholders and implemented well (e.g., with fidelity), which in turn, affects SNaP implementation. Second, successful implementation of SNaP, with high fidelity, penetration, and acceptability will lead to better effectiveness outcomes (ART uptake).

Fig. 1
figure1

Conceptual framework (adapted from Proctor’s framework [44])

Study design

This is a hybrid type III study that has a dual focus on effectiveness and implementation outcomes [52]. We will conduct a cluster randomized controlled trial in 42 HIV testing sites in 10 Vietnamese provinces with high HIV prevalence among PWID. HIV testing sites are the unit of randomization. The sites will receive either standard or tailored approach with 1:1 allocation to each study arm (Fig. 2).

Fig. 2
figure2

Study design overview and randomization scheme

Randomization

During the pre-implementation phase, we conducted in-person site visits, where we evaluated the strength of leadership commitment at each site through observation and communication with site leaders. Based on a brief qualitative description of leaders’ engagement and willingness to participate in SNaP, the strength of leadership commitment was classified as either weak or strong. Clinics were then randomly allocated to the two arms at a 1:1 ratio (21 sites per trial arm), stratified by strength of leadership commitment (weak vs. strong). Random allocation was implemented by study statisticians, who used a random number generator to assign each clinic to an arm at a single point in time. Concealment was not used. Randomization results will be masked to data managers, statistical analysts, and staff who collect and/or manage data on the implementation, effectiveness, and costing outcomes. Randomization was conducted before enrolling participants and asking them to provide informed consent.

Participants

HIV testing sites

We obtained a complete list of the 136 HIV testing sites in Vietnam from the Vietnam Authority of AIDS Control (VAAC), including the number of persons tested per month, positivity rates, and proportion of PWID clients. These data were used to identify proposed HIV testing sites for inclusion in this implementation study. Forty-two HIV testing sites in 10 provinces with the highest PWID HIV prevalence were chosen by the study team. The list of HIV testing sites was reviewed and approved by provincial departments of health and the Vietnam Ministry of Health. The ten selected provinces are located across Vietnam and include Dien Bien, Son La, Thai Nguyen, Phu Tho, Ha Noi, Quang Ninh, Nghe An, Khanh Hoa, Ho Chi Minh City, and Long An.

PWID participants

Following Vietnam’s national HIV testing algorithm, people with positive rapid test results have their diagnosis confirmed at the nearest MOH-certified confirmatory laboratory, using the standard confirmation HIV test [53]. In this study, eligible PWID participants at chosen HIV testing sites must test positive using the standard confirmatory test; be 18 years or older; report a history of injection drug use in the past 6 months; live in the HIV treatment catchment area and be willing to provide informed consent. The total duration of recruitment is 18 months. Up to 6200 HIV-positive participants will be recruited for medical record assessment at baseline. Of those, 4700 will be asked to provide consent only for medical record assessment and will not be re-contacted. The remaining 1500 participants will be enrolled in a subsample cohort for detailed assessments at baseline, 12, and 24 months, including questionnaires and viral load determination. The sub-sample will be re-contacted for interview and assessment of viral suppression 6–12 months after site implementation. The group enrolled in the first 12 months after site implementation will also have 18–24-month assessments.

HIV test site directors and staff

Eligible participants include directors, navigators, counselors, and other staff at HIV testing sites who are willing to provide consent. Six staff at each site will be enrolled and asked to complete brief quantitative surveys at pre-implementation, 12, and 24 months post-implementation. These surveys will be administered online to assess site context measurements, including organizational readiness to change, implementation leadership, and implementation climate. Organizational readiness to change will be measured using the Organizational readiness for implementing change scale—a 12-item scale that evaluates readiness for implementation [54]. Implementation leadership will be measured with the Implementation Leadership Scale, which assesses four dimensions of leadership in EBI implementation: being proactive, knowledgeable, supportive, and perseverant [55]. Implementation climate will be measured using the 18-item Implementation Climate Scale, which evaluates support, recognition, selection, and rewards for innovation use [55] (Additional file 2).

Interventions

Evidence-based intervention: systems navigation and psychosocial counseling (SNaP)

At the individual level, all PWID with confirmed HIV infection at the HIV testing sites will receive the SNaP integrated intervention that has been demonstrated to be effective in HPTN 074 [17]. The intervention was originally designed by the study team to increase engagement in HIV and substance use treatment among PWID [56]. In this study, the SNaP intervention was modified slightly in accordance with the changes in the healthcare system and HIV policies in Vietnam since the HPTN 074 study, such as the merging of district health centers into district hospitals, or payment of HIV care through health insurance instead of international donor funding. Moreover, to increase the feasibility of scaling up, the contents of the original two counseling sessions were combined into one required session only. The intervention has two components: (1) systems navigation to facilitate engagement and retention in HIV care and MOUD (currently methadone in Vietnam), and to negotiate required laboratory tests (e.g. CD4 counts) or transportation; and (2) psychosocial counseling using motivational interviewing, problem solving, skills building, and goal setting to facilitate ART and MOUD initiation and adherence. Systems navigators will initially meet participants twice, in-person or by telephone, within 8 weeks of enrollment. Psychosocial counselors will provide participants with a minimum of one counseling session within 4 weeks of enrollment, with the first session preferably during post-test counseling. To determine the need for additional sessions, the counselor will use a standardized inventory to assess the participants’ need for counseling on risk reduction, drug treatment entry and retention, HIV medical care, ART and MOUD adherence, depression, alcohol dependence, and social support. Participants will be offered the opportunity for additional booster sessions, if needed, at about 1 and 3 months after enrollment.

Process for developing implementation strategies

IM can help improve the design of implementation strategies by incorporating theory, evidence, and stakeholder perspectives to ensure that strategy components effectively address key barriers to change [34]. In this study, we used IM to create a menu of standard implementation strategies selected to be applied to all 42 sites (i.e., the standard implementation package).

The study team worked with local stakeholders to conduct IM through the following steps:

  1. 1)

    Step 1: state outcomes (e.g., implementation outcomes such as fidelity, penetration, acceptability, and costs; effectiveness outcomes such as ART uptake, viral suppression, and MOUD uptake) and performance objectives (e.g., who needs to do what to implement and sustain SNaP).

  2. 2)

    Step 2: identify determinants (barriers and facilitators) of implementation through data from HPTN 074’s qualitative data and formative research, including focus group discussions, and informal interviews with local stakeholders and site visits.

  3. 3)

    Step 3: identify appropriate implementation strategies that can potentially help to address identified determinants and achieve performance objectives, using previously published compilations of implementation strategies and a structured brainstorming process.

For tailored approach sites, the menu of strategies will be further tailored to the needs of each clinic.

Standard approach

We have developed a multifaceted implementation strategy that includes 15 “discrete” implementation strategies to be applied to the standard arm (Table 1). All strategies will be implemented by the central team, with appropriate collaboration with provincial Centers for Disease Control (CDC) leaders, site leaders, and site staff. Each strategy will be tracked throughout the implementation process by collecting information on the actors, actions, dose, timing of activities, and outcomes of the strategy [57].

Table 1 Characteristics of standard implementation strategies (applied to all sites)

Tailored approach

HIV testing sites in the tailored condition have access to the same implementation strategies developed for the standard arm. In addition, tailored approach sites will have access to a broader menu of additional strategies identified through the intervention mapping process. In order to explore site-specific targets for change that could be addressed through tailored implementation strategies, we will conduct an assessment of each of the 21 sites in the tailored approach arm, using a structured online survey prior to implementation. Consistent with our guiding determinant framework (CFIR), we will assess inner setting factors that may influence implementation processes, including organizational readiness to change [54], implementation leadership [58], implementation climate [59], and available resources. We have developed a pre-determined list of additional strategies (Table 2) selected from the Expert Recommendations for Implementing Change (ERIC) menu—a relatively comprehensive list of implementation strategies suggested by stakeholders with expertise in implementation research, applied implementation, and clinical practice [60].

Table 2 List of optional tailored implementation strategies

Through a hands-on 2-day intensive training session, we will work with these sites to tailor their implementation strategies to address their site-specific determinants of SNaP implementation. Tailored approach sites will decide which strategies to implement based on their own needs and capacity. In addition, provincial health officials and HIV testing sites in the tailored arm will receive resources and coaching to assist them in tailoring their implementation strategy to address key determinants of change throughout the implementation process. This additional coaching will be conducted through external phone assistance and regular calls with each tailored approach site to discuss site-specific challenges and assess ongoing implementation. If adjustment is needed, site-specific standard operating procedures will be updated by the site and reviewed centrally. These activities are presented as three mandatory additional strategies applied to tailored approach sites (strategies 16, 17, and 18 in Table 3).

Table 3 Characteristics of tailored implementation strategies applied to all TA sites

Outcomes

Implementation outcomes

The primary implementation outcome is fidelity—the extent to which SNaP is delivered as intended. Fidelity will be measured at the test site level by assessing each site’s success in completing the three protocol-specified sessions (two navigation, one counseling) within the required 8- or 4-week period, respectively, weighted by the central implementation team’s quality rating of those sessions. Session completion will be assessed by reviewing the navigator and counselor logs, while session quality will be assessed by the central implementation team reviewing and scoring of a random 10% of all forms (navigation) and audio-recordings (psychosocial counseling). Central implementation teams will rate them on a 100-point quality scale from poor to excellent. Reviewers will be masked to the arm when reviewing navigation forms or audio-recordings.

$$ \mathrm{Fidelity}=\%\kern0.5em \mathrm{navigation}\kern0.5em \mathrm{sessions}\kern0.5em \mathrm{completed}\ast \mathrm{average}\kern0.5em \mathrm{quality}\kern0.5em \mathrm{score}+\%\kern0.5em \mathrm{counseling}\kern0.5em \mathrm{sessions}\kern0.5em \mathrm{completed}\ast \mathrm{average}\kern0.5em \mathrm{quality}\kern0.5em \mathrm{score} $$

Secondary implementation outcomes are penetration, acceptability, and implementation costs (Table 4).

Table 4 Study outcomes

Effectiveness outcomes

The primary effectiveness outcome is ART uptake among all enrolled PWID. ART uptake is defined as the proportion of participants receiving SNaP with evidence of an ART-related visit in an ART clinic. The secondary effectiveness outcomes include viral suppression and MOUD uptake, assessed among the subsample cohort only (Table 4).

Cost-effectiveness measurements

We will conduct an empirical costing study of SNaP—including both approaches and the actual process of implementation itself—from a societal perspective. We will estimate implementation costs prospectively by embedding a trained costing specialist within each IM team, documenting all resources used (e.g., staff training level and time, travel costs, supplies, etc.) and estimating the unit cost of each resource. To estimate the unit health system cost of each intervention, we will perform detailed budgetary analysis including interviews of key staff, review of logbooks/timesheets, and time-and-motion studies to record navigator, counselor, and other staff time. To estimate patient costs, we will administer a survey to a smaller subset of the 1500-participant cohort at baseline, 12 months, and 24 months to collect data on direct and indirect (lost wages, child care, etc.) costs of clinic visits and other elements (e.g., medication side effects) associated with ART, MOUD, and SNaP itself.

High- and low-performing sites

In HPTN 074, the Vietnam site achieved 86–88% completion of navigation and counseling sessions in the protocol-specified window, and in our counseling studies, we consistently achieve 90–95% quality scores on supervisor-rated counseling sessions [17]. Using the formula to calculate fidelity, a site completing 90% of navigation sessions with an 80% average quality score and 80% of counseling sessions with an 80% average quality score would receive a total score of 136. Our a priori definition of successful implementation at 24 months is a site with a fidelity score of 136 out of 200 and 70% ART uptake among its newly diagnosed or previously diagnosed and not currently on ART participants.

Data collection and analysis

Formative data collection and analysis (year 1, completed)

We are in year 2 of the study and will start enrollment in 2020. In study year 1, as part of the first step of IM, we conducted 2 rounds of focus group discussions among local stakeholders in Hanoi and Thai Nguyen. The first round explored potential structural barriers to and facilitators of SNaP implementation, while the second round discussed appropriateness and feasibility of proposed implementation strategies. During the pre-implementation phase, we also conducted site initial assessments and site in-person visits. A simple initial survey was sent to sites to explore services provided, site’s internet capacity and office space, staffing structure, current referral protocol, leadership strength, and other relevant characteristics. We also visit all sites to communicate with them in-person about the study and qualitatively evaluate the strength of leadership commitment at each site. After each visit, a brief qualitative description on leaders’ engagement and willingness to participate in SNaP was created by the research team. The information and data collected were used for randomization and to inform feasibility of implementation strategies. We also developed a standardized form for collection of cost and resource-use data and have prospectively collected costs during the first year of the study, delineating these costs as research-related versus necessary for programmatic implementation, on a weekly basis.

Data collection and analysis after intervention implementation (year 2–4)

Quantitative data

To compare two implementation approaches in Aim 1, interview data will be collected for both site staff and PWID participants (in the subsample cohort) at baseline, 12, and 24 months follow-up visits. Viral suppression data will also be collected for PWID participants in the subsample cohort. For ART and MOUD uptake data, each patient will have a second masked identification number, which is used to link with their records at HIV and methadone clinics. Only masked study identification numbers of participants will be used to extract information from ART and MOUD clinics to confirm ART initiation and MOUD uptake.

For the cost-effectiveness analysis in Aim 2, we will administer quantitative costing questionnaires for PWID participants randomly selected at each of 12 purposively selected sites (six per arm, selected for broad representation of geography, number of clients, and proportion of clients who are PWID) at baseline and 12-month follow-up visit. In addition, we have developed a quantitative costing tracker to document costing for study implementation at the above-site (central) level and questionnaires for assessment of implementation costs at all 42 sites.

For Aim 3, site characteristics will be assessed with exploratory analyses to examine associations with high- and low-performing clinics. We will use a generalized linear model with a logit link and binomial error distribution to assess the dichotomous outcome of high or low performance.

Qualitative data

As part of Aim 3, we will conduct six semi-structured in-depth interviews with PWID participants in 12 HIV testing sites (for both low- and high-performing sites in two arms at the 24-month follow-up visits). We will ask participants about barriers and facilitators to uptake of ART, ART adherence, MOUD uptake, attitudes, and experiences in the HIV test site and with navigators and counselors. In these same HIV testing sites, we will conduct semi-structured in-depth interviews with navigators/counselors, site staff, site directors, and HIV providers to understand their exposure to and perceptions of SNaP and to inform the context and processes that may underlie SNaP success and failures. All qualitative interviews will be audiotaped, transcribed, translated, coded, and computerized for analysis. Textual data analysis will involve reading for content, deductive and inductive coding, data display to identify emerging themes, data reduction, and interpretation. Responses of navigators and counselors, test site staff, and test site directors will be compared within and across the staff groups and high versus low performing sites. Finally, both qualitative and quantitative data will be combined and triangulated to understand SNaP and two approaches within high- and low-performing sites.

Sample size

Implementation outcomes sample size calculations

For the primary outcome of fidelity, using two-tailed tests with α = 0.05 and assuming a conservatively large standard deviation of 40, 42 sites will give us 80% power to detect a difference between a fidelity score of 136 (high-performing site) in the tailored arm and 100.5 in the standard arm (corresponds to 75% session completion and 67% average quality ratings).

Effectiveness outcomes sample size calculations

We estimate that the intra-cluster correlation coefficient (ICC) may range from 0.01 to 0.05, implying a design effect between 2.5 and 8.4 [63,64,65,66]. Using two-tailed tests and α = 0.05, a sample size of 6200 (available sample after accounting for 12% mortality) will have > 80% power to detect a difference as small as 10 percentage points (e.g., 70% vs. 60% ART uptake) if the ICC is as large as 0.05, and as small as 6 percentage points (e.g., 70% vs. 64% ART uptake) if the ICC is as small as 0.01. For viral load, which is based on a sample of n = 1200 (available sample after accounting for 20% lost to follow-up), assuming the same ICC of 0.01–0.05, we will have 80% power to detect differences of 10–14 percentage points in viral suppression between arms.

Discussion

The HIV burden among PWID in low-resource settings will only be reduced when EBIs are effectively implemented at scale. To our knowledge, the proposed study will be the first to use IM to design a multifaceted implementation package for PWID at a national level. It will evaluate the best approach to identifying implementation strategies to scale up the SNaP intervention in a low-resource setting.

The lack of a systematic approach to developing implementation strategies can lead to failure to address determinants of implementation [67, 68]. More systematic and rigorous methods are recommended for the design and tailoring implementation strategies for EBIs, such as concept mapping, group model building, conjoint analysis, and IM [32]. In this study, to develop the standard implementation package, we used IM—a mixed-method framework that provides many advantages. Within the literature on tailoring implementation strategies, the approaches used to identify barriers to implementation vary widely [39]. We applied a mix of quantitative and qualitative methods, including focus group discussions and informal interviews with local stakeholders, quantitative assessments of sites’ characteristics and implementation climate, and in-person site visits to explore potential barriers and facilitators to intervention implementation. In addition to IM, our tailored implementation approach allows for flexibility in developing strategies through a two-step local process: rapid assessment of implementation barriers and facilitators in each site; and selection of site-specific strategies using a pre-identified menu of potential strategies to address barriers. Moreover, our continuous interactions with tailored approach sites through monthly calls will provide additional opportunities to communicate with sites about their specific needs and improve SNaP implementation.

This study addresses priorities in the field of implementation science in multiple ways:

  • It is a true cluster randomized effectiveness-implementation trial: most HIV studies are individually randomized and/or measure effectiveness rather than implementation outcomes [69]. Our study will randomize at the site-level and will collect primary and secondary implementation outcomes at the site-level.

  • It scales up a highly effective HIV intervention for PWID: few HIV trials for PWID have yielded such promising findings across multiple self-reported and biological outcomes as HPTN 074 [17]. Bringing a successful EBIs to scale with careful implementation assessment has the potential to curb the global PWID HIV epidemic.

  • It assesses the role of HIV test site context for implementation: while IM has long emphasized the importance of implementation [25, 34, 35], using IM as a method to tailor implementation strategies has rarely been evaluated. The tailored approach allows site-level variables, such as readiness to change and implementation climate, to be addressed as implementation strategies are selected.

  • It incorporates cost-effectiveness to inform policy makers in low-resource settings: even though economic evaluations help guide decision making regarding the allocation of resources to the implementation and scale-up of EBIs, they are not routinely done in implementation studies [41, 70]. This study allows for assessments of the incremental costs of the standard versus tailored approach to implementation. Moreover, our cost-effectiveness aim incorporates prospective, empirical costing of the full implementation process (including all aspects of IM), not just the intervention itself.

  • It identifies site characteristics to inform future scale-up: the focus on test site-level predictors of successful implementation will be critical for scale-up efforts of EBIs. These data will provide insight into characteristics that influence successful EBI implementation among PWID, thereby informing governments’ decisions about allocation of limited resources.

  • It improves tracking and reporting of implementation strategies: poor reporting of implementation strategies makes it impossible to replicate effective strategies or learn from ineffective strategies [25, 28, 57]. To address these limitations, we will carefully track the agencies’ use of implementation strategies using established methods [71, 72]. We will also report the use of strategies using established guidelines [57], which will involve naming, defining, and specifying implementation strategies in sufficient detail to enable replication in other settings.

The biggest challenge to this study is the logistics of implementing a large, cluster randomized study in 10 different provinces across the country. This challenge has been alleviated by the collaboration of our well-trained and experienced permanent UNC-Vietnam study team and our implementing partners in HMU and VAAC, who will oversee implementation and provide technical assistance. A second concern is our ability to track PWID participants as they initiate ART and MOUD, due to the lack of adequate clinical records in Vietnam. We will reduce this concern by establishing effective communication between HIV testing sites and ART clinics, as well as using masked identification numbers to verify and match participants when reviewing clinical records.

Conclusions

In summary, PWID need impactful interventions to reduce their HIV-associated morbidity and mortality and slow the broader HIV epidemic. This implementation trial will provide critical guidance to policy-makers worldwide who are responsible for reducing the burden of HIV infection among PWID. Regardless of the outcome, the trial will contribute to the field of implementation science through its examination of implementation and effectiveness outcomes, cost, and characterization HIV testing sites that successfully or unsuccessfully implement the intervention.

Availability of data and materials

Data collection for this study is ongoing, so no data and materials are currently available.

Abbreviations

ART:

Antiretroviral therapy

CDC:

Center for Disease Control

CFIR:

Consolidated Framework for Implementation Research

EBI:

Evidence-based intervention

HMU:

Hanoi Medical University

HPTN:

HIV Prevention Trial Network

IM:

Intervention mapping

MOUD:

Medications for opioid use disorder

PWID:

People who inject drugs

SNaP:

Systems navigation and psychosocial counseling

UNC:

University of North Carolina, Chapel Hill

VAAC:

Vietnam Authority of HIV/AIDS Control

References

  1. 1.

    United Nations of Office on Drug and Crime. World Drug Report Booket 2: global overview of drug demand and supply. 2019.

  2. 2.

    Wandeler G, Johnson LF, Egger M. Trends in life expectancy of HIV-positive adults on antiretroviral therapy across the globe: comparisons with general population. Curr Opin HIV AIDS. 2016;11(5):492–500.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Vallecillo G, Robles MJ, Duran X, Lerma E, Horcajada JP, Torrens M. Trends in AIDS Mortality, Retention in Opioid Agonist Therapy, and HIV RNA Suppression in HIV-Infected People Who Injected Drugs from 2000 to 2015. AIDS Behav. 2018;22(9):2766–72.

    CAS  PubMed  Google Scholar 

  4. 4.

    Larney S, Peacock A, Leung J, Colledge S, Hickman M, Vickerman P, et al. Global, regional, and country-level coverage of interventions to prevent and manage HIV and hepatitis C among people who inject drugs: a systematic review. Lancet Glob Health. 2017;5(12):e1208–e20.

    PubMed  PubMed Central  Google Scholar 

  5. 5.

    Boltaev AA, El-Bassel N, Deryabina AP, Terlikbaeva A, Gilbert L, Hunt T, et al. Scaling up HIV prevention efforts targeting people who inject drugs in Central Asia: a review of key challenges and ways forward. Drug Alcohol Depend. 2013;132(Suppl 1):S41–7.

    PubMed  Google Scholar 

  6. 6.

    Bridge J, Lazarus JV, Atun R. HIV epidemics and prevention responses in Asia and Eastern Europe: lessons to be learned? AIDS (London, England). 2010;24 Suppl 3:S86-S94.

  7. 7.

    Degenhardt L, Mathers BM, Wirtz AL, Wolfe D, Kamarulzaman A, Carrieri MP, et al. What has been achieved in HIV prevention, treatment and care for people who inject drugs, 2010-2012? A review of the six highest burden countries. The International journal on drug policy. 2014;25(1):53–60.

    PubMed  Google Scholar 

  8. 8.

    Strathdee SA, Shoptaw S, Dyer TP, Quan VM, Aramrattana A. Towards combination HIV prevention for injection drug users: addressing addictophobia, apathy and inattention. Curr Opin HIV AIDS. 2012;7(4):320–5.

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    UNAIDS. Vietnam Country factsheets. 2016.

  10. 10.

    Khuu NV, Nguyen TV, Tran HP, Nguyen PD, Vu TX, Tran T, et al. Viral load testing to monitor the HIV epidemic among PWID in Vietnam. Online J Public Health Inform. 2018;10(1):e198.

    PubMed Central  Google Scholar 

  11. 11.

    Nghiem VT, Bui TC, Nadol PP, Phan SH, Kieu BT, Kling R, et al. Prevalence and correlates of HIV infection among men who inject drugs in a remote area of Vietnam. Harm Reduct J. 2018;15(1):8.

    PubMed  PubMed Central  Google Scholar 

  12. 12.

    Nguyen TMT, Tran BX, Fleming M, Pham MD, Nguyen LT, Nguyen ALT, et al. HIV knowledge and risk behaviors among drug users in three Vietnamese mountainous provinces. Subst Abuse Treat Prev Policy. 2019;14(1):3.

  13. 13.

    UNAIDS. 90-90-90: An ambitious treatment target to help end the AIDS epidemic. 2014.

  14. 14.

    UNAIDS. Viet Nam is the first country in Asia to commit to new HIV treatment targets: UNAIDS; 2014 [Available from: https://www.unaids.org/en/resources/presscentre/featurestories/2014/october/20141027vietnamtargets.

  15. 15.

    Hirsch JS, Giang LM, Parker RG, Duong LB. Caught in the middle: the contested politics of HIV/AIDS and health policy in Vietnam. J Health Polit Policy Law. 2015;40(1):13–40.

    PubMed  Google Scholar 

  16. 16.

    Vietnam Ministry of Health. Optimizing Viet Nam’s HIV Response: An Investment Case. 2014.

  17. 17.

    Miller WC, Hoffman IF, Hanscom BS, Ha TV, Dumchev K, Djoerban Z, et al. A scalable, integrated intervention to engage people who inject drugs in HIV care and medication-assisted treatment (HPTN 074): a randomised, controlled phase 3 feasibility and efficacy study. Lancet (London, England). 2018;392(10149):747–59.

    Google Scholar 

  18. 18.

    Hardee K, Rottach E, Jolivet R, Kiesel R. The Policy Dimensions of Scaling Up Health Initiatives. Washington DC; 2012.

  19. 19.

    Barker PM, Reid A, Schall MW. A framework for scaling up health interventions: lessons from large-scale improvement initiatives in Africa. Implement Sci. 2016;11(1):12.

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Proctor EK, Landsverk J, Aarons G, Chambers D, Glisson C, Mittman B. Implementation research in mental health services: an emerging science with conceptual, methodological, and training challenges. Admin Pol Ment Health. 2009;36(1):24–34.

    Google Scholar 

  21. 21.

    Dutta A, Wirtz AL, Baral S, Beyrer C, Cleghorn FR. Key harm reduction interventions and their impact on the reduction of risky behavior and HIV incidence among people who inject drugs in low-income and middle-income countries. Curr Opin HIV AIDS. 2012;7(4):362–8.

    PubMed  Google Scholar 

  22. 22.

    Gilchrist G, Swan D, Widyaratna K, Marquez-Arrico JE, Hughes E, Mdege ND, et al. A Systematic Review and Meta-analysis of Psychosocial Interventions to Reduce Drug and Sexual Blood Borne Virus Risk Behaviours Among People Who Inject Drugs. AIDS Behav. 2017;21(7):1791–811.

    PubMed  PubMed Central  Google Scholar 

  23. 23.

    Lazarus L, Patel S, Shaw A, Leblanc S, Lalonde C, Hladio M, et al. Uptake of Community-Based Peer Administered HIV Point-of-Care Testing: Findings from the PROUD Study. PLoS One. 2016;11(12):e0166942.

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Strathdee SA, Beletsky L, Kerr T. HIV, drugs and the legal environment. The International journal on drug policy. 2015;26 Suppl 1(0 1):S27-S32.

  25. 25.

    Powell BJ, Haley AD, Patel SV, Amaya-Jackson L, Glienke B, Blythe M, et al. Improving the implementation and sustainment of evidence-based practices in community mental health organizations: a study protocol for a matched-pair cluster randomized pilot study of the Collaborative Organizational Approach to Selecting and Tailoring Implementation Strategies (COAST-IS). Implementation Science Communications. 2020;1(1):9.

    PubMed  PubMed Central  Google Scholar 

  26. 26.

    Koorts H, Eakin E, Estabrooks P, Timperio A, Salmon J, Bauman A. Implementation and scale up of population physical activity interventions for clinical and community settings: the PRACTIS guide. Int J Behav Nutr Phys Act. 2018;15(1):51.

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    van der Wees PJ, Jamtvedt G, Rebbeck T, de Bie RA, Dekker J, Hendriks EJM. Multifaceted strategies may increase implementation of physiotherapy clinical guidelines: a systematic review. Australian Journal of Physiotherapy. 2008;54(4):233–41.

    PubMed  Google Scholar 

  28. 28.

    Powell BJ, Fernandez ME, Williams NJ, Aarons GA, Beidas RS, Lewis CC, et al. Enhancing the Impact of Implementation Strategies in Healthcare: A Research Agenda. Front Public Health. 2019;7:3.

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Marlies Hulscher MW. Multifaceted Implementation Strategies. In: Michel Wensing RG, Jeremy Grimshaw, editor. Improving Patient Care: The Implementation of Change in Health Care, Third Edition: John Wiley & Sons Ltd; 2020. p. 313-27.

  30. 30.

    Glasgow RE, Chambers D. Developing Robust, Sustainable, Implementation Systems Using Rigorous, Rapid and Relevant Science. Clinical and Translational Science. 2012;5(1):48–55.

    PubMed  PubMed Central  Google Scholar 

  31. 31.

    Hull L, Athanasiou T, Russ S. Implementation Science: A Neglected Opportunity to Accelerate Improvements in the Safety and Quality of Surgical Care. Ann Surg. 2017;265(6):1104–12.

    PubMed  Google Scholar 

  32. 32.

    Powell BJ, Beidas RS, Lewis CC, Aarons GA, McMillen JC, Proctor EK, et al. Methods to Improve the Selection and Tailoring of Implementation Strategies. The journal of behavioral health services & research. 2017;44(2):177–94.

    Google Scholar 

  33. 33.

    Colquhoun HL, Squires JE, Kolehmainen N, Fraser C, Grimshaw JM. Methods for designing interventions to change healthcare professionals’ behaviour: a systematic review. Implement Sci. 2017;12(1):30.

    PubMed  PubMed Central  Google Scholar 

  34. 34.

    Fernandez ME, ten Hoor GA, van Lieshout S, Rodriguez SA, Beidas RS, Parcel G, et al. Implementation Mapping: Using Intervention Mapping to Develop Implementation Strategies. Front Public Health. 2019;7:158.

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Fernandez ME, Gonzales A, Tortolero-Luna G, Partida S, Bartholomew LK. Using intervention mapping to develop a breast and cervical cancer screening program for Hispanic farmworkers: Cultivando La Salud. Health Promot Pract. 2005;6(4):394–404.

    PubMed  Google Scholar 

  36. 36.

    Bartholomew Eldridge LKMC, Ruiter RAC, Fernández ME, Kok G, Parcel GS. Planning Health Promotion Programs: An Intervention Mapping Approach. 4th edition. San Francisco: Jossey-Bass, Inc; 2016.

    Google Scholar 

  37. 37.

    Mittman BS. Implementation science in health care. In: Brownson RCCG, Proctor EK, editors. Dissemination and Implementation Research in Health: Translating Science to Practice. New York: Oxford University Press; 2012. p. 400–18.

    Google Scholar 

  38. 38.

    Baker R, Camosso-Stefinovic J, Gillies C, Shaw EJ, Cheater F, Flottorp S, et al. Tailored interventions to overcome identified barriers to change: effects on professional practice and health care outcomes. The Cochrane database of systematic reviews. 2010;3:Cd005470.

    Google Scholar 

  39. 39.

    Baker R, Camosso-Stefinovic J, Gillies C, Shaw EJ, Cheater F, Flottorp S, et al. Tailored interventions to address determinants of practice. The Cochrane database of systematic reviews. 2015;4:Cd005470.

    Google Scholar 

  40. 40.

    Roberts SLE, Healey A, Sevdalis N. Use of health economic evaluation in the implementation and improvement science fields—a systematic literature review. Implement Sci. 2019;14(1):72.

    PubMed  PubMed Central  Google Scholar 

  41. 41.

    Reeves P, Edmunds K, Searles A, Wiggers J. Economic evaluations of public health implementation-interventions: a systematic review and guideline for practice. Public Health. 2019;169:101–13.

    CAS  PubMed  Google Scholar 

  42. 42.

    Pinnock H, Barwick M, Carpenter CR, Eldridge S, Grandes G, Griffiths CJ, et al. Standards for Reporting Implementation Studies (StaRI) Statement. BMJ (Clinical research ed). 2017;356:i6795.

    Google Scholar 

  43. 43.

    Schulz KF, Altman DG, Moher D. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMJ (Clinical research ed). 2010;340:c332.

    Google Scholar 

  44. 44.

    Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Admin Pol Ment Health. 2011;38(2):65–76.

    Google Scholar 

  45. 45.

    Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation science : IS. 2009;4:50.

    PubMed  Google Scholar 

  46. 46.

    Nilsen P. Making sense of implementation theories, models and frameworks. Implementation science : IS. 2015;10:53.

    PubMed  Google Scholar 

  47. 47.

    Lash SJ, Timko C, Curran GM, McKay JR, Burden JL. Implementation of evidence-based substance use disorder continuing care interventions. Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors. 2011;25(2):238–51.

    Google Scholar 

  48. 48.

    Helfrich CD, Weiner BJ, McKinney MM, Minasian L. Determinants of implementation effectiveness: adapting a framework for complex innovations. Medical care research and review : MCRR. 2007;64(3):279–303.

    PubMed  Google Scholar 

  49. 49.

    Lau R, Stevenson F, Ong BN, Dziedzic K, Treweek S, Eldridge S, et al. Achieving change in primary care--causes of the evidence to practice gap: systematic reviews of reviews. Implementation science : IS. 2016;11:40.

    Google Scholar 

  50. 50.

    Guerrero EG, Fenwick K, Kong Y. Advancing theory development: exploring the leadership-climate relationship as a mechanism of the implementation of cultural competence. Implementation science : IS. 2017;12(1):133.

    PubMed  Google Scholar 

  51. 51.

    Patel B, Usherwood T, Harris M, Patel A, Panaretto K, Zwar N, et al. What drives adoption of a computerised, multifaceted quality improvement intervention for cardiovascular disease management in primary healthcare settings? A mixed methods analysis using normalisation process theory. Implementation science : IS. 2018;13(1):140.

    PubMed  Google Scholar 

  52. 52.

    Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50(3):217–26.

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Vietnam Ministry of Health. National Guidelines on HIV testing. 2018.

  54. 54.

    Shea CM, Jacobs SR, Esserman DA, Bruce K, Weiner BJ. Organizational readiness for implementing change: a psychometric assessment of a new measure. Implement Sci. 2014;9(1):7.

    PubMed  PubMed Central  Google Scholar 

  55. 55.

    Ehrhart MG, Aarons GA, Farahnak LR. Assessing the organizational context for EBP implementation: the development and validity testing of the Implementation Climate Scale (ICS). Implement Sci. 2014;9(1):157.

    PubMed  PubMed Central  Google Scholar 

  56. 56.

    Lancaster KE, Miller WC, Kiriazova T, Sarasvita R, Bui Q, Ha TV, et al. Designing an Individually Tailored Multilevel Intervention to Increase Engagement in HIV and Substance Use Treatment Among People Who Inject Drugs With HIV: HPTN 074. AIDS education and prevention : official publication of the International Society for AIDS Education. 2019;31(2):95–110.

    Google Scholar 

  57. 57.

    Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implementation science : IS. 2013;8:139.

    PubMed  Google Scholar 

  58. 58.

    Aarons GA, Ehrhart MG, Farahnak LR. The implementation leadership scale (ILS): development of a brief measure of unit level implementation leadership. Implement Sci. 2014;9(1):45.

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Weiner BJ, Belden CM, Bergmire DM, Johnston M. The meaning and measurement of implementation climate. Implementation science : IS. 2011;6:78.

    PubMed  Google Scholar 

  60. 60.

    Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10(1):21.

    PubMed  PubMed Central  Google Scholar 

  61. 61.

    Weiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, et al. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017;12(1):108.

    PubMed  PubMed Central  Google Scholar 

  62. 62.

    Brehaut JC, Graham ID, Wood TJ, Taljaard M, Eagles D, Lott A, et al. Measuring acceptability of clinical decision rules: validation of the Ottawa acceptability of decision rules instrument (OADRI) in four countries. Medical decision making : an international journal of the Society for Medical Decision Making. 2010;30(3):398–408.

    Google Scholar 

  63. 63.

    Smeeth L, Ng ES. Intraclass correlation coefficients for cluster randomized trials in primary care: data from the MRC Trial of the Assessment and Management of Older People in the Community. Control Clin Trials. 2002;23(4):409–21.

    PubMed  Google Scholar 

  64. 64.

    Parker DR, Evangelou E, Eaton CB. Intraclass correlation coefficients for cluster randomized trials in primary care: the cholesterol education and research trial (CEART). Contemporary clinical trials. 2005;26(2):260–7.

    PubMed  Google Scholar 

  65. 65.

    Pals SL, Beaty BL, Posner SF, Bull SS. Estimates of intraclass correlation for variables related to behavioral HIV/STD prevention in a predominantly African American and Hispanic sample of young women. Health education & behavior : the official publication of the Society for Public Health Education. 2009;36(1):182–94.

    Google Scholar 

  66. 66.

    Eldridge SM, Ashby D, Feder GS, Rudnicka AR, Ukoumunne OC. Lessons for cluster randomized trials in the twenty-first century: a systematic review of trials in primary care. Clinical trials (London, England). 2004;1(1):80–90.

    Google Scholar 

  67. 67.

    Aarons GA, Hurlburt M, Horwitz SM. Advancing a Conceptual Model of Evidence-Based Practice Implementation in Public Service Sectors. Adm Policy Ment Health Ment Health Serv Res. 2011;38(1):4–23.

    Google Scholar 

  68. 68.

    Flottorp SA, Oxman AD, Krause J, Musila NR, Wensing M, Godycki-Cwirko M, et al. A checklist for identifying determinants of practice: A systematic review and synthesis of frameworks and taxonomies of factors that prevent or enable improvements in healthcare professional practice. Implement Sci. 2013;8(1):35.

    PubMed  PubMed Central  Google Scholar 

  69. 69.

    Benbow N, Smith JD. Landscape of NIH-funded HIV Implementation Research: Preliminary Results of a Scoping Review. HIV Implementation Science Workshop. Chicago, Illinois: Third Coast CFAR in Chicago, Johns Hopkins University CFAR; 2018.

    Google Scholar 

  70. 70.

    Hoomans T, Severens JL. Economic evaluation of implementation strategies in health care. Implement Sci. 2014;9(1):168.

    PubMed  PubMed Central  Google Scholar 

  71. 71.

    Boyd MR, Powell BJ, Endicott D, Lewis CC. A Method for Tracking Implementation Strategies: An Exemplar Implementing Measurement-Based Care in Community Behavioral Health Clinics. Behav Ther. 2017.

  72. 72.

    Bunger AC, Powell BJ, Robertson HA, MacDowell H, Birken SA, Shea C. Tracking implementation strategies: a description of a practical approach and early findings. Health research policy and systems. 2017;15(1):15.

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank all staff in the SNaP central implementation team at the UNC Project Vietnam for their work in preparing and conducting this trial (Mrs Dang Thi Hong Linh, Nguyen Thanh Van, Le Thi Thu Trang, Tran Thi Van Anh, and Nguyen Thanh Van). We also thank provincial Centers for Diseases Control in the 10 provinces and local stakeholders participating in our focus group discussions for their significant guidance and support throughout the pre-implementation phase.

Funding

This study was supported by a grant from the National Institute of Drug Abuse (NIDA), 1R01DA047876-01. BJP was also supported by the National Institute of Mental Health through K01MH113806. KEL was also supported by the National Institute of Drug Abuse through K01DA048174.

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Authors

Contributions

WM and VG conceived the study and obtained the funding, WM, VG, BJP, MN, TS, HT, AC, AD, and DD contributed to research design and protocol development. BJP helped conceptualize the intervention conditions, contributed to the grant writing, and informed all implementation materials. MN and AC drafted the manuscript, and VG, WM, BJP, TS, and HT revised it critically with important intellectual contents. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Minh X. B. Nguyen or Vivian F. Go.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Institutional Review Boards at the University of North Carolina, Chapel Hill and Hanoi Medical University.

Consent for publication

All participants provided written informed consent before participating in the study, which included consent to publish anonymous quotes from individual participants.

Competing interests

The authors declare that they have no competing interests.

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Supplementary information

Additional file 1.

SNaP checklists of study protocol.

Additional file 2.

Measurement scales.

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Nguyen, M.X.B., Chu, A.V., Powell, B.J. et al. Comparing a standard and tailored approach to scaling up an evidence-based intervention for antiretroviral therapy for people who inject drugs in Vietnam: study protocol for a cluster randomized hybrid type III trial. Implementation Sci 15, 64 (2020). https://0-doi-org.brum.beds.ac.uk/10.1186/s13012-020-01020-z

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Keywords

  • Implementation science
  • Implementation strategies
  • Tailoring implementation strategies
  • Intervention mapping
  • People who inject drugs
  • Vietnam
  • HIV
  • System navigation
  • Psychosocial counseling
  • Intervention
  • Cost-effectiveness
  • Economic evaluation