Suicide Prediction and Prevention for People at Risk for Opioid Use Disorder: Supplement to COMPUTE 2.0
Phase: NA
Conditions: Opioid Use, Opioid-use Disorder, Suicide
Sponsor: HealthPartners Institute

 
 
 
 
 
 
 
 
 
 
 
Suicide Prediction and Prevention for 
People at Risk for Opioid Use 
Disorder Protocol 
 
3UG1DA040316-06S3 
Supplement to COMPUTE 2.0 
 
 
 
 
Lead Investigators: Rebecca Rossom, MD, MS; Gavin Bart, MD, PhD  
 
 
 
 
October 27, 2020 
Version 1.0

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 
 
Stephanie Hooker, PhD; Co-Investigator, HealthPartners 
 
Laurel Nightingale, MPH; Project Manager, HealthPartners 
 
Caitlin Borgert-Spaniol, MA; Project Manager, 
HealthPartners 
 
Rashmi Sharma; EPIC Programmer, HealthPartners 
 
Debbie McCauley; EPIC Programmer, HealthPartners 
 
Deepa Appana; Web Programmer, HealthPartners 
 
Jenn Boggs, PhD; Consultant, Kaiser Permanente Colorado 
 
Julie Richards, PhD; Consultant, Kaiser Permanente 
Washington  
 
NIDA CCTN Scientific Officer: 
Kristen Huntley, PhD 
 
 

A. List of Abbreviations 
Abbreviation 
Definition 
BPA 
Best Practice Advisory 
CDS 
Clinical Decision Support 
CSSRS 
Columbia Suicide Severity Risk Scale 
CTN 
Clinical Trials Network of NIDA 
DSMB 
Data Safety Monitoring Board 
ED 
Emergency Department 
EHR 
Electronic health record 
IRB 
Institutional Review Board 
MHRN 
Mental Health Research Network 
NIDA 
National Institute on Drug Abuse 
NIH 
National Institutes of Health 
OUD 
Opioid use disorder 
PCC 
Primary care clinician 
B. Summary 
This study integrates the Mental Health Research Network (MHRN) suicide risk models into 
Opioid Wizard, an electronic health record (EHR) clinical decision support (CDS) to identify and 
treat patients at high risk of opioid use disorder (OUD)/overdose or diagnosed with OUD, to alert 
primary care clinicians (PCCs) to patients at elevated risk for suicide and guide them through 
structured suicide risk assessment. In both intervention and control clinics, suicide risk scores will 
be calculated for all Opioid Wizard-eligible patients and relevant EHR data to inform analyses will 
be archived. In intervention clinics, Opioid Wizard will alert PCCs to Opioid Wizard-eligible 
patients who are at increased risk of suicide and coach them through use of the Columbia Suicide 
Severity Risk Scale (CSSRS), a structured tool in the EHR that will help PCCs assess immediate 
suicide risk. Based on the resulting CSSRS score, Opioid Wizard will provide EHR links for risk-
based referrals and follow-up recommendations, including care as usual, routine or emergent 
referral to behavioral health, or transportation to the emergency department (ED) for further 
assessment. Primary outcome measures include completion of CSSRS assessments for at-risk 
patients and patient engagement in outpatient mental health care.   
C. Background and Rationale 
Two public health issues of paramount importance -- suicide and opioid overdose -- have 
substantial overlap. Depression and other mental health conditions increase the risk of both opioid 
use disorder (OUD) and suicide, and people with OUD are more likely to have depression and 
other mental health conditions. In fact, the risk of both suicide and opioid overdose is likely highest 
in those with both OUD and mental health diagnoses.1 More than 48,000 people died of suicide 
and 46,000 of an opioid overdose in the US in 2018, and over 40% of suicide and overdose deaths 
involved opioids.2,3 Ultimately, people with OUD are 13 times more likely to die by suicide than 
the general population.4  
OUD and opioid misuse are associated with suicidal ideation and suicide attempts,5,6 but 
distinguishing intentional and unintentional overdoses is complicated. The proportion of opioid-
overdose deaths that are suicides is likely considerable and underestimated, as it is challenging 
to classify overdoses according to intent.7,8 Furthermore, intentionality of overdose is likely 
dimensional, rather than categorical, with many overdoses not fully intentional or unintentional.9 

Suicide deaths and overdose deaths share common risk factors,6,10-17 and while historically most 
overdoses have been thought to be unintentional, more recent evidence suggests that a 
significant proportion – estimated to be 20 to 30% - are intentional.18  
The US Preventative Services Task Force found insufficient evidence to support universal 
screening for suicide risk, but this is not to discourage screening at-risk populations, such as 
people with or at high risk for OUD or opioid overdose.19 A recent commentary in the New England 
Journal of Medicine states that improved screening for suicide risk along with rapid access to 
treatment is critical to prevent opioid-related suicide deaths in patients with OUD.20 Ultimately, 
people with OUD should be targeted for prevention of both suicide and opioid overdose, 
recognizing that mental health conditions in this population will further increase risk.16,21 To that 
end, this ancillary study, which will help primary care clinicians (PCCs) both identify people at risk 
for OUD/opioid overdose and a subset at increased risk of suicide, is particularly timely and 
important. In addition to guiding PCCs through structured assessment of suicide risk and 
providing decision support for recognition and treatment of depression, our study’s potential to 
improve access to medications for OUD is also thought to reduce rates of intentional (and 
unintentional) overdose.22   
D. Specific Aims & Hypotheses 
People with OUD are at increased risk of depression and other mental health conditions, and a 
significant proportion of opioid-related deaths are likely suicides.23,24 Yet systematic screening of 
patients with OUD for suicide risk is rarely done.25 Nearly 50% of patients who die by suicide 
make a healthcare visit in the prior month, most often to primary care.26 Primary care has an 
important role to play in suicide prevention.   
In the NIMH-funded Mental Health Research Network (MHRN; 1U19MH121738), research team 
members developed and validated electronic health record (EHR)-based suicide risk prediction 
models that substantially outperform previous such tools.27 These validated suicide risk models 
were developing using machine learning with a large number of EHR and administrative database 
variables to estimate risk of suicide, with an area under the curves (AUC) of 0.83 to 0.86.27 The 
team is now updating this tool to add predictors specific to a population of people with OUD to the 
model, including prescription opioid use, opioid dose reduction, opioid discontinuation, and 
medications to treat OUD (R01DA047724). To date, this risk prediction tool has not been 
integrated into routine care processes in large healthcare delivery systems.   
In the NIDA Clinical Trials Network-funded study COMPUTE 2.0 (CTN-0095), our research team 
has developed a clinical decision support (CDS) system that is integrated with the EHR and is 
designed to guide primary care clinicians (PCCs) in the identification, diagnosis and treatment of 
OUD. This non-proprietary tool, coined Opioid Wizard, uses a proven point-of-care CDS platform 
to guide PCCs in screening for OUD and common comorbid conditions, including depression and 
anxiety. Opioid Wizard includes an EHR-based tool that calculates risk of opioid overdose or OUD 
and alerts PCCs to patients at increased risk. It also algorithmically identifies and alerts PCCs to 
patients with OUD diagnoses or a history of opioid overdose. 
In both intervention and control clinics, suicide risk scores will be calculated for all Opioid Wizard-
eligible patients (at high risk of OUD/overdose or diagnosed with OUD) and archive relevant EHR 
data to inform analyses. In intervention clinics, Opioid Wizard will alert PCCs to Opioid Wizard-
eligible patients who are at increased risk of suicide and coach them through use of the Columbia 
Suicide Severity Risk Scale (CSSRS), a structured tool in the EHR that will help PCCs assess 
immediate suicide risk. Based on the resulting CSSRS score, Opioid Wizard will provide EHR 
links for risk-based referrals and follow-up recommendations, including care as usual, routine or 

emergent referral to behavioral health, or transportation to the emergency department for further 
assessment. 
Specific Aims: 
Aim 1. Evaluate the impact of Opioid Wizard + Suicide Risk Prediction on suicide 
assessment process measures. 
H1: Opioid Wizard-eligible patients (patients with OUD or at elevated risk of OUD/overdose) with 
elevated suicide risk in intervention clinics will have higher rates of completed CSSRS 
assessments than similar patients in control clinics.   
Aim 2. Examine the impact of Opioid Wizard + Suicide Risk Prediction on patient 
engagement in mental health care.   
H2: Opioid Wizard-eligible patients with elevated suicide risk in intervention clinics will have higher 
rates of engagement in their outpatient mental health care than similar patients in control clinics.    
 E. Study Design 
 1. Overview of Study Design. When a patient is at elevated risk of suicide, the PCC will be 
prompted by Opioid Wizard to complete the CSSRS, easily available to all PCCs in the EHR 
and saved as discrete data elements. Risk-based (depending on CSSRS score) referral and 
follow-up recommendations for suicide prevention will be given, with specific care 
recommendations ranging from care as usual (very low risk) to referral to behavioral health for 
evaluation and safety planning (moderate to high risk) to immediate evaluation in the emergency 
department and potential inpatient admission (very high risk), building on workflows developed 
for use by care managers in in our recently completed suicide prevention trial of over 19,000 
people at elevated risk of suicide.28  
The MHRN suicide risk models will be programmed into the EHR, a rigorous process that will 
take approximately 6 months. This process includes building the model in a testing environment 
in the EHR, testing the model with fictitious patients in a EHR testing environment and 
conducting chart audits, revising as needed, testing the model in a different EHR testing 
environment with real patient data, revising as needed, testing the model by running it silently 
in the EHR production environment and conducting chart audits, and revising as needed. This 
is followed by testing in the EHR production environment with 5-15 physicians in 1-2 pilot clinics. 
Prior to the go-live date for the suicide risk calculator, training on use and interpretation of the 
suicide risk model and the CSSRS will be provided to all PCCs and their rooming staff in 
intervention clinics. Training for control clinics will be separate and will provide training on the 
use of the CSSRS. 
2. Duration of Study and Visit Schedule. In the parent trial, HealthPartners primary care 
clinics (n=30) will be randomized to receive or not receive access to the OUD-CDS. In this 
supplemental study, the clinics receiving access to the OUD-CDS (n=15) will be further 
randomized (1:1) to receive or not receive access to the MHRN suicide risk models and 
associated CDS. PCCs in HealthPartners clinics with CDS access will have access to the main 
OUD-CDS intervention for up to 30 months from date of implementation.  PCCs in 
HealthPartners clinics randomized to the suicide model intervention will have access to the 
suicide supplement intervention for up to 12 months from date of implementation. 

In Suicide Supplement control clinics, the OUD-
CDS will run silently in the background over the 
same 
time 
periods, 
collecting 
data 
without 
displaying. There is no study-determined visit 
schedule; rather, patient visits will be jointly 
determined by the patient and PCC. 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. 
F. Study Population 
1. Primary Care Clinics: For this supplemental 
study, study clinics will include all 15 HealthPartners primary care clinics randomized to the 
intervention in the parent study (COMPUTE 2.0); half of these clinics will be randomized to 
receive access to the suicide risk models and alerts, and half will not.  Each primary care clinic 
has at least 3 eligible PCCs and 50 adult patients who meet inclusion criteria for the parent 
study (see Section C.6 in the COMPUTE 2.0 Protocol). 
 
2. Primary Care Clinicians (PCC): To be eligible for inclusion in the parent study (and therefore 
also this supplemental study), a PCC must practice at least 0.5 full-time equivalent at a study-
eligible primary care clinic and be a family physician, general internist or adult-care non-obstetric 
nurse practitioner or physician assistant. PCCs are study-eligible regardless of whether they 
are waivered to prescribe buprenorphine. PCCs in the intervention clinics will be encouraged 
but not required to use Opioid Wizard with eligible patients; the decision to use or not use the 
CDS at a given clinical encounter is up the PCC at each clinical encounter.  
Consent: We will request a waiver of written informed consent from the IRB for PCCs for 
the intervention, because the CDS is based on current national standards of care and does 
not make treatment recommendations that are not accepted as community standards of 
care, and because consenting PCCs would compromise the external validity of the study by 
introducing selection effects. Our IRB has granted such waivers for similar studies, including 
the parent study.  
3. Patients: To be eligible for inclusion in the parent study (and therefore also this supplemental 
study), a patient must: (a) be aged 18-75 years, inclusive; (b) have an OUD diagnosis, be 
prescribed an active MOUD, or be identified by the opioid risk models as being at high risk of 
OUD or overdose; and (c) be identified at high risk of suicide by the suicide risk models. There 
are no exclusions for pregnancy, lactation, or mental health or behavioral health diagnoses. The 
first visit at which all eligibility criteria are met will be the index visit. Patients who meet the 
following criteria at their index visit will be excluded and not be exposed to the intervention: (a) 
active parenteral chemotherapy within the last year; (b) stage 4 or equivalent cancer diagnoses; 
or (c) enrolled in hospice or palliative care programs. Patients will accrue in the first 9 months 
of the 12 month intervention period to allow for at least 3 months of data collection for every 
patient.  All PCCs and eligible patients will be attributed to the clinic at which they practice (PCC) 
or their index visit took place (patients) and to the arm to which their clinic is randomly assigned. 
Consent: We will request and anticipate receiving a waiver of written informed consent from 
the IRB for patient participation because the study is minimal or less than minimal risk 
Table 1. Summary of Clinic Access & Training 
Suicide Supplement 
Intervention Clinics 
Suicide Supplement 
Control Clinics 
EHR alerts to patients 
at elevated risk of 
suicide per the MHRN 
suicide risk models 
No EHR alerts 
EHR access to the CSSRS that includes risk-
based referral and follow-up recommendations for 
care based on CSSRS score 
Training on use of the CSSRS via live and recorded 
webinars and follow-up handouts 

compared to the risk associated with any primary care encounter, and because the study 
could not practically be conducted if written informed consent were required to be obtained 
in the context of busy community-based primary care clinics. We have requested and 
received such waivers in several similar prior studies, including the parent study. Patients 
who have requested non-participation in research studies 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 or for suicide attempts or deaths, 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 are housed on a web platform that interacts with the EHR to pull 
data elements to run risk equations and determine patient eligibility.  Separate risk models for 
OUD/overdose and suicide attempt/death will be used.  
G. Study Procedures 
1. Index Visit 
There is no study-determined visit schedule. Patient visits with their PCCs 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. 
2. Treatment/Intervention 
The intervention is the availability of the suicide prevention CDS in approximately half of the 
parent study’s intervention primary care clinics. 
3. Premature Withdrawal of Participants 
Once randomized, all primary care clinics are anticipated to remain enrolled for the duration 
of the study. All PCCs 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. 
4. Follow-Up 
There is no study-determined visit schedule. Patient visits with their PCCs 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. 
H. Data Collection and Management 
1. Measures of Primary and Secondary Outcomes 
Primary and secondary outcomes will be assessed using the data collected from the EHR 
via the OUD-CDS and from EHR (Clarity) data pulls.  
Primary outcome measures include: 
a) Columbia Suicide Severity Rating Scale (CSSRS): frequency of completion, distribution of 
CSSRS scores, and Behavioral Health or ED referrals due to CSSRS scores 
b) Frequency and continuity of primary care and mental health visits (post-index visit) 
c) Identification of fatal and non-fatal suicide attempts, using ICD-10 codes 
d) Identification of Opioid overdose, using ICD-10 codes 

2. Demographics Form 
We will collect age, gender, race/ethnicity, years of practice and medical specialty (primary 
care vs. internal medicine) for PCC 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. 
3. Contact Information 
We will keep a list of participating primary care clinics, their administrative leaders and their 
PCCs on a secure server at HealthPartners. This list will include the PCC name, primary 
care clinic name, phone number of the clinic and provider email address.  
4. 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 both OUD and suicide 
prevention. Prior to implementation, we will train all intervention PCCs 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 PCCs 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 PCC to answer the question, discuss steps 
taken to address the issue, or gather additional information if needed to further trouble-
shoot. PCCs 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 PCCs 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. 
I. Randomization 
In the parent trial, HealthPartners primary care clinics (n=30) will be randomized to receive or not 
receive the intervention. In this supplemental study, simple randomization will allocate the 
intervention clinics (n=15) approximately evenly to receive or not receive access to the MHRN 
suicide risk models and associated CDS.  
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. 
J. Analysis 
1. Study Hypotheses 
H1: Opioid Wizard-eligible patients (patients with OUD or at elevated risk of OUD/overdose) 
with elevated suicide risk in intervention clinics will have higher rates of completed CSSRS 
assessments than similar patients in control clinics.   

H2: Opioid Wizard-eligible patients with elevated suicide risk in intervention clinics will have 
higher rates of engagement in their outpatient mental health care than similar patients in 
control clinics.    
The hypotheses for this supplemental study predict that the Opioid Wizard + Suicide Risk 
Prediction intervention will increase (a) the likelihood that Opioid Wizard-eligible patients 
with elevated suicide risk are assessed at the index visit for immediate suicide risk using the 
CSSRS (H1); and (b) the rate of post-index primary care visits with a mental health diagnosis 
or with a behavioral health clinician (H2). These hypotheses will be tested using generalized 
linear mixed models so that each outcome may be estimated among intervention relative to 
control clinics while accounting for patient outcomes clustered within randomized clinics via 
a random clinic intercept. Both outcomes will likely be normalized with a Poisson-Normal 
link function, although the distribution of visits may warrant using a Negative Binomial-
Normal link.  
2. Projected Number of Clinics 
We anticipate that the 15 intervention clinics from the parent study will be included in this 
study and will be randomized to receive or not receive the suicide prevention module. 
3. Statistical Power 
Based on preliminary data, 1619 diagnosed (median=89, range=39-267 per clinic) and 3349 
at-risk (median=41, range=19-129) patients were seen in the clinics eligible for the parent 
study over the course of one year for a total of 4968 (median=130, range=66-387) OUD-
CDS-eligible patients. Assuming that 5%, 10% or 20% of approximately 2500 patients are 
evaluated and considered at high risk for suicide, we estimate that 125 (2500 * 5%), 250 or 
500 patients will be eligible for this study over one year of accrual. 
A power analysis estimated the minimum detectable risk ratio for CSSRS and visit rates in 
intervention relative to control clinics. It relied on data-informed assumptions regarding the 
number of randomized clinics (n=15) and eligible patients per clinic (pts/clin =8, 16, 33); a 
range of clinic intraclass correlations consistent with those observed for other process 
measures at HealthPartners (ICCclin = 0.01, 0.03, 0.05); and outcome likelihood estimates 
in control clinics (screening=1%, 3%, 5%; visit rate=2, 3, 4/year).  
Assuming 3% of control clinic patents are screened for suicide risk, the analysis will be 
powered (power=0.80, α2=0.05) to detect an outcome should at least 14.2% (ICCclin=0.01, 
33 pts/clin, risk ratio = 4.72) to 65.0% (ICCclin=0.05, 8 pts/clin, RR=21.66) of intervention 
clinic patients be screened. The comparable range of detectable differences for outcomes 
with a 5% screening rate among control clinic patients is 16.8% (RR=3.36) to 54.8% 
(RR=5.80).  
Power for Aim 2 analyses is not as sensitive to sample size assumptions. Under the most 
generous assumptions (ICCclin= 0.01, 33 pts/clin), small increases in visits rates (2.4 vs. 
2.0, RR=1.22; 4.6 vs. 4.0, RR=1.15) will be detectable. Larger but still attainable increases 
(3.0 vs. 2.0, RR=1.49; 5.3 vs. 4.0, RR=1.33) will be detectable under the most conservative 
of assumptions (ICCclin=0.05, 8 pts/clin).  
4. Exploratory Analyses 
In exploratory analyses, we will also examine (a) intervention effects on outcomes such as 
depression screening via the Patient Health Questionnaire (PHQ9), suicide attempt, opioid 
overdose, emergency department visits and hospitalizations, and continuity of care; and (b) 
treatment effect heterogeneity among patients with OUD who are vs. are not prescribed 

OUD medications, and patients with vs. without diagnosed comorbid mental health 
conditions. Results of this work will provide a workable prototype for timely provision of 
critically important suicide prevention for patients at risk for or diagnosed with OUD or opioid 
overdose.   
K. 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. 
L. 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. PCCs can choose 
to follow or not follow the guidance of the CDS at any given time in any given patient encounter. 
PCCs 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 research 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 PCC who is unfamiliar or uncomfortable with OUD or suicide 
risk assessment, use of the CDS will likely make care safer by providing suggestions to screen 
and assess patients using validated tools, and by encouraging referrals when patients are 
classified as high risk. 
M. Participant and Data Confidentiality 
Participant confidentiality and privacy is strictly held in trust by the participating investigators, their 
staff, and the funding agency, and will be maintained in accordance with all applicable federal 
and/or state regulations and laws. 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.  
Participant records will be held confidential by the use of study codes for identifying participants, 
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 at least three years after 
database lock or longer if required by the IRB. 
N. Safety Reporting 
We do not anticipate that a Data and Safety Monitoring Board (DSMB) will monitor this study. We 
will report any unanticipated safety events to the HealthPartners IRB, as required. 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 or mental health treatment in primary care, but rather are attempting to help PCCs 
achieve this standard of care. PCCs will be trained that, as with other clinical decision tools, the 

OUD-CDS and the suicide risk module are meant to supplement but not supersede clinical 
judgment. PCCs will be able to choose to follow or to not follow the guidance of the CDS at any 
given time for any given patient. PCCs will be asked to use the Feedback Tab within the tool to 
let the team know of questions, potential errors, or 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. 
O. Study Timeline 
The study timeline began on October 1, 2020. Trial preparation will include obtaining Institutional 
Review Board (IRB) approval, building and testing the Suicide Risk Models, and training 
clinicians. Active intervention and data collection will continue for 12 months, including at least 3 
months follow-up per patient.  
Study Timeline 
2020-2021 
2021-2022 
Quarter Oct-
Dec
Jan-
Mar
Apr-
Jun
Jul-
Sep
Oct-
Dec
Jan-
Mar
Apr-
Jun
Jul-
Sep
Phase 1: Development, Testing, Training 
 
 
 
 
 
 
 
 
Finalize protocol, obtain IRB approval 
 
 
 
 
 
 
 
 
Build, install and test the MHRN suicide risk calculator in the 
EHR 
 
 
 
 
 
 
 
 
Clinic trainings 
 
 
 
 
 
 
 
 
Phase 2: Active Intervention 
 
 
 
 
 
 
 
 
Go live & primary data collection 
 
 
 
 
 
 
 
 
Patient recruitment (allowing for >3 months follow-up per 
patient) 
 
 
 
 
 
 
 
 
Monitor use rates, provide clinic- and PCC-level use reports  
 
 
 
 
 
 
 
Update, troubleshoot algorithms as needed 
 
 
 
 
 
 
 
 
Phase 3: Analysis and Reporting 
 
 
 
 
 
 
 
 
Preliminary reports of available data to funder 
 
 
 
 
 
 
 
 
Consolidate/analyze final data  
 
 
 
 
 
 
 
 
Dissemination activities, submit manuscript for publication 
 
 
 
 
 
 
 
 
 
P. Trial Registration, Publication, Dissemination and Data Sharing 
1. Trial Registration. In keeping with NIH policy, this trial will be registered at ClinicalTrials.gov, 
and results information from this trial will be submitted to ClinicalTrials.gov.  
2. Publication policy. We will publish results in peer-reviewed journals.  The planning, 
preparation and submission of publications will follow the policies of the Publications Committee 
of the CTN. 
3. Disseminating results to the public. As a result of our previous and ongoing OUD and 
mental health research, we have established communication channels with key stakeholders in 
our health system, as well as with external stakeholders, including the NIDA CTN, MHRN, the 
Midwest Research Network, and the Health Care Systems Research Network. We anticipate 
that our findings will be of significant interest to these groups, and we will disseminate our 
findings, methods and resources. We will share our findings immediately through presentations 
at local and national meetings. We will publish our findings in peer-reviewed journals and 
communicate our findings to public media outlets. 
4. Data Sharing. The study investigators will share a limited de-identified data set used for 
primary outcome analysis with NIDA for NIDA’s Data Share website. The CTN’s Data and 
Statistics Center (DSC) can assist study investigators with providing the data set to the 
designated party to ensure de-identification, and for posting, storing, and archiving on NIDA’s 

Data Share website. Data Share is an online repository of data from studies funded by the NIDA 
and is located at: https://datashare.nida.nih.gov/. 
 
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Grella CE, Karno MP, Warda US, Niv N, Moore AA. Gender and comorbidity among 
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2. 
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