Opiod Use DisorderC-DOSETaPNCT07498322
Chicago Data-driven Opioid Use Disorder Screening, Engagement, Treatment and Planning System
A study testing OUD screening, MOUD and Continuity of care in people with Opiod Use Disorder, run by University of Illinois Chicago at 1 site in United States.
Trial summary
This study, called the Chicago Data-driven Opioid use disorder Screening, Engagement, Treatment and Planning (C-DOSETaP) System, tests a new system of clinical care for patients with opioid use disorder (OUD) across a large health system. The main questions this study aims to answer are: 1. Read more about this study
- Who is it for?
- Ages 16 years and olderHealthy volunteers can take part
- Conditions the study is for
- Opiod Use Disorder
- What is being tested?
- OUD screening, MOUD and Continuity of care
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 271,031 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Jan 2027to 30 Jun 2029
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 16 years and older
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- Participant must be a patient seen at the University of Illinois Hospital and Clinics
- Adults and adolescents age 16 or older
Who cannot join
- Children younger than age 16
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site
University of Illinois Hospitals and Clinics (UI Health)
Chicago, Illinois, 60608
Niranjan S. Karnik, MD, PhD, 312-273-0185, nkarnik@uic.edu
Neeraj Chhabra, MD, neeraj1@uic.edu
About this study
This study, called the Chicago Data-driven Opioid use disorder Screening, Engagement, Treatment and Planning (C-DOSETaP) System, tests a new system of clinical care for patients with opioid use disorder (OUD) across a large health system.
The main questions this study aims to answer are:
- Does the C-DOSETaP System increase screening for patients with OUD;
- Does the C-DOSETaP System improve continuity of health care for patients with OUD;
- Does the C-DOSETaP System increase use of medications for opioid use disorder; and
- Does the C-DOSETaP System reduce the number of opioid-related deaths in the neighborhoods served.
Read the detailed description
The Chicago Data-driven Opioid use disorder Screening, Engagement, Treatment and Planning (C-DOSETaP) System, tests an innovative approach leveraging healthcare data harmonization, digital tools, and clinical workflows to improve the care for patients with opioid use disorder (OUD) across a large health system serving a population heavily affected by the opioid overdose epidemic. The C-DOSETaP system will implement a diverse set of screening tools across the health systems' numerous clinical domains, improve healthcare engagement and utilization of OUD treatments, and pursue a data-forward approach leveraging electronic health record (EHR) data to track care delivery and engage with patients at risk for treatment dropout or failure.
The investigators hypothesize that implementation of the C-DOSETaP system alongside a locally developed system-level opioid response plan will result in: 1) increased OUD screening rates; 2) improved continuity of care; 3) increased utilization of medications for opioid use disorder (MOUD); and 4) reduced mortality in neighborhoods served by the primary study institution.
Primary Outcomes Three dimensions of OUD treatment and engagement will be assessed as primary outcomes for the study. The investigators will measure: 1) screening rates; 2) continuity of care; and 3) use of MOUD across the health system. Screening rates will be measured as the proportion of all patients with encounters in the health system that have a completed screening for opioid misuse within the preceding 12 months. Continuity of care will be assessed by appointment follow-up and completed referral to the next care site. Use of MOUD will be measured as the number of patients actively on MOUD as a proportion of all patients with documented OUD within the health system as defined by International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes.
Secondary Outcomes The investigators plan to evaluate aggregate impact of interventions and primary measures on OUD mortality reported in neighborhoods served by the primary study institution during the phased stepped wedge rollout across system-associated clinics. The secondary outcomes for this phase include quarterly opioid-related mortality by zip codes served by the primary institution.
- Conditions
- Opiod Use Disorder
- Being tested
- OUD screening, MOUD, Continuity of care
- Keywords
- Opioid Use Disorder (OUD), Natural language processing (NLP), Machine learning (ML), Medications for opioid use disorder (MOUD), health systems, Artificial Intelligence (AI), opioid misuse, Buprenorphine
- Medical subject headings
- Opioid-Related Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
OUD screeningOther
Completed screening for opioid use disorder
MOUDOther
Medication treatment for opioid use disorder
Continuity of careOther
Facilitation of outpatient treatment linkages
| Study group | Role | What they receive |
|---|---|---|
| Patients with OUD | Experimental | Patients with opioid use disorder identified through C-DOSETaP system Receives: Other: OUD screening; Other: MOUD; Other: Continuity of care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of people screened for OUD
Aggregate rate of data-driven OUD screening across the health system
Measured: Rolling measure of annual rates (12 months) measured over the implementation period.
Continuity of care for patients with OUD
Continuity of care will be assessed through appointment follow-up and completion of referral to the next care site within 30 days.
Measured: 30 days and 12 months
Utilization of MOUD across the health system
MOUD use will be measured as the number of patients actively on MOUD as a proportion of all patients within the health system and of those with documented OUD within the health system as defined by International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes.
Measured: Baseline and 12 months
Secondary outcomes (3)
Regional opioid-related mortality
Quarterly opioid-related mortality rate by zip codes served by the primary institution reported to the Illinois Department of Public Health
Measured: Baseline and 12 months
Regional OUD Screening
Quarterly opioid-related screening rates by zip codes served by the primary institution reported to the Illinois Department of Public Health
Measured: Baseline and 12 months
Regional MOUD utilization
Quarterly MOUD utilization rates by zip codes served by the primary institution reported to the Illinois Department of Public Health
Measured: Baseline and 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Mar 2026
- Study start1 Jan 2027 (estimated)
- Primary completion31 Dec 2028 (estimated)
- Study completion30 Jun 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Opiod Use DisorderStudies of the same condition, open and under way.
- More trials run by University of Illinois ChicagoThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- The C-DOSETaP system represents a health system-level approach to OUD screening, treatment engagement, and patient retention, which comprises multiple clinical contexts, including inpatient hospital-based care, emergency care, primary care, and specialist outpatient care. Screening activities across these domains will take advantage of digital AI classifiers using EHR data in the inpatient and emergency settings and self-report measures in the outpatient clinics. Results from the opioid misuse screeners will be integrated into local clinical workflows and data aggregated to a digital dashboard for use by the health system's OUD Command Center (OCC) to track referrals for OUD care, follow-up care, and prescriptions. Automated flags will alert the OCC for signs potentially indicative of patient dropout from OUD treatment including missed appointments by more than 48 hours, missed prescriptions, and and lack of any follow-up data. Flags will trigger outreach by peer-recovery specialists.
- Masking
- None (open label)
- Enrolment
- 271,031 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Illinois Chicago
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute on Drug Abuse (NIDA)
- Responsible party
- Principal investigator, Niranjan Karnik, University of Illinois Chicago
- Investigators
- Michelle Hribar, PhD, Principal investigator, UIC, College of MedicineNeeraj Chhabra, MD, Principal investigator, UIC, College of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07498322
- Sponsor's protocol ID
- 2024-0243
- Other IDs
- 1R61DA057629
- Acronym
- C-DOSETaP
- Status last verified
- Oct 2026
- First submitted
- 13 Mar 2026
- Last updated
- 8 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: A de-identified research dataset will be submitted to NIH data repository per the approved Data Management and Sharing Plan following R33 completion.
Publications
Afshar M, Sharma B, Dligach D, Oguss M, Brown R, Chhabra N, Thompson HM, Markossian T, Joyce C, Churpek MM, Karnik NS. Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study. Lancet Digit Health. 2022 Jun;4(6):e426-e435. doi: 10.1016/S2589-7500(22)00041-3.
PubMed 35623797Shahid U, Parde N, Smith DL, Dickinson G, Bianco J, Thorpe D, Hota M, Afshar M, Karnik NS, Chhabra N. Development and Evaluation of Machine Learning Models for the Detection of Emergency Department Patients with Opioid Misuse from Clinical Notes. medRxiv [Preprint]. 2024 Dec 12:2024.12.11.24318875. doi: 10.1101/2024.12.11.24318875.
PubMed 39711725Chhablani C, Shahid U, Parde N, Muslmani S, Hu H, Thorpe D, Afshar M, Karnik N, Chhabra N. Machine learning models to detect opioid misuse in emergency department patients at triage. Am J Emerg Med. 2026 Jun;104:17-23. doi: 10.1016/j.ajem.2026.02.037. Epub 2026 Feb 26.
PubMed 41785519
Study at a glance
From the registry record, last updated by the sponsor on 8 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Chicago Data-driven Opioid Use Disorder Screening, Engagement, Treatment and Planning System
- ClinicalTrials.gov ID
- NCT07498322
- Acronym / sponsor ID
- C-DOSETaP / 2024-0243
- Conditions
- Opiod Use Disorder
- Keywords
- Opioid Use Disorder (OUD), Natural language processing (NLP), Machine learning (ML), Medications for opioid use disorder (MOUD), health systems, Artificial Intelligence (AI), opioid misuse, Buprenorphine
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 271,031 participants (estimated)
- Lead sponsor
- University of Illinois ChicagoUniversity, hospital or other
- Collaborators
- National Institute on Drug Abuse (NIDA)
- Study start
- 1 Jan 2027 (estimated)
- Primary completion
- 31 Dec 2028 (estimated)
- Study completion
- 30 Jun 2029 (estimated)
- First posted
- 27 Mar 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study, called the Chicago Data-driven Opioid use disorder Screening, Engagement, Treatment and Planning (C-DOSETaP) System, tests a new system of clinical care for patients with opioid use disorder (OUD) across a large health system.
The main questions this study aims to answer are:
- Does the C-DOSETaP System increase screening for patients with OUD;
- Does the C-DOSETaP System improve continuity of health care for patients with OUD;
- Does the C-DOSETaP System increase use of medications for opioid use disorder; and
- Does the C-DOSETaP System reduce the number of opioid-related deaths in the neighborhoods served.
Detailed description
The Chicago Data-driven Opioid use disorder Screening, Engagement, Treatment and Planning (C-DOSETaP) System, tests an innovative approach leveraging healthcare data harmonization, digital tools, and clinical workflows to improve the care for patients with opioid use disorder (OUD) across a large health system serving a population heavily affected by the opioid overdose epidemic. The C-DOSETaP system will implement a diverse set of screening tools across the health systems' numerous clinical domains, improve healthcare engagement and utilization of OUD treatments, and pursue a data-forward approach leveraging electronic health record (EHR) data to track care delivery and engage with patients at risk for treatment dropout or failure.
The investigators hypothesize that implementation of the C-DOSETaP system alongside a locally developed system-level opioid response plan will result in: 1) increased OUD screening rates; 2) improved continuity of care; 3) increased utilization of medications for opioid use disorder (MOUD); and 4) reduced mortality in neighborhoods served by the primary study institution.
Primary Outcomes Three dimensions of OUD treatment and engagement will be assessed as primary outcomes for the study. The investigators will measure: 1) screening rates; 2) continuity of care; and 3) use of MOUD across the health system. Screening rates will be measured as the proportion of all patients with encounters in the health system that have a completed screening for opioid misuse within the preceding 12 months. Continuity of care will be assessed by appointment follow-up and completed referral to the next care site. Use of MOUD will be measured as the number of patients actively on MOUD as a proportion of all patients with documented OUD within the health system as defined by International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes.
Secondary Outcomes The investigators plan to evaluate aggregate impact of interventions and primary measures on OUD mortality reported in neighborhoods served by the primary study institution during the phased stepped wedge rollout across system-associated clinics. The secondary outcomes for this phase include quarterly opioid-related mortality by zip codes served by the primary institution.
Study design
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- The C-DOSETaP system represents a health system-level approach to OUD screening, treatment engagement, and patient retention, which comprises multiple clinical contexts, including inpatient hospital-based care, emergency care, primary care, and specialist outpatient care. Screening activities across these domains will take advantage of digital AI classifiers using EHR data in the inpatient and emergency settings and self-report measures in the outpatient clinics. Results from the opioid misuse screeners will be integrated into local clinical workflows and data aggregated to a digital dashboard for use by the health system's OUD Command Center (OCC) to track referrals for OUD care, follow-up care, and prescriptions. Automated flags will alert the OCC for signs potentially indicative of patient dropout from OUD treatment including missed appointments by more than 48 hours, missed prescriptions, and and lack of any follow-up data. Flags will trigger outreach by peer-recovery specialists.
| Arm | Type | Receives |
|---|---|---|
| Patients with OUD | Experimental | Other: OUD screening, Other: MOUD, Other: Continuity of carePatients with opioid use disorder identified through C-DOSETaP system |
Who may qualify
- Ages
- 16 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Participant must be a patient seen at the University of Illinois Hospital and Clinics
- Adults and adolescents age 16 or older
Key exclusion criteria (1 listed)
- Children younger than age 16
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| OUD screeningCompleted screening for opioid use disorder | Other | Patients with OUD |
| MOUDMedication treatment for opioid use disorder | Other | Patients with OUD |
| Continuity of careFacilitation of outpatient treatment linkages | Other | Patients with OUD |
Primary outcome
Number of people screened for OUD
Time frame: Rolling measure of annual rates (12 months) measured over the implementation period.
Aggregate rate of data-driven OUD screening across the health system
Continuity of care for patients with OUD
Time frame: 30 days and 12 months
Continuity of care will be assessed through appointment follow-up and completion of referral to the next care site within 30 days.
Utilization of MOUD across the health system
Time frame: Baseline and 12 months
MOUD use will be measured as the number of patients actively on MOUD as a proportion of all patients within the health system and of those with documented OUD within the health system as defined by International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes.
3 secondary outcomes
Regional opioid-related mortality
Time frame: Baseline and 12 months
Regional OUD Screening
Time frame: Baseline and 12 months
Regional MOUD utilization
Time frame: Baseline and 12 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Oct 2026.
- Background: PubMed 35623797Afshar M, Sharma B, Dligach D, Oguss M, Brown R, Chhabra N, Thompson HM, Markossian T, Joyce C, Churpek MM, Karnik NS. Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study. Lancet Digit Health. 2022 Jun;4(6):e426-e435. doi: 10.1016/S2589-7500(22)00041-3.
- Background: PubMed 39711725Shahid U, Parde N, Smith DL, Dickinson G, Bianco J, Thorpe D, Hota M, Afshar M, Karnik NS, Chhabra N. Development and Evaluation of Machine Learning Models for the Detection of Emergency Department Patients with Opioid Misuse from Clinical Notes. medRxiv [Preprint]. 2024 Dec 12:2024.12.11.24318875. doi: 10.1101/2024.12.11.24318875.
- Background: PubMed 41785519Chhablani C, Shahid U, Parde N, Muslmani S, Hu H, Thorpe D, Afshar M, Karnik N, Chhabra N. Machine learning models to detect opioid misuse in emergency department patients at triage. Am J Emerg Med. 2026 Jun;104:17-23. doi: 10.1016/j.ajem.2026.02.037. Epub 2026 Feb 26.
- The AI.Health4All Center, University of Illinois at ChicagoLink provided by the sponsor.
- Individual participant dataSharing planned: No. A de-identified research dataset will be submitted to NIH data repository per the approved Data Management and Sharing Plan following R33 completion.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Michelle Hribar, PhD principal investigator
UIC, College of Medicine
Neeraj Chhabra, MD principal investigator
UIC, College of Medicine
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing OUD screening, MOUD and Continuity of care in people with Opiod Use Disorder, run by University of Illinois Chicago at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 8 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Neeraj Chhabra, MD ((312) 413-1226, neeraj1@uic.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of people screened for OUD (time frame: Rolling measure of annual rates (12 months) measured over the implementation period.). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07498322, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Oct 2026.