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Published in final edited form as: Drug Alcohol Depend. 2021 May 21;225:108767. doi: 10.1016/j.drugalcdep.2021.108767

A mapping review of NIDA-funded implementation research studies on treatments for opioid and/or stimulant use disorders

Hannah Cheng 1, Hélène Chokron Garneau 1, Mina Yuan 1, Mark P McGovern 1,2
PMCID: PMC8282719  NIHMSID: NIHMS1709353  PMID: 34052689

Abstract

Background:

The biomedical research enterprise invests greatly in discovery-oriented science, but significantly less in how to implement the most effective of these innovations. The return on investment in public health benefit is therefore low. In the context of substance-related overdose epidemics, presently with opioids and/or stimulants, the gap in proven treatments and routine access is amplified. Implementation research is designed to deepen understanding of how best to scale-up proven treatments. This study assessed how implementation research has been deployed in the National Institute on Drug Abuse (NIDA) efforts to address the opioid and stimulant epidemics.

Methods:

Adapting a procedure developed to categorize HIV-focused research, a four-stage systematic mapping review of NIDA-funded R01, R34, R61, and U studies pertaining to opioids and/or stimulants funded between 2015 and 2019 was performed. Abstracts were retrieved using NIH Research Portfolio Online Reporting Tools. Key study characteristics were abstracted and coded by two independent reviewers.

Results:

An initial search across NIH institutes yielded 5,963 relevant records. Of these, 666 (11.2%) were NIDA funded. One-hundred-and-thirty-four (20.1%) of the 666 studies were opioid and/or stimulant treatment related. Of these, 28 (4.2%) were categorized as Implementation Preparation (IP), and 16 (2.4%) categorized as Implementation Research (IR). Over the five-year period, there was a gradual increase in both IP and IR studies.

Conclusions:

Implementation research is a small but slowly growing component of the federal portfolio to address substance-related public health issues. To more effectively respond to contemporary epidemics, implementation research must take on an even more significant role.

Keywords: Implementation Research, Opioids, Stimulants, Addiction, Addiction Treatment

1.0. INTRODUCTION

As the biomedical research enterprise rapidly grows, the science to translate the discoveries of effective treatments into routine practice evolves more slowly (Balas and Boren, 2000; Colditz and Emmons, 2019; Morris et al., 2011; Moses et al., 2015; National Institutes of Health, 2021). The urgent need to close the gap in proven treatments and routine public access is amplified in this era of twin substance-related epidemics (Ellis et al., 2018). In 2018 alone, an average of 128 people in the US died daily from overdosing on opioids (National Institute on Drug Abuse, 2020). Presently, the opioid epidemic is undergoing a dynamic shift from opioids to stimulants and their combination (Al-Tayyib et al., 2017; Barocas et al., 2019; Centers for Disease Control and Prevention, 2021; Hedegaard et al., 2020; Jones et al., 2020; McCall Jones et al., 2017). In fact, more than 50 percent of all stimulant-related overdose deaths in 2017 have involved drugs contaminated with synthetic opioids (Hoots et al., 2020; Substance Abuse and Mental Health Services Administration, 2020). Clearly, there is a pressing need to bring the science of implementation to effectively and efficiently respond to this crisis—where access to proven treatments can and would save lives.

Acquiring the knowledge to translate research into practice requires rigorous methods, systematic measures, and standardization to foster replicability different than traditional efficacy and effectiveness trials. Implementation research methods are intended to expand access to and scale-up evidence-based treatments in the real-world (Bauer and Kirchner, 2020; Wensing and Grol, 2019). These methods have the potential to bridge the documented research-to-practice gap, optimize the translational efficiency of the research enterprise, and maximize the economic return on investment for the greater public health benefit (Collins, 2011; Emmons and Colditz, 2017; Woolf, 2008).

Adopting the NIH definition of implementation research, Smith et al. (2020) detailed an organizing framework of implementation projects on a continuum from Implementation Preparation to Implementation Research. Implementation Preparation (IP) refers to studies that prepare for implementation but do not meet NIH definition of implementation research to evaluate the impact of implementation strategies. The focus of these studies can be subdivided into: 1) Characterizing contextual barriers and facilitators; 2) Measuring some implementation outcomes such as reach or adoption; and, 3) Utilizing but not evaluating documented implementation strategies. As an example, an IP study might only examine barriers and facilitators to the implementation of a proven treatment, such as buprenorphine in primary care settings, but does not evaluate the implementation strategies deployed to support primary care providers in adopting this medication in their routine practice. Implementation Preparation type projects can help to elucidate and seek to overcome multi-level contextual barriers that would otherwise hinder implementation across different settings. Whereas NIH-defined Implementation Research (IR) refers to inquiries that examine contexts, outcomes, and the implementation strategies used to scale-up evidence-based treatments (National Institutes of Health, 2019a). These studies are designed to: 1) Evaluate the impact of one or more sets of strategies or versus implementation as usual; and/or 2) Compare two or more sets of strategies (National Institutes of Health, 2019a). To illustrate, an IR study might evaluate and compare implementation strategies such as implementation facilitation or learning collaboratives as strategies for the implementation of buprenorphine in 30 primary care clinics in a health care system. Implementation Research evaluates the causal mechanisms of implementation strategies to improve implementation outcomes such as reach (patient access) and adoption (routine delivery). In addition to evaluating cost, IR provides clarity as to which strategies are most effective and efficient to implement any given treatment (Lewis et al., 2020, 2018; Powell et al., 2019). Figure 1 illustrates the two categories of implementation studies as outlined by Smith et al., 2020, and in contrast to traditional efficacy and effectiveness trials. With each successive tier, a more detailed inquiry into the metaphorical “black box” of implementation occurs.

Figure 1: Tiers of implementation research categories based on approaches to the “black box” of implementation strategies—the interventions of implementation.

Figure 1:

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Figure 1 illustrates how Smith et al. (2020) continuum of implementation studies differs from traditional efficacy and effectiveness trials. The top tier represents the approach to traditional efficacy and effectiveness trials that focus on determining if a treatment works. Patient-level outcomes are the primary specific aim. For new treatments, or for treatments being adapted or delivered using a new platform (e.g., apps), this first-tier research is essential. In the second tier (labelled by Smith et al., as “Implementation Preparation”), the intervention has already established a track record of efficacy and effectiveness. The new questions are what contextual factors influence its routine implementation (or sustainment) in real world settings (e.g., systems, organizational, clinician, patient); and also what factors influence outcomes such as reach (who gets it), adoption (who delivers it), intervention fidelity/adherence (is it delivered as designed), and equity. In the third tier (labeled by Smith et al., as Implementation Research”), the focus is evaluating the implementation strategies used to install or sustain the intervention, and how these strategies are selected and adapted, their cost, and impact on implementation outcomes such as reach and adoption. Unlike traditional efficacy and effectiveness trials that study whether a treatment works to impact patient-level health outcomes, the third tier of implementation research examines the contextual determinants, implementation outcomes, and the implementation strategies used to scale-up evidence-based treatments. This progression is depicted as the iterative opening of the “black box” of implementation inquiry.

The present study adopts the methodology of Smith et al. (2020) used with HIV research categorization, and maps NIDA-funded studies to: 1) Characterize the current trends of NIDA investment in implementation studies for opioids and/or stimulants; and 2) Inform future direction in dissemination and implementation (D&I) addiction health services research. Opioid use disorder and stimulant use disorder are targeted for two reasons: 1) The present public health crisis associated with the overdose epidemics related to opioids and/or stimulants; and, 2) Effective medications (for opioid use disorder) and psychosocial interventions (for stimulant use disorder) exist. Thus, the more pressing need is to leverage implementation research to scale-up treatments that are known to be effective in the real world. This is an implementation research focused mapping review of NIDA-funded original research investigations from 2015 to 2019 pertaining to opioids and/or stimulants.

2.0. METHODS

A four-stage systematic mapping review was conducted using the methodology developed by Smith et al. (2020). The four-stage review process included (1) Identification; (2) Screening and Eligibility Assessment; (3) Iterative Codebook Development; and (4) Data Extraction.

2.1. Identification

To characterize NIDA-funded research pertaining to opioids and/or stimulants, an advanced search on NIH Research Portfolio Online Reporting Tools (NIH RePORTER) (National Institutes of Health, 2020) was performed. Search terms included “opioid” or “opioid use disorder” or “cocaine” or “methamphetamine”. Funding agencies were narrowed to “NIH Institutes and Centers”. Funding mechanisms included “Research Project Grants”, “Research Centers”, and “Other Research-Related” with project start date between January 1, 2015 and December 31, 2019. Similar to Smith et al. (2020), a five-year index period to examine the recent funding profile was selected. To verify all relevant studies were identified, 10 studies were randomly selected from NIH HEAL’s list of funded projects on its website to ensure they were captured in the search results (National Institutes of Health, 2019b). Given that the NIH HEAL Initiative is a trans-institute effort to address the opioid epidemic, cross-validating studies funded through the initiative can help to confirm the search strategies were inclusive of all NIH-funded opioid and/or stimulant studies. No additional relevant study was identified.

2.2. Screening and Eligibility Assessment

All records identified using the above search strategy were exported from NIH RePORTER to an Excel workbook for additional screening and eligibility assessment. Inclusion criteria were: (1) Project start date between January 1, 2015 and December 31, 2019; (2) Studies pertaining to opioids and/or stimulants; (3) Studies funded by NIDA; and (4) Studies with the following funding mechanism: R01, R34, R61, U. These selective funding mechanisms were targeted as they are original research projects and cooperative agreements. Exclusion criteria were: (1) Supplemental studies, and (2) Duplicates. Supplemental studies are records of supplemental funds awarded to an existing parent grant. Duplicates are repeated records of the same grant across the active project years. These exclusion criteria ensure that only unique studies are captured in the data extraction process.

2.3. Iterative Codebook Development

An iterative codebook was developed to characterize the NIDA-funded studies pertaining to opioids and/or stimulants. Extracted information included: (1) General grant characteristics; (2) Addiction treatment characteristics; and (3) Implementation study categories and subcategories. Table 1 displays the final data extraction codebook.

Table 1:

Data extraction codebook

Categories Variables Codes
General Grant Characteristics Activity code R01; R34; R61; U
Project start year 2015; 2016; 2017; 2018; 2019
Project focus Basic science & Imaging; Neither opioid nor stimulant treatment; Opioid and/or stimulant treatment
Addiction Treatment Characteristics Location United States; International
Population* General population; Adolescents; Women; Racial/ethnic minorities; Incarcerated; HIV-positive; Co-morbid SUD/mental health disorders
Treatment domain Policy; Health services and intervention research; Risk reduction
Implementation Study Categories and Subcategories Category Not implementation research; Implementation Preparation (IP); Implementation Research (IR) (adopted from Smith et al., 2020)
Subcategory* IP: Identify barriers and facilitators; IP: Identify/select/develop/adapt implementation strategies; IP: Pilot implementation strategies; IR: Evaluate the impact of one set of strategies; IR: Comparative implementation (adopted from Smith et al., 2020)
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*

Not mutually exclusive; can have more than one for each study

2.3.1. General Grant Characteristics

General grant characteristics of interest were activity code, project start year, and project focus, which included (1) Basic science and imaging; (2) Neither opioid nor stimulant treatment; and, (3) Opioid and/or stimulant treatment.

2.3.2. Addiction Treatment Characteristics

Addiction treatment characteristics were collected only for studies with a project focus on opioid and/or stimulant treatments. These characteristics included study location, population, and treatment domain. The treatment domain was sorted into (1) Policy (e.g., opioid/stimulant policies); (2) Health services and intervention research (e.g., medications for opioid use disorder, linkage to care, cognitive behavioral therapy, contingency management); and (3) Risk reduction (e.g., naloxone distribution, syringe exchange).

2.3.3. Implementation Study Categories and Subcategories

Adhering to the Smith et al. (2020) methodology, codes of implementation study categories and subcategories for projects on opioid and/or stimulant treatment were developed. To determine the implementation study categories, the NIH definition of Implementation Preparation (IP) and Implementation Research (IR) (National Institutes of Health, 2019a) was utilized. Studies that did not fall into either the IP or IR category were categorized as Not Implementation Research (NIR). Studies that were identified as IP or IR were further grouped into subcategories (see Table 1).

2.4. Data Extraction

All records of the unique NIDA-funded studies pertaining to opioids and/or stimulants were entered to Covidence for data extraction. Abstracts of study records were reviewed and coded using the final data codebook (Table 1) with the consensus of two reviewers (first author and second/third author). Discrepancies were resolved by consultation with a mediator (last author). Descriptive statistics of abstracted codes were summarized.

3.0. RESULTS

Using the predefined search strategies, a total of 5,963 records on NIH RePORTER were identified. Among these, 507 supplemental studies; 2,376 non R01, R34, R61, or U studies; 1,933 duplicates; 74 studies with a project start date after December 31, 2019; and 407 studies funded by agencies other than NIDA were removed. The remaining 666 unique NIDA studies were eligible for data extraction. Figure 2 is the extended PRISMA diagram that details the number of records identified, included, and excluded.

Figure 2:

Figure 2:

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Extended PRISMA diagram

3.1. Project Focus

Among 666 NIDA-funded studies pertaining to opioids and/or stimulants, 134 (20.1%) studies involved opioid and/or stimulant treatment. The remainder were either basic science or imaging studies (n=428, 64.3%), or did not focus on opioid/stimulant treatment (n=104, 15.6%). Figure 2 displays the details of this breakdown.

3.2. Implementation Study Categories and Subcategories

Most of the 134 studies targeting opioid/stimulant addiction treatment were NIR (n=90, 67.2%). Twenty-eight (4.2%) were IP studies. These IP studies identified barriers and facilitators (n=16); utilized but did not evaluate documented implementation strategies (n=10); and/or piloted implementation strategies (n=11). The IR studies were even more scarce, totaling to only 16 (2.4%). These IR studies evaluated the impact of one set of strategies (n=12) or compared two or more sets of implementation strategies (n=4). Figure 3 depicts the funnel of categories of NIDA-funded grants for treatments of opioid and/or stimulant use disorders.

Figure 3:

Figure 3:

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Categories of NIDA-funded grants for treatments of opioid and/stimulant use disorders: 2015–2019

3.3. Implementation Study Categories by Project Start Year

NIDA funding trends of implementation studies were characterized over time. From 2015 to 2019, there was an encouraging uptick in both IP and IR studies. Specifically, between 2018 and 2019, the count of IP and IR had doubled but remained low ([2018] IP=5, IR=5; [2019] IP=12, IR=9). Figure 4 displays the categories of NIDA-funded grants for treatments of opioid and/or stimulant use disorders by project start year.

Figure 4:

Figure 4:

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Categories of NIDA-funded grants for treatments of opioid and/or stimulant use disorders by project start year: 2015–2019 (N=134)

3.4. Implementation Study Categories by Addiction Treatment Domain

The addiction treatment domain(s) that are most likely to integrate implementation science work were also examined. Most of IP and IR studies focused on health services and intervention research (IP=20, IR=13), followed by a focus on risk reduction (IP=8, IR=3). No IP and IR studies were related to policy.

4.0. DISCUSSION

This mapping review provides an overview of the landscape of NIDA’s investment in implementation research related to opioid and/or stimulant treatment between 2015 and 2019. Slightly over 2% of the total number of NIDA-funded opioid and/or stimulant treatment studies met the definition of IR. The number of funded IR studies increased from 2 (2.3%) in 2015 to 9 (4.1%) by 2019. The jump in funded IR studies from 5 (3.7%) to 9 (4.1%) between 2018 and 2019 coincides with the influx of funds from the U.S. Congressional appropriation for the opioid-focused HEAL Initiative (National Institutes of Health, 2019c).

This is the first systematic examination of NIDA-funded implementation work in addiction treatment research. There are several methodological limitations to acknowledge. The NIH RePORTER abstract is only a brief representation of the funded study and may not capture the study’s full implementation research plans. The search was limited to NIDA-funded studies, excluded studies funded by other federal and non-federal agencies or foundations, and purposefully excluded other substance use disorders, such as alcohol, tobacco, and cannabis. Future efforts to assess implementation research within addiction treatment could also include comprehensive scans of published work. The scope might be broadened to include other funding agencies and other substances of interest as well as to assess the quality--- in addition to quantity--- of the implementation research studies.

This mapping review reveals three important insights. First, there are significant missed opportunities with IP studies (4.2%) that did not evaluate implementation strategies, and with effectiveness trials (20.3%) that did not evaluate the potential implementability of the intervention being tested. Referring to Figure 1, transitioning tier 1 efficacy/effectiveness studies into tier 2 (IP), and transitioning tier 2 IP studies into tier 3 (IR) would rapidly accelerate the science and in turn the public health access to effective addiction treatments. Researchers might optimize or capitalize on the opportunity to conduct an IR level study by examining implementation strategies in IP studies, and perform an IP level study by exploring implementation factors in efficacy and effectiveness trials.

Second, in order for researchers to effectively integrate implementation research elements in study designs, a level of D&I science expertise is necessary. The National Cancer Institute (NCI) and National Institute on Mental Health (NIMH) have been exemplar in developing this capacity through formal D&I training and mentorship (Brownson et al., 2017; Chambers et al., 2017; Chambers et al., 2020; Davis and D’Lima, 2020).

Lastly, few NIDA-funded studies between 2015 and 2019 featured more advanced implementation research level studies (see Figure 1 bottom tier). In fact, over 50% of NIH-funded D&I studies had been funded by NCI and NIMH since a decade ago, while NIDA-funded studies only made up approximately 11% of all NIH-funded D&I studies (Tinkle et al., 2013). Further, a review of active P30 and P50 centers with an implementation research component across NIH institutes revealed that only 2 out of 12 centers were funded by NIDA, in comparison to 4 by NIMH and 6 by NCI.

There are several established and emerging agency-level efforts to expand implementation research in the field of addiction health services, including Dissemination and Implementation research at NIDA, Demonstration and Dissemination projects at Agency for Healthcare Research and Quality (AHRQ), support for the adoption of evidence-based practices at Substance Abuse and Mental Health Services Administration (SAMHSA), and the Quality Enhancement Research Initiative at the Veterans Health Administration (VHA).

Across all these agencies, there is a pressing need for more research and increased standardization and rigor in IP and IR investigations specific to addiction treatment. Although there are no cures, effective treatments for addiction do exist. Efforts to bring these treatments to scale, equitably and efficiently, so that the public can benefit, should be prioritized in the collective research mission.

HIGHLIGHTS.

  • Implementation research aims to improve access to the most effective treatments

  • Implementation research makes up a small share of substance-related treatment studies

  • Implementation research studies of addiction treatment are slowly growing

Acknowledgements

The authors are grateful to Rebecca McGovern for her graphic design contribution. The authors would also like to specifically thank the staff of Center for Behavioral Health Services and Implementation Research for manuscript review and editing feedback.

Role of Funding Source

This study was funded by NIDA through grants [R01DA037222 & R01DA037222–05S1, PI: McGovern, Ford]. NIDA was not involved in data collection, data analysis or writing of this paper. The statements made here are those of the authors.

Footnotes

CONFLICT OF INTEREST

No conflict declared.

AUTHOR DISCLOSURES

Declarations of Interest

None

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