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Current CTN HSN-led studies

For information on CTN studies led by other nodes, click here.

Funded in 2016:

Katharine Bradley

PROUD Trial (Primary Care Opioid Use Disorder CTN 0074)
Katharine Bradley, PI

The US is facing an epidemic of opioid use disorders (OUDs). Treatment with medications markedly improves outcomes for OUDs, but OUDs remain under-diagnosed and under-treated. In Massachusetts, a nurse-based collaborative care model of OUD primary care treatment was used to increase 1) the number of patients who initiated OUD treatment with medications and 2) persistence of OUD treatment, known to improve health outcomes for patients with OUDs. In the PROUD trial, we will test whether the Massachusetts model of OUD treatment in primary care, compared to usual primary care increases the number of patients who receive medication treatment for OUDs, and/or increase the persistence of OUD treatment in those who initiate treatment, in medical settings in 6 other states. All data will be obtained from electronic health records, claims, and other secondary data sources. Phase 1 of the PROUD trial will evaluate OUD diagnosis and treatment across 11 health care systems, and in Phase 2 we will field the cluster randomized trial to compare the Massachusetts model to usual care.


Constance Weisner 

Examine Patient and System-Level Factors Associated with HEDIS AOD-IET Measure Performance across Health Systems (CTN-0072)
Constance Weisner, PI

Access to care for alcohol and drug disorders (AOD) is problematic in the U.S.—only 10% of patients receive recommended care, and most of it is in specialty programs. Little is known about the HEDIS AOD Initiation and Engagement in Treatment (IET) measures and factors related to higher performance, but understanding their scope in identifying problems, referral to treatment, and engagement in AOD treatment (whether within primary care or in specialty AOD care) could be a first step for improving AOD care nationwide. In seven health plans, this study will examine how performance on the AOD initiation and engagement measures vary by characteristics of the eligible population; how performance on the AOD initiation and engagement measures vary by system characteristics; and structural differences and policies within each region and for specific facilities which may explain variations in performance on the HEDIS AOD Initiation and Engagement measures.

Funded in 2015:

Katharine Bradley 

Evaluation of Drug Screening Implementation in Primary Care (CTN-0065)
Katharine Bradley, PI

Recent trials of screening and brief intervention for drug use have no demonstrated benefit compared to screening alone. However, the value of screening for drug use, compared to no screening, has not been evaluated. Screening for drug use may identify patients with drug use disorders who might need more intensive treatments than brief intervention. In states where marijuana use is now legal for recreation, as well as medical uses, clinicians want to be aware of and assess risks of marijuana use. Further, little is known about the predictive validity of screens for marijuana and/or drug use/misuse for subsequent adverse health outcomes. To that end, this study seeks to evaluate implementation of drug screening , among all Group Health patients who seek care in the Group Health primary care clinics. to: 1) describe rates of drug and marijuana screening, and positive screens, as well as barriers and facilitators to population-based screening; 2) assess changes in rates of assessment and identification; and 3) assess whether drug and marijuana use is associated with increased subsequent urgent care, ED, and hospitalization.


Cynthia Campbell 

Kaiser Virtual Data Warehouse - Prescription Opioid Users (CTN-0061)
Cynthia Campbell, PI

Analyzing data stored in Kaiser Permanente Northern California's Virtual Data Warehouse, this study will assess adult new and long-term prescription opioid users in a large integrated health care delivery system to identify treatment patterns, risk factors, and associated outcomes over time, and compare them to matched controls not using an opioid in 2011. This will allow us to describe the differences between opioid users to non-users at a given point in time. We will be able to compare the two samples with more rigor, and learn how opioid users are different from non-users.

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