Denise Chang

BACKGROUND Caring Contacts is a low-cost and low-resource suicide prevention intervention that involves sending a series of non-demanding messages that convey care and support. While Caring Contacts is well studied among veteran and adult populations, intervention implementation preferences remain underexplored for adolescents and young adults, especially regarding its delivery in primary care settings. As primary care providers are often constrained in their capacity to respond to the time-sensitive needs of these patients while they wait to be connected to specialty care, identifying if current technologies that can help alleviate these time barriers are acceptable among adolescents and young adult patients is an important next step. OBJECTIVE We evaluated the preferences of adolescents and young adults regarding the delivery of Caring Contacts. We also examined their perspectives on if and how artificial intelligence should be incorporated into the Caring Contacts intervention. METHODS Semi-structured interviews were conducted with 10 adolescents and young adults who reported a history of suicidal thoughts and behaviors. Interview transcripts were analyzed using qualitative coding techniques to evaluate their preferences and identify overarching themes. RESULTS Participants described a preference for receiving Caring Contacts via SMS text messaging, noting its perceived usability as the main contributor to this preference. While patient portals and physical letters were noted as other acceptable delivery methods, challenges to accessing them easily and in a timely manner made them less desirable compared to SMS text messaging. Regarding the incorporation of artificial intelligence into Caring Contacts, participants generally viewed these technologies negatively and with hesitancy describing it as potentially impersonal given the context of suicidality and wanting transparency if it were to be used. CONCLUSIONS This study suggests that adolescents and young adults have distinct preferences for how they want Caring Contacts to be delivered compared to previously studied veteran and adult patient populations. Artificial intelligence may help address primary care provider time and resource constraints, but its implementation must carefully address the concerns raised by adolescents and young adults, particularly around transparency in its use and its perceived impersonal nature.

The collaborative care model (CoCM) is an effective strategy to manage common mental disorders in primary care. Despite the growing adoption of newer CoCM billing codes to support these programs, few studies have investigated the use of these codes. This column evaluated the implementation of CoCM billing codes by comparing clinics using different billing strategies and assessed the impact of CoCM code implementation on revenue and on clinical , process-of-care outcomes. Qualitative data were obtained to understand provider perspectives. The results indicate that CoCM billing code implementation is operationally feasible, does not adversely affect the de-livery of patient care or revenue , is acceptable to providers.

Comments on the article by B. L. Duncan et al (see record 2021-76744-003). As a physician and a Clinical Associate Professor in the Department of Psychiatry and Behavioral Sciences at the University of Washington, the author asks several questions related to this randomized clinical trial. How do the research questions and findings in this paper resonate with your experience as a clinician? What Is one thing you might do differently in your practice after reading this paper? What factors might facilitate or hinder the uptake/implementation of this research in practice? What is one unanswered question that you would like to see pursued as a follow-up to this research? (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Introduction With the growing prevalence of value-based contracts, health systems are incentivized to consider population approaches to service delivery, particularly for chronic conditions like depression. To this end, UW Medicine implemented the Depression–Population Approach to Health (PATH) program in primary care (PC) as part of a system-wide Center for Medicare and Medicaid Innovation (CMMI) quality improvement (QI) initiative. Aim To examine the feasibility of a pilot PATH program and its impact on clinical and process-of-care outcomes. Setting A large, diverse, geographically disparate academic health system in Western Washington State including 28 PC clinics across five networks. Program Description The PATH program was a population-level, centralized, measurement-based care intervention that utilized a clinician to provide remote monitoring of treatment progress via chart review and facilitate patient engagement when appropriate. The primary goals of the program were to improve care engagement and increase follow-up PHQ-9 assessments for patients with depression and elevated initial PHQ-9 scores. Program Evaluation We employed a prospective, observational study design, including commercially insured adult patients with new depression diagnoses and elevated initial PHQ-9 scores. The pilot intervention group, consisting of accountable care network (ACN) self-enrollees (N = 262), was compared with a similar commercially insured cohort (N = 2527) using difference-in-differences analyses adjusted for patient comorbidities, initial PHQ-9 score, and time trends. The PATH program was associated with three times the odds of PHQ-9 follow-up (OR 3.28, 95% CI 1.79–5.99), twice the odds of a follow-up PC clinic visit (OR 1.74, 95% CI 0.99–3.08), and twice the odds of treatment response, defined as reduction in PHQ-9 score by ≥ 50% (OR 2.02, 95% CI 0.97–4.21). Discussion Our results demonstrate that a centralized, remote care management initiative is both feasible and effective for large academic health systems aiming to improve depression outcome ascertainment, treatment engagement, and clinical care.