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Introduction Methods Results Conclusions Psychiatric measurement‐based care (MBC) can be more effective than usual care, but health systems face implementation challenges. Achieving attitudinal alignment before implementing MBC is critical, yet few studies incorporate perspectives from multiple stakeholders this early in planning. This analysis identifies alignment and themes in pre‐implementation feedback from patients, providers, and administrators regarding a planned MBC implementation in a safety net psychiatry clinic.We used interview guides informed by Conceptual Model of Implementation Research to gather qualitative pre‐implementation attitudes about perceived Appropriateness, Acceptability, and Feasibility of an MBC measure (Computerized Adaptive Test—Mental Health; CAT‐MH) from five patients, two providers, and six administrators. We applied rapid qualitative analysis methods to general actionable feedback for department leadership still planning implementation. We used a multistep process to generate thematic findings with potential relevance for other similar mental health settings.There was more attitudinal alignment across stakeholder groups regarding MBC's Acceptability and Feasibility than its Appropriateness. All three groups agreed that it was important to contextualize MBC for patients and providers, anticipate MBC's impact on patient–provider relationships, and consider the system's capacity to respond to patient needs unearthed by CAT‐MH before implementation began. Our thematic analysis suggests: (1) Introducing MBC may complicated patient–provider relationships by adding a new and potentially conflicting input for decision making, that is, MBC data, to the more typical inputs of patient report and provider expertise; (2) MBC poses theoretical risks to health equity for safety net patients because of limitations in access to MBC tools themselves and the resources needed to respond to MBC data; and (3) Tension exists between individual‐ and system‐level applications of MBC.Our analysis highlights shifting treatment dynamics, equity considerations, and tension between individual‐ and population‐level needs that our participants anticipated when planning for MBC implementation in a safety net psychiatry clinic. [ABSTRACT FROM AUTHOR]

Introduction: Behavioral measurement‐based care (MBC) can improve patient outcomes and has also been advanced as a critical learning health system (LHS) tool for identifying and mitigating potential disparities in mental health treatment. However, little is known about the uptake of remote behavioral MBC in safety net settings, or possible disparities occurring in remote MBC implementation. Methods: This study uses electronic health record data to study variation in completion rates at the clinic and patient level of a remote MBC symptom measure tool during the first 6 months of implementation at three adult outpatient psychiatry clinics in a safety net health system. Provider‐reported barriers to MBC adoption were also measured using repeated surveys at one of the three sites. Results: Out of 1219 patients who were sent an MBC measure request, uptake of completing at least one measure varied by clinic: General Adult Clinic, 38% (n = 262 of 696); Substance Use Clinic, 28% (n = 73 of 265); and Transitions Clinic, 17% (n = 44 of 258). Compared with White patients, Black and Portuguese or Brazilian patients had lower uptake. Older patients also had lower uptake. Spanish language of care was associated with much lower uptake at the patient level. Significant patient‐level disparities in uptake persisted after adjusting for the clinic, mental health diagnoses, and number of measure requests sent. Providers cited time within visits and bandwidth in their workflow as the greatest consistent barriers to discussing MBC results with patients. Conclusions: There are significant disparities in MBC uptake at the patient and clinic level. From an LHS data infrastructure perspective, safety net health systems may need to address the need for possible ways to adapt MBC to better fit their populations and clinical needs, or identify targeted implementation strategies to close data gaps for the identified disparity populations. [ABSTRACT FROM AUTHOR]