Clinic-Randomized Trial of Clinical Decision Support for Opioid Use Disorders in Medical Settings (COMPUTE 2.0)
Phase: NA
Conditions: Opioid-use Disorder
Sponsor: HealthPartners Institute

 
 
 
 
 
 
 
 
 
 
 
NIDA CTN Protocol 0095 
 
Clinic-Randomized Trial of Clinical 
Decision Support for Opioid Use 
Disorders in Medical Settings 
(COMPUTE 2.0) 
 
 
 
 
Lead Investigators: Gavin Bart, MD, PhD; Rebecca Rossom, MD, MS 
 
 
Funded by: National Institute on Drug Abuse (NIDA) 
 
March 31, 2023 
 
Version 6.0 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
i 
PROTOCOL DEVELOPMENT TEAM 
 
Lead Investigators (LI): 
Gavin Bart, MD, PhD 
 
NorthStar Node 
 
Hennepin Health; University of Minnesota 
 
Rebecca Rossom, MD, MS 
 
NorthStar Node 
 
HealthPartners Institute; University of Minnesota 
Study Team: 
JoAnn Sperl-Hillen, MD; Co-Investigator, HealthPartners 
 
Patrick O’Connor, MD, MS, MA; Co-Investigator, 
HealthPartners 
 
A. Lauren Crain, PhD; Co-Investigator, HealthPartners 
 
Steven Dehmer, PhD; Co-Investigator, HealthPartners 
 
Michael Maciosek, PhD; Co-Investigator, HealthPartners 
 
Anne Pylkas, MD; Co-Investigator, HealthPartners 
 
Leif Solberg, MD; Co-Investigator, HealthPartners 
 
Stephanie Hooker, PhD; Co-Investigator, HealthPartners 
 
Ben Crabtree, PhD; Consultant, 
Robert Wood Johnson Medical School 
 
Laurel Nightingale, MPH; Project Manager, HealthPartners 
 
Anna Bergdall, MPH; Project Manager, HealthPartners 
 
Caitlin Borgert-Spaniol, MPH; Project Manager, 
HealthPartners 
 
Rashmi Sharma; EPIC Programmer, HealthPartners 
 
Debbie McCauley; EPIC Programmer, HealthPartners 
 
Deepa Appana; Web Programmer, HealthPartners 
NIDA CCTN Scientific Officer: 
Kristen Huntley, PhD 
Emmes: 
Paul Van Veldhuisen, PhD; DSC PI 
 
Jennifer McCormack, MS; DSC Co-PI, Statistician 
 
Lauren Yesko, PMP; DSC Project Director 
 
Eve Jelstrom, MBA, CRNA; CCC PI 
 
Dikla Blumberg, PhD; CCC Co-PI 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
ii 
TABLE OF CONTENTS 
1.0 
LIST OF ABBREVIATIONS ............................................................................................ 1 
2.0 
STUDY SYNOPSIS ......................................................................................................... 3 
 
Study Objectives .......................................................................................................... 3 
 
Study Design and Outcomes ....................................................................................... 5 
 
Sample Size and Study Population .............................................................................. 6 
 
Treatment/Assessment/Intervention and Duration........................................................ 7 
 
Safety Reporting .......................................................................................................... 7 
 
Analyses ...................................................................................................................... 7 
3.0 
STUDY SCHEMA ............................................................................................................ 9 
 
Key Research Site Roles ............................................................................................. 9 
4.0 
INTRODUCTION ............................................................................................................10 
 
Background and Significance to the Field ...................................................................10 
5.0 
OBJECTIVES.................................................................................................................14 
 
Primary Objectives ......................................................................................................14 
 
Secondary Objective(s) ...............................................................................................15 
 
Exploratory Objective(s) ..............................................................................................15 
6.0 
STUDY DESIGN ............................................................................................................16 
 
Overview of Study Design ...........................................................................................16 
 
Duration of Study and Visit Schedule ..........................................................................16 
7.0 
OUTCOME MEASURES ................................................................................................17 
 
Outcome Measures .....................................................................................................17 
 
Study Timeline ............................................................................................................18 
8.0 
STUDY POPULATION ...................................................................................................20 
 
Primary Care Clinics ...................................................................................................20 
 
PCPs and Clinic Staff ..................................................................................................20 
 
Patients .......................................................................................................................21 
 
Healthcare System Leaders ........................................................................................22 
 
Strategies for Recruitment and Retention ...................................................................22 
9.0 
SITE SELECTION ..........................................................................................................27 
 
Number of Sites ..........................................................................................................27 
 
Site Characteristics .....................................................................................................27 
 
Rationale for Site Selection .........................................................................................28 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
iii 
10.0 
STUDY PROCEDURES .................................................................................................30 
 
Index Visit ...................................................................................................................30 
 
Randomization ............................................................................................................30 
 
Treatment/Intervention ................................................................................................31 
 
Premature Withdrawal of Participants .........................................................................31 
 
Study Halting Rules ....................................................................................................31 
 
Follow-Up ...................................................................................................................31 
 
Participant Reimbursement .........................................................................................31 
11.0 
STUDY ASSESSMENTS ...............................................................................................32 
 
Table of Assessments .................................................................................................32 
 
Mixed Methods ...........................................................................................................33 
 
General Measures ......................................................................................................44 
 
Contact Information..............................................................................................44 
 
Demographics Form ............................................................................................44 
 
Measures of Primary and Secondary Outcomes .........................................................44 
 
Clinical and Safety Assessments ................................................................................44 
12.0 
TRAINING REQUIREMENTS ........................................................................................45 
 
Overall ........................................................................................................................45 
13.0 
STATISTICAL DESIGN AND ANALYSES .....................................................................46 
 
General Design ...........................................................................................................46 
 
Study Hypotheses ................................................................................................46 
 
Primary and Secondary Outcomes (Endpoints) ...................................................46 
 
Recruitment .........................................................................................................47 
 
Randomization and Factors for Stratification ........................................................48 
 
Prediction Models ................................................................................................49 
 
Rationale for Sample Size and Statistical Power .........................................................50 
 
Projected Number of Sites ...................................................................................50 
 
Projected Number of Participants per Site ...........................................................50 
 
Statistical Methods for Primary and Secondary Outcomes ..........................................52 
 
Qualitative Data Analysis .....................................................................................53 
 
PCP Survey Data Analysis ...................................................................................54 
 
Patient Survey Data Analysis ...............................................................................54 
 
Significance Testing ....................................................................................................54 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
iv 
 
Interim Analysis ..........................................................................................................55 
 
Exploratory Analysis ...................................................................................................55 
 
Missing Data and Dropouts .........................................................................................56 
 
Demographic and Baseline Characteristics .................................................................56 
 
Safety Analysis ...........................................................................................................56 
14.0 
REGULATORY COMPLIANCE, REPORTING AND MONITORING ..............................57 
 
Statement of Compliance ............................................................................................57 
 
Institutional Review Board Approval ............................................................................57 
 
Informed Consent .......................................................................................................57 
 
OUD-CDS Implementation ...................................................................................57 
 
Patient, PCP and Health System Leader Interviews and Surveys ........................58 
 
Quality Assurance Monitoring .....................................................................................59 
 
Participant and Data Confidentiality ............................................................................59 
 
Certificate of Confidentiality .................................................................................59 
 
Health Insurance Portability and Accountability Act (HIPAA) ................................60 
 
Investigator Assurances ..............................................................................................60 
 
Financial Disclosure/Conflict of Interest ...............................................................60 
 
Clinical Monitoring.......................................................................................................60 
 
Inclusion of Women and Minorities .............................................................................61 
 
Prisoner Certification ...................................................................................................61 
 Regulatory Files ..........................................................................................................61 
 Records Retention and Requirements ........................................................................61 
 Reporting to Sponsor ..................................................................................................62 
 Audits..........................................................................................................................62 
 Study Documentation ..................................................................................................62 
 Protocol Deviations .....................................................................................................62 
 Safety Monitoring ........................................................................................................63 
 
Data and Safety Monitoring Board (DSMB) ......................................................63 
 
Safety Events ...................................................................................................63 
15.0 
DATA MANAGEMENT ..................................................................................................65 
 
Design and Development ............................................................................................65 
 
Site Responsibilities ....................................................................................................65 
 
Data Collection/Acquisition and Entry .........................................................................65 
 
Qualitative Data ...................................................................................................65 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
v 
 
Survey Data .........................................................................................................66 
16.0 
PUBLIC ACCESS AND DATA SHARING PLAN ...........................................................67 
17.0 
PROTOCOL SIGNATURE PAGE ..................................................................................68 
18.0 
REFERENCES ...............................................................................................................69 
19.0 
APPENDIX A: DATA AND SAFETY MONITORING PLAN ...........................................72 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
1 
1.0 
LIST OF ABBREVIATIONS 
Abbreviation 
Definition 
BPA 
Best Practice Advisory 
CCC 
Clinical Coordinating Center 
CCTN 
Center for the Clinical Trials Network 
CDS 
Clinical Decision Support 
CFR 
Code of Federal Regulations 
CMS 
Centers for Medicare and Medicaid Services 
CoC 
Certificate of Confidentiality 
CRF 
Case Report Form 
CTN 
Clinical Trials Network 
DSC 
Data and Statistics Center 
DSM-5 
Diagnostic and Statistical Manual of Mental Disorders, 5th Edition 
DSMB 
Data Safety Monitoring Board 
ED 
Emergency Department 
EHR 
Electronic Health Record 
ERC 
Ethics Review Committee 
FTE 
Full-Time Equivalent 
FWA 
Federal wide Assurance 
GCP 
Good Clinical Practice 
HHS 
Department of Health and Human Services 
HIPAA 
Health Insurance Portability and Accountability Act 
HPMG 
HealthPartners Medical Group 
HSP 
Human Subjects Protection 
ICD-10 
International Classification of Diseases, 10th Revision 
ICH 
International Council for Harmonisation of Technical Requirements  
for Pharmaceuticals for Human Use 
IRB 
Institutional Review Board 
IT 
Information Technology 
MAT 
Medication Assisted Treatment 
MD 
Medical Doctor 
MOUD 
Medications for Opioid Use Disorder 
NHLB 
National Heart Lung and Blood Institute 
NIDA 
National Institute on Drug Abuse 
NIH 
National Institutes of Health 
NP 
Nurse Practitioner 
OHRP 
Office for Human Research Protection 
OUD 
Opioid Use Disorder 
PA 
Physician Assistant 
PCP 
Primary Care Provider 
PI 
Principal Investigator 
PNMG 
Park Nicollet Medical Group 
QA 
Quality Assurance 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
2 
Abbreviation 
Definition 
RE-AIM 
Reach, Effectiveness, Adoption, Implementation, Maintenance 
RN 
Registered Nurse 
RVU 
Relative Value Units 
SMI 
Serious Mental Illness 
TAPS 
Tobacco, Alcohol, Prescription Medication and other Substance use 
TCRRVs 
Total Care Relative Resource Values TM 
UC 
Usual Care 
XR-NTX 
Extended-Release Injectable Naltrexone 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
3 
2.0 
STUDY SYNOPSIS 
 
Study Objectives 
Objective: Through CTN-0076-Ot (Clinical Decision 
Support for Opioid Use Disorders in Medical Settings: 
Pilot Usability Testing in an EMR (COMPUTE)), our team 
has iteratively developed and piloted a web-based and 
electronic health record (EHR)-integrated Opioid Use 
Disorder (OUD) Clinical Decision Support (CDS) system 
to offer expert guidance to primary care providers (PCPs) 
on the diagnosis and management of OUD. The OUD-
CDS has been implemented within the EPIC EHR of one 
large care system and was piloted with 55 providers to 
ensure content validity and provider satisfaction. Our 
team will now implement this OUD-CDS in a large multi-
site clinic-randomized controlled trial to evaluate its 
impact on practice process measures and patient 
outcomes. We also aim to prepare for scalability (i.e., 
integration into usual primary care practice after the study 
is complete) and dissemination by evaluating facilitators 
and barriers to implementation, determining the costs of 
implementation and maintenance, and assessing the 
short-term cost impacts of the OUD-CDS. 
The study will include three large diverse care systems 
and randomize a minimum of 30 clinics to receive the 
OUD-CDS intervention or usual care (UC). In intervention 
clinics, the OUD-CDS will identify patients who are at 
high risk for OUD or diagnosed with OUD; use data 
stored in the EHR for each eligible patient to assemble 
treatment recommendations tailored to each patient’s 
current needs; display these recommendations to PCPs via the OUD-CDS user interface; and 
store analytic data from all targeted visits. In UC clinics, the OUD-CDS will run invisibly in the 
background to identify high-risk or OUD patients, assemble treatment recommendations tailored 
to each eligible patient’s needs, and store analytic data from all targeted visits. 
Specific Aims: 
Aim 1. To implement OUD CDS in primary care settings and assess its impact on process 
measures related to diagnosis of patients at high risk for OUD, as well as prescription of 
naloxone for patients at high risk for or diagnosed with OUD. 
H1.1: Patients previously undiagnosed with OUD but identified as high risk by the OUD-CDS 
at an index visit will be more likely to receive an OUD diagnosis (in the problem list or as an 
International Classification of Diseases, 10th Revision (ICD-10) visit code) in intervention 
clinics than in UC clinics within 30 days post-index. 
Definitions 
Intervention Period 
 Varies by system 
 OUD-CDS implementation date 
through a predetermined time at 
which the Wizard interfaces will 
be turned off in the intervention 
clinics  
Accrual Period 
 Varies by system 
 OUD-CDS implementation date 
through a predetermined time at 
which no more people will be 
included in the analytic sample 
Index Date 
 Varies by patient 
 First visit at which the OUD-CDS 
identifies that the patient is study 
eligible 
Observation Period 
 Varies by patient 
 Index visit date through a 
predetermined time at which 
outcome data will no longer be 
accumulated 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
4 
H1.2: Patients previously diagnosed with OUD or identified as high risk by the OUD-CDS at 
an index visit will be more likely to have naloxone rescue kits ordered in the intervention clinics 
than in the UC clinics within 30 days post-index. 
Aim 2. To assess the impact of OUD-CDS on important patient outcomes of initiation and 
maintenance of Medications for Opioid Use Disorder (MOUD) in patients identified as 
having OUD or being at high risk for OUD. 
H2.1: Patients identified as having OUD or as being at high-risk for OUD by the OUD-CDS at 
an index visit will be more likely to have MOUD orders or referral for OUD treatment within 30 
days post-index in intervention clinics than in UC clinics. 
H2.2: Patients identified as having OUD or as being at high-risk for OUD by the OUD-CDS at 
an index visit will have significantly more days covered by a MOUD prescription at 90 days 
post-index in intervention clinics than in UC clinics. 
Aim 3. To assess the long-term impact of OUD CDS on important patient outcomes in 
patients with OUD or identified as high risk for OUD. 
H3.1: Patients with OUD or identified as high-risk for OUD by the OUD-CDS who are cared 
for in intervention clinics will have significantly fewer post-index emergency department (ED) 
visits during the observation period (i.e., the period between each patient’s index date and 
last observation) compared to patients cared for in UC clinics. 
H3.2: Patients with OUD or identified as high-risk for OUD by the OUD-CDS who are cared 
for in intervention clinics will have significantly fewer post-index hospitalizations during the 
observation period compared to patients cared for in UC clinics. 
Aim 4. To describe and quantify costs of OUD-CDS implementation and maintenance and 
the short-term cost impacts of the OUD-CDS. 
H4.1: After controlling for demographics, baseline clinical status and prior costs of care, 
patients with OUD or identified as high risk for OUD by the OUD-CDS will have lower 
healthcare costs in intervention compared to UC clinics during the observation period (i.e., 
savings from lower ED visits and hospitalizations will outweigh increased costs of OUD 
treatment and naloxone rescue kits and OUD-CDS implementation and maintenance). 
Aim 5. To use mixed quantitative and qualitative methods to identify, describe and quantify 
barriers and facilitators to implementation of the OUD-CDS so that it can be adapted to 
maximize its use and effectiveness. 
Secondary Analyses: As secondary outcomes, we may assess whether patients with OUD or 
identified as high risk for OUD by the OUD-CDS who are cared for in intervention clinics have 
lower post-index rates of all cause death and of fatal or non-fatal opioid overdoses during the 
intervention period compared to similar patients in UC clinics. We will also assess OUD-CDS use 
rates for intervention clinics and assess whether the effectiveness of OUD-CDS varies as a 
function of site, clinic, provider or patient characteristics. Finally, we will assess whether PCP 
ratings of confidence in treating patients with OUD differ at 9 months between treatment groups, 
and how intervention PCPs rate satisfaction and acceptability of the OUD-CDS tool at 9 months. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
5 
Exploratory Analyses: In exploratory analyses, we will assess whether (a) PCPs in intervention 
clinics who are non-waivered at go-live dates are more likely to become buprenorphine-waivered 
than PCPs in UC clinics during the intervention period; (b) waivered PCPs in intervention clinics 
are more likely to prescribe buprenorphine than PCPs in UC clinics during the intervention period; 
(c) whether PCPs in intervention clinics who are non-waivered at go-live dates are reportedly 
more likely to prescribe buprenorphine should a waiver no longer be required than PCPs in UC 
clinics measured prior to go-live dates and at 9 months following go-live dates; (d) if we have 
adequate data, potentially via health plan or Surescripts data, whether adherence/persistence to 
methadone, buprenorphine, XR-NTX or therapy for patients with OUD differs for patients in 
intervention vs. UC clinics during the observation period; and (e) PCPs in intervention clinics are 
more likely to screen their patients for mental health conditions and infectious diseases than PCPs 
in UC clinics during the intervention period. 
Notes: The COVID-19 pandemic has delayed implementation, and these impacts to date are 
reflected in the updated timeline (Section 7.2). HealthPartners vanguard clinic sites went live on 
February 3, 2021; and remaining randomized clinics went live on April 7, 2021. The vanguard 
clinic site at Geisinger is anticipated to go live in November 2021, with remaining sites anticipated 
to be operational in December 2021 or January 2022. The vanguard clinic site at Essentia is 
anticipated to go live in January 2022, with remaining sites anticipated to be operational by April 
2022. 
Two supplemental studies are associated with this study and will be conducted only at 
HealthPartners. The first, 3UG1DA040316-06S3 (aka CTN-0095-A-1), is a cluster-randomized 
trial that randomizes half of COMPUTE intervention clinics to receive decision support aimed at 
suicide prevention. The second, 3UG1DA040316-06S4 (aka CTN-0095-A-2), is a clinician-
randomized trial of an intervention aimed at reducing OUD stigma for PCPs. Separate protocols 
for each supplemental application reference this protocol.  
 
Study Design and Outcomes 
In this multicenter clinic-randomized pragmatic trial, clinics will be randomized 1:1 to OUD-CDS 
or to UC within each healthcare system. To encourage a larger number of buprenorphine-
waivered PCPs in both intervention and UC clinics, we may offer financial incentives to become 
waivered. 
Primary outcome measures will include: 
1. OUD diagnosis (in the problem list or as an ICD-10 visit code) within 30 days of index 
visit for patients identified by the OUD-CDS as being at high risk of OUD 
2. Naloxone prescription within 30 days of index visit for patients with OUD or identified by 
the OUD-CDS as being at high risk for OUD 
3. MOUD orders or referral to OUD treatment within 30 days of index visit for patients with 
OUD or identified by the OUD-CDS as being at high risk for OUD 
4. Total days covered by an MOUD prescription in the 90 days after index visit for patients 
with OUD or identified by the OUD-CDS as being at high risk for OUD 
Secondary outcome measures will include: 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
6 
1. OUD diagnosis (in the problem list or as an ICD-10 visit code) at index or within 90 days 
of index visit for patients identified by the OUD-CDS as being at high risk of OUD 
2. Naloxone prescription at index or within 90 days of index visit for patients with OUD or 
identified by the OUD-CDS as being at high risk for OUD 
3. MOUD orders or referral to OUD treatment at index or within 90 days of index visit for 
patients with OUD or identified by the OUD-CDS as being at high risk for OUD 
4. Number of ED visits during the observation period for patients with OUD or identified by 
the OUD-CDS as being at high risk for OUD 
5. Number of hospitalizations during the observation period for patients with OUD or 
identified by the OUD-CDS as being at high risk for OUD 
6. Healthcare costs during the observation period for patients with OUD or identified by the 
OUD-CDS as being at high risk for OUD, compared with healthcare costs over the same 
interval preceding the observation period 
7. Cost of OUD-CDS implementation and maintenance 
8. All-cause mortality rates during the observation period for patients at high risk of OUD 
9. Fatal and non-fatal opioid overdoses during the observation period for patients at high 
risk of OUD 
10. Rates of OUD-CDS use in intervention clinics 
11. PCP ratings of confidence in treating patients with OUD at baseline and 9 months 
12. Intervention clinic PCP ratings of satisfaction and acceptability of the OUD-CDS at 9 
months 
Other outcome variables will include: 
1. Number of non-waivered PCPs becoming buprenorphine waivered during the 
intervention period, assessed via health system administrative data 
2. Number of buprenorphine prescriptions written by waivered PCPs during the intervention 
period 
3. PCP ratings of likelihood to prescribe buprenorphine for patients with OUD, should no 
waiver be required, measured prior to go-live dates and at 9-months following go-live 
dates 
4. Adherence to therapy during the observation period, assessed via Clarity and claims 
data 
5. Number of patients diagnosed with OUD screened for mental health comorbidities and 
infectious diseases during the observation period 
 
Sample Size and Study Population 
The study will be conducted at a minimum of 30 primary care clinics within 3 healthcare systems 
in the United States that are geographically dispersed and will include a racially, ethnically and 
socioeconomically diverse population. Clinics will be randomized equally within each care system 
and balanced on pre-randomization outcomes, such as the percentage of patients at high-risk or 
with diagnosed OUD, and on clinic characteristics that may enhance or impede intervention 
uptake and adherence, such as the number of buprenorphine-waivered PCPs (see Section 10.2). 
PCPs who practice at randomized clinics will be asked to complete pre-and post-implementation 
surveys assessing their comfort and confidence treating patients with OUD. Primary and 
secondary outcomes data will be collected from the EHR or CDS tool for each patient with an 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
7 
eligible index visit. Following intent-to-treat principles, all PCPs and eligible patients will be 
attributed to the arm to which their clinic is randomly assigned. Surveys will also ask providers in 
intervention clinics about their perceptions of the OUD-CDS. Additionally, we will conduct surveys 
with patients and interviews with PCPs, clinic staff, clinic leaders and patients to understand their 
perceptions of the acceptability of OUD treatment in primary care and their impressions of the 
OUD-CDS to help improve the implementation and uptake of the OUD-CDS. 
 
Treatment/Assessment/Intervention and Duration 
The OUD-CDS provides clinical guidance to PCPs in the screening, diagnosis and treatment of 
OUD, along with common comorbid conditions, and will display for patients with OUD or at high 
risk for OUD in intervention primary care clinics during each site’s intervention period (see 
timeline). PCPs are also able to access the OUD-CDS in EPIC for patient encounters for which it 
did not display (e.g., new patient visits). Patient follow-up time from the date of index visit is 
estimated to range from 18 to 31 months. 
The OUD-CDS will be tested and evaluated prior to implementation, in the early implementation 
phase, and during the maintenance phase at each site by a combination of qualitative data 
collection, monitoring of use rates and PCP surveys at all time points. 
 
Safety Reporting 
This study will randomize clinics to receive or not receive a CDS tool to facilitate the provision or 
accepted standards of care. With this work, we are not attempting to change the standard of care 
for OUD treatment in primary care, but rather are attempting to help PCPs achieve this standard 
of care in OUD treatment. PCPs will be trained that, as with other clinical decision tools, the OUD-
CDS is meant to supplement but not supersede clinical judgment. PCPs will be able to choose to 
follow or to not follow the guidance of the CDS at any given time for any given patient. PCPs will 
be asked to use the Feedback Tab within the tool to let the team know of questions or potential 
errors in the CDS. Additionally, PCPs will be trained to let the research team know via the 
Feedback Tab when their clinical judgment is inconsistent with the CDS. This feedback will be 
monitored by the treatment team and the CDS algorithms adjusted if indicated. 
An independent Clinical Trials Network (CTN) Data and Safety Monitoring Board (DSMB) will 
monitor this study. Tables will summarize, by site and blinded treatment group, (a) number of 
patients, index visits and eligible clinic encounters during the intervention period; (b) rates of OUD-
CDS use in intervention clinics; (c) baseline clinic and patient characteristics; and (d) safety 
measures (overdose rates, hospitalization rates, ED visit rates, content of PCP feedback via 
Feedback Tab and any actions taken in response). Reports will be provided to the DSMB at a 
frequency the DSMB requests. The CTN DSMB will be responsible for conducting periodic 
reviews of accumulating study data. The CTN DSMB will provide an opinion on whether there is 
support for continuation of the trial, evidence that study procedures should be changed, or 
evidence that the trial should be halted for any reason, such as the safety of study participants, 
the efficacy of the treatment under study or inadequate trial performance. 
 
Analyses 
Aims 1 through 3 pertain to the effectiveness of the OUD-CDS intervention relative to UC, 
predicting that it will increase diagnosis, naloxone prescribing, and access to MOUD, and 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
8 
decrease ED visits and inpatient hospital stays. These hypotheses will be tested using 
generalized linear mixed models to account for clustering of outcomes within eligible patients and 
randomized clinics or generalized estimating equations to compare event rates across clinics. 
Outcomes will be normalized via distribution-appropriate link functions (e.g., logistic-Normal, 
Poisson-Normal). Clinic-randomized treatment group, care system and other predictors will be 
treated as fixed effects. 
For Aim 4, OUD-CDS implementation and maintenance costs will include programming, training 
and ongoing algorithm maintenance but exclude research costs, using micro-cost accounting 
methods and nationally-representative pricing of inputs. A generalized linear model, allowing 
clustering by clinic and controlling for demographics and baseline clinical risk factors, will estimate 
costs by study arm to account for the skewed distribution of costs.[1-3] Economic analyses will 
be done in consultation with the NIDA P-30 CHERISH program. 
The Aim 5 mixed methods analysis will include an iterative, team-based, triangulation of 
quantitative and qualitative data sources. Qualitative analysis of the field notes, observations and 
interviews will be conducted using techniques of qualitative content analysis based on a 
deductive-directed approach to evaluate the factors influencing RE-AIM constructs.[4] 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
9 
3.0 
STUDY SCHEMA 
Overview of COMPUTE 2.0: (Note: go-live and intervention periods have been impacted by 
delays due to COVID-19.  Please refer to Section 7.2 Study Timeline.) 
Site 1
10+ primary care 
clinics
OUD-CDS tool
5+ primary care clinics
No OUD-CDS tool
5+ primary care clinics
Site 2
10+ primary care 
clinics
OUD-CDS tool
5+ primary care clinics
No OUD-CDS tool
5+ primary care clinics
Site 3
10+ primary care 
clinics
OUD-CDS tool
5+ primary care clinics
No OUD-CDS tool
5+ primary care clinics
Data collection from all sites, all clinics (control and intervention) during intervention period (OUD-CDS data, EHR 
data, claims data): OUD-CDS use rates, OUD diagnoses, naloxone orders, MOUD orders, OUD referrals, 
days covered by MOUD prescriptions, ED visits, hospitalizations, all-cause mortality, opioid overdoses, # waivered 
PCPs, MOUD & therapy adherence, screening for infectious diseases and mental health issues
Go-live: April 2020 
Go-live: Jan 2022
Go-live: March 2022
Data Collection
PCP Interviews (Design and Implementation)
PCP Surveys (Implementation-Baseline, 9 months)
Patient Interviews (Design and Implementation)
Patient Surveys (Implementation)
Leader Interviews (Implementation)
PCP Interviews (Design and Implementation)
PCP Surveys (Implementation-Baseline, 9 months)
Patient Interviews (Design and Implementation)
Patient Surveys (Implementation)
Leader Interviews (Implementation)
PCP Interviews (Design and Implementation)
PCP Surveys (Implementation-Baseline, 9 months)
Patient Interviews (Design and Implementation)
Patient Surveys (Implementation)
Leader Interviews (Implementation)
 
 
Key Research Site Roles 
Prime Healthcare System: HealthPartners 
Co-Lead and Site Principal Investigator (MD, DO, PhD) 
Co-Investigator 
Health Economist 
Biostatistician 
Clinical Champion (MD, PhD, NP, PA, DO) 
Project Manager 
Research Assistant 
EPIC Programmer 
Web Programmer 
User Experience Expert 
Data/Clarity Programmer 
Mixed Methods Consultant 
 
Partner Healthcare Systems (Geisinger and Essentia): 
Site Principal Investigator (MD, DO, PhD) 
Co-Investigator with mixed methods experience 
Clinical Champion (MD, PhD, NP, PA, DO) 
Research Coordinator/Project Manager 
EPIC Programmer 
Data/Clarity Programmer 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
10 
4.0 
INTRODUCTION 
 
Background and Significance to the Field 
Statement of the Problem. We are in the midst of an opioid epidemic.[5] More than 72,000 
people in the US died from drug overdoses in 2017, including illicit and prescription opioids.[6] 
Approximately 20% of patients diagnosed with OUD seek treatment, but only 25% of those 
receive MOUD.[7] Primary care is the most common point of healthcare contact in the US and 
may be able to help reduce this significant treatment gap. Buprenorphine and monthly injections 
of XR-NTX show promise for OUD treatment in primary care.[8-14] Over 50,000 physicians are 
waivered to prescribe buprenorphine, but only 14,000 (28%) do.[15] Providers identify time 
constraints, poor access to clinical guidelines, and lack of institutional support, staff training and 
confidence as barriers to using buprenorphine.[15-18] Similar barriers limit the use of XR-NTX.[19] 
In the last decade, EHR-linked web-based point-of-care CDS systems designed to improve quality 
of chronic disease care have become increasingly sophisticated and successful [20-22]. Our 
team has developed a CDS system that improves glucose and blood pressure control in adults 
with diabetes, reduces 10-year cardiovascular risk in high risk patients, and increases recognition 
of adolescents with hypertension in clinic-randomized trials. [23-27] Use rates of the CDS system 
remain high at 70-80% of targeted encounters, and the CDS tools have obtained 95% PCP 
satisfaction ratings. This web-based CDS system is designed for scalability, is used by 4 large 
health care systems serving approximately 2 million patients and has recently been implemented 
through a National Heart, Lung, and Blood Institute (NHLBI) grant at 60 federally health care 
qualified centers in 10 states. 
Prior Work. Through CTN-0076-Ot, we piloted a CDS tool that supports the diagnosis and 
treatment of OUD in primary care at HealthPartners. A total of 55 enrolled PCPs included 8 of our 
11 buprenorphine-waivered MDs, 24 non-waivered medical doctors (MDs), and 22 non-waivered 
advanced practice PCPs. The OUD-CDS tool translates the NIDA CTN Blending Initiative White 
Paper [unpublished] into web-based algorithms that identify patients at high risk for OUD and 
provides a usable and intuitive interface that guides PCPs through OUD management and 
referrals, when indicated. The OUD-CDS tool links to the prescription drug monitoring database. 
It uses the Tobacco, Alcohol, Prescription medication and Substance Use (TAPS) tool [28] to 
screen patients for OUD and prompts use of Diagnostic and Statistical Manual of Mental 
Disorders, 5th Edition (DSM-5) [29] diagnostic criteria for patients with positive TAPS screens. 
Next, the treatment selection module alerts PCPs to any relative contraindications to certain 
MOUDs, and guides prescription of MOUDs or referral for OUD treatment, as appropriate. It 
provides patient educational materials, including a one-page summary of MOUDs, as well as 
detailed MOUD-specific handouts. The final module prompts screening for common 
comorbidities, such as infectious diseases and mental health conditions, and includes 
recommendations to bring vaccinations up-to-date. All modules contain active guidelines that 
make it easy to order recommended labs, medications and referrals by clicking on links within the 
text, saving the PCP time and clicks. The orders are then reviewed within the EHR prior to signing. 
In CTN 0076-Ot, use rates were disappointingly low, in that PCPs used the OUD-CDS in 5% of 
eligible encounters with patients identified at high risk. PCPs reported that barriers to use included 
not seeing the alert banner in EPIC, not feeling they had enough time to address opioid risk, or 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
11 
feeling OUD was a low priority for the patient or that the PCP could tell who was at risk for OUD. 
This PCP feedback has been instrumental in our planning for this trial, as it gives us actionable 
steps to take to improve use rates of the OUD-CDS, which we outline in Section 8.5 (Strategies 
for Recruitment and Retention). One key change in the larger study will be to have multiple 
alerts to the care team that a patient has been identified as high risk and that use of the OUD-
CDS is recommended, including alerts to the rooming staff. In prior work, this has substantially 
improved uptake of the CDS tool. 
In surveys, 66% of intervention PCPs (21 of 32 PCPs) and 
75% of waivered intervention PCPs (6 of 8 PCPs) were 
moderately or very likely to recommend the tool to 
colleagues. In all, 89% of PCPs thought the OUD-CDS 
helped them screen for OUD, 86% felt the tool made them 
feel more comfortable in prescribing MOUDs, 93% felt the 
tool made it easier to discuss treatment options with 
patients, 93% felt the tool helped them know when to refer 
patients, and 82% felt the tool saved them time. 
Intervention PCPs (both waivered and non-waivered) 
reported increased confidence in screening for OUD after 
the intervention on 4-point Likert scales (Figure 1), while 
only non-waivered PCPs saw a significant increase in 
confidence in diagnosing OUD by the end of the trial 
(Figure 2). None of the PCPs reported a significant 
increase in treating OUD by the end of the trial (Figure 3). 
Early feedback from the COMPUTE 1.0 pilot has informed 
research strategies to further improve uptake of the tool 
and the user experience, such as considering use of other 
care opportunities (e.g., telephone encounters where 
opioid prescription renewals are requested; annual 
renewal of opioid use agreements), involving rooming 
staff in the screening process, changing the type of EHR 
alert, and simplifying the user interface. We will 
incorporate these changes in COMPUTE 2.0 as detailed 
in Section 8.5, as well as provide clinic- and PCP-specific 
use rates to clinic leadership, which in prior work has 
increased use rates to 70-80% of eligible encounters.[30] 
Summary of Study Design. The proposed study will include 3 large diverse healthcare systems 
and randomize a minimum of 30 clinics equally within each system to receive the OUD-CDS 
intervention or UC. In intervention and UC clinics, the OUD-CDS will identify study-eligible 
patients, those who are at high risk for OUD or diagnosed with OUD; and will use data stored in 
the EHR to assemble treatment recommendations tailored to the needs of each study-eligible 
patient. In intervention clinics, these treatment recommendations will be displayed via the OUD-
CDS user interface. Finally, data from all targeted visits in all randomized clinics will be stored in 
a data repository for analysis and reporting needs. The targeted visits for each study-eligible 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
12 
patient in all randomized clinics will be the index visit, the first visit at which the OUD-CDS 
identifies that the patient is study eligible, and all post-index visits through the end of the 
intervention period, regardless of continued eligibility. This pragmatic cluster-randomized design 
is the optimal design to effectively and efficiently implement this tool in primary care clinics while 
protecting against study contamination and allowing for collection of process and outcome data 
at UC clinics. 
Statement of Hypotheses. We hypothesize that patients at high-risk for OUD in intervention 
clinics will be more likely to be diagnosed with OUD, and that those at high-risk for or diagnosed 
with OUD will be more likely to receive naloxone rescue kits, have MOUD orders or referrals, 
have more days covered by MOUD prescriptions, have fewer ED visits and hospitalizations, and 
have lower healthcare costs. We hypothesize that qualitative data will help to identify barriers and 
facilitators to implementation and propose steps to mitigate barriers. 
Mixed Methods Approach. Virtually every evidence-based intervention in medicine has turned 
out to be difficult to implement and maintain in real life practice and to fall far short of fidelity to 
the process used in randomized trials.[31, 32] As a result, a whole new field of dissemination and 
implementation research has been developing over the last 20 years. These studies have now 
gone well beyond the previous paradigm of focusing on changing the attitudes and behaviors of 
individual physicians to a growing awareness that the need instead is to alter the environment in 
which physicians work so that it is easier to do the desired evidence-based thing than to stick with 
old established habit patterns.[33] That means focusing change efforts on organizational factors 
and practice systems. The Solberg conceptual framework has proven to be particularly helpful in 
clarifying this new approach.[34] 
Simultaneously, there has been increasing interest in transitioning effectiveness clinical trials from 
traditionally highly selective and controlled circumstances to pragmatic trials that make use of 
normal care delivery processes and patients.[35] The measurement of such trials has been 
facilitated by the development of a conceptual framework called RE-AIM, an acronym for 5 key 
facets of such studies – Reach, Effectiveness, Adoption, Implementation, and Maintenance.[36, 
37] Recently, the developers of RE-AIM have recognized the need for more flexible use of this 
framework, greater use of qualitative methods to understand why interventions are not used 
consistently, and making adaptations in the implementation approach based on such 
understandings.[38-41] We propose to use the RE-AIM framework to guide (1) a monitoring 
system for intervention problems, (2) a mixed methods evaluation of the reasons for those 
problems, and (3) modification of the intervention to reduce those problems. These steps will be 
reiterated in a cyclic fashion, resulting in a more sophisticated approach to the long-standing 
quality improvement emphasis on Plan-Do-Study-Act rapid cycle tests of change.[42, 43] 
Furthermore, we will take advantage of the staggered implementation of the study through three 
different care systems to ensure that the solutions for intervention problems in Site 1 are not 
assumed to be the same as the approach in subsequent sites without further RE-AIM monitoring 
and evaluation. 
Potential Risks and Benefits. There is a small but important risk that the OUD-CDS could 
provide the wrong treatment advice at the wrong time. As with other clinical decision tools, the 
OUD-CDS makes suggestions for patient care that are meant to supplement but not supersede 
clinical judgment. PCPs can choose to follow or not follow the guidance of the CDS at any given 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
13 
time in any given patient encounter. PCPs will be trained to let the research team know via the 
Feedback Tab in the CDS when their clinical judgment leads them to a different action than that 
suggested by the CDS. These events will be monitored in real time by the treatment team and 
the CDS algorithms adjusted if there are found to be errors. Every clinical encounter requires 
medical judgment and poses some element of risk to patients. In the situation of a PCP who is 
unfamiliar or uncomfortable with OUD, use of the CDS will likely make care safer by providing 
suggestions to screen and assess for OUD using validated tools, and to encourage referrals when 
patients are classified as high risk. We will not be encouraging buprenorphine use in non-certified 
providers, and this will be reinforced in PCP training on the CDS. For buprenorphine-certified 
providers, the use of the CDS may improve the likelihood of using MOUD in high-risk situations; 
however, the risks of MOUD are generally considered lower than untreated OUD in high-risk 
situations. This is a minimal risk study and the risk to a patient who is not receiving MOUD greatly 
exceeds the risk of the CDS intervention. Overall, the potential benefits of providing the OUD-
CDS to intervention clinics, which include the ability to improve the identification of patients at-
risk for OUD, to guide screening and diagnosis of OUD, and to guide treatment selection and 
prescription of MOUDs or referrals for people with OUD, ultimately increasing access to OUD 
treatment for patients with OUD in primary care, outweigh the potential risks outlined above. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
14 
5.0 
OBJECTIVES 
 
Primary Objectives 
The overarching aim of this study is to implement this OUD-CDS in a large multi-site clinic-
randomized controlled trial to evaluate its impact on practice process measures and patient 
outcomes in at least 30 primary care clinics across three healthcare systems. 
Specific Aims: 
Aim 1. To implement OUD CDS in primary care settings and assess its impact on process 
measures related to diagnosis of patients at high risk for OUD, as well as prescription of 
naloxone for patients at high risk for or diagnosed with OUD. 
H1.1: Patients previously undiagnosed with OUD but identified as high risk by the OUD-CDS 
at an index visit will be more likely to receive an OUD diagnosis (in the problem list or as an 
ICD-10 visit code) in intervention clinics than in UC clinics within 30 days post-index. 
H1.2: Patients previously diagnosed with OUD or identified as high risk by the OUD-CDS at 
an index visit will be more likely to have naloxone rescue kits ordered in the intervention clinics 
than in the UC clinics within 30 days post-index. 
Aim 2. To assess the impact of OUD-CDS on important patient outcomes of initiation and 
maintenance of Medications for Opioid Use Disorder (MOUD) in patients identified as 
having OUD or being at high risk for OUD. 
H2.1: Patients identified as having OUD or as being at high-risk for OUD by the OUD-CDS at 
an index visit will be more likely to have MOUD orders or referral for OUD treatment within 30 
days post-index in intervention clinics than in UC clinics. 
H2.2: Patients identified as having OUD or as being at high-risk for OUD by the OUD-CDS at 
an index visit will have significantly more days covered by a MOUD prescription at 90 days 
post-index in intervention clinics than in UC clinics. 
Aim 3. To assess the long-term impact of OUD CDS on important patient outcomes in 
patients with OUD or identified as high risk for OUD. 
H3.1: Patients with OUD or identified as high-risk for OUD by the OUD-CDS who are cared 
for in intervention clinics will have significantly fewer post-index ED visits during the 
observation period (i.e., the period between each patient’s index date and last observation) 
compared to patients cared for in UC clinics. 
H3.2: Patients with OUD or identified as high-risk for OUD by the OUD-CDS who are cared 
for in intervention clinics will have significantly fewer post-index hospitalizations during the 
observation period compared to patients cared for in UC clinics. 
Aim 4. To describe and quantify costs of OUD-CDS implementation and maintenance and 
the short-term cost impacts of the OUD-CDS. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
15 
H4.1: After controlling for demographics, baseline clinical status and prior costs of care, 
patients with OUD or identified as high risk for OUD by the OUD-CDS will have lower 
healthcare costs in intervention compared to UC clinics during the observation period (i.e., 
savings from lower ED visits and hospitalizations will outweigh increased costs of OUD 
treatment and naloxone rescue kits and OUD-CDS implementation and maintenance). 
Aim 5. To use mixed quantitative and qualitative methods to identify, describe and quantify 
barriers and facilitators to implementation of the OUD-CDS so that it can be adapted to 
maximize its use and effectiveness. 
 
Secondary Objective(s) 
Among patients with OUD or identified as high-risk for OUD, we will assess secondary outcomes, 
which include whether those who are cared for in intervention clinics have lower rates of all-cause 
death and of fatal and non-fatal opioid overdoses during the intervention period compared to 
similar patients in UC clinics during the observation period. 
Treatment effectiveness may vary as a function of contextual as well as patient factors. In 
secondary analyses, care system indicators (Site 1, Site 2, Site 3) and clinic characteristics (e.g., 
proportion of primary care patients eligible for OUD-CDS, proportion of clinic patients with 
government-sponsored insurance) may be added to the primary model as main effects and in 
interaction with the treatment group indicator to assess treatment heterogeneity due to contextual 
factors. Patient characteristics (e.g., race, ethnicity, age, estimated neighborhood income and 
education, documented heroin vs. oral opioid use) may be similarly added to the primary model 
to assess treatment heterogeneity due to patient factors. 
The OUD-CDS tool is hypothesized to improve process measures of appropriate care for patients 
at high risk for or diagnosed with OUD by alerting PCPs to the risk of OUD and presenting them 
with tools and treatment advice that support the delivery of recommended care. For each PCP 
who practices at an intervention clinic, we will assess the extent to which engagement with the 
OUD-CDS (e.g., opening or printing OUD-CDS recommendations, use of embedded screening 
tools) is associated with patient outcomes. Via surveys, we will also assess PCP ratings of 
confidence in treating OUD and their satisfaction with the OUD-CDS. 
 
Exploratory Objective(s) 
In exploratory analyses, we may assess whether (a) PCPs in intervention clinics who are non-
waivered at go-live dates are more likely to become buprenorphine-waivered than PCPs in UC 
clinics during the intervention period; (b) waivered PCPs in intervention clinics are more likely to 
prescribe buprenorphine than PCPs in UC clinics during the intervention period; (c) whether PCPs 
in intervention clinics who are non-waivered at go-live dates are reportedly more likely to prescribe 
buprenorphine should a waiver no longer be required than PCPs in UC clinics measured prior to 
go-live dates and at 9 months following go-live dates; (d) if we have adequate data, potentially via 
health plan or Surescripts data, whether adherence/persistence to methadone, buprenorphine, 
XR-NTX or therapy for patients with OUD differs for patients in intervention vs. UC clinics during 
the observation period; and (e) PCPs in intervention clinics are more likely to screen their patients 
for mental health conditions and infectious diseases than PCPs in UC clinics during the 
intervention period. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
16 
6.0 
STUDY DESIGN 
 
Overview of Study Design 
We propose to implement OUD-CDS in a large multi-site clinic randomized pragmatic trial to 
evaluate its impact on practice process measures and patient outcomes. We also aim to prepare 
for scalability by evaluating facilitators and barriers to implementation, determining the costs of 
implementation and maintenance, and assessing cost effectiveness of the OUD-CDS. The trial 
will include three large geographically dispersed care systems that constitute a racially, ethnically 
and socioeconomically diverse patient population. At least 30 clinics will be randomized to receive 
the OUD-CDS intervention or UC. Randomization will be stratified by care system, with key pre-
randomization clinic measures balanced across treatment arms. Randomization in each 
healthcare system will be approximately 1:1. In intervention clinics, the OUD-CDS will identify 
patients who are at high risk for or previously diagnosed with OUD; use data stored in the EHR 
for these patients to assemble treatment recommendations tailored to the current needs of each 
patient; display these recommendations via the OUD-CDS user interface; and store analytic data 
from all targeted visits. In UC clinics, the OUD-CDS will run invisibly in the background to identify 
high-risk and OUD diagnosed patients, assemble treatment recommendations and store analytic 
data from all targeted visits. The targeted visits for each study-eligible patient in all randomized 
clinics will be the index visit, the first visit at which the OUD-CDS identifies that the patient is 
eligible, and all post-index visits through the end of the observation period. Patients who are 
identified as eligible during the accrual period and meet all inclusion and exclusion criteria will be 
considered for inclusion in the primary outcome analyses. Patient outcomes will be derived from 
the data elements stored by the OUD-CDS at all targeted visits. To the extent it is available, EHR 
data from the year prior to the index visit through the end of the observation period will be included 
in primary and secondary analyses. Process outcomes at or following the index visit (Aims 1 and 
2), and clinical outcomes following the index visit through the end of the observation period (Aim 
3), will be compared between patients cared for in intervention and UC clinics to assess the 
effectiveness of OUD-CDS. 
 
Duration of Study and Visit Schedule 
Primary care clinics will be randomized within each health care system to receive or not receive 
access to the OUD-CDS. Once OUD-CDS is implemented in each health care system, its 
algorithms automatically identify eligible patients in all randomized intervention and UC clinics, 
independent of any PCP actions. PCPs in clinics with CDS access are anticipated to have access 
to the OUD-CDS intervention through May 2024, depending on factors such as healthcare system 
leader preference. In UC clinics, the OUD-CDS will run silently in the background over the same 
time period, collecting data without displaying. There is no study-determined visit schedule; rather, 
patient visits will be jointly determined by the patient and PCP. We plan to stop collecting outcome 
data in October 2023 at all sites. We anticipate patient observation periods of 19 to 31 months 
from date of index visit, depending on the site. Having the OUD-CDS run from implementation 
through the end of the observation period in all randomized clinics in each health care system 
ensures that identical methods are used to identify study-eligible patients and track patterns of 
OUD-related care so that we may quantify the impact of the OUD-CDS on OUD identification and 
care. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
17 
7.0 
OUTCOME MEASURES 
 
Outcome Measures 
Primary outcome measures will include: 
1. OUD diagnosis (in the problem list or as an ICD-10 visit code) within 30 days of index 
visit for patients identified by the OUD-CDS as being at high risk of OUD 
2. Naloxone prescription within 30 days of index visit for patients with OUD or identified by 
the OUD-CDS as being at high risk for OUD 
3. MOUD orders or referral to OUD treatment within 30 days of index visit for patients with 
OUD or identified by the OUD-CDS as being at high risk for OUD 
4. Total days covered by an MOUD prescription in the 90 days after index visit for patients 
with OUD or identified by the OUD-CDS as being at high risk for OUD 
Secondary outcome measures will include: 
1. OUD diagnosis (in the problem list or as an ICD-10 visit code) at index or within 90 days 
of index visit for patients identified by the OUD-CDS as being at high risk of OUD 
2. Naloxone prescription at index or within 90 days of index visit for patients with OUD or 
identified by the OUD-CDS as being at high risk for OUD 
3. MOUD orders or referral to OUD treatment at index or within 90 days of index visit for 
patients with OUD or identified by the OUD-CDS as being at high risk for OUD 
4. Number of ED visits during the observation period for patients with OUD or identified by 
the OUD-CDS as being at high risk for OUD 
5. Number of hospitalizations during the observation period for patients with OUD or 
identified by the OUD-CDS as being at high risk for OUD 
6. Healthcare costs during the observation period for patients with OUD or identified by the 
OUD-CDS as being at high risk for OUD, compared with healthcare costs over the same 
interval preceding the observation period 
7. Cost of OUD-CDS implementation and maintenance 
8. All-cause mortality rates during the observation period for patients at high risk of OUD 
9. Fatal and non-fatal opioid overdoses during the observation period for patients at high 
risk of OUD 
10. Rates of OUD-CDS use in intervention clinics 
11. PCP ratings of confidence in treating patients with OUD prior to go-live date and 9 
months following go-live date 
12. Intervention clinic PCP ratings of satisfaction and acceptability of the OUD-CDS at 9 
months following go-live date 
Exploratory outcome measures may include: 
1. Number of non-waivered PCPs becoming buprenorphine waivered during the 
intervention period, assessed via health system administrative data 
2. Number of buprenorphine prescriptions written by waivered PCPs during the intervention 
period 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
18 
3. PCP ratings of likelihood to prescribe buprenorphine for patients with OUD should no 
waiver be required, measured prior to go-live dates and at 9-months following go-live 
dates 
4. Adherence to therapy during the observation period, assessed via Clarity and claims 
data 
5. Number of patients diagnosed with OUD screened for mental health comorbidities and 
infectious diseases during the observation period 
 
Study Timeline 
After receiving Center for the Clinical Trials Network (CCTN) approval of the final protocol, 
approximately 9-12 months of trial preparation activities will elapse prior to commencing 
enrollment (“go-live”) at Site 1. The intervention at Site 2 is anticipated to begin 6-9 months after 
go-live date at Site 1, and the intervention at Site 3 will begin 12-15 months after the go-live date 
at Site 1. Selection of Geisinger as Site 2 and Essentia as Site 3 occurred subsequent to the initial 
CCTN approval of the final protocol and initial IRB submission. Trial preparation will include 
obtaining Institutional Review Board (IRB) approval, customizing the OUD-CDS for each 
healthcare system, harmonizing data elements for EHR installation at each site, installing of EHR 
custom code at each site, recruiting and randomizing primary care clinics at each site, conducting 
PCP training at each site, integration of CDS into workflow at each site, and completing baseline 
PCP surveys at each site.  
As noted previously, the COVID-19 pandemic delayed implementation by approximately 8 
months. Accrual periods will range from 7 to 18 months based on site. During the accrual period, 
the study team will monitor accrual rates to determine when a sufficient number of patients have 
been enrolled to support the analysis plan. If enrollment is lower than expected, we may choose 
to extend the accrual period up to 3 additional months (through January 2023). Observation will 
begin with index dates at each site and are anticipated to continue through October 2023.  
Anticipated Accrual + Observation Periods per Site:  
 
HealthPartners – April 2021 to Oct 2023 (31 months) 
 
Geisinger – Dec 2021 to Oct 2023 (22 months) 
 
Essentia – April 2022 to Oct 2023 (18 months) 
 
Anticipated Accrual* Periods per Site:  
 
HealthPartners – April 2021 to Oct 2022 (18 months) 
 
Geisinger – Dec 2021 to Oct 2022 (10 months) 
 
Essentia – April 2022 to Oct 2022 (7 months) 
  
* We may extend the accrual period an additional 3 months based on enrollment trends. 
 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
19 
COMPUTE 2.0 Study Timeline 
Study Timeline 
Year 1 
Year 2 
Year 3 
Year 4 
Year 5 
2019
2020 
2021 
2022 
2023 
2024
Quarter
3
4 1 2 3 4 1 2 3 4 1 2 3 4 1 2
3
4
1 2
Phase 1: Development Phase 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Finalize protocol, obtain IRB approval (Site 1)  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Obtain IRB approval at Sites 2 & 3 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Customize OUD-CDS for each partner site 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Clinic randomization, baseline surveys 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Phase 2: Active Intervention Phase 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Go live: HealthPartners, Geisinger, Essentia 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Accrual (adding patients to analytic data set) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Observation (index visit to end of outcome data)  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
All Sites: monitor use rates, provide reports 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
All Sites: Update, troubleshoot algorithms 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Conduct surveys, semi-structured interviews 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Phase 3: Analysis and Reporting 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Preliminary reports of available data to funder  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Consolidate/analyze final data  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Dissemination activities, submit manuscript  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
20 
8.0 
STUDY POPULATION 
 
Primary Care Clinics 
This randomized clinical trial is a clinic-randomized study. A minimum of ten primary care clinics 
to be included in the study at each of three sites will be selected in partnership with primary care 
leadership at each site. To be eligible for randomization in this study, a primary care clinic must: 
(a) be included in one of the three care delivery systems included in this study, (b) have a 
minimum of 3 full-time PCPs who do not regularly work at any other primary care clinic, and (c) 
have an estimated minimum of 50 adult patients who meet study criteria for OUD or high risk for 
OUD. Exclusion criteria for potentially eligible primary care clinics include (a) plans to close or 
transfer ownership of the clinic within 24 months after the anticipated OUD-CDS go-live date, or 
(b) clinic not using their current EHR system for at least 12 months before the anticipated OUD-
CDS go-live date at the clinic. Primary care clinics that have fewer than 50 patients at risk for 
OUD may not be eligible for randomization. However, consideration will be given to small clinics 
that may be part of a larger spoke and hub primary care clinic system, depending on the 
organizational structure of included care systems. For example, clinics X and Y in healthcare 
system 2 may be too small to consider randomizing them on their own, but because they are 
affiliated with clinic Z and most PCPs at clinic Z practice a day or two a week at clinics X and Y, 
clinics X, Y and Z would be randomized as one potential unit (thereby avoiding potential 
contamination). 
Primary care clinics that pass all these eligibility and exclusion criteria will be randomized (within 
study site) using a validated computer-generated randomization scheme that takes into 
consideration such factors as overall clinic size, number of PCPs, number of buprenorphine 
PCPs, and baseline prevalence of diagnosed OUD. All PCPs and their study-eligible patients will 
be assigned to the treatment group of their randomized primary care clinic. 
 
PCPs and Clinic Staff 
To be eligible for inclusion in this study, a PCP must be a family physician, general internist, or 
adult-care non-obstetric nurse practitioner (NP) or physician assistant (PA) working at a study-
eligible primary care clinic. PCPs who are and who are not buprenorphine-waivered are study 
eligible. PCPs in the intervention clinics will be encouraged but not required to use the OUD-CDS 
with eligible patients, so that the decision to use or not use OUD-CDS at a given clinical encounter 
is up the PCP at each clinical encounter. All PCPs will be asked to consent to and complete pre-
and post-implementation surveys and may receive modest compensation for completing these 
surveys. In the intervention phase, PCPs who are high-, moderate- and low/non-users of the 
OUD-CDS will be invited to participate in interviews. Clinic staff associated with invited PCPs 
(e.g., rooming staff, nurses) will also be invited to participate. PCPs and staff who are asked to 
participate in interviews will be consented for those interviews and may receive modest 
compensation. Exclusive of consenting PCPs for interviews and surveys, we will request a waiver 
of written informed consent for PCPs from the IRB for the intervention because (a) the OUD-CDS 
is based on current national standards of OUD identification and management and does not make 
any treatment recommendations that are not accepted as community standard of care, and (b) 
consenting PCPs would compromise the external validity of the study by introducing selection 
effects. Measures to protect the privacy of PCPs participating in this study are described further 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
21 
below. The OUD-CDS may also be turned on for non-PCP clinicians affiliated with intervention 
clinics, such as pharmacy staff, and a similar waiver of written informed consent will be requested 
by the IRB. These non-PCP clinicians may also be invited to participate in surveys or interviews. 
 
Patients 
To be eligible for inclusion in the study, a patient must meet all the following eligibility criteria: (a) 
be aged 18-75 years, inclusive, at the time of an index visit; (b) have been diagnosed with OUD, 
currently prescribed MOUD, or identified by study algorithms as being at high risk of OUD. There 
are no exclusions for pregnancy, lactation, or mental health or behavioral health issues. However, 
patients who meet the following criteria at the time of their index visit will be excluded and not be 
exposed to the OUD-CDS intervention: (a) those receiving active parenteral chemotherapy within 
the last year, (b) those with stage 4 or equivalent cancer diagnosis, (c) those enrolled in hospice 
care or palliative care programs. All women and members of racial or ethnic minority groups and 
their subpopulations who meet the above eligibility criteria and do not meet exclusion criteria will 
be included in accordance with the National Institutes of Health (NIH) Policy on Inclusion of 
Women and Minorities as Participants in Research Involving Human Subjects. A sample of 
patients with diagnoses of OUD and/or identified as being at high risk for OUD and/or referred by 
a PCP will be invited to participate in interviews and surveys. Patients who are asked to complete 
surveys or participate in interviews will be consented and will receive modest compensation. 
Beyond survey and interview participation, we will request and anticipate receiving a waiver of 
written informed consent from the governing IRB for patient participation because the study is 
minimal or less than minimal risk compared to the risk associated with any primary care 
encounter, and because the study could not be conducted if written informed consent were 
required to be obtained in the context of busy community-based primary care clinic environments. 
We have requested and received such waivers of written informed consent for patients in several 
similar prior studies. Note that patients who have requested non-participation in research studies 
at any of the participating care delivery systems will be excluded from all analyses. 
Definition of High Risk: Algorithms determine when a patient is identified as being at high risk 
for OUD or opioid overdose, and, in intervention clinics, this will trigger a best practice alert to be 
displayed for a particular patient at a particular clinic encounter. These algorithms, like all of the 
OUD-CDS algorithms, are housed on a web platform that interacts with the EHR to pull data 
elements to run risk equations and determine patient eligibility. We anticipate that how the 
algorithms will identify patients at high risk of OUD or opioid overdose will evolve over time as our 
ability to predict risk improves. In early phases of this study, we may use EHR data elements such 
as long-acting opioid prescriptions, concomitant benzodiazepine and opioid prescriptions, mental 
health diagnoses, alcohol and substance use diagnoses and previous opioid overdose diagnoses 
to identify patients at increased risk of OUD or opioid overdose.[31] We may also use, in care 
systems where this is available, a risk equation developed and validated by EPIC that estimates 
a patient’s risk of OUD or opioid overdose within the next year. As the study progresses, we 
anticipate incorporating additional calculators for high risk into our algorithms. In work funded by 
NIDA (1R01DA047724-01, PI Yarborough), we are developing risk calculators for suicide in 
people with OUD, as well as risk calculators for unintentional opioid overdoses, in a population of 
nearly 8 million patients across 7 care systems. Variables in these risk models will include 
prescription opioid use, prescription opioid use reduction, prescription opioid discontinuation, 
opioid-related overdose, OUD and/or MOUD prescription, and illicit opioid use. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
22 
As more sophisticated risk equations for OUD and opioid overdose risk become available, our 
team will write new draft algorithms to identify patients at risk in Visio. Once we have a good 
understanding of how these draft algorithms would work with the data available to us in EPIC, we 
will meet with the DSMB to discuss this potential change in identification of at-risk patients to 
present our proposed changes, receive feedback, make any necessary edits and request 
approval. Once approved, these risk equations would replace the previous risk equations in our 
algorithms at a pre-specified and documented date and time, and would be used to identify 
patients at risk of OUD or opioid overdose. Any and all changes in these OUD-CDS algorithms 
will be documented in a log to allow us to take these changes into account in analyses and 
understand how such changes may have influenced study outcomes. For each patient at each 
encounter, we will know why that patient was identified as high risk. 
 
Healthcare System Leaders 
We will work with study teams and healthcare system leadership at each site to identify up to 15 
leaders at each site with various levels of engagement with the OUD-CDS implementation and 
oversight to provide input into perceived value of the OUD-CDS, barriers and facilitators to 
implementation of the OUD-CDS, and costs associated with implementation and maintenance. 
Leaders will be recruited to provide wide representation of influence within the organization, 
including high-level decision makers and mid-level supervisors, such as clinic manager and care 
team leaders. Leaders will be consented to participate in interviews. 
 
Strategies for Recruitment and Retention 
Clinic Recruitment and Retention: Our team will work as directed by the funding agency, their 
contractors, and the study teams and clinical leadership at each healthcare site to determine 
which primary care clinics will be eligible for inclusion in this study. All PCPs and their patients 
who meet the criteria defined in Sections 8.2 and 8.3 will be included in this study. 
Through prior work, we know that feedback about use rates of the OUD-CDS tool, provided at the 
clinic level and the individual PCP level, is crucial for achieving and maintaining high use rates of 
the CDS tool, essentially one important measure of retention and continued engagement. To 
promote high and sustained use rates of the OUD-CDS, we will work with each system’s primary 
care leadership to identify to which clinic leaders such use reports should be sent, and whether 
we will be able to offer incentives to clinics to achieve and maintain high use rates. In previous 
studies, incentives have included clinic lunches or contributions to the general clinic fund that is 
used to pay for such things as flowers to mark important life events for clinic employees. 
Strategies to achieve and maintain high use rates may include the following multi-pronged 
strategies: 
1. We will use a multi-level approach to prompt PCPs to screen and treat patients for OUD. 
Depending on the healthcare system, this will include several or all of the strategies 
below, and potentially additional strategies based on healthcare system leader 
recommendations. After a high-risk patient is screened and not assessed to have OUD, 
all alerts for that patient would be silenced for a period of time depending on the 
underlying algorithms. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
23 
a. We will display a best practice advisory (BPA) for rooming staff in EPIC that 
prompts the rooming staff to print the patient and PCP interfaces of the tool with 
one click. The patient printout prompts patients to discuss any concerns they 
have about opioid use with their PCP, while it notifies the PCP that this is a 
patient who has been identified as needing screening and possibly treatment for 
OUD. It will also alert patients and PCPs when OUD has been identified in the 
electronic health record, with or without corresponding MOUDs. 
b. We will prompt the screening of patients identified at high risk for OUD at refill 
encounters for opioid medications. Such encounters may occur either in clinic 
with the PCP, via phone with registered nurse (RN) refill encounters, or via other 
encounter types depending on the care system. 
c. At healthcare systems that require that PCPs complete contracts with their 
patients that outline agreements re: use of their opioids, we will prompt 
assessment of patients for OUD when those contracts are due to be renewed. At 
HealthPartners, such contracts occur annually and are identified via a health 
maintenance alert in EPIC. Our team will work to determine whether such opioid 
contracts are employed at Sites 2 & 3, whether they are tracked/prompted in 
EPIC, and whether these encounters may provide additional opportunities for 
OUD screening. 
2. We will provide monthly clinic- and provider-level feedback of use rates to clinic 
leadership, and, where allowed, offer clinic-level incentives to achieve and maintain high 
use rates. In other CDS studies, we have found that providing clinic-level and PCP-level 
use reports data has dramatically improved and sustained use rates for the duration of 
the intervention. 
One month after each healthcare system’s go-live date, study staff will begin sending 
intervention clinic leaders monthly reports that include (1) each clinic’s use rate of the 
OUD-CDS in the previous month, compared to other clinics in that healthcare system 
(and, as available as the study progresses, previous months’ use rates), ranked from 
highest-use clinics to lowest-use clinics, and (2) the use rates for each primary care 
provider (PCP) in that particular clinic (i.e., clinic leaders only get use rate reports at the 
PCP level for their own clinic, not other primary care clinics). Accompanying these 
monthly use rate reports is clear communication of the use rate goal of 60% or more of 
targeted encounters, and, where allowed, the threshold to reach a clinic incentive (such 
as achieving target use rates for at least 3 consecutive months to earn a clinic lunch). 
The example report below is from an implementation of a cardiovascular decision 
support tool, where target use rates were 80% of eligible encounters. Leadership at 
every primary care clinic in that care system received emailed monthly reports. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
24 
 
Key: 
Green= Use rates at or above 80% goal 
Yellow = Use rates below goal (65%-79%) 
Red = Use rates significantly below goal (<65%) 
At the clinic level, clinic leaders will also be provided with a monthly use rate report by 
PCP: 
Clinic H Wizard Use Rate Report: 
December 2018 
# Eligible 
Visits 
% Visits where CV Wizard  
Opened and Printed 
CLINICIAN A 
56 
100% 
CLINICIAN B 
11 
100% 
CLINICIAN C 
112 
100% 
CLINICIAN D 
95 
88% 
CLINICIAN E 
39 
62% 
CLINICIAN F 
81 
61% 
CLINICIAN G 
58 
43% 
CLINICIAN H 
0 
N/A 
TOTAL 
452 
85% 
 
Clinics will have two months following the go-live date to bring their use rates up to the 
60% of eligible encounters target use rate. After that run-in period, study staff will reach 
out to clinic leaders by email and/or by phone to discuss use rates that are below targeted 
rates. Study staff will review both the clinic-level and PCP-level reports with clinic leaders 
Clinic 
Jan
Feb
Mar
Apr
May Jun
Jul 
Aug Sep 
Oct 
Nov
Dec
Jan 
Clinic A 
93% 91% 95% 92% 92% 94% 93% 92% 76%
83%
86%
96%
96%
Clinic B 
93% 90% 91% 91% 94% 93% 95% 95% 92%
96%
96%
81%
95%
Clinic C 
98% 97% 98% 97% 95% 94% 91% 85% 93%
83%
95%
98%
94%
Clinic D 
89% 98% 96% 98% 99% 93% 83% 74% 78%
86%
91%
97%
92%
Clinic E 
99% 93% 90% 95% 95% 95% 87% 88% 95%
93%
91%
92%
91%
Clinic F 
94% 98% 94% 91% 86% 89% 95% 94% 97%
76%
65%
75%
90%
Clinic G 
95% 92% 88% 92% 94% 94% 98% 95% 95%
95%
91%
84%
88%
Clinic H 
96% 93% 95% 96% 92% 93% 96% 91% 83%
89%
75%
80%
87%
Clinic I 
78% 94% 94% 86% 89% 68% 65% 49% 49%
74%
93%
88%
77%
Clinic J 
71% 78% 91% 86% 92% 69% 84% 88% 57%
64%
83%
73%
75%
Clinic K 
81% 68% 78% 85% 95% 91% 83% 70% 88%
88%
79%
79%
69%
Clinic L 
90% 90% 91% 90% 88% 93% 87% 76% 65%
72%
66%
51%
64%
Clinic M 
77% 76% 64% 70% 52% 63% 74% 78% 81%
82%
78%
83%
81%
Clinic N 
55% 63% 79% 73% 71% 57% 63% 74% 74%
73%
82%
79%
74%

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
25 
and discuss potential strategies for increasing use rates, including training or retraining for 
rooming staff of PCPs with low use rates and qualitative interviews with care teams to 
understand potential barriers to use (Is the rooming staff seeing the best practice alert? 
Are there issues with being able to print the CDS? Does the PCP feel he or she doesn’t 
have time to integrate this tool with their usual workflow, or that OUD is not a clinical priority 
for his or her patients?) and any concerns or questions about the OUD-CDS tool itself. 
3. We will conduct a pre-implementation pilot phase at each site that includes qualitative data 
collection from PCPs and patients experiencing the OUD-CDS and make any 
improvements needed to the tool and workflow prior to live implementation. The step-wise 
evaluation of the OUD-CDS by site roll-out will inform the implementation at subsequent 
sites. Ongoing evaluation during implementation will offer continuous process 
improvement for the OUD-CDS with a goal of optimizing PCP use rates. 
4. One example of the effectiveness of these strategies is seen in Serious Mental Illness 
Wizard (SMI), an NIH-funded study that aimed to reduce cardiovascular risk in people with 
SMI. Our team used clinic-and PCP-specific use rates and clinic lunch incentives to 
achieve use rates well above the goal of 80% of eligible encounters. Of note, the best 
practice alert was sent to rooming staff, not the PCP, accounting for the higher baseline 
rates (prior to use rate report feedback) of 30% vs 5% in the COMPUTE pilot study. 
Figure 4. Print Rates over the Intervention Period for SMI Wizard 
 
Patient Recruitment: A random sample of patients eligible for recruitment for surveys and 
interviews will be identified. Patients will be recruited via mailed letters or e-mail. Surveys will be 
completed online via a link or QR code provided in the letters or emails, and consent to participate 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
26 
will be included in the online survey. Interviews will be completed via phone or in person, 
according to patient preference. Consent will be obtained verbally after the patient reviews the 
elements of consent included in the recruitment letter and also asks any questions of the 
interviewer. Modest compensation will be provided for patient surveys and interviews. 
PCP and Clinic Staff Recruitment: All randomized PCPs will be invited to participate in surveys 
via email prior to the go-live date and during early implementation (9-months after go-live date). 
Consent to participate in the survey will be included in the online survey. A sample of PCPs eligible 
for recruitment for interviews will be identified from administrative data, and PCPs and their clinic 
staff will be invited to participate via email. Interviews will be completed via phone or in person, 
according to PCP/staff preference, and consent will be obtained verbally after the interviewee 
reviews the elements of consent included in the recruitment letter and asks any questions of the 
interviewer. Modest compensation may be offered for PCP surveys and PCP or clinic staff 
interviews. 
Leader Recruitment: Clinic and administrative leaders will be identified for interviews in 
partnership with healthcare leadership and site investigators, and leaders will be invited to 
participate via email. Interviews will be completed via phone or in person, according to leader 
preference, and verbal consent will be obtained. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
27 
9.0 
SITE SELECTION 
 
Number of Sites 
Healthcare Systems 
HealthPartners, Geisinger and Essentia will participate in this study. 
Primary Care Clinics 
At least 30 primary care clinics from three healthcare systems will participate in this study. 
 
Site Characteristics 
Healthcare Systems 
 
Requirements for the Two Additional Healthcare Systems (assessed via surveys distributed 
on 4/17/19. Several items were optional and are so indicated. Six healthcare systems returned 
surveys to express interest in participating in COMPUTE 2.0, and all six satisfied required criteria). 
1. Use of EPIC 2018 or later 
2. Willingness to use active guidelines (an existing module within EPIC) 
3. Willingness to accept custom code 
4. Use of EPIC Interconnect with clinical services turned on 
5. Willingness to add an alert to initiate activity around opioids to EPIC, such as a generic 
navigator report section or a BPA 
6. Willingness to run Opioid Wizard during primary care office visits 
7. Willingness to allow custom doc flowsheet rows and smart data elements to file back into 
EPIC 
8. Willingness to allow the prime site to remotely view and help troubleshoot issues in the 
EPIC Development environments with the site’s EPIC team 
9. Use of the EPIC Beaker lab module (optional; informative question only) 
10. Access to EPIC via Citrix (optional; informative question only) 
11. Access to EPIC via VDI (optional; informative question only) 
12. Ability to provide preliminary data to assess feasibility of the site, such as number of 
patients per clinic, general demographics, opioid prescriptions, OUD diagnoses, or 
prevalence of patients using medications for OUD (i.e., buprenorphine, XR-NTX, and 
methadone) 
13. At least 10 primary care clinics that operate under one EPIC instance with centralized 
Information Technology (IT) that are willing to participate and be randomly assigned to a 
treatment group by clinic 
14. Care system willingness and ability to encourage PCPs to become waivered to prescribe 
buprenorphine. 
15. Leadership support for managing OUD patients in primary care when appropriate 
16. The availability of a site Principal Investigator (PI), clinical champion, project manager, 
EPIC analyst and data programmer. If there is not an EPIC analyst available, access to 
an EPIC team that can help implement the OUD-CDS in a timely manner 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
28 
17. The availability of researchers who are highly engaged with the care system who can 
assess the healthcare system’s willingness to implement the OUD-CDS within EPIC 
18. The ability to procure a letter from the IT group and care system leadership indicating 
support of implementation of the OUD-CDS 
19. The ability to obtain timely IT security clearance 
20. The ability of the organization to sign a business associate’s agreement or service 
agreement for OUD-CDS services 
21. The ability to harvest data from Clarity 
22. The willingness to allow the prime site to retain a limited data set for analysis (provided 
that the appropriate agreements are in place and the IRB allows this, depending on 
requiring or waiving consent) 
23. Willingness to cede to a central IRB 
24. Access to claims data (Medicare, commercial or Medicaid; optional) 
25. Use of the EPIC 2018 adherence module or access to Surescripts pharmacy dispense 
data (optional) 
 
Rationale for Site Selection 
A total of three study sites involving at least 30 primary care clinics (at least 10 primary care clinics 
in each healthcare system) will provide for diversity in primary care practices, patient race and 
ethnicity, geographical distribution, and rural/urban representation. 
HealthPartners will serve as Site 1 for this study and served as the sole site for the CTN-0076-Ot 
pilot study. HealthPartners is the largest consumer-governed nonprofit health care organization 
in the country, providing care, coverage, research, and education to improve health and well-
being in partnership with its members, patients and community. HealthPartners serves more than 
1.5 million medical and dental health plan members and more than1 million patients in its 
HealthPartners Medical Group (HPMG) and Park Nicollet Medical Group (PNMG) clinics and 
hospitals. In 2013, HealthPartners and Park Nicollet combined under the name HealthPartners 
and a single consumer-governed board of directors. The new organization includes a 
multispecialty group practice of more than 1,700 physicians, seven hospitals, 47 primary care 
clinics, 22 urgent care locations, 22 dental clinics, and numerous specialty practices in Minnesota 
and western Wisconsin. The majority of HPMG and PNMG patients (>80%) have commercial 
health insurance, while approximately 6% are insured via Medicare and 4% via Medicaid. HPMG 
and PNMG offer outpatient primary and specialty addiction care, day programs, partial 
hospitalization programs and inpatient treatment for OUD and other substance use disorders. The 
medical groups refer out for methadone maintenance; for the approximately 40% of patients who 
are also HealthPartners Insurance members, we will be able to capture data on their methadone 
prescription dispensings. 
The remaining two study sites, Geisinger and Essentia, were selected based on the availability 
and engagement of an effective clinicians champion, and the care system’s ability to: (a) obtain 
adequate support from their primary care and other care system leadership, (b) modify and install 
custom EHR code, (c) help determine best ways to integrate the CDS into their clinical workflows 
and achieve and maintain high clinical use, (d) provide required training for PCPs and staff, and 
(e) obtain timely IT security clearance and a letter of support from their IT group. These criteria 
are imperative for ensuring proper functioning and maintenance of the OUD-CDS. They were also 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
29 
selected based on their ability to provide diversity in primary care practices, patient race and 
ethnicity, geographic distribution, and rural/urban representation. 
Primary Care Clinics 
In this clinic-randomized trial, decisions about which primary care clinics may be ineligible for 
inclusion will be made in partnership with primary care leadership. Primary care clinics that have 
fewer than 50 patients meeting eligibility criteria may not be eligible for randomization. However, 
consideration will be given to small clinics that may be part of a larger spoke and hub primary 
care clinic system, depending on the organizational structure of included care systems. For 
example, clinics X and Y in healthcare system 2 may be too small to consider randomizing them 
on their own, but because they are affiliated with clinic Z and most PCPs at clinic Z practice a day 
or two a week at clinics X and Y, clinics X, Y and Z would be randomized as one potential unit 
(thereby avoiding potential contamination). 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
30 
10.0 STUDY PROCEDURES 
 
Index Visit 
There is no study-determined visit schedule. Patient visits with their PCPs in the randomized 
clinics will take place without any interference or involvement from the study team. The first visit 
at which the OUD-CDS algorithms determine that a patient is eligible for the intervention will be 
denoted as the index visit. 
 
Randomization 
The OUD-CDS software is a system level intervention comprised of 1) a passively operating web 
service that gathers, analyzes and retains information pertinent to every web service call, and 2) 
a user interface that presents a summary of algorithm results to front end users. The web service 
documents every web service call made by all front-end users in all participating locations so that 
data pertinent to all targeted visits from all eligible and enrolled patients will be identically collected 
and available in both treatment arms. The user interface will function as the intervention delivery 
vehicle and therefore be operative only in intervention locations. Intervention or Control 
designation will vary randomly by clinic. The OUD-CDS web service will therefore operate 
passively in all participating clinics but the user interface will only be turned on in clinics that are 
randomly assigned to the intervention treatment group. 
To the extent that patients tend to receive most of their care over time at a single clinic, and that 
clinicians tend to practice at a single clinic, it is reasonable to assert that the risk of intervention 
contamination across clinics is low. However, because it is common for patients to see more than 
one clinician in a clinic location over time, and for clinicians within a clinic location to discuss 
aspects of care delivery with each other, the risk of intervention contamination within clinics is 
rather high. Randomizing by clinic rather than by PCP or patient will minimize risk of intervention 
contamination. 
Generally speaking, randomization should balance treatment groups on factors that enhance or 
impede intervention uptake and adherence, that are related to and including study outcomes, and 
on any other unmeasured factors that may affect statistical power. However, the likelihood that 
factors related to these considerations are balanced may be diminished in cluster-randomized 
trials due to relatively few randomized units.[33, 34] Covariate constrained randomization of the 
clinics will be implemented to balance treatment groups across the study and within health care 
systems (strata) on factors related to study outcomes, implementation of the intervention, and 
potential treatment modifiers. Potential balancing factors include:  
 
% of all patients with diagnosed OUD with a current MOUD 
 
% of all patients with diagnosed OUD 
 
% of all patients at high risk for OUD 
 
% of patients at high risk for OUD provided a with naloxone rescue kit 
 
n of adult patients at clinic 
 
% of adult patients with government sponsored insurance 
 
% of adult patients who are non-Hispanic White 
 
n of waivered providers 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
31 
Each patient will be considered to belong to the clinic in which his or her first visit that is eligible 
for the OUD-CDS intervention (i.e., index visit) takes place, and as such will be in the treatment 
group to which their clinic was randomly assigned. Post-index visits may take place in the same 
or different clinics or treatment groups relative to the index visit and may or may not be eligible 
for the OUD-CDS to offer treatment recommendations. In keeping with an intent-to-treat principle, 
all index and post-index visits and outcome measures for each patient will be attributed to the 
treatment group assignment of the clinic where the index visit took place. 
 
Treatment/Intervention 
The intervention is the availability of the OUD-CDS display in approximately half of randomized 
primary care clinics. 
 
Premature Withdrawal of Participants 
Once randomized, all primary care clinics are anticipated to remain enrolled for the duration of 
the study. All PCPs in randomized clinics will be followed for the duration of the study unless they 
die or leave the employment of the clinic. All study-eligible patients with OUD or identified by the 
algorithms as being at high risk of OUD in randomized clinics will be followed for the duration of 
the study unless they die or leave the care system. Patients who have opted out of research will 
be excluded from all analyses. 
 
Study Halting Rules 
Reasons for the DSMB, investigator or sponsor to halt the study may include, but are not limited 
to, lack of funding or early termination of the study for safety reasons. If the study is prematurely 
terminated or temporarily suspended, the PI will promptly inform the IRB and sponsor and provide 
the reason(s) for the termination or temporary suspension. 
 
Follow-Up 
There is no study-determined visit schedule. Patient visits with their PCPs in the randomized 
clinics will take place without any interference or involvement from the study team. Primary care 
visits that take place after the index visit and prior to the end of the observation period will be 
denoted as post-index visits. The OUD-CDS will flag the occurrence of all index and post-index 
visits so that EHR data documented from each may be extracted and assembled into an analytic 
dataset. 
 
Participant Reimbursement 
We will not be directly reimbursing PCPs and patients to participate in the OUD-CDS intervention. 
However, where allowed by participating healthcare system leadership and when approved by 
the IRB of record, we will be offering clinic incentives to encourage high use rates of the OUD-
CDS (see Section 8.5). Additionally, we may offer incentives to PCPs to complete surveys and 
to PCPs and clinic staff to participate in interviews where allowed by participating healthcare 
system leadership and when approved by the IRB of record. This may include, but is not limited 
to, cash incentives, gift cards, donations to charities or chocolates. We will offer patients modest 
monetary incentives to participate in surveys and interviews. We do not plan to offer clinic or 
administrative leaders incentives to participate in interviews. At healthcare systems where this is 
allowed, we may provide incentives to PCPs in randomized clinics (i.e., PCPs in both intervention 
and UC clinics) to become buprenorphine-waivered during each site’s implementation period. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
32 
11.0 STUDY ASSESSMENTS 
 
Table of Assessments 
Table 1. Assessment of Primary, Secondary and Exploratory Outcomes 
Outcome 
Timing* 
Data Source 
OUD diagnosis 
Index date, 30 days, 90 days 
EHR/OUD-CDS data 
Naloxone prescription 
Index date, 30 days, 90 days 
EHR/OUD-CDS & Claims data 
MOUD orders or referral 
Index date, 30 days, 90 days 
EHR/OUD-CDS & Claims data 
days covered by MOUD 
prescription 
Index date, 30 days, 90 days 
EHR data 
ED visits 
Observation period 
EHR & Claims data 
Hospitalizations 
Observation period 
EHR & Claims data 
Health care costs 
Observation period, with pre-
observation period matched for 
number of days 
EHR & Claims data 
Costs of OUD-CDS 
implementation and 
maintenance 
Mid-intervention period 
Interviews/surveys with 
implementation site staff 
All-cause mortality 
Observation period 
EHR data, Claims data, State 
mortality data 
Opioid overdoses 
Observation period 
EHR & Claims data 
OUD-CDS use rates 
Intervention period 
EHR/OUD-CDS data 
PCP confidence in treating 
patients with OUD 
Baseline, 9 months 
PCP surveys 
PCP ratings of likelihood to 
prescribe buprenorphine for 
patients with OUD should no 
waiver be required 
Baseline, 9 months 
PCP surveys 
Intervention PCP ratings of 
OUD-CDS satisfaction and 
acceptability 
9 months 
PCP surveys 
Waivered PCPs 
Pre-intervention, intervention 
period 
Administrative data 
Buprenorphine prescriptions 
written by waivered PCPs 
Intervention period 
EHR/OUD-CDS data 
Adherence to therapy 
Intervention period 
EHR/OUD-CDS data 
Screening for comorbid 
conditions 
Observation period 
EHR/OUD-CDS data 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
33 
*Definitions: 
Index Date 
 Varies by patient 
 First visit at which the OUD-CDS identifies that the patient is study eligible  
Intervention Period 
 Varies by system 
 OUD-CDS implementation date through a predetermined time at which the Wizard interfaces will be 
turned off in the intervention clinics  
Observation Period 
 Varies by patient 
 Index visit date through a predetermined time at which no more outcome data will be included in the 
analytic sample 
 
 
Mixed Methods 
We will rely on the RE-AIM framework to construct a quantitative monitoring system that will 
identify implementation problems as early as possible, followed by selective interviews and 
surveys to identify specific barriers and facilitators that can be addressed iteratively as each site 
initiates the OUD-CDS. We will also document any adaptations made and their impact on our 
measures. The RE-AIM constructs and measures are listed in Table 2. 
Table 2. RE-AIM Evaluation and Monitoring System 
Constructs 
Evaluation Goal 
Quantitative Measures 
Reach 
Maximize the eligible patients 
receiving the OUD-CDS 
during primary care encounter 
% of eligible encounters in intervention 
clinics for which the OUD-CDS is opened 
and used 
Effectiveness 
Maximize the effectiveness of 
the OUD-CDS tool to achieve 
study outcomes. 
% of study eligible patients who receive an 
OUD diagnosis, naloxone, MOUD, referral 
for OUD treatment, or screening for 
infectious diseases or mental health 
conditions 
Adoption 
Minimize the variation in 
Reach, Effectiveness, and 
Implementation across 
different clinics and clinicians 
Size of one standard deviation among 
clinics and among clinicians in the process 
and outcome measures listed under reach 
and effectiveness 
Implementation
Maximize fidelity to optimal 
intervention with patients or 
modify the intervention to fit 
clinic realities 
% of patients with an OUD diagnoses who 
refill MOUDs, attend therapy appointments 
or return for follow-up care 
Maintenance 
Maintain the optimal level of 
patient intervention over time 
Change in RE-AIM measures over time 
 
The following methods will be used to conduct an assessment of the reasons for problems 
identified by the monitoring system and identification of barriers and facilitators to the use of the 
OUD-CDS through a mixed-methods approach guided by the measures in the monitoring system 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
34 
above. The monitoring data will be collected routinely at each clinic and site as it implements 
either pilots or full implementation. Findings from early monitoring will inform the need for 
interviews with key informants to identify changeable barriers and facilitators. Adaptations and 
adjustments to the intervention delivery and learnings from earlier sites will inform the 
implementation approach at subsequent clinics and sites. The data collection and analysis 
methodology for each data collection event is meant to be rapid in nature, so as to make the most 
expedient and beneficial use of the findings during active implementation. However, a larger 
implementation analysis will conclude in the later phase of the study in order to inform broader 
dissemination recommendations in other settings. In order to maximize the benefit of early 
learnings, qualitative investigators at subsequent sites will be involved in planning and analysis 
of both monitoring activities and qualitative data. 
Pre-Implementation/Design Phase Activities 
1. Design phase PCP interviews: Conduct up to 10 semi-structured interviews with key 
informants (PCPs, clinic staff and health system leaders) about the design and workflow 
for the OUD-CDS and related post-index follow-up care to ensure acceptability, and 
feasibility of the intervention design. 
2. Design phase patient interviews: Conduct up to 30 semi-structured interviews at 
baseline with patients previously diagnosed with OUD, identified as high risk for OUD, or 
referred by their PCP about the design, content, and messaging of any patient-facing 
materials related to the OUD-CDS and patient perspective on discussing opioid related 
care in primary care encounters. 
3. Plan data monitoring approach: Plan and construct a monitoring system to identify in real 
time the use of the OUD-CDS and intervention-related post-index care at the levels of 
the health system, randomized clinics, individual clinicians, and individual patients. This 
monitoring system will be utilized during active implementation to provide feedback to 
clinics and system leaders and support the ongoing assessment of barriers and 
facilitators to the use of the OUD-CDS as well as modifications in adoption and 
implementation. 
4. Mini-pilot: Conduct a mini-pilot or other usability testing of the OUD-CDS with a small 
number of clinicians in order to test the OUD-CDS tool and the monitoring and feedback 
system. Collect feedback from pre-pilot clinicians and other clinic staff through site visits 
and refine the design and workflow. 
5. Pilot: Pilot test the OUD-CDS in 1-2 clinic sites in the care system. 
6. Finalize implementation plan: Make adjustments to final implementation analysis where 
feasible and necessary, and document implementation-related issues from multiple 
stakeholder perspectives prior to moving forward. 
7. Baseline PCP surveys: Collect baseline surveys (prior to vanguard or overall go-live 
dates, depending on clinic) of all PCPs in randomized clinics to assess confidence in 
assessing, diagnosing, treating, and referring patients with OUD. 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
35 
Implementation Activities 
1. Monitoring: Produce monitoring data reports developed during the pre-implementation 
phase that describe the use of the OUD-CDS and the types of post-index follow-up care 
received by patients identified via OUD-CDS. 
2. Feedback: Distribute monitoring reports to clinic leaders on a periodic basis (at least 
monthly). 
3. Interview selection: Utilize the monitoring reports to identify and compare characteristics 
of clinics and clinicians with high and low rates of OUD-CDS use as well as high and low 
proportions of patients receiving post-index care. 
4. PCP/staff/leader interviews: Conduct up to 30 semi-structured interviews with clinicians, 
clinic staff and health system leaders in OUD-CDS randomized clinics to identify the 
main barriers and facilitators to the use of OUD-CDS, solicit suggestions for improving 
the intervention and post-index follow-up care, and understand support for maintaining 
or modifying the OUD-CDS system after the research project. 
5. Patient interviews: Conduct up to 90 semi-structured interviews with patients previously 
diagnosed with OUD, identified as high risk for OUD, or referred by their PCP to gather 
reactions and suggestions for improving the intervention from the patient perspective. 
6. Patient Surveys (0-6 months after go-live date): Collect up to 130 patient surveys to test 
and quantify conclusions developed from the patient interviews. 
7. Adaptation: Work with system and clinic leaders to devise and implement adaptations to 
the original design and workflows that address any barriers identified above and 
document all changes and known factors contributing to barriers and facilitators. 
8. Adaptation: Make continuous recommendations to Sites 2 and 3 about their 
implementation plan based on findings from early implementation analysis in Site 1. 
9. Follow-up PCP Surveys (9-months after go-live date): Collect 9-month surveys of all 
primary care clinicians in randomized clinics to assess change in confidence assessing, 
diagnosing, treating, and referring patients with OUD. Include set of questions about the 
usability, accuracy, likelihood to recommend the tool, and barriers and facilitators 
identified through the clinician interviews for PCPs in OUD-CDS randomized clinics. 
 
The above series of activities will be repeated at each site. Data collected will be analyzed rapidly 
and any adjustments to the intervention needed to optimize the uptake of the intervention will be 
made and applied to subsequent sites.   
Subject Recruitment and Data Collection 
A. PCP Surveys 
All PCPs in intervention and control randomized clinics will be surveyed at Baseline and 9 months 
to assess change over time in PCP’s perceived ability to appropriately assess, diagnose, treat, 
and refer patients with OUD and their satisfaction with the OUDS-CDS. Baseline surveys will be 
conducted in the 1-2 months prior to intervention going live in each care system. A vanguard 
phase for each care system will occur approximately 2 months prior to each care system’s official 
go-live date to pilot the roll-out of the baseline surveys and go-live procedures in a select subset 
of clinics. Follow-up surveys will be conducted after the intervention has been live for 9 months in 
each system. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
36 
For PCPs in intervention-randomized clinics, the 9-month surveys will also include a portion 
regarding barriers and facilitators to use of the OUD-CDS tool itself. Questions assessing the use 
of the tool in the 9-month survey will be designed by the study team based on findings during the 
early implementation phase from the quantitative monitoring data and qualitative interview data. 
This section of questions will help quantify barriers and facilitators to PCP use of the OUD-CDS. 
Samples for PCP surveys will be identified by the on-site study teams for recruitment and data 
collection. Samples will include all clinicians working as PCPs in study-randomized clinics at the 
time of the survey. 
The DSC will work with the Lead Node and each study site to construct a survey that will be 
acceptable within each care system. The survey data will be collected by the DSC electronically. 
The DSC will provide each study site with a list of unique survey links, one of which will be included 
in each invitation to a PCP to respond to the survey. The survey will appear to originate within the 
health system. All surveys will include a consent form which will allow the respondent to agree to 
the collection and storage of the respondent’s data prior to proceeding with the survey. Clinicians 
may receive an incentive for participation. 
The initial PCP survey (“Baseline Survey”) will focus on confidence in their ability to appropriately 
assess, diagnose, treat and refer patients with OUD, assessed via 4- or 5-point Likert scales. At 
intervention end, PCPs will again be surveyed about their confidence in OUD care (“Follow-up 
Survey”), and PCPs in intervention clinics will also complete survey questions specific to the OUD-
CDS, including questions regarding usability, accuracy, and provider likelihood to recommend the 
tool. A draft of specific items in the surveys follows. The survey draft that follows is provided as 
an example, is subject to change, and may differ slightly between healthcare systems. 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
37 
Draft of Primary Care Provider Survey for COMPUTE 2.0 
Please answer the following questions to the best of your ability. Your answers will help 
us understand the impact Opioid Wizard may have on clinician ability to diagnose and 
treat opioid use disorder, and the usefulness of the tool. 
1. What is your primary clinic? 
 
2. What is your age? 
 
3. What is your gender 
 
4. With which race/ethnicity do you identify? 
o Asian 
o Hispanic 
o Native American/Alaskan Native 
o Non-Hispanic black 
o Pacific Islander/Native Hawaiian 
o White 
o Mixed race or other 
o Prefer not to answer 
 
5. How many years have you been in practice following residency or fellowship? 
o 0-5 
o 6-10 
o 11-15 
o 16-20 
o 21+ 
 
6. What is your medical specialty? 
o Family Practice 
o Internal Medicine 
o Med Peds 
o Other (please specify) 
 
7. On average, how many days a week do you see patients in clinic?  
o 0 
o 1 
o 2  
o 3 
o 4 
o 5 or more 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
38 
Answer the questions below about your knowledge and approach to management of patients with 
Opioid Use Disorder (OUD). Choose only one answer. 
8. How often do you formally assess patients for opioid use disorder (OUD)? 
Very often 
Often 
Sometimes 
Occasionally 
Never 
 
9. How confident do you feel about screening your patients for OUD? 
Very confident 
Moderately 
confident 
Somewhat 
confident 
Not at all 
confident 
 
10. How often do you provide treatment or refer your patients for treatment of OUD? 
Very often 
Often 
Sometimes 
Occasionally 
Never 
 
11. How confident are you at diagnosing patients with OUD?  
Very confident 
Moderately 
confident 
Somewhat 
confident 
Not at all 
confident 
 
12. How confident are you at treating your patients with medications such as buprenorphine or 
naltrexone for OUD?  
Very confident 
Moderately 
confident 
Somewhat 
confident 
Not at all 
confident 
 
13. How confident are you that you know when to refer your patients with OUD for treatment by 
addiction specialists? 
Very confident 
Moderately 
confident 
Somewhat 
confident 
Not at all 
confident 
 
14. (Skip if PCP waivered to prescribe buprenorphine) To what extent do you agree or disagree 
with the following statement: The availability of EHR-integrated clinical decision support for 
how to use buprenorphine and/or naloxone and manage OUD would make it more likely that 
I would become a certified buprenorphine prescriber. 
Strongly agree
 Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
39 
15. Please rate your ability to effectively manage patients with the following treatment strategies:  
 
High ability (on 
par with 
subspecialists) 
Moderately 
high ability 
Adequate 
ability 
Some ability; 
could use 
improvement 
Low 
ability 
Brief 
motivational 
counseling 
1 
2 
3 
4 
5 
Overdose 
prevention 
1 
2 
3 
4 
5 
Extended-
release 
naltrexone 
(Vivitrol) 
1 
2 
3 
4 
5 
Buprenorphine 
(as 
monotherapy or 
in combination 
with naloxone 
(Suboxone)) 
1 
2 
3 
4 
5 
Referral for 
methadone 
1 
2 
3 
4 
5 
 
NOTE: **The follow-up survey will repeat the questions above, and, for PCPs with CDS 
access, these additional questions will be asked** 
Please answer the questions below concerning work flow and ease of use of the Opioid Wizard 
Clinical Decision Support. 
 
16. How likely are you to recommend Opioid Wizard to a colleague?  
Very 
likely 
Moderately 
likely 
Somewhat 
likely 
Not very likely 
Not at all likely 
17. Opioid Wizard is a tool that helps me screen for OUD. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
18. Opioid Wizard makes me feel more comfortable prescribing medications for OUD in my 
practice.  
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
40 
19. Using the Opioid Wizard makes it easier for me to discuss treatment options of OUD with 
patients and determine their preference. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly disagree 
20. Opioid Wizard helps me know when to refer patients for methadone or other specialty 
treatment. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
21. When I want or need to address OUD with patients, the Opioid Wizard saves me time. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
 
22. Opioid Wizard improves my office efficiency. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
 
23. Time using the Opioid Wizard with patients is time well spent. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
24. Opioid Wizard influences my treatment recommendations. 
Strongly agree
Somewhat 
Agree 
Somewhat 
Disagree 
Strongly 
disagree 
 
25. How useful are the following Opioid Wizard features? 
Feature 
Very 
useful 
Moderately 
useful 
Somewhat 
useful 
Slightly 
useful 
Not at all 
useful 
 
1 
2 
3 
4 
5 
Screening tools 
(TAPS) 
 
 
 
 
 
Diagnosis tools (DSM 
criteria) 
 
 
 
 
 
Prescribing rescue 
kits (naloxone) 
 
 
 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
41 
Feature 
Very 
useful 
Moderately 
useful 
Somewhat 
useful 
Slightly 
useful 
Not at all 
useful 
 
1 
2 
3 
4 
5 
Guidance for 
screening for 
comorbidities such as 
alcohol use disorder, 
hepatitis, pregnancy 
 
 
 
 
 
Deciding which 
treatment approach is 
best for the patient 
(medications for OUD 
in primary care, 
referral to an 
addiction specialist, 
safer use, further 
discussion, etc.) 
 
 
 
 
 
Deciding between 
different medications 
for OUD (extended 
release injectable 
naltrexone vs. 
buprenorphine vs. 
methadone) 
 
 
 
 
 
Safety alerts for 
drug/drug interactions 
 
 
 
 
 
Urine drug screen 
testing reminders  
 
 
 
 
 
26. How could we make Opioid Wizard more useful? 
 ______________________________________________________________________  
 ______________________________________________________________________  
27. Do you have any other feedback you’d like to share, or ways in which you think Opioid Wizard 
could be improved? 
 ______________________________________________________________________  
 
Thank you for your participation. Your input is greatly appreciated! 
----------------------------------------------------------------------------------------------------- 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
42 
B. Semi-Structured Interviews 
A trained qualitative interviewer from within each health system will conduct all clinician, clinic 
staff, health system leader, and patient interviews at that site. 
Clinicians and clinic staff will be recruited for interviews for the purpose of explaining and 
identifying barriers and facilitators to use. Specific criteria for recruitment of clinicians will depend 
on the implementation issue being investigated. However, a diversity of perspectives from 
clinicians will be sought in all data collection events. 
Patients will be recruited for interviews who are referred by their PCP, diagnosed with or identified 
as high-risk for OUD. Because of the sensitivity of the topic of opioid use, the study team will work 
with a variety of stakeholders to create an acceptable recruitment method, including potentially 
recruiting through physicians with existing relationships with patients under treatment for OUD. A 
diversity of perspectives from patients will be sought in all data collection events.  
Health system leaders will be recruited across sites based on their positions within the 
organization. The study team will recruit leaders from various levels of influence within the 
organizations, including high level decision makers and mid-level supervisors like clinic managers 
and care team leads. Selection for interviews will be as broad as possible to gain the most 
organizational context. 
Recruitment for all interviews will be conducted by the on-site study team in a method that is 
acceptable in each setting. All recruitment materials will be developed and submitted for IRB 
review when data collection is indicated. Interview guides will be developed by the study team 
and submitted for IRB review and approval. 
Clinician interviews will explore questions about the workflow of the OUD-CDS within the primary 
care setting; ease of use, areas of confusion, and potential improvements in overall usefulness 
for clinicians; options for overcoming barriers in primary care encounters for using the OUD-CDS; 
and appropriateness of the tool for clinicians’ priorities in identifying and treating OUD. Clinician 
interviews will aim to explore and explain specific observations from the quantitative data, such 
as: differences between experiences of high and low clinician users of the OUD-CDS; relationship 
between the tool and process measures developed by the team; relationship between the tool 
and clinician outcomes like clinician waiver status, and/or patient outcomes like diagnosis, 
treatment, and post-index follow-up status. Clinician interviews will be relatively brief in nature, 
particularly during the active intervention phase when they will be used to learn more about 
problems, troubleshoot, and learn more about specific barriers. 
Patient interviews will explore questions about how patients interpret the tool; reactions to having 
OUD raised during the primary care encounter; reactions to seeing language around their opioid 
use on the tool; preferences for addressing risks around opioid use in primary care settings; 
preferences for effective communication between patients and physicians about OUD; likelihood 
of accepting treatment recommendations from the OUD-CDS. Patient interviews will also aim to 
explore and explain specific observations from the quantitative data, such as: differences in 
patients identified by the OUD-CDS whose physician did or did not utilize the tool in their index 
encounter; differences in patients who did or did not receive post-index care or initiate treatment 
for OUD; differences between patients by demographics, biomedical characteristics, and co-

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
43 
morbid substance use disorders. Patient interviews will be relatively specific in scope and carefully 
crafted for sensitivity. 
All interviews will be conducted by a qualitative interviewer in a private 1-on-1 setting, either in-
person or by phone. All participants will receive an informed consent document that includes all 
elements of consent. Consent status of all recruited participants will be documented by the study 
team. Interviews will be audio-recorded and submitted for verbatim transcription. Patients will 
receive a small incentive for each semi-structured interview. Clinicians and health care system 
leaders may be offered modest incentives for participation. 
C. Patient Surveys 
Following analysis of each round of patient interviews, each site will collect up to 130 brief surveys 
from patients in order to quantify the observations and conclusions drawn from the interviews. 
Samples for evaluation surveys will be defined and identified by the on-site study team for 
recruitment and data collection. Recruitment samples will be balanced by relevant patient 
characteristics, such as race/ethnicity, gender, or presence/absence of an OUD diagnosis in order 
to draw generalizations from the survey results. 
The DSC will work with the Lead Node and each study site to construct a survey that will be 
acceptable within each care system. The survey data will be collected by the DSC electronically. 
The DSC will provide each study site with a list of unique survey links, one of which will be included 
in each invitation to a patient to respond to the survey. The survey will appear to originate within 
the health system where possible. All surveys will include a consent form for the respondent to 
agree to the collection and storage of the respondent’s data prior to proceeding with the survey. 
Patients will receive a small incentive for survey completion. 
Patient interviews will be designed first to solicit patient input on their perception about the 
acceptability of PCPs addressing OUD in general, feedback on the OUD-CDS in particular and 
how it affects this discussion, and how to better fit the tool into clinical workflows from the patient 
perspective. Patient survey content will then be designed based on the findings of the qualitative 
patient interviews, and as such, we are not submitting a draft of this survey at this time. 
D. Field Notes and Observation Data 
Throughout the project, each study site will maintain careful notes related to health system 
stakeholder engagement that include meeting notes, clinic visits, and major health system 
initiatives related to opioid treatment. 
Each study team will contribute information from field notes to a central implementation log held 
and maintained by the main site. The implementation log will track major issues related to the RE-
AIM constructs and contextual factors related to the care system, individual clinics, adaptations 
by systems and clinics, and technical changes over time in the intervention. Notes will also capture 
broader macro-environment issues affecting opioid treatment policy including changes in expert 
guidelines. Each study site will contribute updates to the implementation log on a quarterly basis. 
Original primary notes will be held by the study teams as a resource to reference through the 
analysis process. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
44 
 
General Measures 
 
Contact Information 
We will keep a list of participating primary care clinics, their administrative leaders and their PCPs 
on a secure server at HealthPartners. This list will include the PCP name, primary care clinic 
name, phone number of the clinic and provider email address. We will also keep a separate list 
of healthcare system administrative leaders to engage in administrative interviews, including 
leader name, phone number and email address. We will keep a list of patients to engage in patient 
interviews and surveys, including patient name, primary care clinic name, patient phone number 
and patient mailing address. 
 
Demographics Form 
We will collect age, gender, race/ethnicity, years of practice and medical specialty (primary care 
vs. internal medicine) for PCP participants. Patient-level data required to assess study objectives 
will be collected from the EHR by the OUD-CDS and stored in a secure analytic database. Data 
will be collected from the EHR via the OUD-CDS tool itself, with data stored in a secure server 
located behind multiple HealthPartners firewalls. 
 
Measures of Primary and Secondary Outcomes 
Primary and secondary outcomes will be assessed using the data collected from the EHR via the 
OUD-CDS, from EHR (Clarity) data pulls, through PCP surveys and qualitative interviews, patient 
surveys and qualitative interviews, healthcare administrator interviews, and site implementation 
staff interviews. The specific outcome measures are described in Section 7.0. 
 
Clinical and Safety Assessments 
This intervention is being delivered by way of CDS prompts to influence provider actions to 
incorporate evidence-based best practice standards related to OUD. Prior to implementation, we 
will train all intervention PCPs and their rooming staff on the importance of helping us identify any 
clinician-identified safety events or near-misses that may be related to the EHR or CDS. We will 
systematically educate them in identification of potential safety events and near-misses and 
informing us of these events via use of the Feedback Tab in the CDS or email. We will also ask 
PCPs to notify us of any clinical situations where their clinical judgment differs from the CDS. 
Use of the Feedback Tab will automatically generate an email that is sent to study team members, 
including PIs and programmers. The study team will then discuss this feedback and any 
necessary actions, and reply to the PCP to answer the question, discuss steps taken to address 
the issue, or gather additional information if needed to further trouble-shoot. PCPs will be asked 
to submit feedback any time their clinical judgment is inconsistent with the CDS tool. Additionally, 
the emails of study investigators will be listed on the CDS interface for providers, and PCPs will 
be encouraged to contact us directly with any questions or concerns if they’d rather not use the 
Feedback Tab in the OUD-CDS. This feedback will be provided to the DSMB twice per year or at 
the frequency determined by the DSMB. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
45 
12.0 TRAINING REQUIREMENTS 
 
Overall 
A comprehensive Training Plan will be developed to incorporate general training, study-specific 
training, and mechanisms for competency assessment. The Investigative Team is responsible for 
the development of a comprehensive Training Plan, instructional material, and delivery of the 
training (e.g., via self-study, online, webcast, or teleconference), with the team comprised of the 
Lead Node, Clinical Coordinating Center (CCC), Data and Statistics Center (DSC), as well as 
other participating nodes and subject matter experts, as applicable. PCPs who are in primary care 
clinics randomized to receive the OUD-CDS will be trained on how to diagnosis and manage OUD 
in primary care, use of the OUD-CDS, and the importance of using the Feedback Tab to let the 
study team know of any issues or questions. Traditionally, we have completed such trainings at 
in-person lunch meetings with clinic personnel, but will also consider other training modalities, 
such as web-based trainings or teleconferences, depending on the standard training practices at 
partner sites and clinic leadership preference. 
Study staff will be trained as specified in the Study Training Plan and are required to complete 
institutionally required training per their research site, IRB(s), and authorities with regulatory 
oversight. Training will include Human Subject Protection (HSP) and Good Clinical Practice 
(GCP), as well as protocol-specific training. Tracking of training completion for individual staff as 
prescribed for assigned study role(s) will be documented, endorsed by the site Principal 
Investigator and the Lead Node, and audited by the CCC. As changes occur in the prescribed 
training, the Training Plan and training documentation tracking forms will be amended to reflect 
these adjustments. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
46 
13.0 STATISTICAL DESIGN AND ANALYSES 
 
General Design 
 
Study Hypotheses 
H1.1: Patients previously undiagnosed with OUD but identified as high risk by the OUD-CDS at 
an index visit will be more likely to receive an OUD diagnosis (in the problem list or as an ICD-10 
visit code) in intervention clinics than UC clinics within 30 days post-index. 
H1.2: Patients previously diagnosed with OUD or identified as high risk by the OUD-CDS at an 
index visit will be more likely to have naloxone rescue kits ordered in the intervention clinics than 
in the UC clinics within 30 days post-index. 
H2.1: Patients identified as having OUD or as being at high-risk for OUD by the OUD-CDS at an 
index visit will be more likely to have MOUD orders or referral for OUD treatment within 30 days 
post-index in intervention clinics than in UC clinics. 
H2.2: Patients identified as having OUD or as being at high-risk for OUD by the OUD-CDS at an 
index visit will have significantly more days covered by a MOUD prescription at 90 days post-
index in intervention clinics than in UC clinics. 
H3.1: Patients with OUD or identified as high-risk for OUD by the OUD-CDS who are cared for in 
intervention clinics will have significantly fewer post-index ED visits during the observation period 
(i.e., the period between each patient’s index date and last observation) compared to patients 
cared for in UC clinics. 
H3.2: Patients with OUD or identified as high-risk for OUD by the OUD-CDS who are cared for in 
intervention clinics will have significantly fewer post-index hospitalizations during the observation 
period compared to patients cared for in UC clinics. 
H4.1: After controlling for demographics, baseline clinical status and prior costs of care, patients 
with OUD or identified as high risk for OUD by the OUD-CDS will have lower healthcare costs in 
intervention compared to UC clinics during the observation period (i.e., savings from lower ED 
visits and hospitalizations will outweigh increased costs of OUD treatment and naloxone rescue 
kits and OUD-CDS implementation and maintenance). 
 
Primary and Secondary Outcomes (Endpoints) 
Primary outcome measures will include: 
1. OUD diagnosis (in the problem list or as an ICD-10 visit code) within 30 days of index 
visit for patients identified by the OUD-CDS as being at high risk of OU 
2. Naloxone prescription within 30 days of index visit for patients with OUD or identified by 
the OUD-CDS as being at high risk for OUD 
3. MOUD orders or referral to OUD treatment within 30 days of index visit for patients with 
OUD or identified by the OUD-CDS as being at high risk for OUD 
4. Total days covered by an MOUD prescription in the 90 days after index visit for patients 
with OUD or identified by the OUD-CDS as being at high risk for OUD 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
47 
Secondary outcome measures will include: 
1. OUD diagnosis (in the problem list or as an ICD-10 visit code) at index or within 90 days 
of index visit for patients identified by the OUD-CDS as being at high risk of OUD 
2. Naloxone prescription at index or within 90 days of index visit for patients with OUD or 
identified by the OUD-CDS as being at high risk for OUD 
3. MOUD orders or referral to OUD treatment at index or within 90 days of index visit for 
patients with OUD or identified by the OUD-CDS as being at high risk for OUD 
4. Number of ED visits during the observation period for patients with OUD or identified by 
the OUD-CDS as being at high risk for OUD 
5. Number of hospitalizations during the observation period for patients with OUD or 
identified by the OUD-CDS as being at high risk for OUD 
6. Healthcare costs during the observation period for patients with OUD or identified by the 
OUD-CDS as being at high risk for OUD, compared with healthcare costs over the same 
interval preceding the observation period 
7. Cost of OUD-CDS implementation and maintenance 
8. All-cause mortality rates during the observation period for patients at high risk of OUD 
9. Fatal and non-fatal opioid overdoses during the observation period for patients at high 
risk of OUD 
10. Rates of OUD-CDS use in intervention clinics 
11. PCP ratings of confidence in treating patients with OUD prior to go-live date and 9-
months following go-live date 
12. Intervention clinic PCP ratings of satisfaction and acceptability of the OUD-CDS at 9 
months following go-live date 
Exploratory outcome measures may include: 
1. Number of non-waivered PCPs becoming buprenorphine waivered during the 
intervention period, assessed via health system administrative data 
2. Number of buprenorphine prescriptions written by waivered PCPs during the intervention 
period 
3. PCP ratings of likelihood to prescribe buprenorphine for patients with OUD should no 
waiver be required, measured prior to go-live dates and 9-months following go-live dates 
4. Adherence to therapy during the observation period, assessed via Clarity and claims 
data 
5. Number of patients diagnosed with OUD screened for mental health comorbidities and 
infectious diseases during the observation period 
 
Recruitment 
COMPUTE 2.0 will be conducted at a minimum of 30 primary care clinics within 3 care systems 
that are geographically dispersed and will include a racially, ethnically and socioeconomically 
diverse population. Site 1 is HealthPartners, which was the sole site for the COMPUTE 1.0 pilot 
study, while Site 2 is Geisinger and Site 3 is Essentia. A minimum of 10 primary care clinics to be 
included per site will be selected in partnership with site PIs and primary care leadership at each 
site, taking into consideration such factors as overall clinic size, number of waivered PCPs, and 
baseline prevalence of diagnosed OUD. Clinics will be randomized equally within care system 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
48 
and balanced on pre-randomization outcomes, such as the percentage of study-eligible patients 
with diagnosed OUD, and on clinic characteristics that may enhance or impede intervention 
uptake and adherence, such as the number of waivered PCPs (see Section 10.2). 
PCPs who practice at randomized clinics will be asked to complete surveys prior to go-live date 
and 9-months after go-live date assessing their comfort and confidence treating patients with 
OUD, and among providers in intervention clinics their perceptions of the OUD-CDS. The DSC 
will work with the Lead Node and each study site to construct a survey that will be acceptable 
within each care system. The survey data will be collected by the DSC electronically. Samples for 
PCP surveys will be identified by the on-site study teams for recruitment and data collection. The 
DSC will provide each study site with a list of unique survey links, one of which will be included in 
each invitation to a PCP to respond to the survey. The survey will appear to originate within the 
health system where possible. All surveys will include a consent form which will allow the 
respondent to agree to the collection and storage of the respondent’s data prior to proceeding 
with the survey. Clinicians may be offered an incentive for participation.  
A sample of patients who have been diagnosed with OUD, have been identified as being at high 
risk for OUD or opioid overdose, or referred by a PCP will be recruited to participate in surveys 
and interviews via a mailed or emailed invitation based on standard processes at each site. 
Samples for evaluation surveys will be defined and identified by the on-site study team for 
recruitment and data collection. Survey recruitment samples will be balanced by relevant patient 
characteristics, such as race/ethnicity, gender, or presence/absence of an OUD diagnosis in order 
to draw generalizations from the survey results. The DSC will work with the Lead Node and each 
study site to construct a survey that will be acceptable within each care system. The survey data 
will be collected by the DSC electronically. The DSC will provide each study site with a list of 
unique survey links, one of which will be included in each invitation to a patient to respond to the 
survey. The survey will appear to originate within the health system where possible. All surveys 
will include an informed consent document with the elements of consent for the respondent to 
agree to prior to proceeding with the survey. Patients will receive a small incentive for survey 
completion. 
Clinic and administrative leaders will be identified as potential candidates for interviews in 
conjunction with site investigators and healthcare system leadership. Leaders will be emailed an 
invitation to participate in a phone or in-person interview, and leaders will complete verbal consent 
to participate at the beginning of the phone interview. 
 
Randomization and Factors for Stratification 
The OUD-CDS software is a system-level intervention comprised of 1) a passively operating web 
service that gathers, analyzes and retains information pertinent to every web service call, and 2) 
a user interface that presents a summary of algorithm results to front end users. The web service 
documents every web service call made by all front-end users in all participating locations so that 
data pertinent to all targeted visits from all eligible and enrolled patients will be identically collected 
and available in both treatment arms. The user interface will function as the intervention delivery 
vehicle and therefore be operative only in intervention locations. Intervention or Control 
designation will vary randomly by clinic. The OUD-CDS web service will therefore operate 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
49 
passively in all participating clinics but the user interface will only be turned on in clinics that are 
randomly assigned to the intervention treatment group. 
To the extent that patients tend to receive most of their care over time at a single clinic, and that 
clinicians tend to practice at a single clinic, it is reasonable to assert that the risk of intervention 
contamination across clinics is low. However, because it is common for patients to see more than 
one clinician in a clinic location over time, and for clinicians within a clinic location to discuss 
aspects of care delivery with each other, the risk of intervention contamination within clinics is 
rather high. Randomizing by clinic rather than by PCP or patient will minimize risk of intervention 
contamination. 
Generally speaking, randomization should balance treatment groups on factors that enhance or 
impede intervention uptake and adherence, that are related to and including study outcomes, and 
on any other unmeasured factors that may affect statistical power. However, the likelihood that 
factors related to these considerations are balanced may be diminished in cluster-randomized 
trials due to relatively few randomized units.[33, 34] Covariate constrained randomization will be 
implemented to balance treatment groups across the study and within health care systems (strata) 
on factors related to study outcomes, implementation of the intervention, and potential treatment 
modifiers. 
Potential balancing factors include: 
 
n of waivered providers 
 
n of adult patients at clinic 
 
% of adult patients with government sponsored insurance 
 
% of adult patients who are non-Hispanic White 
 
% of all patients at high risk for OUD 
 
% of patients at high risk for OUD provided a with naloxone rescue kit 
 
% of all patients with diagnosed OUD 
 
% of all patients with diagnosed OUD with a current MOUD 
Each patient will be assigned to the clinic in which his or her first visit that is eligible for the OUD-
CDS intervention (i.e., index visit) takes place, and as such will be assigned to the treatment group 
to which their clinic was randomly assigned. Post-index visits may take place in the same or 
different clinics or treatment groups relative to the index visit and may or may not be eligible for 
the OUD-CDS to offer treatment recommendations. In keeping with an intent-to-treat principle, all 
index and post-index visits and outcome measures for each patient will be attributed to the 
treatment group assignment of the clinic where the index visit took place. 
Further details regarding the randomization procedures including the final balancing factors 
included in the randomization are provided in a separate study randomization plan.  
 
Prediction Models 
Aims 1 through 3 pertain to the effectiveness of the OUD-CDS intervention relative to UC, 
predicting that it will increase diagnosis, naloxone prescribing, and access to MOUD, and 
decrease ED visits and inpatient stays. These hypotheses will be tested using generalized linear 
mixed models to account for clustering of outcomes within eligible patients and randomized 
clinics, or using generalized estimating equations to compare event rates. Outcomes will be 
normalized via distribution-appropriate link functions (e.g., logistic-Normal, Poisson-Normal). 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
50 
Clinic-randomized treatment group, care system and other predictors will be treated as fixed 
effects. 
 
Rationale for Sample Size and Statistical Power 
 
Projected Number of Sites 
At least 30 primary care clinics at three participating healthcare systems (i.e., at least 10 primary 
care clinics per healthcare system) are expected to participate in this study. 
 
Projected Number of Participants per Site 
There must be at least 50 patients with or at high risk for OUD at an index visit at a randomized 
clinic for it to be included in the analyses. Based on the number of patients with study-eligible 
visits in the COMPUTE 1.0 pilot study, we expect this will be a low threshold for clinics to attain. 
The COMPUTE 1.0 intervention was implemented for six months among 55 randomized providers 
who practiced in 30 clinics. During that time, these providers saw between 14 and 137 patients 
(provider median = 77; 37-412 patients per clinic, clinic median = 163) who were eligible for the 
pilot OUD-CDS intervention. To the extent the COMPUTE 2.0 intervention is expected to collect 
outcome data on patients for 19 to 31 months in the randomized clinics, and study-eligible patients 
will be seen by all clinic providers, it is plausible to expect that 1,000 study-eligible patients could 
have index visits at many clinics. 
 
Statistical Power 
A preliminary power analysis was conducted to estimate the minimum detectable difference in 
the likelihood of OUD diagnosis (H1.1), naloxone rescue kit order (H1.2) and MOUD order or 
referral for treatment (H2.2) within 30 days of the index visit, and the number of days covered by 
a MOUD prescription in the 90 days post-index (H2.2) among patients cared for in OUD-CDS 
relative to UC clinics (see Section 13.4). The power analysis relied on conservative assumptions 
regarding the numbers of randomized clinics (10, 30, 50) and of eligible patients (50 or 100 per 
clinic); a range of clinic intraclass correlations consistent with those observed for other process 
measures at HealthPartners (i.e., ICCclin = 0.01, 0.03, 0.05); and central tendency estimates for 
the outcomes (2%, 5%, 10% and 20% or 70, 50, 30 days not covered in UC). Power estimates 
will be updated after Sites 2 and 3 are selected and preliminary data to inform analysis 
assumptions become available. 
Effect size estimates for the binary outcomes were calculated using the NIH group randomized 
trial sample size calculator.[48] The difference in days covered was estimated using the Poisson 
regression module of PASS 11 software[49] after calculating an effective sample size (i.e., Neff = 
(n clinics*m patients per clinic) / (1+(m-1)*ICCclin)). In addition, the Poisson model power analysis 
was conducted to estimate the minimally detectable decrease in days NOT covered in the 90 
days to post-index among OUD-CDS relative to UC patients to ensure that the estimated days in 
both groups remained between 0 and 90 days. 
Table 3 summarizes the minimum detectable increases in outcome rates among OUD-CDS 
relative to UC patients given the aforementioned assumptions. Assuming 30 randomized clinics 
with 50 high risk patients each, that 5% of UC patients have an OUD diagnosis within 30 days of 
their index visit and ICCclin = 0.03, the H1.1 analysis would be powered (power=0.80, α2 = 0.05) 
to detect a difference if ≥11.35% (odds ratio = 2.43) of OUD-CDS patients have an OUD diagnosis 
within 30 days of their index visit. For an event occurring among 10% of UC patients given the 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
51 
same assumptions otherwise, an analysis would be powered to detect a difference if it occurs 
among ≥ 18.12% (odds ratio = 1.99) of OUD-CDS patients. Having more patients per clinic (e.g., 
30 clinics * 100 patients each = 3000 patients) results in a smaller detectable effect size (i.e., 
17.18 OUD-CDS vs. 10% UC; odds ratio = 1.87) although randomizing more than the minimum 
30 clinics (e.g., 50 clinics * 50 patients each = 2500 patients) would reduce the minimum 
detectable effect (i.e., 16.02 OUD-CDS vs. 10% UC; odds ratio = 1.72) further with fewer patients. 
Table 3 also demonstrates that site-specific analyses of the OUD-CDS treatment effect would be 
sufficiently powered to detect only large effect sizes (e.g., 26.73% vs. 10%; odds ratio = 3.28) 
with 30 randomized clinics. 
Table 3. Minimum detectable increase in the proportion of OUD-CDS relative to UC patients to experience 
the H1.1, H1.2 and H2.1 outcomes at the index visit, assuming n=(50, 100) patients per clinic, m=(10, 30, 
50) randomized clinics, ICCclin=(.01, .03, .05) and 2%, 5%, 10%, 20% outcome rates in UC. 
UC % 
2% 
5% 
10% 
20% 
2% 
5% 
10% 
20% 
 
n patients / clinic = 50 
 
n patients / clinic = 100 
ICCclin 
m=10 clinics (minimum site-specific) 
 
m=10 clinics (minimum site-specific) 
0.05 
15.86 
21.97 
30.19 
43.77 
 
14.52 
20.52 
28.60 
41.98 
0.03 
12.89 
18.54 
26.73 
40.08 
12.07 
16.91 
24.56 
37.79 
0.01 
9.86 
15.11 
22.62 
35.51 
8.42 
13.08 
20.08 
32.50 
ICCclin 
m=30 clinics (minimum study-wide) 
m=30 clinics (minimum study-wide) 
0.05 
8.01 
12.89 
19.84 
32.10 
 
7.32 
12.15 
19.03 
31.18 
0.03 
6.85 
11.35 
18.12 
30.52 
6.12 
10.62 
17.18 
29.08 
0.01 
5.46 
9.80 
16.22 
27.80 
4.74 
8.80 
14.93 
26.28 
ICCclin 
m=50 clinics  
m=50 clinics  
0.05 
6.14 
10.73 
17.27 
29.09 
 
5.85 
10.17 
16.66 
28.41 
0.03 
5.40 
9.64 
16.02 
27.62 
4.95 
9.10 
15.33 
26.8 
0.01 
4.45 
8.49 
14.59 
25.86 
3.94 
7.84 
13.68 
24.75 
 
Table 4 provides a comparable summary for the H2.2 outcome, days covered by a MOUD 
prescription in the 90 days post-index. The inverse of the H2.2 outcome was used to calculate 
the minimum detectable difference in MOUD coverage days to ensure that estimated decreases 
in days not covered (or, increases in days covered) remained between 0 and 90 days. Continuing 
with the assumptions from the prior examples, the H2.2 analysis would be sufficiently powered to 
detect a decrease in days not covered by a MOUD if UC patients had 50 of their 90 post-index 
days uncovered (40 covered) but OUD-CDS patients had at least 37.0 uncovered (53.0 covered) 
days. 
Table 4. Minimum detectable decrease in 90 days post-index without a MOUD prescription among OUD-
CDS relative to UC patients, assuming n=(50, 100) patients per clinic, m=(10, 30, 50) randomized clinics, 
ICCclin=(.01, .03, .05) and 30, 50, 70 days not covered in UC. 
UC  
RR 
30 
50 
70 
RR 
30 
50 
70 
 
n patients / clinic = 50 
 
n patients / clinic = 100 
ICCclin 
m=10 clinics (minimum site-specific) 
 
m=10 clinics (minimum site-specific) 
0.05 
0.615 
18.5 
30.8 
43.1 
 
0.638 
19.1 
31.9 
44.7 
0.03 
0.665 
19.9 
33.4 
46.5 
 
0.695 
20.9 
34.8 
48.6 
0.01 
0.731 
21.9 
36.4 
51.2 
 
0.775 
23.2 
38.7 
54.2 
ICCclin 
m=30 clinics (minimum study-wide) 
m=30 clinics (minimum study-wide) 
0.05 
0.760 
22.8 
38.0 
53.2 
 
0.775 
23.3 
38.8 
54.3 
0.03 
0.739 
22.2 
37.0 
51.7 
 
0.813 
24.4 
40.6 
56.9 
0.01 
0.836 
25.1 
41.8 
58.5 
 
0.864 
25.9 
43.2 
60.5 
ICCclin 
m=50 clinics  
m=50 clinics  
0.05 
0.809 
24.3 
40.5 
56.6 
 
0.822 
24.7 
41.1 
57.5 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
52 
0.03 
0.836 
25.1 
41.8 
58.6 
 
0.852 
25.6 
42.6 
59.7 
0.01 
0.871 
26.1 
43.6 
61.0 
 
0.893 
26.8 
44.7 
62.5 
 
Statistical Methods for Primary and Secondary Outcomes 
This section provides an overview of the statistical methods to be employed in testing the primary 
and secondary outcomes. A more detailed description of the analysis may be found in the 
Statistical Analysis Plan. The Statistical Analysis Plan will provide more clarity about the 
underlying assumptions and methodological decisions regarding primary outcome analyses, 
including the extent to which either supplement alters the treatment effect.  
Hypotheses for Aims 1 and 2 predict that the OUD-CDS intervention will increase the likelihood 
that patients at high risk of OUD are diagnosed with OUD (H1.1); and that among those at high 
risk or diagnosed with OUD it will increase the likelihoods that a naloxone rescue kit is ordered 
(H1.2) and that MOUD is ordered or the patient is referred to a provider who can order MOUD 
(H2.1), and the number of days covered by an MOUD prescription (H2.2). The hypotheses from 
Aims 1 and 2 will be tested using generalized linear mixed models so that the likelihood or counts 
of outcomes may be accurately estimated among OUD-CDS relative to UC clinics, accounting for 
the clustering of patients within randomized clinics. Binary outcomes (H1.1, H1.2, H2.1) will be 
normalized using a logistic-Normal link function, while it is anticipated that the count outcome 
(H2.2) will be normalized using a Poisson-Normal link function. The model will estimate fixed 
effects of OUD-CDS, care system and other covariates on outcomes, and random intercepts for 
clinics and patients (H1.1, H1.2, H2.1) or for clinics (H2.2). 
Hypotheses for Aim 3 predict fewer ED visits (H3.1) and inpatient stays (H3.2) during the 
observation period of patients receiving care in the OUD-CDS relative to UC clinics. The rate at 
which each of these outcomes occurs per patient-year will be compared across clinics using 
generalized estimating equations. Clinic-aggregated counts of ED visits and inpatient stays will 
be normalized using a Poisson-Normal link function, and the intercept offset by the log of patient-
years within the clinic. The model will estimate fixed effects of OUD-CDS, care system and other 
covariates on the rate of each outcome per patient-year. Should it be feasible, we will also collect 
and count ED visits and inpatient stays that occurred in the year prior to each patient’s index visit 
so that treatment group differences in pre-post changes in event rates can be quantified (i.e., 
treatment by time interaction). 
Hypotheses for Aim 4 predict lower healthcare costs and the identification and mitigation of 
barriers and identification of facilitators to OUD-CDS implementation and uptake. Analysis of 
costs for this aim will include delivery costs of the OUD-CDS and incremental medical care costs 
attributable to the intervention, defined from the health system perspective. Intervention costs 
may include resources used for implementation, maintenance, compensation, and PCP and staff 
training – which may be assessed by interviews/surveys with implementation site staff or study 
resource use documentation, as appropriate – but will exclude research, development, and 
measurement costs, using standard micro-cost accounting methods and nationally-representative 
pricing of inputs. Medical care costs will include all prescribed medications and clinical inpatient, 
emergency, outpatient, and skilled nursing facility services incurred in the pre- and post-index 
observation periods by participants in each study group, as indicated by insurance claims and 
clinical encounter data. The study sample for the cost analysis will be participants who have 
continuous insurance coverage during the study period, including pharmacy benefits. This sample 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
53 
will be compared to patients without continuous insurance coverage to assess representativeness 
and comparative completeness of utilization measurement in comparison to all study participants. 
Paid amounts for medical claims that are specific to medical groups and insurance plans may 
provide a biased view of costs between pre- and post-intervention periods. To address this, claims 
will be converted to dollar amounts using Total Care Relative Resource Values TM (TCRRVs), 
which are a nationally standardized set of measures that have been endorsed by the National 
Quality Forum[50] and are derived from Centers for Medicare and Medicaid Services (CMS) 
relative value units (RVUs). TCRRVs extend CMS RVU measures to include utilization categories, 
such as laboratory services and medications, which do not have CMS RVU weights.[51] Inpatient 
costs are calculated by applying TCRRVs to the diagnosis-related group classification and length 
of stay of the hospitalization. 
Standard health econometric and specification testing methods will be used to assess the 
incremental differences in healthcare costs between study groups [1, 2, 39]. Specifically, 
healthcare care costs will be analyzed using a generalized hierarchical model with a time x study 
group interaction term that can account for clinic-level clustering and the correlation in each 
subjects’ repeated measures of costs over time (i.e., pre-index and post-index). Demographics 
and baseline clinical status will be controlled for based on randomization imbalances and model 
fit criteria. The marginal effect of being assigned to an intervention clinic will provide an estimate 
of the incremental medical cost associated with the OUD-CDS intervention. To account for the 
non-normality in costs, the distribution family will be specified appropriately, such as by using the 
modified Park test,[2] and the goodness of fit for the specified link function will be tested, such as 
by using modified Hosmer and Lemeshow and Pregibon link tests.[53, 54] Confidence intervals 
will be estimated using heteroscedasticity-robust estimation methods.[55] 
Mixed method data analysis for Aim 5 will occur rapidly as data are collected, so that new 
information can support decision making about revisions in the implementation plan and 
adaptations as the study proceeds. All data analysis and subsequent conclusions and decisions 
made during live implementation will be carefully documented. 
After the implementation phase is complete at all sites, monitoring data, survey data, and 
qualitative data from all sites will be triangulated to draw conclusions about the barriers, 
facilitators, adaptations, and recommendations for future dissemination of the OUD-CDS tool. 
 
Qualitative Data Analysis 
All interview data (from patients, PCPs and leaders) will be analyzed in two phases by a team 
consisting of the interviewers and analysts from each of the sites: 
1. Small samples will be reviewed immediately without coding to identify specific 
intervention problems needing prompt attention and revision in implementation 
approach. 
2. As larger samples are created, we will use a more standard content analysis employing 
an iterative data-reduction method.[56] 
A draft codebook will be developed based on the structure and content of the interview guide. 
That will be revised during application in early interviews by the analysis group so that eventually 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
54 
coding can be performed by pairs of analysts while the larger analytic group can focus on the 
identification of categories, themes, and patterns emerging from the data. The main analytic 
purpose is to identify the clinic, PCP and patient barriers and facilitators to consistent effective 
use of the OUD-CDS.[57] Classification schemes and typologies will be used to identify and 
develop themes, concepts, and patterns. Coding and managing qualitative analyses will be 
conducted using appropriate software. 
We will maintain a data codebook and audit trail in order to map decision points in the analysis. 
Individual interviews that do not fit evolving patterns in the data will get special attention. The 
analysis team will work to agree on final themes and patterns in the data and interview data will 
be triangulated with other data sources. These themes and patterns will then be developed into 
recommendations for larger, less immediate adaptations in the use of the OUD-CDS that can then 
be tested in subsequent interviews with key informants. 
 
PCP Survey Data Analysis 
PCP survey analyses will compare providers’ pre- and post-implementation reports of confidence 
in treating patients with OUD and other items included in both PCP surveys; and to assess 
intervention providers’ post-implementation ratings of satisfaction and acceptability of the OUD-
CDS. Generalized linear mixed models will compare pre-post PCP ratings to account for repeated 
survey measures from PCPs and to ensure all PCP ratings are included in the estimated changes 
in ratings. Changes in PCP ratings may vary as a function of contextual factors or PCP 
characteristics. In secondary analyses of the PCP ratings, care system indicators (Site 1, Site 2, 
Site 3), clinic (e.g., proportion of primary care patients eligible for OUD-CDS, proportion of clinic 
patients with government-sponsored insurance), and provider (e.g., waiver status, number of 
patients eligible for OUD-CDS) characteristics may be considered as main effects or in interaction 
with each other or the treatment group indicator to assess their relationship with pre-post changes 
in survey outcomes. Provider ratings may also be used to represent provider characteristics that 
may modify the OUD-CDS treatment effectiveness. 
 
Patient Survey Data Analysis 
Patient survey analyses will be descriptive to assess the extent to which themes identified in 
patient interviews are confirmed in a larger sample, and to identify correlates between these 
themes and other patient characteristics, such as racial/ethnic group, age group, or being at high 
risk for OUD vs. having diagnosed OUD. 
Secondary outcomes analyses will follow the same logic as the primary outcomes analyses. 
Secondary outcomes that quantify person-based outcomes (e.g., MOUD maintenance and 
adherence) will be analyzed using generalized linear mixed models while those that represent 
population-averaged event rates (e.g., all-cause death rates, fatal and non-fatal opioid overdose 
rates) will be analyzed using generalized estimating equations. 
 
Significance Testing 
The H1.1, H1.2 and H2.1 outcomes will be assessed 3 times for each patient – at the index visit 
(0 days), and 30 (for primary outcomes) and 90 days post-index. Outcomes that occur at an index 
visit will be coded as also having occurred by days 30 and 90. Similarly, outcomes that occur 
between days 1 and 30 will be coded as having occurred by days 30 and 90; and those occurring 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
55 
between days 31 and 90 will be coded as having occurred by day 90. We expect that the 
documented actions that providers take will be overwhelmingly attributable to the index visit. 
Some actions that providers initiate at the index visit, such as placing a treatment referral order, 
may not be complete until considerations related to safety or availability are addressed. The 
primary outcome for H1.1, H1.2 and H2.1 will be assessed at 30 days so that these actions, likely 
initiated at the index visit, may be completed prior to assessing the outcome. It is possible that 
outcomes will not be documented for patients who have post-index visits within 90 days at non-
participating clinics. We assume that these eventualities will be rare and equally likely across 
treatment groups. 
Because virtually all of the information pertinent to the H1.1, H1.2 and H2.1 outcomes will be 
captured by the day 30 measure, the primary hypothesis test for these models will compare the 
likelihood of the day 30 outcome by treatment group. The primary hypothesis test for the H2.2 
outcome will compare the likelihood of the day 90 outcome by treatment group. These 
comparisons will be evaluated using a two-sided test with a Type I error rate of 5%. Comparisons 
at other time points will aid understanding of how relative differences in OUD-CDS versus UC 
settings may increase or decrease in the short term. For example, OUD-CDS might initiate a 
course of provider actions that otherwise would not occur (increase) or merely hasten action that 
eventually takes place in UC settings (decrease). 
The Aim 3 outcomes represent counts of events that accrue over the post-index observation 
periods. The event rates in OUD-CDS versus UC clinics will be evaluated using a two-sided test 
with a Type I error rate of 5%. 
For Aim 4, Hypothesis 4.1, the marginal effect of being assigned to an intervention clinic will 
provide an estimate of the incremental medical cost associated with the OUD-CDS intervention. 
Analyses will be 2-sided, and p-values of less than .05 will be considered statistically significant. 
Confidence intervals will be estimated using heteroscedasticity-robust estimation methods.[55] 
There are several secondary outcomes; however, multiple comparisons will not be adjusted for 
since these are not part of the study’s primary objective. 
 
Interim Analysis 
There are no planned interim analyses. 
 
Exploratory Analysis 
Treatment effectiveness may vary as a function of contextual as well as patient factors. In 
secondary analyses of the primary outcomes, care system indicators (Site 1, Site 2, Site 3), clinic 
(e.g., proportion of primary care patients eligible for OUD-CDS, proportion of clinic patients with 
government-sponsored insurance), and provider (e.g., waiver status, number of patients eligible 
for OUD-CDS, confidence in treating patients with OUD, intent to prescribe buprenorphine if 
waiver no longer required) characteristics may be added to the primary model as main effects 
and in interaction with the treatment group indicator to assess treatment heterogeneity due to 
contextual factors. Patient characteristics (e.g., race, ethnicity, age, estimated neighborhood 
income and education, documented heroin vs. oral opioid use) may be similarly added to assess 
treatment heterogeneity due to patient factors. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
56 
 
Missing Data and Dropouts 
We expect person-based missingness to be extremely rare. Patients are unlikely to be aware that 
their data are being used for this research. They will not be consented and are unlikely to request 
that their data be excluded from analyses. Only patients who have requested that their data not 
be used for research and appear on site-maintained opt out lists will be excluded. 
The primary data source for the Aim 1 through 3 hypotheses will be gathered from EHR-based 
data repositories at each participating site. The stored EHR data elements required for calculating 
the primary and secondary outcomes are extracted from live production tables. Medical care costs 
for Aim 4 will come from administrative claims systems that are relied upon for reimbursement of 
medical care services. The absence of documentation of a care process, vital sign, or medication 
should not be interpreted as a missing value but rather as indicative of a care process or test not 
having been performed or medication not prescribed within the health system. Likewise, absence 
of utilization indicated by billing claims almost always indicates that the utilization (such as a 
hospitalization) did not occur. Truly missing field-based observations (e.g., OUD diagnosis 
assigned, action not observed) will be extremely rare, undetectable and assumed to be missing 
at random. 
 
Demographic and Baseline Characteristics 
Demographic and clinical variables available in the EHR at the index visits will be summarized for 
all enrolled study participants, overall and by site and treatment group. Descriptive summaries of 
the distribution of continuous baseline variables will be presented with percentiles (median, 25th 
and 75th percentiles), and with mean and standard deviation. Categorical variables will be 
summarized in terms of frequencies and percentages. 
 
Safety Analysis 
We will assess the rates of ED use, hospitalization and opioid overdoses that occur in intervention 
and control clinics during each patient’s observation period. The rate at which each of these 
outcomes occurs per patient-year will be compared across clinics using generalized estimating 
equations. Clinic-aggregated counts of ED visits and inpatient stays will be normalized using a 
Poisson-Normal link function, and the intercept offset by the log of patient-years within the clinic. 
The model will estimate fixed effects of OUD-CDS, care system and other covariates on the rate 
of each outcome per patient-year. Should it be feasible, we will also collect and estimate the rate 
at which these events occurred in the year prior to each patient’s index visit so that treatment 
group differences in pre-post changes in event rates can be quantified (i.e., treatment by time 
interaction). 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
57 
14.0 REGULATORY COMPLIANCE, REPORTING and MONITORING 
 
Statement of Compliance 
This study will be conducted in accordance with the current version of the protocol, in full 
conformity with the ethical principles outlined in the Declaration of Helsinki, the Protection of 
Human Subjects described in the International Council for Harmonisation (ICH) GCP Guidelines, 
applicable United States Code of Federal Regulations (CFR), the NIDA Terms and Conditions of 
Award, and all other applicable state, local and federal regulatory requirements. The PIs will 
assure that no deviation from, or changes to, the protocol will take place without prior agreement 
from the Sponsor and documented approval from the IRB, except where necessary to eliminate 
an immediate hazard(s) to the trial participants. An Operations Manual will be provided as a study 
reference guide and study quality assurance tool. 
 
Institutional Review Board Approval 
Prior to initiating the study, participating site investigators will obtain written IRB approval from the 
IRB to conduct the study at their respective sites, which will include approval of the study protocol. 
If changes to the study protocol become necessary, protocol amendments will be submitted in 
writing by the investigators for IRB approval prior to implementation. In addition, IRBs will approve 
all consent forms, recruitment materials, and any materials given to the participant, and any 
changes made to these documents throughout study implementation. For changes to the consent 
form, a decision will be made regarding whether previously consented participants need to be re-
consented. IRB continuing review will be performed annually, or at a greater frequency contingent 
upon the complexity and risk of the study. Each Site PI is responsible for maintaining copies of all 
current IRB approval notices, IRB-approved consent documents, and approval for all protocol 
modifications. These materials must be received by the investigator prior to the initiation of 
research activities at the site and must be available at any time for audit. Unanticipated problems 
involving risk to study participants will be promptly reported to and reviewed by the IRB of record, 
according to its usual procedures. 
HealthPartners will serve as Site 1, and as such, the HealthPartners IRB will serve as the central 
IRB for this study. The IRBs at Sites 2 and 3 will be expected to cede to the HealthPartners IRB 
and enter into reliance/authorization agreements for Protocol CTN 0095. The HealthPartners IRB 
will provide study oversight in accordance with 45 CFR 46. HealthPartners IRB will follow written 
procedures for reporting its findings and actions to appropriate officials at each participating 
institution. Of note, it is possible a partner site may meet Exception Criteria to the NIH sIRB (single 
IRB) Policy and may not utilize the IRB of Record. 
 
Informed Consent 
 
OUD-CDS Implementation 
We will request a waiver [or alteration] of informed consent of patients and PCPs from the IRB of 
record for this study to implement and run the OUD-CDS in primary care clinics. In accordance 
with applicable federal regulations (45 CFR 46.116(f)), the study protocol meets the following 
required criteria as defined in 45 CFR 46.116(f)(3)): 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
58 
 
The research involves no more than minimal risk to the subjects; 
 
The research could not practicably be carried out without the requested waiver or 
alteration; 
 
The waiver or alteration will not adversely affect the rights and welfare of the subjects; 
and 
 
Whenever appropriate, the subjects or legally authorized representatives will be 
provided with additional pertinent information after participation. 
COMPUTE 2.0 uses secondary observational data to evaluate outcomes that result from primary 
care clinics randomized to receive or not receive access to the OUD-CDS. Use of these 
observational data pose no more than minimal risk of harm to subjects, with the risk chiefly being 
loss of confidentiality of data. The risk of using these data is no greater than the risk of routine 
uses of healthcare data for quality improvement by the health systems. Subjects’ access to 
healthcare or healthcare benefits will not be affected by this study. 
The primary objective of this study could not be achieved if only consenting a sub-sample of 
patients were included. Moreover, to identify these subjects and conduct outreach to obtain 
signed authorization would greatly increase the risk of breach of confidentiality. Additionally, we 
estimate our patient enrollment numbers will exceed 10,000 across the three participating 
healthcare systems. The study could not therefore be practically carried out if consent were 
required. 
The integration of the OUD-CDS into primary care clinics involves no more than minimal risk to 
PCPs and patients, as the OUD-CDS is meant to help PCPs achieve the standard of care for 
OUD, not to change the standard of care. Historically this waiver has been granted by our and 
other participating site IRBs for similar CDS studies. 
 
Patient, PCP and Health System Leader Interviews and Surveys 
All patients, PCPs and health system leaders will be consented to participate in any interviews or 
surveys. The informed consent process is a means of providing study information to each 
prospective participant and allows for an informed decision about participation in the study. The 
informed consent forms will include all of the required elements of informed consent. Every 
interview or survey participant is required to give consent verbally, electronically, or physically (via 
study staff prior to in-person interviews) prior to the initiation of any interview or survey. Every 
participant providing consent verbally or electronically will have the opportunity to obtain a hard 
copy of the consent form. 
Prior to informed consent, research staff will provide a detailed description of the study and 
interview or survey to the potential participant and provide a copy of the consent to read. If the 
participant is interested in participating in the interview or survey, he or she will have the 
opportunity to ask any questions related to participation. 
The informed consent forms will be updated or revised whenever important new safety information 
is available or whenever the protocol is amended in a way that may affect participants’ 
participation in the trial. Participants will be informed that their participation is voluntary and they 
may withdraw from the study at any time, for any reason, without penalty. Individuals who refuse 
to participate in interviews or surveys or who withdraw will be treated without prejudice. Study 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
59 
sites will be responsible for maintaining signed consent forms as source documents for quality 
assurance (QA) review and regulatory compliance in a manner that is in compliance with the 
overseeing IRB and its institutional policies. 
 
Quality Assurance Monitoring 
In accordance with federal regulations, the study sponsor is responsible for ensuring proper 
monitoring of an investigation and ensuring that the investigation is conducted in accordance with 
the protocol. Qualified monitors will oversee aspects of site conformity to make certain the site 
staff is operating within the confines of the protocol, and in accordance with GCP. This includes 
but is not limited to protocol compliance, documentation auditing, and ensuring the informed 
consent process is being correctly followed and documented. Non-conformity with protocol and 
federal regulations will be reported as a protocol deviation and submitted to the study sponsor 
and study IRB of record for further review. 
 
Participant and Data Confidentiality 
Participant confidentiality and privacy is strictly held in trust by the participating investigators, their 
staff, the safety and oversight monitor(s), and the sponsor and funding agency, and will be 
maintained in accordance with all applicable federal regulations and/or state/Commonwealth law 
and regulations. This confidentiality is extended to the data being collected as part of this study. 
Data that could be used to identify a specific study participant will be held in strict confidence 
within the research team. No personally-identifiable information from the study will be released to 
any unauthorized third party without prior written approval of the sponsor/funding agency and the 
participant. 
All research activities will be conducted in as private a setting as possible. 
The study monitor, other authorized representatives of the sponsor or funding agency, 
representatives of the Institutional Review Board (IRB), or regulatory agencies may inspect all 
documents and records required to be maintained by the investigator. The clinical study site will 
permit access to such records. 
Participant records will be held confidential by the use of study codes for identifying participants 
on CRFs, secure storage of any documents that have participant identifiers, and secure 
computing procedures for entering and transferring electronic data. The study participant’s 
contact information will be securely stored at each clinical site for internal use during the study. 
At the end of the study, all records will continue to be kept in a secure location for as long a period 
as denoted in Section 14.11, Records Retention and Requirements. 
By signing the protocol signature page, the investigator affirms that information furnished to the 
investigator by NIDA will be maintained in confidence and such information will be divulged to the 
IRB/Privacy Board, Ethical Review Committee, or similar expert committee; affiliated institution; 
and employees only under an appropriate understanding of confidentiality with such board or 
committee, affiliated institution and employees. 
 
Certificate of Confidentiality 
To further protect the privacy of study participants, the Secretary, Health and Human Services 
(HHS), has issued a Certificate of Confidentiality (CoC) to all researchers engaged in biomedical, 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
60 
behavioral, clinical or other human subjects research funded wholly or in part by the federal 
government. Recipients of NIH funding for human subjects research are required to protect 
identifiable research information from forced disclosure per the terms of the NIH Policy (see 
https://humansubjects.nih.gov/coc/index). This protects participants from disclosure of sensitive 
information (e.g., drug use). It is the NIH policy that investigators and others who have access to 
research records will not disclose identifying information except when the participant consents or 
in certain instances when federal, state, or local law or regulation requires disclosure. NIH expects 
investigators to inform research participants of the protections and the limits to protections 
provided by a Certificate issued by this Policy. 
 
Health Insurance Portability and Accountability Act (HIPAA) 
Study sites may be required by their institutions to obtain authorization from participants for use 
of protected health information. Sites will be responsible for communicating with the IRBs or 
Privacy Boards of record and obtaining the appropriate approvals or waivers to be in regulatory 
compliance. Releases of participant identifying information that are permitted by the HIPAA 
regulations, but which are prohibited by other applicable federal regulations and/or 
state/Commonwealth law and regulation, are prohibited. 
 
Investigator Assurances 
Each site must file (or have previously filed) a Federalwide Assurance (FWA) with the HHS Office 
for Human Research Protection (OHRP) setting forth the commitment of the organization to 
establish appropriate policies and procedures for the protection of human research subjects in 
alignment with 45 CFR 46, Subpart A, with documentation sent to NIDA or its designee. Research 
covered by these regulations cannot proceed in any manner prior to NIDA receipt of certification 
that the research has been reviewed and approved by the IRB provided for in the assurance (45 
CFR 46.103). Prior to initiating the study, the PI at each study site will sign a protocol signature 
page and investigator agreement, providing assurances that the study will be performed 
according to the standards stipulated therein. 
 
Financial Disclosure/Conflict of Interest 
All investigators will comply with the requirements of 42 CFR Part 50, Subpart F to ensure that 
the design, conduct, and reporting of the research will not be biased by any conflicting financial 
interest. Everyone with decision-making responsibilities regarding the protocol will confirm to the 
sponsor annually that they have met their institutional financial disclosure requirements. 
 
Clinical Monitoring 
Investigators may host periodic visits by NIDA contract monitors who will examine whether study 
procedures are conducted appropriately and that study data are generated, documented and 
reported in compliance with the protocol, GCP, and applicable regulations. These monitors will 
audit, at mutually agreed upon times, regulatory documents, case report forms (CRFs), informed 
consent forms and corresponding source documents for each participant. Monitors will have the 
opportunity and ability to review any study-associated document or file. 
NIDA-contracted monitors will assess whether submitted data are accurate and in agreement with 
source documentation and will also review regulatory/essential documents such as 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
61 
correspondence with the IRB. Areas of particular concern will be participant informed consent 
forms, protocol adherence, reported safety events and corresponding assessments, and PI 
oversight and involvement in the trial. Reports will be prepared following the visit and forwarded 
to the site principal investigator, the lead investigator and NIDA CCTN. 
Qualified node personnel (Node QA monitors) or other designated parties will provide site 
management for each site during the trial. Node QA staff or other designated parties will audit 
source documentation, including informed consent forms and HIPAA forms. This will take place 
as specified by the local protocol team, node PI or lead team and will occur as often as needed 
to help prevent, detect, and correct problems at the study sites. Node QA personnel will verify 
that study procedures are properly followed and that site personnel are trained and able to 
conduct the protocol appropriately. If the node personnel’s review of study documentation 
indicates that additional training of site study personnel is needed, node QA personnel will 
undertake or arrange for that training. Details of the contract, node QA and data monitoring are 
found in the study QA monitoring plan. 
 
Inclusion of Women and Minorities 
All patients aged 18-75, inclusive, who have a diagnosis of OUD or are determined by the OUD-
CDS algorithms to be at high risk for OUD and who meet all other protocol-defined eligibility 
criteria will be included in the study, regardless of sex or racial/ethnic group. Patients who have 
opted out of research will be excluded from analyses. All PCPs in randomized clinics will be 
included in the study, regardless of sex or racial/ethnic group. Patients who meet the per 45 CFR 
46 Subpart C definition of prisoner will be excluded from surveys and interviews. 
 
Prisoner Certification 
As per 45 CFR 46 Subpart C, there are additional protections pertaining to prisoners as study 
participants. A prisoner is defined as any individual involuntarily confined or detained in a penal 
institution. The term is intended to encompass individuals sentenced to such an institution under 
a criminal or civil statute, individuals detained in other facilities by virtue of statutes or commitment 
procedures which provide alternatives to criminal prosecution or incarceration in a penal 
institution, and individuals detained pending arraignment, trial, or sentencing. 
Due to the nature of the OUD CDS, a prisoner certificate is not applicable to this data collection. 
Patient participants who meet the OHRP definition of “prisoner” will be ineligible for participation 
in any interview or survey. 
 
Regulatory Files 
The regulatory files should contain all required regulatory documents, study-specific documents, 
and all important communications. Regulatory files will be checked at each participating site for 
regulatory document compliance prior to study initiation, throughout the study, as well as at study 
closure. 
 
Records Retention and Requirements 
Research records for all study participants will be maintained by the study team in a secure 
location for a minimum of 3 years after the study is completed and closed. These records are also 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
62 
to be maintained in compliance with IRB, state and federal requirements, whichever is longest. 
The sponsor and Co-Lead Investigators must be notified in writing and acknowledgment from 
these parties must be received by the site prior to the destruction or relocation of research records. 
 
Reporting to Sponsor 
The lead investigators agree to submit accurate, complete, legible and timely reports to the 
Sponsor, as required. These include, but are not limited to, reports of any changes that 
significantly affect the conduct or outcome of the trial or increase risk to study participants. Safety 
reporting will occur as previously described. At the completion of the trial, the Co-Lead 
Investigators will provide a final report to the Sponsor. 
 
Audits 
The Sponsor has an obligation to ensure that this trial is conducted according to good clinical 
research practice guidelines and may perform quality assurance audits for protocol compliance. 
The Lead Investigator and authorized staff from the Northstar Node; the NIDA CTN (the study 
sponsor); NIDA’s contracted agents, monitors or auditors; and other agencies such as the HHS, 
the OHRP and the IRB of record may inspect research records for verification of data, compliance 
with federal guidelines on human participant research, and to assess participant safety. 
 
Study Documentation 
Each participating site will maintain appropriate study documentation (including medical and 
research records) for this trial, in compliance with ICH E6 R2 and regulatory and institutional 
requirements for the protection of confidentiality of participants. Study documentation includes all 
CRFs, workbooks, source documents, monitoring logs, sponsor-investigator correspondence, 
and signed protocol and amendments, ERC or IRB correspondence and approved consent form 
and signed participant consent forms. As part of participating in a NIDA-sponsored study, each 
site will permit authorized representatives from NIDA and regulatory agencies to examine (and 
when permitted by law, to copy) clinical records for the purposes of quality assurance reviews, 
audits, and evaluation of the study safety, progress, and data validity. 
Source documents include all recordings of observations or notations of clinical activities and all 
reports and records necessary for the evaluation and reconstruction of the clinical research study. 
Whenever possible, the original recording of an observation should be retained as the source 
document; however, a photocopy is acceptable provided that it is a clear, legible, and exact 
duplication of the original document. 
 
Protocol Deviations 
This protocol defines a protocol deviation as any noncompliance with the clinical trial protocol. 
The noncompliance may be either on the part of the participant, the investigator, or the study site 
staff. As a result of deviations, corrective actions will be developed by the site and implemented 
promptly.  
These practices are consistent with ICH GCP:  
• 
Section 4.5 Compliance with Protocol, subsections 4.5.1, 4.5.2, and 4.5.3 
• 
Section 5.1 Quality Assurance and Quality Control, subsection 5.1.1 
• 
Section 5.20 Noncompliance, subsections 5.20.1, and 5.20.2. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
63 
Any departure from procedures and requirements outlined in the protocol will be classified as 
either a major or minor protocol deviation. The difference between a major and minor protocol 
deviation has to do with the seriousness of the event and the corrective action required. A minor 
protocol deviation is considered an action (or inaction) that by itself is not likely to affect the 
scientific soundness of the investigation or seriously affect the safety, rights, or welfare of a study 
participant. Major protocol deviations are departures that may compromise the participant safety, 
participant rights, inclusion/exclusion criteria or the integrity of study data and could be cause for 
corrective actions if not rectified or prevented from re-occurrence. Sites will be responsible for 
developing corrective action plans for both major and minor deviations as appropriate. Those 
corrective action plans may be reviewed/approved by the Lead Node and the CCC with overall 
approval by the IRB of record. All protocol deviations will be monitored at each site for (1) 
significance, (2) frequency, and (3) impact on the study objectives, to ensure that site performance 
does not compromise the integrity of the trial. 
All protocol deviations will be recorded. 
Additionally, each site is responsible for reviewing the IRB of record’s definition of a protocol 
deviation or violation and understanding which events need to be reported. Sites must recognize 
that the CTN and IRB definition of a reportable event may differ and act accordingly in following 
all reporting requirements for both entities. 
 
Safety Monitoring 
 
Data and Safety Monitoring Board (DSMB) 
An independent CTN DSMB will examine accumulating data to assure protection of participants’ 
safety while the study’s scientific goals are being met. The CTN DSMB is responsible for 
conducting periodic reviews of accumulating safety and efficacy data. It will provide an opinion on 
whether there is support for continuation of the trial, or evidence that study procedures should be 
changed, or if the trial should be halted, for reasons relating to the safety of the study participants, 
the efficacy of the treatment under study, or inadequate trial performance (e.g., poor recruitment). 
 
Safety Events 
This study is being conducted at the provider level using CDS prompts for evidence-based best 
practice standards related to OUD. As such, we are not trying to change the standard of care for 
OUD in primary care, but rather to help PCPs achieve this standard of care in their care of patients 
with OUD. Prior to implementation, we will train all intervention PCPs and their rooming staff on 
the importance of helping us identify any safety events or near-misses that may be related to the 
EHR or CDS. We will systematically educate them in identification of potential safety events and 
near-misses and informing us of these events via use of the Feedback Tab in the CDS or email. 
We will also ask PCPs to notify us of any clinical situations where their clinical judgment differs 
from the CDS. Use of the Feedback Tab automatically generates an email that is sent to the study 
team. The study team then discusses this feedback and any necessary actions, and connects 
with the PCP to answer the question, discuss steps taken to address the issue, or gather 
additional information and further trouble-shoot. In addition, at HealthPartners, the emails of Drs. 
Rossom and Sperl-Hillen are listed on the CDS interface for providers, and PCPs are encouraged 
to contact us directly with any questions or concerns if they’d rather not use the Feedback Tab in 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
64 
the OUD-CDS. At Sites 2 and 3, study teams will determine what email address should be listed 
on the CDS interfaces for PCPs to contact with questions or concerns. All PCP feedback will be 
provided to the DSMB twice per year. 
This is a minimal risk study. Adverse events and Serious Adverse events are not collected in the 
context of this trial. ED Visits, hospitalizations, Overdose events and deaths (all cause) will be 
captured through data pulls. 
The site will follow local standard operating procedures (SOPs) for managing any medical or 
psychiatric emergencies. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
65 
15.0 DATA MANAGEMENT 
 
Design and Development 
The OUD-CDS itself will house the algorithms, communicate with and display within the EHR, 
and store data required to assess study objectives in a secure analytic database at 
HealthPartners Institute. These data, supplemented by EPIC Clarity data, will be used to assess 
CDS use rates, diagnosis of OUD, treatment of and referral for treatment of OUD, hospitalizations 
and emergency department visits. Data collected from the PCPs, patients and leadership via 
surveys will be collected and housed by the Data and Statistics Center. 
 
Site Responsibilities 
Investigators at each site, including a clinical champion at each site, will be responsible for leading 
healthcare system engagement with clinic and administrative leaders, and for partnering with 
Emmes to facilitate survey administration. An EPIC programmer at each site will be responsible 
for helping coordinate the installation of custom EPIC code to allow the OUD-CDS to run at the 
site. A data programmer at each site will be responsible for pulling preliminary Clarity data at each 
site to allow for harmonization of medication, lab, diagnosis and other data between each site and 
HealthPartners. In partnership with each site’s study team, we will determine whether qualitative 
work at that site will be done by a site co-investigator or by the HealthPartners’ team. Encounter 
data will be collected by the OUD-CDS itself from each care system, and each care system’s data 
will be maintained separately on secure servers. The data programmer at each partner site will 
pull Clarity data to assess such outcomes as orders placed outside of the OUD-CDS tool, 
emergency department visits and hospitalizations. 
 
Data Collection/Acquisition and Entry 
Much of the data for this study will be collected directly by the OUD-CDS tool and stored on secure 
servers at HealthPartners behind multiple firewalls accessible only by authorized personnel. 
Programmers at each partner site will pull data from Clarity to assess such outcomes as orders 
placed outside of the OUD-CDS tool, ED visits and hospitalizations to send to HealthPartners, 
where these data will be stored on secure servers behind multiple firewalls and only accessible 
by authorized personnel. 
 
Qualitative Data 
All qualitative data will be collected and stored by each study site, with master files of all qualitative 
data stored at the main site. Original audio files will be kept on-site behind secure firewalls until 
transcription is complete. Verbatim transcripts of audio-recorded interviews will be made and de-
identified before being stored on local, secure servers. All sites will collaborate on analysis of 
original, de-identified transcript data. Transcripts will be stored on secure servers behind multiple 
firewalls at each site. All field notes and other observation data will be kept by each site. Sites will 
contribute non-primary field note data to the study-wide implementation log described above, kept 
by HealthPartners. All qualitative data will be stored in a de-identified format until study 
completion. All identifiable qualitative data (audio recordings, speaker IDs) will be destroyed when 
analysis is complete. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
66 
 
Survey Data 
All survey data will be collected and stored electronically by the DSC. The DSC will provide 
cleaned survey data back to the prime site for analysis. The link between the surveys and person 
identifiers will be maintained by the study teams. All necessary data agreements will be in place 
prior to exchange of identifiable data, and all parties will protect data behind secure firewalls 
according to institutional policies and IRB requirements.  

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
67 
16.0 PUBLIC ACCESS AND DATA SHARING PLAN 
This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-
Funded Clinical Trial Information and the Clinical Trials Registration and Results Information 
Submission rule. As such, this trial will be registered at ClinicalTrials.gov, and results information 
from this trial will be submitted to ClinicalTrials.gov. In addition, every attempt will be made to 
publish results in peer-reviewed journals. The planning, preparation, and submission of 
publications will follow the policies of the Publications Committee of the CTN. Considerations for 
ensuring confidentiality of any shared data are described in Section 14.5. 
Additional information is included in the CTN-0095 Data Share Plan. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
68 
17.0 PROTOCOL SIGNATURE PAGE 
 
SPONSOR’S REPRESENTATIVE (CCTN SCIENTIFIC OFFICER OR DESIGNEE) 
 
 
 
 
 
      
 
 
 
 
Printed Name 
 
Signature 
 
Date 
ACKNOWLEDGEMENT BY INVESTIGATOR: 
 
I am in receipt of version 4.0 of the protocol and agree to conduct this clinical study in 
accordance with the design and provisions specified therein. 
 
I agree to follow the protocol as written except in cases where necessary to protect the 
safety, rights, or welfare of a participant, an alteration is required, and the sponsor and IRB 
have been notified prior to the action. 
 
I will ensure that the requirements relating to obtaining informed consent and institutional 
review board (IRB) review and approval in 45 CFR 46 are met. 
 
I agree to personally conduct or supervise this investigation at this site and to ensure that 
all site staff assisting in the conduct of this study are adequately and appropriately trained 
to implement this version of the protocol and that they are qualified to meet the 
responsibilities to which they have been assigned. 
 
I agree to comply with all the applicable federal, state, and local regulations regarding the 
obligations of clinical investigators as required by the Department of Health and Human 
Services (HHS), the state, and the IRB. 
 
SITE’S PRINCIPAL INVESTIGATOR 
 
 
 
 
 
Printed Name 
 
Signature 
 
Date 
 
Clinical Site Name  
 
 
Node Affiliation  
 
 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
69 
18.0 REFERENCES 
1. 
Blough, D.K., C.W. Madden, and M.C. Hornbrook, Modeling risk using generalized linear 
models. J Health Econ, 1999. 18(2): p. 153-71. 
2. 
Manning, W.G. and J. Mullahy, Estimating log models: to transform or not to transform? 
J Health Econ, 2001. 20(4): p. 461-94. 
3. 
Liang, K.-Y. and S.L. Zeger, Longitudinal data analysis using generalized linear models. 
Biometrika, 1986. 73(1): p. 13-22. 
4. 
Hsieh, H.F. and S.E. Shannon, Three approaches to qualitative content analysis. Qual 
Health Res, 2005. 15(9): p. 1277-88. 
5. 
CDC grand rounds: prescription drug overdoses - a U.S. epidemic. MMWR Morb Mortal 
Wkly Rep, 2012. 61(1): p. 10-3. 
6. 
Scholl L, S.P., Kariisa M, Wilson N, Baldwin G., Drug and Opioid-Involved Overdose 
Deaths — United States, 2013–2017. . 2019. p. 1419-1427. 
7. 
Substance Abuse and Mental Health Services Administration. Rockville, M., Office of 
Applied Studies. Treatment episode data set - admissions (TEDS-A). 2012 [cited 2018 
May 15]; Available from: http://wwwdasis.samhsa.gov/webt/quicklink/US09.htm. 
8. 
Alford, D.P., et al., Collaborative care of opioid-addicted patients in primary care using 
buprenorphine: five-year experience. Arch Intern Med, 2011. 171(5): p. 425-31. 
9. 
Liebschutz, J.M., et al., Buprenorphine treatment for hospitalized, opioid-dependent 
patients: a randomized clinical trial. JAMA Intern Med, 2014. 174(8): p. 1369-76. 
10. 
Moore, B.A., et al., Primary care office-based buprenorphine treatment: comparison of 
heroin and prescription opioid dependent patients. J Gen Intern Med, 2007. 22(4): p. 
527-30. 
11. 
Schackman, B.R., et al., Cost-effectiveness of long-term outpatient buprenorphine-
naloxone treatment for opioid dependence in primary care. J Gen Intern Med, 2012. 
27(6): p. 669-76. 
12. 
Soeffing, J.M., et al., Buprenorphine maintenance treatment in a primary care setting: 
outcomes at 1 year. J Subst Abuse Treat, 2009. 37(4): p. 426-30. 
13. 
Weiss, L., et al., Integration of buprenorphine/naloxone treatment into HIV clinical care: 
lessons from the BHIVES collaborative. J Acquir Immune Defic Syndr, 2011. 56 Suppl 
1: p. S68-75. 
14. 
Coviello, D.M., et al., A multisite pilot study of extended-release injectable naltrexone 
treatment for previously opioid-dependent parolees and probationers. Subst Abus, 2012. 
33(1): p. 48-59. 
15. 
Hutchinson, E., et al., Barriers to primary care physicians prescribing buprenorphine. 
Ann Fam Med, 2014. 12(2): p. 128-33. 
16. 
Barry, D.T., et al., Integrating buprenorphine treatment into office-based practice: a 
qualitative study. J Gen Intern Med, 2009. 24(2): p. 218-25. 
17. 
Netherland, J., et al., Factors affecting willingness to provide buprenorphine treatment. J 
Subst Abuse Treat, 2009. 36(3): p. 244-51. 
18. 
Walley, A.Y., et al., Office-based management of opioid dependence with 
buprenorphine: clinical practices and barriers. J Gen Intern Med, 2008. 23(9): p. 1393-8. 
19. 
Alanis-Hirsch, K., et al., Extended-Release Naltrexone: A Qualitative Analysis of Barriers 
to Routine Use. J Subst Abuse Treat, 2016. 62: p. 68-73. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
70 
20. 
Ammenwerth, E., P. Schnell-Inderst, and A. Hoerbst, The Impact of Electronic Patient 
Portals on Patient Care: A Systematic Review of Controlled Trials. Journal of Medical 
Internet Research, 2012. 14(6): p. e162. 
21. 
Druss, B.G. and L. Dimitropoulos, Advancing the adoption, integration and testing of 
technological advancements within existing care systems. Gen Hosp Psychiatry, 2013. 
35(4): p. 345-8. 
22. 
Roshanov, P.S., et al., Impact of a computerized system for evidence-based diabetes 
care on completeness of records: a before-after study. BMC Med Inform Decis Mak, 
2012. 12: p. 63. 
23. 
Desai, J.R., J.M. Sperl-Hillen, and P.J. O'Connor, Patient preferences in diabetes care: 
overcoming barriers using new strategies. J Comp Eff Res, 2013. 2(4): p. 351-4. 
24. 
Gilmer, T.P., et al., Cost-effectiveness of an electronic medical record based clinical 
decision support system. Health Serv Res, 2012. 47(6): p. 2137-58. 
25. 
Kharbanda, E.O., et al., TeenBP: Development and Piloting of an EHR-Linked Clinical 
Decision Support System to Improve Recognition of Hypertension in Adolescents. 
EGEMS (Wash DC), 2015. 3(2): p. 1142. 
26. 
O'Connor, P.J., et al., Impact of electronic health record clinical decision support on 
diabetes care: a randomized trial. Ann Fam Med, 2011. 9(1): p. 12-21. 
27. 
Sperl-Hillen, J.M., et al., Simulated physician learning program improves glucose control 
in adults with diabetes. Diabetes Care, 2010. 33(8): p. 1727-33. 
28. 
McNeely, J., et al., Performance of the Tobacco, Alcohol, Prescription Medication, and 
Other Substance Use (TAPS) Tool for Substance Use Screening in Primary Care 
Patients. Ann Intern Med, 2016. 165(10): p. 690-699. 
29. 
Association, A.P., Diagnostic and Statistical Manual of Mental Disorders. 5th ed. 2013, 
Washington DC. 
30. 
Sperl-Hillen, J.R., RC; Kharbanda, EO; Gold, R; Geissal, ED; Elliott, TE; Desai, JR; 
Rindal, DB; Saman, DM; Waring, SC; Margolis, KL; O'Connor, PJ. , Priorities Wizard: 
Multisite Web-Based Primary Care Clinical Decision Support Improved Chronic Care 
Outcomes with High Use Rates and High Clinician Satisfaction Rates. . eGEMs 
(Generating Evidence & Methods to Improve Patient Outcomes), 2019. 7(1): p. 9. 
31. 
Ferlie, E., L. Fitzgerald, and M. Wood, Getting evidence into clinical practice: an 
organisational behaviour perspective. J Health Serv Res Policy, 2000. 5(2): p. 96-102. 
32. 
Chambers, D.A., Advancing the science of implementation: a workshop summary. Adm 
Policy Ment Health, 2008. 35(1-2): p. 3-10. 
33. 
Yano, E.M., The role of organizational research in implementing evidence-based practice: 
QUERI Series. Implement Sci, 2008. 3: p. 29. 
34. 
Solberg, L.I., Improving medical practice: a conceptual framework. Ann Fam Med, 2007. 
5(3): p. 251-6. 
35. 
Ware, J.H. and M.B. Hamel, Pragmatic trials--guides to better patient care? N Engl J Med, 
2011. 364(18): p. 1685-7. 
36. 
Gaglio, B., et al., How pragmatic is it? Lessons learned using PRECIS and RE-AIM for 
determining pragmatic characteristics of research. Implement Sci, 2014. 9: p. 96. 
37. 
Glasgow, R.E. and D. Chambers, Developing robust, sustainable, implementation 
systems using rigorous, rapid and relevant science. Clin Transl Sci, 2012. 5(1): p. 48-55. 
38. 
Glasgow, R.E. and P.E. Estabrooks, Pragmatic Applications of RE-AIM for Health Care 
Initiatives in Community and Clinical Settings. Prev Chronic Dis, 2018. 15: p. E02. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
71 
39. 
Glasgow, R.E., et al., RE-AIM Planning and Evaluation Framework: Adapting to New 
Science and Practice With a 20-Year Review. Front Public Health, 2019. 7: p. 64. 
40. 
Harden, S.M., et al., RE-AIM in Clinical, Community, and Corporate Settings: 
Perspectives, Strategies, and Recommendations to Enhance Public Health Impact. Front 
Public Health, 2018. 6: p. 71. 
41. 
Rabin, B.A., et al., Systematic, Multimethod Assessment of Adaptations Across Four 
Diverse Health Systems Interventions. Front Public Health, 2018. 6: p. 102. 
42. 
Langley, G.J.N., K.M.; Nolan, T.W. , The foundation of improvement. . Qual Prog., 
1994(27): p. 81-86. 
43. 
Speroff, T. and G.T. O'Connor, Study designs for PDSA quality improvement research. 
Qual Manag Health Care, 2004. 13(1): p. 17-32. 
44. 
Glanz, J.M., et al., Prediction Model for Two-Year Risk of Opioid Overdose Among 
Patients Prescribed Chronic Opioid Therapy. J Gen Intern Med, 2018. 33(10): p. 1646-
1653. 
45. 
NARxCHECK® Score as a Predictor of Unintentional Overdose Death. [cited 2019 April 
4]; Available from: http://pmp.pharmacy.state.mn.us/assets/files/NARxCHECK-Score-as-
a-Predictor1.pdf. 
46. 
Chaudhary, M.A. and L.H. Moulton, A SAS macro for constrained randomization of 
group-randomized designs. Comput Methods Programs Biomed, 2006. 83(3): p. 205-10. 
47. 
Greene, E.J., A SAS Macro for Covariate-Constrained Randomization of General 
Cluster-Randomized and Unstratified Designs. J Stat Softw, 2017. 77(Cs1). 
48. 
Sample Size Calculator for GRTs. [cited 2019 May 3]; Available from: 
https://researchmethodsresources.nih.gov/SampleSizeCalculator.aspx. 
49. 
Hintze, J., PASS 11. . 2011, Kaysville, Utah. : NCSS, LLC. 
50. 
Press release: NQF Endorses Resource Use Measures. Jan 31, 2012 [cited 2018 Jun 
12]; Available from: 
http://www.qualityforum.org/News_And_Resources/Press_Releases/2012/NQF_Endors
es_Resource_Use_Measures.aspx. 
51. 
HealthPartners, Total Care Relative Resource Value (TCRRVTM): A Measurement 
Approach to Achieve the Triple Aim. HealthPartners White Paper, 
https://www.healthpartners.com/ucm/groups/public/@hp/@public/documents/documents
/cntrb_039627.pdf. Sep 21, 2017, HealthPartners: Bloomington, MN. 
52. 
Mullahy, J., Much ado about two: reconsidering retransformation and the two-part model 
in health econometrics. J Health Econ, 1998. 17(3): p. 247-81. 
53. 
Hosmer, D.W.J., S. Lemeshow, and R.X. Sturdivant, Applied Logistic Regression. 3rd 
ed. 2013, Hoboken, NJ: Wiley. 
54. 
Pregibon, D., Goodness of link tests for generalized linear models. Journal of the Royal 
Statistical Society. Series C (Applied Statistics), 1980. 29(1): p. 15-14. 
55. 
White, H., A heteroskedasticity-consistent covariance matrix estimator and a direct test 
for heteroskedasticity. Econometrica, 1980. 48(4): p. 817-838. 
56. 
Marshall, C. and G.B. Rossman, Designing Qualitative Research, 5th edition. 5th ed. 
2011, Newbury Park: Sage Publications. 
57. 
Saldana, J., The coding manual for qualitative researchers. 2nd edition ed. 2013, 
Thousand Oaks, CA: Sage Publications. 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
72 
19.0 APPENDIX A: DATA AND SAFETY MONITORING PLAN 
Data and Safety Monitoring Plan Template 
1.0 
BRIEF STUDY OVERVIEW 
Through CTN-0076-Ot, our team has developed and piloted a web-based and EHR-integrated 
Opioid Use Disorder (OUD) Clinical Decision Support (CDS) system to offer expert guidance to 
primary care providers (PCPs) on the management of OUD. The OUD-CDS has been 
implemented within the EPIC electronic health record (EHR) of one large care system and was 
piloted with 55 providers to ensure content validity and provider satisfaction. Our team will now 
implement this OUD-CDS in a large multi-site clinic-randomized controlled trial to evaluate its 
impact on practice process measures and patient outcomes. We also aim to prepare for scalability 
by evaluating facilitators and barriers to implementation, determining the costs of implementation 
and maintenance, and assessing cost effectiveness of the OUD-CDS. This study will randomize 
a minimum of 30 clinics to receive the OUD-CDS intervention or usual care (UC) across three 
large diverse healthcare systems. In intervention clinics, the OUD-CDS will identify patients at 
high risk for OUD, display the OUD-CDS and store analytic data from all eligible visits. In UC 
clinics, the OUD-CDS will run invisibly in the background to identify high risk patients and store 
analytic data. 
2.0 
OVERSIGHT OF CLINICAL RESPONSIBILITIES 
A. 
Site Principal Investigator 
Each participating site’s Principal Investigator (PI) is responsible for study oversight, including 
ensuring human research subject protection by designating appropriately qualified, trained 
research staff and by overseeing training of PCPs to ensure adequate reporting of safety events 
as defined by the study protocol. 
B. 
CCC Medical Monitor 
It is not anticipated that a CCC Medical Monitor will be assigned to this study. Drs. Rossom and 
Sperl-Hillen and the Site PIs for Sites 2 and 3 will monitor all PCP feedback and make adjustments 
to the OUD-CDS as clinically indicated. 
C. 
Data and Safety Monitoring Board (DSMB) 
An independent CTN DSMB will monitor this study. The CTN DSMB is responsible for conducting 
periodic reviews of accumulating safety and efficacy data. It will provide an opinion on whether 
there is support for continuation of the trial, or evidence that study procedures should be changed, 
or if the trial should be halted, for reasons relating to the safety of the study participants, the 
effectiveness of the intervention under study, or inadequate trial performance (e.g., poor 
recruitment). 
Following each DSMB meeting, the NIDA CCTN will communicate the outcomes of the meeting, 
based on DSMB recommendations, in writing to the study Lead Investigator. This communication 
summarizing study safety information will be submitted to participating IRBs. 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
73 
D. 
Quality Assurance (QA) Monitoring 
Quality assurance monitoring will be accomplished via pre-implementation testing to confirm that 
the CDS is collecting and storing the data as expected. After implementation and throughout the 
intervention phase, data will be repeatedly tested to ensure all data elements necessary for 
analysis are collected from all three sites on secure servers, and Dr. Crain will conduct periodic 
test analyses to ensure that all the data she requires for analysis are complete. Additionally, Drs. 
Rossom and Sperl-Hillen and investigators from Sites 2 and 3 will conduct periodic chart audits 
to ensure that data collected by the CDS is accurate and complete. 
E. Management of Risks to Participants 
Confidentiality 
Confidentiality of participant records will be secured by the secure storage of any documents that 
have participant identifiers on-site, as well as secure computing procedures for collecting, storing, 
entering and transferring electronic data. Any documents or logs linking study codes with study 
participants  on-site will be kept locked/secured separately from the study files and the medical 
records. No identifying information will be disclosed in reports, publications or presentations. 
Information That Meets Reporting Requirements 
We anticipate that the IRB of record will grant a waiver of consent for PCPs and patients to 
participate in the OUD-CDS intervention. PCPs will be using the OUD-CDS during their care of 
patients, and PCPs are required to report any suspected or known sexual or physical abuse of a 
child or elders to the appropriate authorities. PCPs are also expected to act on patient threats of 
violence to self and/or others. 
Participant Protection 
PCP participant protection: This study will provide OUD-CDS to approximately half of randomized 
primary care clinics and their employed PCPs. Practice decisions made during the course of any 
patient encounters will not be reported to the practice group, thus preventing adverse employment 
or incentive-based decisions being made solely as a result of study participation. 
Patient participant protection: With this work, we are not attempting to change the standard of 
care for OUD treatment in primary care, but rather are attempting to help PCPs achieve this 
standard of care in OUD treatment. There is a small but important risk that the OUD-CDS may 
malfunction or provide inaccurate information. PCPs will be trained that, as with other clinical 
decision tools, the OUD-CDS is meant to supplement but not supersede clinical judgment. PCPs 
can choose to follow or not follow the guidance of the CDS at any given time for any given patient. 
PCPs will be asked to use the Feedback Tab within the tool to let the team know of questions or 
potential errors in the CDS. Additionally, PCPs are trained to let the research team know via the 
Feedback Tab when their clinical judgment is inconsistent with the CDS. This feedback will be 
monitored by the treatment team and the CDS algorithms adjusted if indicated. 
Pregnancy 
There are algorithms specific to treatment of pregnant women in the OUD-CDS. At HealthPartners 
clinics, for example, it is recommended that all pregnant women at high risk for OUD be referred 
to the Healthy Beginnings program for treatment by high-risk perinatologists and consideration of 
treatment with monotherapy buprenorphine for OUD. There are also algorithms that recommend 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
74 
pregnancy tests for women of child-bearing ages throughout the OUD-CDS. Algorithms guiding 
the referral of pregnant women with OUD to specialty care is anticipated to be different at each 
study site, but the algorithms will be consistent in informing PCPs that pregnant women with OUD 
require referral to specialty care. 
Study Specific Risks 
There is a small but important risk that the OUD-CDS could provide the wrong treatment advice 
at the wrong time. As with other clinical decision tools, the Opioid Wizard makes suggestions for 
patient care that are meant to supplement but not supersede clinical judgment. PCPs can choose 
to follow or not follow the guidance of the CDS at any given time in any given patient encounter. 
PCPs will be trained to let the research team know via the Feedback Tab in the CDS when their 
clinical judgment leads them to a different action than that suggested by the CDS. These events 
will be monitored by the treatment team and the CDS algorithms adjusted if there are found to be 
errors. Every clinical encounter requires medical judgment and poses some element of risk to 
patients. In the situation of a PCP who is unfamiliar or uncomfortable with OUD, use of the CDS 
will likely make care safer by providing suggestions to screen and assess for OUD using validated 
tools, and to encourage referrals when patients are classified as high risk. We will not be 
encouraging buprenorphine use in non-certified providers, and this will be reinforced thoroughly 
in provider training on the CDS. For buprenorphine-certified providers, the use of the CDS may 
improve the likelihood of using Medication Assisted Treatment (MAT) in high risk situations; 
however, the risks of MAT are generally considered lower than untreated OUD in high-risk 
situations. 
3.0 
DATA MANAGEMENT PROCEDURES 
This protocol will utilize a centralized Data and Statistics Center (DSC). A web-based distributed 
data entry model will be implemented. This electronic data capture system will be developed to 
ensure that guidelines and regulations surrounding the use of computerized systems in clinical 
trials are upheld. Data collected by the OUD-CDS and from Clarity pulls will be stored on secure 
servers behind multiple firewalls at HealthPartners Institute in a secure project folder only 
accessible by authorized study personnel. 
4.0 
DATA AND STATISTICS CENTER RESPONSIBILITIES 
The DSC will: 1) develop and apply data management procedures to ensure the collection of 
accurate and good-quality survey data, 2) prepare instructions for the use of the electronic data 
capture system, 3) conduct ongoing monitoring activities on study data collected from all 
participating sites, and 4) perform survey data cleaning activities as necessary prior to the transfer 
of data resulting from the conduct of each survey. There will be no interim monitoring analyses 
for this study.  
5.0 
DATA MONITORING, CLEANING AND EDITING 
All OUD-CDS, Clarity and interview data will be monitored, cleaned and edited at HealthPartners 
Institute on secure servers and accessible only by study personnel. Survey data will be monitored, 
cleaned and edited by the DSC. 
 
 

NIDA CTN-0095 
Version 6.0
COMPUTE 2.0 
March 31, 2023
 
Confidential 
75 
6.0 
DATABASE LOCK AND TRANSFER 
At the conclusion of data collection for each survey, the DSC will perform final data cleaning 
activities and will “lock” the survey database from further modification. The final analysis dataset 
will be transferred to the Lead Investigator or designee. De-identified versions of these datasets 
will also be provided to the NIDA CCTN-designated parties for posting on Datashare, as well as 
storage and archiving. 
Reference: http://grants.nih.gov/grants/guide/notice-files/not98-084.html