Consortium to Disseminate and Understand Implementation of Opioid Use Disorder Treatment (PII 19-321)
Phase: NA
Conditions: Opioid Medication Assisted Treatment
Sponsor: VA Office of Research and Development

 
 
 
 
 
 
 
Consortium to Disseminate and Understand 
Implementation of Opioid Use Disorder Treatment (CONDUIT) 
NCT04178551 
June 11, 2019 
 
 

 
 
A. Background and significance 
 
Opioid and other drug overdose is now the number one cause of accidental death in the U.S. by a wide 
margin.1 This is due to multiple factors, most notably a marked surge in opioid prescribing f or pain from the 
early 1990’s to the mid-2010’s.2 Veterans are a particularly vulnerable group, experiencing opioid overdose at 
nearly twice the rate of non-Veterans.3 Many overdose victims have opioid use disorder (OUD), a condition 
defined by compulsive use of opioids despite negative consequences and use of illegal opiates including 
heroin. Therefore, to combat the opioid overdose epidemic in the U.S. particularly among Veterans, improved 
diagnosis and treatment of OUD is paramount.4 Furthermore, to break the cycle of over-reliance on opioids for 
pain treatment, alternative therapies for pain must be made readily accessible. Veterans already on risky long-
term opioid therapy (LTOT) for chronic pain, the group perhaps at highest risk for developing OUD, need 
structured, coordinated efforts to treat their pain more effectively and safely. 
 
Fortunately, unlike some addictive disorders, there are evidence-based, effective medications for opioid 
use disorder (MOUD), including buprenorphine/naloxone, methadone and naltrexone.5 The Veterans Health 
Administration (VHA) seeks to make these potentially life-saving treatments available to every Veteran with 
OUD. While the Substance Use Disorder national program office within VHA's Office of Mental Health and 
Suicide Prevention (OMHSP) has prioritized dissemination of MOUD across VHA, rates of uptake of MOUD 
are highly variable throughout VHA. This is in part due to the stigma associated with OUD, and reluctance of 
providers to engage in caring for this stigmatized group, especially if they have experienced difficulty with a 
prior patient with OUD. Thus, in 2017, the VHA National Leadership Council identified three priority goals, one 
of which was the improvement of “access to medication-assisted therapy for opioid use disorder and 
alternative therapies for pain.” In response and in recognition of major gaps in understanding effective MOUD 
implementation activities, VHA’s QUality Enhancement Research Initiative (QUERI) created the Veteran 
Integrated Service Network (VISN)-Partnered Implementation Initiative (PII), which in 2018 funded five projects 
co-led by VISN leadership and implementation experts. These five one-year Phase 1 projects have 
implemented evidence-based programs in four VISNs across a range of clinical settings using evidence-based 
Implementation Facilitation (IF), described below. This Phase 2 proposal aims to integrate and expand these 
projects over three additional years as a single 
Consortium to Disseminate and Understand 
Implementation of Opioid Use Disorder Treatment (or 
CONDUIT), to serve the dual purpose of expanding 
access to MOUD while examining effective IF activities 
that drive these outcomes. CONDUIT consists of 4 
external facilitation (EF) teams partnering with internal 
facilitation teams at 57 sites across 6 VISNs to implement 
evidence-based practices across the OUD/pain continuum 
of care: Primary care, specialty care, acute care (hospital 
and emergency department) and telehealth (Figure 1). 
Three Cores – Veteran Engagement, Implementation, and 
Quantitative/Economic will work across teams and sites to 
ensure alignment of measures and to support cross-
CONDUIT deliverables. Together, as a consortium, we 
will leverage our collective pilot work, resources and 
expertise to have the whole be greater than the sum of 
the parts.  
B. Innovation 
 
The VHA Consortium to Disseminate and Understand Implementation of Opioid Use Disorder Treatment 
(CONDUIT) will improve access to evidence-based MOUD and advance the science of implementation in 
several ways. First, CONDUIT will provide an integrated, multidisciplinary approach to implementation of 
evidence-based MOUD across the continuum of care in VHA. CONDUIT implementation teams incorporate 
expertise from addiction medicine and addiction psychiatry, primary care and hospital medicine, 
implementation science and health economics. As VHA facilities across the six Phase 2 VISNs will have a 
range of goals, this multidisciplinary approach will allow CONDUIT to work across the continuum of care at 
implementation facilities (Figure 1). Second, CONDUIT is well-positioned to advance the science of 
Figure 1. Continuum of OUD care and 
CONDUIT Core organization  

 
implementation while improving OUD care for Veterans. The CONDUIT Implementation Core brings together a 
national network of implementation experts with specific experience in addiction and pain. Third, CONDUIT will 
meaningfully engage Veterans throughout the project, ensuring that improvements in access to MOUD are 
Veteran-centered and responsive to the needs of this extremely vulnerable group. The CONDUIT Veteran 
Engagement Board will build on best practices across VHA and on local experience with Veteran engagement 
at CONDUIT sites. Finally, CONDUIT is well-positioned to collaborate with ongoing VHA initiatives such as the 
Opioid Safety Initiative, the Stepped Care for Opioid Use Disorder Treatment (SCOUTT) Initiative and the 
Health Services Research and Development (HSR&D) Pain/Opioid Consortium of Research (CORE) (Figure 
2). CONDUIT Principal Investigators are well-represented in leadership positions of these initiatives, and 
CONDUIT will both be bolstered by and simultaneously enrich these sister initiatives. 
C. Preliminary work 
C.1. Partnered Implementation Initiative (PII) Phase 1: In 2018, QUERI funded five projects co-led by VISN 
leadership and implementation experts, each addressing the VHA National Leadership Council healthcare 
priority goal to improve “access to medication-assisted therapy for opioid use disorder and alternative therapies 
for pain.” These five, one-year Phase 1 projects implemented evidence-based programs using IF in 7 medical 
centers and 8 community-based outpatient clinics (CBOCs) in 4 VISNs and across a range of clinical settings. 
Phase 1 PIIs have led to multiple activities and products with measurable impacts on the number of Veterans 
receiving MOUD and on the number of providers qualified to prescribe buprenorphine for OUD (Table 1). 
VISN1: The two VISN1 PII teams worked in parallel to expand specialty care and telehealth resources. 
They engaged teams in weekly/biweekly conference calls, performed formative evaluations, systematically 
identified capacity to implement core components and developed the business case for the value of the clinic 
model to a facility, conducted site visits and developed detailed action plans. As a result of VISN1 efforts in 
telehealth, two new prescribers were trained and tele-prescribed MOUD to Veterans at the target CBOCs; the 
three target CBOCs went from no patients treated with MOUD to 12. The VISN1 team created a toolkit 
including descriptions of logistical, legal and clinical procedures to guide spoke sites in the care of Veterans 
participating in clinical video teleconferencing, answers to frequently asked questions (FAQs), and information 
sheets to assist primary care providers (PCPs) in working with patients on buprenorphine. 
VISN19: The VISN19 PII team has delivered three buprenorphine waiver trainings in primary care settings 
to expand the workforce of prescribers qualified to prescribe buprenorphine. As of May 2019, there are 59 
prescribers in the VA Eastern Colorado Health Care System (ECHCS) with a buprenorphine waiver with 7 
PCPs and 8 Internal Medicine residents completing waiver training during Phase 1. In the VA Salt Lake City 
Healthcare System, there are 78 prescribers with a buprenorphine waiver. They have met with VISN 
leadership on a quarterly basis during Phase 1 to discuss progress and barriers. In collaboration with the MAT-
VA Initiative, they have led monthly webinars on OUD diagnosis and treatment for a national audience. They 
Table 1. PII Phase 1 Impacts 
 
 
Implementation Site 
Phase 1 MOUD rate 
FY19 buprenorphine capacity 
 
Q2 FY18 
Q2 FY19 
Waivered* 
Prescribing** 
VISN1 
2,117 (35%) 
2,216 (40%) 
 
 
VA Bedford HCS 
200 (34%) 
203 (35%) 
27 
16 
Manchester VAMC 
153 (22%) 
139 (46%) 
11 
5 
VA Maine HCS  
158 (26%) 
210 (33%) 
26 
14 
VISN19 
833 (24%) 
863 (26%) 
 
 
VA E. Colorado HCS 
189 (20%) 
173 (19%) 
57 
17 
Salt Lake City VA HCS 
197 (24%) 
227 (28%) 
74 
48 
VISN22 
1,554 (25%) 
1,701 (28%) 
 
 
S. Arizona VA HCS 
212 (32%) 
261 (44%) 
44 
20 
Phoenix VA HCS 
281 (29%) 
342 (34%) 
57 
20 
VISN23 
485 (20%) 
538 (24%) 
 
 
Iowa City VA HCS 
77 (23%) 
87 (28%) 
10 
4 
Data from the VA Academic Detailing Buprenorphine Dashboard (accessed 5/22/19). *Waivered = Number 
of providers who have completed required training; **Prescribing = Number of providers with at least 1 
active buprenorphine prescription in Q2 FY19. 

 
have also engaged Veterans, completing 10 semi-structured interviews of Veterans with OUD at VA Salt Lake 
City to understand perspective on primary care-based OUD treatment.  
VISN22: The VISN22 PII team conducted key stakeholder interviews among PCPs, nurses, pain providers, 
addiction psychiatrists, and Veterans and analyzed site-specific baseline data on process and outcome 
measures for our two VISN22 pilot sites. They led three waiver trainings for a total of 46 providers at 2 sites. 
They are developing multiple products to support expanded implementation: a PowerPoint presentation for 
PCPs on how to recognize and treat OUD; a coding “cheat sheet” for PCPs and psychiatrists to use in 
managing patients with OUD (including ICD-10 and CPT codes); a training pathway for X-waivered prescribers 
to increase confidence in prescribing buprenorphine.  
VISN23: The VISN23 PII team developed an opioid management guide to promote changes in inpatient 
opioid prescribing practices and improve recognition and management of OUD. They developed an order set 
to facilitate use of non-pharmacologic pain 
treatment options available in the hospital. Based 
on a survey of nationally available resources and 
guides for MOUD, they drafted a VHA-specific 
toolkit for improving recognition and management 
of OUD in the inpatient setting. One hospitalist 
prescriber has obtained an X-waiver during Phase 
1. Finally, they identified synergies with 
colleagues expanding MOUD to Emergency 
Department settings where shared 
implementation strategies will be beneficial. 
Since December 2018, these Phase 1 teams 
plus EF teams from VISN7 and VISN20 have met 
weekly to align implementation and measurement 
strategies. These 6 VISNs represent a diverse 
geographic sample of Veterans, healthcare providers and a range of baseline rates of MOUD at the VISN level 
(CONDUIT VISNs shown in blue in Figure 2). 
C.2. Emerging VISN Priorities: This PII Phase 2 proposal incorporates two key emerging VISN and QUERI 
priorities. First, this proposal incorporates the VISN20 EF team leading the implementation of a telehealth-
based pain management program (Tele-Pain: see Appendix 3). This project was selected for PII Phase 1 
funding starting June 2019 and offers several key points of synergy. This project shares the VHA National 
Leadership Council healthcare priority goal of improving OUD and pain treatment and is led by Dr. Steve 
Zeliadt, who co-leads the Quantitative/Economic Core of CONDUIT. Though at a more nascent stage, this 
project’s incorporation into CONDUIT will create opportunities to align measures of patient outcomes and cost 
that will benefit CONDUIT overall. Additionally, we will approach Tele-Pain sites to determine interest in 
adapting VISN1’s toolkit for tele-prescribing of MOUD, noting that about 5% of the target pain population in the 
Tele-Pain implementation sites have an OUD diagnosis. Second, this proposal expands the range of clinical 
settings targeted during Phase 1 to now include Emergency Department (ED) settings, tightly aligned with 
inpatient settings, as is consistent with real-world clinical practice. With funding from the Comprehensive 
Addiction and Recovery Act of 2016, an EF team led by Dr. Comilla Sasson, MD, PhD has led implementation 
of several ED-based opioid initiatives since 2018. Based in VISN19 at the VA ECHCS and partnered with 
national Emergency Medicine leadership in VHA, this team has led implementation of efforts to promote non-
opioid pain treatments, increase opioid overdose education and naloxone distribution and expand access to 
MOUD in ED settings.  
D. Approach 
D.1. Overview: CONDUIT’s overall objective is three-fold: 1) increasing uptake of evidence-based MOUD 
(specifically buprenorphine formulations FDA-approved for OUD and injectable naltrexone) across 4 distinct 
clinical settings using IF strategies; 2) evaluating the effectiveness of those strategies across highly-salient 
metrics of implementation success and 3) estimating costs of implementation activities. CONDUIT uses 
evidence-based IF consisting of 4 EF teams partnering with internal facilitation teams at 57 sites across 6 
VISNs to implement evidence-based practices across the OUD/pain continuum of care. Three Cores – Veteran 
Engagement, Implementation, and Quantitative/ Economic – will work across teams and sites to ensure 
alignment of measures and to support cross-CONDUIT deliverables. 
Figure 2. Proportion of Veterans with OUD Receiving MOUD 
0%
5%
10%
15%
20%
25%
30%
35%
VISN 04
VISN 01
VISN 10
VISN 12
VISN 05
VISN 17
VISN 02
VISN 20
VISN 22
VISN 21
VISN 07
VISN 06
VISN 23
VISN 19
VISN 08
VISN 15
VISN 16
VISN 09

 
 
 
D.2. Cross-CONDUIT Cores supporting overarching goals: 
Veteran Engagement Core: The Veteran Engagement Core will seek to ensure the relevance of this work 
to Veterans and to facilitate successful implementation. This Core will consist of a Veteran Engagement Board 
(VEB) and support staff. The goals of this Board are to provide feedback and oversight to CONDUIT and to 
ensure the Veteran-centeredness of implementation and dissemination. The VEB will draw on community-
based participatory research (CBPR) methods, modeled after the Veteran Research Engagement Board at the 
VA ECHCS, established as one of the first center-level Veteran engagement groups in 2014. Since March 
2019, we have engaged and met monthly with one of the Veteran Peer Support Specialists at VA ECHCS on 
the development of the CONDUIT VEB. We will also draw from experiences of Veteran Research Engagement 
Boards at VISN PII partner sites in Iowa City, Los Angeles, West Haven and Palo Alto. Finally, we will consult 
resources such as the Strengthening Excellence in Research through Veteran Engagement toolkit to ensure 
that the board has agency and a true voice in projects. 
We will recruit 1-2 Veterans from each of the VHA systems in this PII application for a total of 12-14. The 
recruitment strategy will be modeled on the successful strategy to create a national Veteran engagement panel 
for an ongoing PCORI-funded clinical trial. Recruitment will leverage the expertise and relationships of Veteran 
peer support specialists and other providers in VHA and local clinical settings at these sites, who will assist in 
identifying candidates. We will seek candidates who meet each of several criteria: 1) personal experience with 
OUD and in treatment/recovery for at least 1 year; 2) willing to work collaboratively; 3) able to demonstrate 
ability to use technology for distance participation; and 4) interested in 3-year participation. We will conduct 
preliminary meetings by telephone with participants to discuss potential roles of the VEB and request a written 
statement of interest. Candidates will then be invited to conduct a 30-minute telephone interview. A final 
summary meeting will be convened to select final candidates for invitation to the Board. The final board will be 
selected with a goal of diversity across several key domains: 1) time in treatment or recovery; 2) treatment 
received (e.g., VHA/non-VHA, MOUD/other types of treatment); 3) age; 4) gender; 5) race/ethnicity; 6) service 
era/service branch; 7) education. No previous research engagement experience will be required.  
The VEB will begin in the first half of the first year of the CONDUIT project with a 2-day, in-person meeting 
held in conjunction with the CONDUIT kick-off meeting. Members of VEB will meet once monthly for 60-90 
minutes by teleconference to provide feedback to individual EF teams and on the overall Consortium. Before 
each monthly meeting, the presenters will submit a brief project update and 2-3 questions for discussion. VEB 
members at a given site will be encouraged to meet in-person for these monthly meetings. Feedback will be 
collected from Veterans and investigators 1 week and 3 months after each meeting. The Board will hold an 
annual one-day in-person meeting in conjunction with a project-related meeting. All meetings will be facilitated 
by an experienced facilitator. Local PIs will communicate current project status to their local VEB members at 
least monthly and solicit feedback on progress, barriers and dissemination. Veterans will be compensated for 
their time at a rate of $599 annually and their travel costs for the annual meeting will be covered.  
Implementation Core: The primary aim of the Implementation Core is to work across CONDUIT to ensure 
standardized measurement of implementation activities and coordinate with the Quantitative/Economic Core to 
ensure measures are aligned with key implementation and economic outcomes. To ensure project efforts are 
maximally Veteran-centered, the Implementation Core will work closely with the VEB to engage Veterans in the 
efforts of EF/internal facilitation teams. For example, if leadership and providers are strongly resistant to 
change, then the VEB will engage regularly with them as part of the facilitation team’s work, particularly in the 
early stages. This approach is similar to methods used in CBPR, and Dr. Frank’s expertise in incorporating 
Veterans into work will be instrumental to the successful integration of Veterans into implementation teams. 
Quantitative/Economic Core: The Quantitative/Economic Core will support assessment of key outcomes 
across the 64 sites aligned with the RE-AIM framework and quantify the value of the proposed IF efforts 
through measurement of implementation costs. The overarching goal of the Quantitative/Economic Core will be 
to harmonize definitions and quantitative data extraction, accounting for potential differences in the individual 
facilities. A distributed effort model will be utilized in which a core analytic team at the Seattle-Denver COIN led 
by Dr. Zeliadt will be supported by analytic staff working with each of the local mPIs. Code will be 
collaboratively developed and reviewed across all analytic team members, and tasks will be distributed across 
the national team as needed (e.g. analysts in Los Angeles may be supporting production of audit and feedback 
reports for Maine sites). This effort is modeled after other national partnered evaluation efforts and is efficient 

 
in reducing duplication of effort while providing flexibility in supporting individual investigators. We will use SQL 
and R analytic software, and coding activities will be conducted in a shared VINCI operations workspace.  
D.3. Specific Aim 1: Implement expanded access to evidence-based MOUD in 57 sites in 6 VISNs using 
evidence-based IF activities, tailored based on CFIR-guided formative evaluation. 
D.3a. Evidence-based, effective treatment: Medication treatment of opioid use disorder  
OUD is a problematic pattern of opioid use leading to clinically significant impairment or distress. T he 
Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)6 defines OUD as the presence of 
at least 2 of 11 criteria, such as adverse consequences, craving and loss of control in a 12-month period. OUD 
may take any of several different 
forms: use of illicit heroin or fentanyl, 
non-medical use of prescription 
opioid medications such as 
oxycodone, or iatrogenic OUD in the 
setting of LTOT prescribed for 
chronic pain. 
Medication treatment for OUD 
(MOUD) is an essential component 
of evidence-based care. Strong 
evidence supports MOUD, and they 
are the “gold standard” treatments 
for OUD in VHA.7 MOUD have been 
shown to substantially decrease risk 
for all-cause mortality and overdose 
mortality in people with OUD.8 The 
treatment of OUD involves several 
FDA-approved, VA-formulary 
medications including injectable 
naltrexone, methadone, and 
buprenorphine/naloxone and 
buprenorphine (hereafter collectively 
termed buprenorphine). Methadone 
has been used successfully for more 
than 40 years to treat OUD but must 
be dispensed through specialized 
opioid treatment programs.9 Unlike 
methadone, buprenorphine and 
naltrexone for OUD can be 
prescribed in settings such as 
primary care, specialty care, 
inpatient and ED settings. 
Buprenorphine is a partial opioid 
agonist. It binds to opioid receptors 
but activates them less strongly than 
full agonists (such as heroin) do, 
reducing cravings and opioid 
withdrawal symptoms in a person 
with OUD without producing 
euphoria. To qualify to prescribe 
buprenorphine for OUD, physicians 
must meet one of several 
requirements; most providers qualify 
by completing no less than 8 hours 
of training through an accredited 
training organization in the diagnosis 
Table 2. CONDUIT implementation sites 
Implementation Site 
Phase 1 
Phase 2 
VAMC 
CBOC 
Q2 FY19 
OUD 
prevalence 
Q2 FY19 
MOUD 
rate* 
NATIONAL 
 
1.51% 
23.7% 
VISN1 
 
2.47% 
34.1% 
VA Bedford HCS 
X 
X 
1 
 
3.04% 
33.8% 
VA Boston HCS  
 
X 
1 
 
2.46% 
36.6% 
VA Connecticut HCS 
 
X 
 
2 
2.38% 
40.3% 
VA CW Mass. HCS 
 
X 
 
2 
2.93% 
27.1% 
Manchester VAMC 
X 
X 
1 
3 
1.41% 
32.0% 
VA Maine HCS   
X 
X 
 
4 
1.76% 
26.6% 
VISN7 
 
1.06% 
19.7% 
Birmingham VAMC 
 
X 
1 
1 
1.64% 
20.5% 
Columbia VA HCS 
 
X 
1 
2 
0.85% 
24.2% 
C. Alabama VA HCS  
 
X 
1 
1 
0.54% 
11.0% 
VISN19 
 
1.24% 
19.2% 
VA E. Colorado HCS  
X 
X 
1 
2 
1.14% 
12.0% 
Salt Lake City VA HCS  
X 
X 
1 
2 
1.40% 
16.9% 
E. Oklahoma VA HCS  
 
X 
1 
1 
1.41% 
12.9% 
Okla. City VA HCS  
 
X 
1 
1 
1.15% 
35.4% 
Grand Junction VAMC 
 
X 
1 
1 
0.63% 
8.5% 
Montana VA HCS  
 
X 
1 
1 
1.02% 
26.6% 
VISN20 
 
1.57% 
23.4% 
Boise VAMC 
 
X 
1 
 
0.94% 
20.8% 
VA Puget Sound – 
American Lake 
 
X 
1 
1 
1.45% 
38.3% 
VA Portland HCS 
 
X 
1 
1 
1.24% 
21.9% 
Alaska VA HCS  
X 
 
 
4 
1.15% 
19.9% 
S. Oregon VA HCS  
X 
 
 
2 
2.18% 
15.0% 
VISN22 
 
1.37% 
22.4% 
S. Arizona VA HCS  
X 
X 
1 
 
1.23% 
31.1% 
Phoenix VA HCS  
X 
X 
1 
2 
1.26% 
27.9% 
Greater LA VA HCS  
 
X 
1 
 
1.62% 
30.7% 
Loma Linda VA HCS 
 
X 
1 
 
0.96% 
16.2% 
VA San Diego HCS 
 
X 
1 
 
1.16% 
13.6% 
N. Arizona VA HCS  
 
X 
1 
 
1.46% 
20.8% 
VA Long Beach HCS 
 
X 
1 
 
1.50% 
13.1% 
N. Mexico VA HCS  
 
X 
1 
 
1.52% 
21.4% 
VISN23 
 
0.76% 
20.6% 
Iowa City VA HCS  
X 
X 
1 
 
0.68% 
21.5% 
*Data from VHA Academic Detailing Opioid Use Disorder Dashboard 
(accessed 5/23/19) 

 
and management of OUD. The vast majority of healthcare providers, nationally and in VHA, have not 
completed this training and are therefore prohibited from prescribing buprenorphine for OUD. 10 Naltrexone is 
an opioid antagonist and by works by blocking the activation of opioid receptors. Instead of controlling 
withdrawal and cravings, it treats OUD by preventing any opioid drug from producing rewarding effects such as 
euphoria. An injectable, long-acting formulation of naltrexone was FDA-approved in 2010 and may be 
appropriate for some patients with OUD. No additional training or certification are required for non-specialty 
providers to prescribe naltrexone. 
D.3c. Implementation sites: CONDUIT will engage a total of 57 sites (24 medical centers and 33 CBOCs; 
Table 2; see Appendix 4 for additional detail). Selection of these sites was guided by our VISN partners and 
informed by Phase 1 experience.  
D.3b. Brief summaries of CONDUIT programs by clinical setting: 
Primary care: Buprenorphine delivered in primary care is associated with decreased opioid use, higher 
quality of care, and improved quality of life.11-13 Thus, evidence-based models of primary care-based OUD 
treatment, namely the Medical Management model14 and the Nurse Care Management model,15 are the focus  
of CONDUIT implementation in primary care settings. In this program, the EF team works collaboratively with 
internal facilitation teams to expand the availability of MOUD in VHA primary care settings by increasing the 
number of providers/teams prepared to initiate and manage evidence-based MOUD.  
Specialty care: This program prioritizes patients on LTOT for chronic pain, as many in this sub-population 
already have OUD, are at high risk for developing it, or may be experiencing negligible benefit. Consistent with 
VA/DoD guidelines16 and a mandate from the Comprehensive Addiction and Recovery Act of 2016,17 we 
developed a multi-disciplinary clinical program—the Opioid Reassessment Clinic (ORC)18-20—that assesses 
benefits and harms, seamlessly initiates MOUD when OUD is diagnosed, and ensures access to evidence-
based non-opioid treatments for pain.  
Acute care (inpatient / emergency department): This program capitalizes on ED visits or hospitalization 
as critical intervention windows by engaging ED physicians and hospitalists to reduce opioid overprescribing 
and increase uptake of MOUD while reaching patients at high-risk due to medical comorbidities. We integrate 
evidence-based and established consensus approaches to opioid prescribingl,21 use of non-pharmacologic 
pain treatment,22 and diagnosis and treatment of OUD in hospitalized patients,23-25 into a coherent approach 
that can be adapted to medical centers with and without specialty pain or addiction medicine services. 
Telehealth: While there is an inadequate number of providers in rural areas certified and/or trained to 
provide MOUD,26 telemedicine has been found to be as effective as in-person visits for treating a range of 
mental illnesses, and for prescribing buprenorphine and other MOUD.27,28  
Each of the EF teams will work collaboratively with internal facilitation teams to deploy the core IF activities 
outlined in Table 3 as well as additional IF activities noted. Evaluations performed by the Implementation Core, 
in partnership with each facilitation team (e.g., formative evaluation, survey, IF logs as outlined in D4 below), 
will identify whether any adaptations need to be made to the IF activities. For example, if the Telehealth EF 
team identifies technical issues as a 
barrier to implementation, they will 
incorporate technical assistance into 
IF, and it will be added to their IF log 
for tracking its use during 
implementation.  
D.3d. Integration of 
implementation activities: The 
foundation of CONDUIT’s 
implementation activities are the 
structured interactions between the 
four EF teams and internal 
facilitation teams. A core set of IF 
activities will be used across all 
facilitation teams, and EF teams will 
use additional ones based on the 
needs of their sites or clinical 
settings (Table 3). EF and internal 
Table 3. Core and Site-specific IF Strategies 
Core IF activities (used across all facilitation teams) 
Monthly site calls between external and internal facilitation teams 
Monthly Community of Practice calls 
Internal facilitation team engages EF team to support implementation 
EF team engages internal facilitation team to support implementation 
Academic Detailing/Education  
Problem-solving based on assessment of implementation barriers and 
facilitators 
Developing materials and adding them to a shared library 
Informing local opinion leaders, leadership, and/or administrators 
Site-specific IF activities 
Audit and feedback (Specialty, Primary Care) 
Site-specific learning collaborative (Acute Care) 
Develop incentives (Primary Care) 
 
Conduct cyclical, small tests of change (Primary Care) 
Technical assistance (Primary Care) 

 
facilitation teams will attend a monthly Community of Practice call. This has the distinct advantage of allowing 
internal facilitation teams across sites to learn about the full range of CONDUIT implementation activities. For 
example, if an internal facilitation team working the Specialty Care EF team is interested in moving beyond 
ORC and enhancing access to MOUD in the inpatient setting, they can learn from the Acute Care EF team. 
The Implementation Core will provide consultative expertise on the IF activities used by each facilitation team.  
D.4. Specific Aim 2: Evaluate Implementation Facilitation using a mixed methods approach to assess 
Reach, Effectiveness, Adoption, Implementation, and Maintenance.  
D.4a. Overview: The CONDUIT evaluation of IF will consist of two strategies: a mixed methods formative 
evaluation to gain site-level, granular understanding of implementation barriers and facilitators and guide IF 
tailoring, and quantitative outcomes evaluation guided by the RE-AIM framework. 
D.4b. Conceptual framework: Two complementary frameworks will guide our evaluation of CONDUIT – the 
Consolidated Framework for Implementation Research29 (CFIR) and the RE-AIM framework,30 similar to 
previous work led by Dr. Midboe.31 The CFIR will guide formative evaluation (Table 4). Within the RE-AIM 
framework, we will assess Reach, Effectiveness, Adoption, Implementation, and Maintenance as they apply to 
project work within each clinical setting (Table 5).  
D.4b. Formative evaluation: A formative evaluation will be conducted at different stages of implementation 
and will assess Implementation and Maintenance outcomes (Table 5);32 see Appendix 5 for a detailed 
timeline. For the developmental (pre-implementation) formative evaluations, the EF and internal facilitation 
teams and their staff will be responsible for collecting data related to facilitators and barriers and using rapid 
analysis techniques.33 They will be trained on rapid analytic techniques, requiring completion of templated 
matrices to identify key themes. If needed, an Implementation Core member will be available to attend calls 
and assist with completion of these evaluations and matrices. The EF team will conduct the developmental 
formative evaluation on a site-specific call during the pre-implementation period. The Implementation Core will 
develop a relatively briefly semi-structured interview guide of the core CFIR constructs (Table 4), and 
incorporate additional items based on unique needs of facilitation teams in differing clinical settings. Given the 
large and rapid scale of implementation, it is not feasible to conduct individual interviews of stakeholders, 
transcribe, and analyze the transcriptions.  
 
For progress-focused formative evaluations, we will collect data in the monthly IF logs (Appendix 6), which 
is the same approach the larger SCOUTT initiative is using. It allows the facilitation teams and Implementation 
Core to track progress and address new barriers on monthly calls as they arise. The Implementation Core will 
provide monthly reports on the IF logs to each of the facilitation teams. For the interpretive evaluation, the 
Implementation Core will use stratified random sampling to select implementation sites for interviews post-
maintenance. Approximately 3 to 5 sites per EF team (strata) will be selected randomly for in-person/phone 
interviews. We aim to interview key stakeholders, including Veterans, at 15 to 25 sites, with a target of 
approximately 5 participants per site, resulting in a final sample of 75 to 125 participants. We will use a CFIR-
Table 4. Core CFIR Constructs Mapped to Implementation Facilitation Activities 
Implementation 
Needs  
CFIR Domain  CFIR Constructs  
Implementation Facilitation (IF) 
Activities  
Engagement of 
key clinical 
stakeholders  
Intervention 
characteristics 
 
Inner setting  
▪ Adaptability  
▪ Design quality & packaging  
▪ Complexity  
▪ Leadership engagement 
▪ Tension for change 
▪ Relative priority 
▪ Academic detailing  
▪ Informing local opinion leaders, 
leadership, administrators  
▪ Problem-solving 
▪ Regular contact with IF team 
▪ Community of practice 
Coordination of 
care across 
clinical settings 
Inner setting 
▪ Networks and 
communications 
▪ Ease of access to 
information/knowledge 
▪ Developing materials (e.g., note 
templates) and adding them to a 
shared library 
▪ Academic detailing 
▪ Problem-solving 
Providers believe 
engaging in 
MOUD is better 
than not engaging 
Characteristics 
of individuals  
▪ Knowledge and beliefs about 
the intervention 
▪ Self-efficacy   
▪ Academic detailing  
▪ Informing local opinion leaders, 
leadership, administrators  

 
guided semi-structured interview guide that will designed to capture barriers, facilitators, and adaptations made 
to the original intervention and implementation activities. Although we plan to use audio recordings, they will 
not be transcribed given the rapid timeline of this project. We will use extensive notes and the recordings as 
needed to conduct a rapid analysis and pull illustrative quotes. Rapid analysis has been shown to produce 
equivalent findings to more resource-intensive, in-depth analytic techniques.33 The Implementation Core, in 
collaboration with the qualitative experts (e.g., Drs. Drummond and Mattocks) across multiple settings, will 
conduct this evaluation.  
D.4c. Tracking IF activities and other implementation strategies: The Implementation Core will rely on a 
standardized REDCap tracking log (see Appendix 6 for sample tracking log) that EF and internal facilitation 
teams will complete monthly during the implementation phase, allowing for efficient data aggregation, cleaning, 
and analysis. See Table 3 for core IF activities that will be captured across all sites as well as site-specific IF  
activities that will be captured in a modified REDCap tracking log that includes additional activities. The final 
format of these logs will be developed in partnership with the Quantitative/Economic Core so that they can be 
used to calculate return on investment in facilitation activities. The Quantitative/Economic Core will be 
responsible for aggregating and cleaning all data to be used for analyses related to implementation and cost, 
but in close partnership with the Implementation Core. If pre-implementation and implementation formative 
evaluation activities reveal barriers that require IF activities to be modified, then the REDCap tracking logs will 
be modified accordingly. For example, if an EF team is not using audit and feedback, but it is clear that a 
clinical setting does not perceive the need to change, they may add audit and f eedback to their IF activities. 
We decided against using a more formal tailoring approach34 because those require more time and resources 
and our operational partners have a more rapid timeline in mind, although we can rely upon them should the 
partners prefer a more systematic approach. 
Given that some site staff may rely on implementation strategies as part of local QI efforts that may fall 
outside of the IF activities measured in the logs, we will also ask internal facilitation teams to complete a web-
based survey at baseline (pre-implementation) and then at the end of each study year. This survey captures a 
wide variety of implementation strategies beyond IF activities and has been used previously to evaluate 
implementation of a national initiative focused on engaging veterans with hepatitis C in treatment. 35 The lead 
author, Dr. Shari Rogal, part of the Implementation Core, will assist with adapting and analyzing the Expert 
Recommendations for Implementing Change (ERIC) survey for the needs of CONDUIT (see Appendix 7 for 
sample survey). Dr. Rogal and her team will summarize data from each site for the Implementation Core so 
that the latter can provide feedback to the EF teams about any implementation strategies to track monthly as 
part of IF activities. This data summary will include descriptive statistics about individual strategies and clusters 
of strategies used at the site over time. Correlational analyses will be conducted to assess the associations 
between strategies (individual strategies, number of strategies used, and clusters) and RE-AIM measures. This 
will allow us to understand which strategies are associated with improved site-level outcomes more broadly. 
Both the IF logs and the ERIC survey will allow us to assess Implementation outcomes (Table 5).  
D.4d. Quantitative evaluation: 
D.4d1. Cohort identification: To assess impact of IF efforts, we will identify a cohort of at-risk patients—those 
who have OUD but are not prescribed MOUD—to track their outcomes over time. Methods to identify at-risk 
patients will be harmonized across all implementation sites. These will include use of available data in the 
Corporate Data Warehouse (CDW), including medication/pharmacy records (inpatient and outpatient), 
toxicology screen results, primary care and mental health care utilization, inpatient admissions, comorbidity 
data, recent treatment and service use such as alternative pain treatments for the subgroup of MOUD patients 
with pain, and other information to determine at-risk Veterans appropriate for referral for MOUD. We will  
compare outcomes at each implementation site during the post-implementation period to outcomes prior to 
implementation, using each site as their own control. Each site will have a defined implementation start date 
and an implementation start-up period of 3-months in which outcomes will not be attributed to either the pre- or  
post-implementation period. For sites that have booster or additional implementation efforts, additional start  
dates of those efforts will be tracked. Harmonization of definitions for at-risk Veterans will also facilitate 
comparing sites across VHA not participating in MOUD-related implementation activities to examine secular 
trends and to rapidly identify targets for expanding the implementation efforts for MOUD referral in additional 
VISNs. A person-years approach will be used as Veterans may be at-risk and eligible for referral for MOUD at 
multiple time points during the three-year project.  
D.4d2. Implementation/clinical outcomes: The Quantitative/Economic Core will work with the 
Implementation Core on two primary areas: (1) ensuring accuracy and consistency of assessments of RE-AIM 

 
outcomes across CONDUIT, with the Quantitative/Economic Core focused on Reach, Effectiveness, and 
Adoption; and (2) assisting in tracking and assessing frequency and duration of IF activities (e.g., logs of time 
related to implementation efforts that includes phone calls, meetings, education) across EF teams so that costs 
can be assigned to implementation efforts (Table 5). Reach: The primary reach outcome is the use of MOUD 
among at-risk individuals. At each implementation site we will identify at-risk individuals during the pre- and 
post-implementation periods, using modified criteria from the MOUD dashboard. Using the cohort definitions 
described above, each at-risk Veteran will be assigned an index date and at-risk person-years will be  
determined for both pre- and post-implementation periods as appropriate. The outcome will be calculated 
based on filling a qualifying prescription for buprenorphine or naltrexone. We note that this outcome is similar 
to the SCOUTT evaluation, however, the SCOUTT evaluation focuses on individual provider prescribing 
practices because providers were the focus of the intervention. In CONDUIT, any fill of buprenorphine or 
naltrexone will be counted because the focus on the implementation efforts are on the entire site, not individual 
provider practices. Effectiveness: Our primary effectiveness outcome will be the number of at-risk Veterans 
who participate in a full course of MOUD. This analysis will be similar to the Reach analysis, but will focus on 
the date of completing a full course of MOUD. Secondary outcomes will include rates of hospitalizations and 
ED visits related to OUD/SUD for Veterans who utilized MOUD compared to Veterans who do not use MOUD 
during the pre- and post-implementation period. Using a person-years approach we will identify at-risk 
individuals and determine the relevant time that they are at risk of potential adverse events. Hospitalization and 
ED visits with a primary or secondary diagnosis code of OUD/SUD will be identified using established 
methods, and will be guided by SCOUTT evaluation. We also propose examining the effect of implementation 
on a) total opioid doses; b) receipt of overlapping opioid-sedative prescriptions, and c) opioid-related or other 
Table 5. Outcomes Mapped to RE-AIM Constructs 
RE-AIM 
Construct 
Primary Outcome(s) 
Secondary Outcomes 
Reach 
Number of patients with OUD initiating MOUD 
during the implementation period in 
implementation sites1 
 
Effectiveness 
Number of patients with OUD retained on 
MOUD at 90 days and 180 days during the 
implementation period (i.e. treatment retention)1 
▪ Hospitalizations and ED visits related 
to OUD post-implementation1 
▪ Opioid-related or other drug 
overdoses in patients with OUD post-
implementation 
▪ Opioid dose for patients on LTOT 
post-implementation1 
▪ Concomitant opioid-sedative 
prescriptions post-implementation1 
Adoption 
Number of providers (and/or clinics) providing 
MOUD post-implementation, stratified by type of 
provider, clinical setting1 
Number of VISTA x-waivered providers 
post-implementation 1 
Implementation 
▪ Facilitators and barriers to implementation2 
▪ Fidelity, as measured by frequency and 
duration of Implementation Facilitation 
strategies3 and other implementation 
strategies4 
▪ Cost of implementation1,3 
Variation in facility-level use of 
implementation strategies over time 
Maintenance 
▪ Summary of facilitators and barriers at 
implementation clinics 6 months post-
implementation2 
▪ Elements of program maintained, including 
adaptations2 
▪ Number of VISTA x-waivered and prescribing 
providers 6-month period post-implementation 
Number of OUD patients receiving 
MOUD 12-24 months after 
implementation 
Data source: 1CDW; 2Semi-structured interviews; 3REDCap facilitation tracking logs; 4REDCap survey of 
ERIC strategies. 

 
drug overdoses.36 Coding strategies will be adapted as necessary to address Cerner adoption and CHOICE 
and MISSION use of community care records. Adoption: Outcomes focused on provider adoption of MOUD 
will be assessed. For each implementation site we will identify providers and assess the proportion of those 
providers who provide MOUD or who are credentialed to provide MOUD (VISTA X-waivered providers). 
Changes in these proportions between the pre- and post-implementation periods will be assessed as an 
indicator of implementation success.  
D.4d3. Analytic approaches: Our non-randomized evaluation design is necessary because randomization 
was not possible due to our partnership with VISN leadership and outreach efforts for individual site 
participation. A key goal is to demonstrate to VISN and facility leadership the value of implementation; 
therefore, we will estimate implementation outcomes for each of our individual sites and pool implementation 
sites as appropriate. This will allow us to provide descriptive quantitative information about individual 
implementation efforts to be combined with qualitative findings about implementation success. Although these 
analyses will allow for some comparison of effectiveness across individual team efforts, we do not propose 
formal direct comparisons of teams. There are several statistical limitations to the non-randomized evaluation 
design that we will address through pragmatic approaches. To account for secular trends in increased use of 
MOUD that may not be due to our implementation efforts, we will track other related implementation efforts 
such as initiation of additional SCOUTT efforts, and monitor national dashboards to generate a secular rate 
among non-intervention sites. We will use this secular rate and test to determine if CONDUIT activities 
increase use of MOUD above this rate, rather than a null hypothesis of 0. Because we are calculating 
outcomes for each of the individual sites, the risk of a spurious finding due to multiple testing is possible. We 
will use caution when interpreting any moderate p-values (e.g. 0.01 to 0.05) as significant. For ease in 
reporting to VISN and site leadership, we will utilize direct pre- and post-implementation period comparisons. 
Additional multivariate adjusted analysis using time-to-event semi-parametric methods will also be explored. 
These models will focus on initiation of MOUD treatment, and will allow for examining clinical and demographic 
characteristics, including time from initial OUD diagnosis. 
D. 4d4. Power and sample size: 
Small facilities will have limited power 
to detect small implementation effects, 
and evaluating implementation 
success for these sites will incorporate 
mixed methods also using qualitative 
findings. The ability to pool sites using 
similar implementation strategies will ensure our evaluation has adequate power. Table 6 highlights that post-
implementation follow-up periods that include samples of 200 patients will allow for detection of meaningful 
effect sizes in the 0.2 range.37,38  
D.5. Specific Aim 3. Estimate the cost of implementation and return on investment  
D.5a. Overview: We use well-established methods with which our team has extensive experience to estimate 
the costs of implementation and return on investment with the primary goal of helping VISN leadership 
evaluate adoption, scale and spread of the clinical programs we implement. 
D.5b. Economic outcomes: The primary economic outcome across all projects is cost per additional Veteran 
initiating MOUD. This includes both implementation costs and costs of delivering the clinical 
program/intervention. Return on investment will also be calculated and will include total costs including 
concurrent/downstream treatment and medical care costs.  
D.5c. External facilitation costs: Cost and expenses associated with EF activities will be directly captured 
through monitoring of expenses associated with QUERI funding as well as VISN contributions. We anticipate 
that nearly 100% of support from QUERI will be allocated to implementation activities and tracked across the 
implementation efforts. Efforts that cannot be allocated individually to a specific clinical program (e.g. general 
interviews with national stakeholders) will be split equally across the relevant EF teams. Implementation staff 
will be asked to log collateral hours of effort they incur in excess of the QUERI and VISN support. Each month 
each investigator and project coordinator on the Implementation Core and each EF team will be asked to 
confirm that the effort allocated to the project (e.g. 10% FTE) and report how those hours were allocated to 
mutually exclusive implementation activities such as outreach/coordination with sites, planning, training, 
technical assistance, feedback, evaluation. This effort will be conducted in coordination with the VISN20 Tele-
Table 6. Power calculation  
Estimated Number of At-
Risk Veterans in Post-
Implementation Period 
50 
75 
200 
750 
Effect size (with 
power=0.80) 
0.40 
0.32 
0.20 
0.10 

 
Pain PII (PI Zeliadt), which is focusing on assessing the implementation costs associated with facilitation of 
expanding Tele-Pain to CBOCs in Alaska and Oregon. A recent effort by Dr. Zeliadt of the QUERI partnered 
evaluation effort assessing implementation costs associated with the adoption of the Whole Health System of 
care utilized a similar strategy. A validation step in which implementation activities were re-reviewed with the 
guidance of a qualitative interviewer found this approach to be robust and reflective of actual implementation 
effort. Notably, some sites identified costs originally logged as implementation to be reclassified as care 
delivery activities or other non-related costs of the implementation effort. For this project, we will incorporate 
brief reviews with key personnel to help ensure appropriate attribution to implementation efforts.  
D.5d. Internal facilitation/site costs: The Implementation and Quantitative/Economic Cores will rely on 
parallel efforts to assign costs to implementation efforts at each site, an approach we have refined in our 
experience with several large projects.39 In conjunction with the Implementation Core, we will develop items to 
be included in the monthly implementation log tracking using REDCap. These logs will be completed by sites’ 
internal facilitators to collect data on personnel (e.g. time spent) and non-personnel costs (e.g. travel, supplies, 
equipment) associated with the implementation efforts. Additional semi-structured interview items capturing 
personnel time associated with any implementation burdens, as well as items for the 12-month post-
implementation survey will also be developed based on the tracking logs and interviews. 
D.5e. Clinical program costs: In order to identify specific delivery costs of each clinical program, we will 
utilize a micro-costing approach in which qualitative assessment of providers’ time associated with the study is 
informed by time and motion studies.40 Process maps of each clinical activity will be generated for each of the 
five programs. Dr. Whittington will train internal facilitators to perform time and motion studies as needed to 
identify estimates of typical times to complete specific program activities. Dr. Whittington is currently leading 
the effort to calculate the cost of implementation for the national implementation of the SCOUTT initiative. 
Methods and tools developed for that evaluation will translate to this work.  
D.5f. Downstream/concurrent costs: Recent literature has found the additional treatment costs of MOUD are 
offset by lower utilization of medical services.41 To calculate the cost offsets associated with MOUD in VHA, we 
will conduct an ancillary analysis of the cost trajectories between patients treated with and without MOUD. This 
will be a national analysis to ensure high numbers of MOUD recipients. We will first identify national sample of 
Veterans eligible for MOUD and the subgroup of those treated with MOUD in 2018. We will extract each 
patient’s healthcare costs using inpatient, outpatient, and pharmacy utilization between 2016 to 2019, which 
will be used to develop of longitudinal cost trajectories similar to prior work led by Drs. Zeliadt and Whittington 
in the areas of complementary and integrative health. To identify the cost or cost savings attributable to  
initiation of MOUD, we will compare the costs over time for those patients that are treated with MOUD to those 
patients that are not treated with MOUD using a difference in differences specification. A generalized gamma 
regression with log link will be specified. Personnel from HERC are included in the Quantitative/Econ Core to 
help identify all relevant clinical care costs, as well as to assist in capture all potential utilization activities 
delivered through community care activities. 
D.5g. Implementation, clinical and cost outcomes analysis: We will aggregate the personnel time and 
financial resource data collected to calculate the total cost of IF for each implementation effort. Using an 
“intent-to-treat” approach with person-years as the unit of analysis, we will calculate separate multilevel mixed 
models for each clinical/RE-AIM outcome and cost outcome. We will pool implementation efforts across clinical 
settings as appropriate (e.g. all primary care implementation efforts will be combined into a single analysis). 
Exposure to IF implementation-as-usual conditions will be based on timing and randomized as appropriate to 
each project, such as stepped-wedge designs. We will account for clustering of patients across multiple 
exposure periods, as well as nesting of patients within clinical settings. This approach will allow assignment of 
at-risk Veterans to different facilitation levels as well as control for secular trends in pre-post implementation 
efforts. At-risk Veterans who were initially exposed to implementation-as-usual condition will be censored 
relative to outcome assessment for that phase if they or their provider is exposed to IF. The model will include 
an indicator variable for implementation and clinic program status, and an interaction between time and this 
indicator variable to assess for the independent effect of implementation separate of secular trends. Longer 
term costs, such as 12-month medical care cost trajectories following exposure to potential referral to MOUD 
will be included as appropriate. Markov models based on the outcome of the point estimates from the clinical 
and economic outcome models will be developed to estimate confidence intervals of key measures such as 
cost per additional at-risk patient receiving MOUD. 
 

 
 
 
 
 
E. Partnerships 
 Our primary partnership will be with the OMHSP’s Substance Use Disorder group, led by Dr. Karen 
Drexler. The Principal Investigator (PI) team has a longstanding history of collaboration with Dr. Drexler’s 
group as well as our other key operational partners – the National Pain Management Program Office (Dr. 
Friedhelm Sandbrink), Primary Care Operations (Dr. Angela Denietolis), and Pharmacy Benefits Management 
(Dr. Fran Cunningham) and its Academic Detailing Service (Dr. Melissa Christopher). Our collective, Phase 1 
work and the proposed work was made possible by the support of a highly collaborative, responsive group of 
Network Directors: Ryan Lilly, MPA (VISN 1); Leslie Wiggins (VISN 7); Ralph T. Gigliotti, FACHE (VISN 19); 
Michael J. Murphy, FACHE (VISN 20); Michael Fisher (VISN 22); Robert P. McDivitt, FACHE (VISN 23).  
F. Study team and relevant experience 
The CONDUIT leadership team brings together a multidisciplinary team of implementation experts, 
researchers and clinicians. The expertise and broad 
experience of this team will allow CONDUIT to work 
effectively across the continuum of care at 
implementation facilities using evidence-based IF to 
leverage resources and address challenges for 
individual implementation sites. The EF teams will 
be led by CONDUIT Principal Investigators 
supported by the Cores (Table 7). All members of 
the leadership team have been integrally involved in 
Phase 1 activities and have established 
partnerships with key collaborators at the VISN and 
facility levels as described above. Individually, the 
CONDUIT leadership team has extensive 
experience supported by focused training in 
Implementation Facilitation. Dr. William Becker 
(corresponding PI) has extensive experience with 
pragmatic effectiveness and implementation 
research in both OUD and chronic pain and has led 
several completed and ongoing multi-site projects. 
 Local resources at CONDUIT leadership team 
facilities are well-suited to contribute to the team’s 
ability to succeed and include: QUERI centers in 
West Haven, Iowa City, Denver, Los Angeles, 
Seattle and Palo Alto; HSR&D Centers of 
Innovation at all seven CONDUIT leadership 
facilities; VISN20 VA Center for Excellence in 
Substance Addiction Treatment and Education 
(CESATE); VISN19 Vulnerable Veteran Integrated 
PACT (VIP) Program at the VA Salt Lake City; 
VISN22 QUERI Complementary and Integrative 
Health Evaluation Center; and VISN7 Mental Illness 
Research, Education and Clinical Center 
(MIRECC). The CONDUIT leadership team is also 
ideally positioned to ensure productive collaboration 
with several related national resources and 
initiatives: 
Stepped Care for Opioid Use Disorder 
(SCOUTT) Initiative: Dr. Adam Gordon (mPI) and 
Dr. Eric Hawkins (Co-I) have leadership roles in the 
implementation and evaluation of SCOUTT. 
Table 7. CONDUIT Study Team 
Core 
Key Personnel 
Veteran 
Engagement 
Joseph Frank, MD, MPH 
 
Implementation 
Amanda Midboe, PhD (Imp. Sci.) 
Mark McGovern, PhD (Imp. Sci.) 
Hildi Hagedorn, PhD (Imp. Sci.) 
Allyson Varley, PhD (Qualitative) 
Kristin Mattocks, PhD (Qualitative) 
Karen Drummond, PhD 
(Qualitative) 
Quantitative / 
Economic 
Steve Zeliadt, PhD (Health 
Economist) 
Melanie Whittington, PhD (Health 
Economist) 
Clinical setting 
External Facilitation team 
Specialty care 
William Becker, MD (Internist) 
Ellen Edens, MD (Psychiatrist) 
Erica Abel, PhD (Informaticist) 
Sara Edmond, PhD (Psychologist) 
Telehealth 
Marc Rosen, MD (Psychiatrist) 
David Moore, MD (Psychiatrist) 
Nicole Brunet, PharmD 
(Pharmacist) 
Dora Wischik, RN, MSN (Nurse) 
Jennifer Bergmann, PsyD 
(Psychologist) 
Primary care 
Evelyn Chang, MD (Internist) 
Joseph Frank, MD (Internist) 
Adam Gordon, MD (Internist) 
Eric Hawkins, PhD (Psychologist) 
Emily Williams, PhD (Imp. Sci.) 
Rebecca Oberman, MSW 
Inpatient / 
Emergency 
Department 
Hilary Mosher, MD (Hospitalist) 
Stefan Kertesz, MD (Internist) 
Comilla Sasson, MD, PhD 
(Emergency physician) 
Underline denotes External Facilitation leads 

 
Multiple CONDUIT team members are engaged within their respective VISNs with SCOUTT implementation 
HSR&D Pain/Opioid Consortium of Research (CORE): With its creation in May 2019, this HSR&D CORE 
will play a key role in shaping HSR&D research priorities. Dr. Becker (mPI) is 1 of 3 co-directors of this group. 
The Opioid Safety Initiative:42 Launched in 2013, this system-wide initiative leveraged the VA’s data 
capabilities and organization to provide facility- and provider-level data in inform opioid safety efforts. 
The Medication for Addiction Treatment in the VA (MAT-VA) Initiative: A national consult service for VA 
clinicians which, since 2007, has provided mentoring and resources for VA clinicians. The MAT-VA Initiative is 
directed by Dr. Adam Gordon (mPI) at the Salt Lake City VA 
G. Management plan and timeline 
G.1. Management plan: Dr. William Becker will serve as corresponding PI and will lead the CONDUIT 
Coordinating Center, responsible for overseeing and ensuring integrated, productive interactions among the 
Cores and among the Cores and the implementation sites. Dr. Joseph Frank will lead the Veteran Engagement 
Core. He will be responsible for coordination of recruitment, orientation and prospective administrative support 
for this group. He will ensure collaboration and alignment with other ongoing Veteran engagement initiatives.  
Dr. Amanda Midboe will lead the Implementation Core and has extensive experience working as an 
implementation scientist and leading implementation work across multiple projects. Drs. Steve Zeliadt and 
Melanie Whittington will lead the Quantitative /Economic Core. Dr. Zeliadt will be responsible for working with 
the Implementation Core to identify direct analytic support needs. He will oversee analytic staff who will extract 
and clean data from CDW and REDCap. Dr. Whittington will oversee economic activities including calculating 
the cost of implementation efforts, estimating the potential cost savings of initiation of MOUD, and calculating 
the return on investment of each project. 
In the first six months of the project, there will be at least bi-weekly phone meetings for among the Core 
leads and Dr. Becker to ensure coordination across External Facilitation teams (Table 7). After six months, 
these meetings will transition to monthly meetings unless more frequent meetings are necessary. There will 
also be regular email and telephone contact. The Implementation and Quantitative/ Economics Core will meet 
weekly with their respective teams. Our operational partners will serve as our Strategic Advisory Group, 
including 1 to 2 Veterans from the CONDUIT VEB. They will guide the consortium with respect to VHA 
priorities. There will be a monthly CONDUIT-wide teleconference for all project personnel. Twice annually, the 
project-wide meeting will include the Strategic Advisory Group. See the Multiple PI Plan for further details 
about the organization, responsibilities and plans for integration of implementation efforts across the EF teams. 
G.2. Deliverables: In Phase 2 of this Partnered Implementation Initiative, CONDUIT will build on Phase 1 
deliverables to generate several products that will advance OUD care more broadly in VA. 
Implementation toolkit: CONDUIT will integrate and iteratively refine current Phase 1 implementation 
toolkits to comprehensively address the continuum of OUD care (Specialty Care, Primary Care, Acute Care, 
Telehealth) and improve access and usability by VA stakeholders. For example, the VISN1 External 
Facilitation team led by Dr. Marc Rosen and Dr. David Moore have created and distributed an implementation 
toolkit to guide MOUD by telehealth. This 54-page Word document covers multiple key domains including 
clinical, logistical and legal considerations related to buprenorphine prescribing using VHA telehealth. 
Training: In Phase 1, all CONDUIT EF teams provided training to key personnel at implementation sites. 
Buprenorphine is an important tool for expanding MOUD provision across the continuum of care but is 
currently restricted to providers who have completed at least 8 hours of training (Table 1 above). For example, 
during Phase 1, Dr. Adam Gordon led 12 buprenorphine waiver trainings in VISN19 and nationally. In Phase 2, 
integration of these EF teams will provide a platform on which to harmonize and expand training opportunities, 
and this expanded training is a key CONDUIT deliverable. 
Provider consultation or technical assistance support: CONDUIT will also leverage and expand upon 
existing consultation resources available throughout the VHA Medication for Addiction Treatment in the VA 
(MAT-VA) Initiative. CONDUIT aims to implement at more than 50 facilities, including small, rural community-
based outpatient clinics. Longitudinal support and consultation resources will be a key deliverable to support 
evidence-based OUD care, especially at these CBOCs.  
G.3. Dissemination: We will provide quarterly briefings to QUERI and key operational partners during the 
project period so that any preliminary information on effective strategies can be disseminated promptly. We will 
disseminate our findings and products to the VA clinical community through established MAT-VA Initiative 
newsletters, email groups, and cyberseminars. We will also disseminate our findings to the scientific 
community by publishing our findings in implementation and substance use disorders journals including  

 
publications reporting the quantitative, formative evaluation and cost and budget impact findings. We will also  
present our finding to VA and non-VA audiences at meetings such as AcademyHealth, VA HSR&D, and 
Addictions Health Services Research. We expect multiple manuscripts will be published, both at the level of 
the Consortium as well as more focused publications at the level of the External Facilitation team. Building on 
team members’ involvement in prior and current multi-site projects, we will adhere to an explicit process for 
coordinating and sharing authorship of peer-reviewed manuscripts and other dissemination efforts (See 
Multiple PI plan for additional details on project governance). 
G.4. Future directions: In year 3 of CONDUIT, we will compete for additional funding to support national 
expansion as Phase 3 of this Partnered Implementation Initiative. CONDUIT’s robust partnerships with national 
and VISN leadership as well as its collaboration with concurrent, related VHA initiatives will ensure that 
CONDUIT is prepared to expand on the successes of Phase 2 to implement the evidence-based, effective 
practice of MOUD across the VHA continuum of care nationally. 
Table 8. CONDUIT Gantt Chart  
 
FY20 
FY21 
FY22 
FY23 
 
PII Phase 2 
 
 
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 
Implementation 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Launch Phase 2 (n of sites) 
 
10 
13 
 
13 
 
 
 
 
 
 
 
 
 
Implementation Facilitation 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Evaluation 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Implementation data 
collection 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  ERIC survey  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  IF log 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Formative evaluation 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Quantitative data collection 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Refine cohort/risk criteria 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Extract/finalize CDW 
outcomes 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Implementation analysis 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  ERIC survey analysis 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  IF log analysis 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Formative evaluation 
analysis 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Quantitative/Econ analyses 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Report Phase 1 outcomes 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Preliminary Phase 2 
outcomes 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Final outcomes 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Report implementation cost 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Downstream costs impact 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Implementation Reporting  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Integration 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
All-project kick-off meeting 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Project-wide teleconferences 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Strategic Advisory Group 
meetings 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Dissemination 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Presentations to partners 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Publications, seminars 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Phase 3 funding application