(118) The UCSF SBIRT Collaborative Care Program for SUD: Design, Development, and Implementation

Background &

Introduction: Despite high prevalence rates of at risk substance use and the substantial proportion of untreated patients with substance use disorders (SUD), evidence-based strategies to screen, briefly intervene, and/or provide ongoing treatment have been disappointing. Screening, brief intervention, and referral to treatment (SBIRT) provides a well established process to transform frontline clinical management but adoption and implementation have been slow with lack of treatment options and low patient engagement cited as common obstacles (Vogel, Ramo, Satterfield, 2020). Stepped collaborative care models have been well validated for chronic behavioral conditions such as depression and have more recently been adapted for patients who have SUD (Coventry et al., 2014; Watkins et al., 2017). The UCSF SBIRT Collaborative Care Program (CCP) creates an enterprise-wide SBIRT program that uses a new substance use registry managed by a multidisciplinary care team(AIMS, 2023). This feasibility and acceptability pilot study was used to identify local needs, select implementation strategies, create necessary digital and other infrastructure to promote uptake, and to create a new collaborative care referral destination that could provide holistic interventions including brief cognitive-behavioral therapy. Lessons learned will be used to make iterative improvements and scale implementation to additional clinics using locally validate models (Sullivan…, Satterfield, 2018).

Methods: SBIRT-CCP develops, implements, and evaluates a multidisciplinary, team-based approach to SBIRT in both adult and adolescent primary care. Universal pre-screening occurs annually using evidence-based instruments fully integrated into the electronic health record followed by a more in depth assessment and brief intervention (BI) for individuals deemed at risk. All at-risk individuals are added to a clinical registry managed by patient care coordinators proficient in motivational enhancement and harm reduction. Patients are regularly re-assessed and triaged to varying intensities of collaborative care follow-up based on degree of risk, unmet social needs, patient readiness, and local clinic and treatment resources. Qualifying patients are referred to a centralized “collaborative care team” comprised of behavioral health providers, social workers, psychiatric residents, nurse practitioners, and addiction medicine physicians for more in depth assessments, brief treatment (BT), pharmacotherapy, and/or facilitated referrals to specialty care. The SBIRT CCP and clinical processes were developed and tested by the UCSF Office of Population Health in one adolescent and one adult primary care clinic in collaboration with local SBIRT experts, implementation scientists, internal clinical champions, and community members. Using continuous feedback for iterative improvements, SBIRT CCP will be sequentially implemented in 4 additional SF adult primary care clinics in 2025.

Results: Following the creation and training of the CCP team along with fully integrated digital tools within the EPIC electronic medical record, a primary care pilot clinic was chosen based on size, diversity, and leadership buy-in. Following needs assessments, qualitative interviews, staff trainings and mock screenings, the SBIRT CCP pilot started 9/2024 with a planned review of all QI performance data collected in 1/2025. During the initial pilot period, n=3,432 patients were seen in the PC clinic. N=1,772 were screened for illicit and prescription drug misuse with the TAPS 1 and TAPS 2 (51.6%). N=2,086 were screened for alcohol use with the AUDIT-C (60.8%). N=195 patients screened positive for at risk drug use and n=55 screened positive for at risk alcohol use. All patients were added to the new electronic registry managed by the SBIRT CCP behavioral health navigators unless removed by their PCP. To further engage and guide PCP’s, best practice alerts were activated for all patients screening positive requiring action on the part of the PCP. PCP’s were supported with EPIC dot phrases and smart sets to facilitate interpretation of screening results, review DSM criteria for SUD, and explore both in session interventions and external referrals. 98% of PCP’s took action and responded to the BPA with only 10% of patients who screened positive being removed from the registry and designated as “do not contact.” All registry patients were called up to 3 times by a behavioral health navigator trained to provide education, harm reduction, and motivational interviewing. Patients who indicated readiness for treatment were presented in the SBIRT CCP case conference where medication, brief treatment, and case management options are discussed. Care coordination notes are sent to the PCP’s along with follow-up plans. At present, 28 patients have been presented in case conference and n=17 have participated in brief treatment. QI data and qualitative feedback are being used to iteratively improve the program and scale to additional UCSF primary care clinics in early 2025.

Conclusion &

Discussion: SBIRT CCP was able to design, implement, and execute universal screening for alcohol and drug use in a pilot primary care clinic. Screening rates fell well below 100% but were seen as notable given this first pass for implementation. Staff noted minimal burden and provided suggestions about including e-visit pre surveys and more resources for non-English speaking patients (who were not included in the pilot). Positive screens for alcohol use were surprisingly low and are currently being explored. PCP’s were highly engaged with the new best practice alert but few did their own screening or an in session brief intervention. The electronic registry was successfully constructed and digital tracking tools have been effective. Overall, the program has been seen as filling a long unmet need and future scale has been encouraged. Future improvements will include inclusion of non-English speaking patients, more rapid review of QI data, developing strategies to promote better patient engagement, and more developed ties with psychiatry and addiction medicine within UCSF.

References: AIMS Center. (2023). Collaborative Care Implementation Guide. University of Washington Department of Psychiatry and Behavioral Sciences, Advancing Integrated Mental Health Solutions (AIMS) Center. https://aims.uw.edu/

Coventry PA, Hudson JL, Kontopantelis E, Archer J, Richards DA, et al. (2014) Characteristics of Effective Collaborative Care for Treatment of Depression: A Systematic Review and Meta-Regression of 74 Randomised Controlled Trials. PLoS ONE 9(9): e108114. doi:10.1371/journal.pone.0108114

O’Sullivan PS, Yuan P, Satre DD, Wamsley M, Satterfield J. A Sequential Implementation Model for Workforce Development: A Case Study of Medical Residency Training for Substance Use Concerns. Teach Learn Med. 2018;30(1):84-94. doi:10.1080/10401334.2017.1314216

Vogel EA, Ly K, Ramo DE, Satterfield J. Strategies to improve treatment utilization for substance use disorders: A systematic review of intervention studies. Drug and Alcohol Dependence. 2020;212:108065. doi:10.1016/j.drugalcdep.2020.108065

Watkins KE, Ober AJ, Lamp K, et al. Collaborative Care for Opioid and Alcohol Use Disorders in Primary Care: The SUMMIT Randomized Clinical Trial. JAMA Intern Med. 2017;177(10):1480. doi:10.1001/jamainternmed.2017.3947