Williams, Mark D.

AbstractPurposeThe Collaborative care model (CoCM) is the leading model for integrating behavioral health into primary care for patients with major depressive disorder (MDD). However, CoCM requires engagement and ongoing participation. We aimed to assess whether two area‐based measures, the area‐deprivation index (ADI) and rurality, were associated with enrollment, participation, and outcomes with CoCM.MethodsThis was an observational analysis of Mayo Clinic patients eligible for CoCM: adults aged ≥18 years, empaneled in primary care, and with a PHQ‐9 of ≥10. We operationalized ADI as quintiles with Q1 being least deprived and Q5 being most deprived and rurality using RUCA codes with two categories: urban and rural. We evaluated enrollment in CoCM, drop out defined by leaving the program early, the count and type of contacts with the care coordinator, and clinical improvement measured using the PHQ‐9.FindingsWe identified 54,030 individuals with 16,532 (30.6%) residing in rural areas and 11,122 (20.6%) residing in the most deprived ADI quintile (Q5). Living in a rural area was associated with lower enrollment in CoCM (–2.3 percentage points [95% confidence interval (CI): –2.5, 2.2]), longer length in CoCM (18.6 days [95% CI: 5.7, 31.5]), more contacts with the care coordinator (1.1 contacts [95% CI: 0.2, 2.0]), and worse response and remission. In contrast, ADI Q5 was only associated with worse response and remission.ConclusionsRurality was associated with lower enrollment, greater engagement, and worse clinical outcomes. More work may be needed to address enrollment barriers for individuals living in rural areas to improve clinical outcomes.

ABSTRACTObjectiveTo build consensus from different stakeholders on the content and digital interactivity of a shared decision making (SDM) tool to guide patient‐clinician collaborative conversations about treatment for bipolar depression.Patients and MethodsThis study was conducted between September 2022 and September 2023. In the first phase, we conducted a narrative review on pharmacological, neuromodulatory, and psychotherapeutic treatments available for bipolar depression. For each option, we assessed treatment effectiveness, side effects, need for clinical monitoring, clinical considerations, and cost. In the second phase, committees comprised of mental health clinicians and people with lived experience with bipolar disorder from a national mood disorders advocacy group identified key features and content to be included in the SDM tool. A thematic analysis of these data then contributed to populate the SDM tool.ResultsTwenty‐one evidence‐based treatment options identified from the narrative review were presented to the four convened committees (clinical, lived experience, peer council, and integrated steering committees) in five meetings. After discussions and thematic analysis, 12 outcomes of interest for each of the therapeutic interventions were delineated for inclusion in a web‐based SDM tool. A detailed description of the development process and SDM tool is provided.ConclusionThis is the first partnership between clinicians and persons with bipolar disorder lived experience charged with the development of a patient‐centered SDM tool to integrate clinical evidence with real‐world clinical practice and patient preferences for use during clinical encounters. Human‐centered design and testing in real clinical encounters will now contribute to refining the instrument and readying it for rigorous evaluation and implementation in practice.

Abstract Background: To describe the process of developing an evolving database for Mayo Clinic primary care patients who screen positive for depression. The databases will support a broad use of these data for current and future quality improvement and research efforts. The description of their development will serve as an example for other institutions attempting to create similar data resources. Methods: The adult database (patients aged ³ 18) has data from 2007 and the adolescent database (patients aged 12 to < 18) from 2011. To be included, a patient had to be eligible for collaborative care model as a primary care patient with at least moderate symptoms of unipolar depression. The patient did not have to be enrolled in collaborative care model. The main domains of measurement are demographics, social determinants of health, mental health and substance abuse conditions, other comorbidities, interaction with collaborative care model, and questionnaire results. The data is being continuously updated as new data becomes available. Results: The adult database currently includes 117,619 unique patients with a mean age of 44.7 years, and is 66.4% female, and 88.1% non-Hispanic white. The adolescent database includes 14,684 unique patients with a mean age of 14.8 years, is 66.7% female, and 79.7% non-Hispanic white. Conclusions: These large, longitudinal, and evolving databases are a key step towards developing a learning environment to improve quality of care and conduct population-based research for patients with depression in primary care settings.

Abstract Integrated behavioral health is a population-based approach that acknowledges the chronic nature of most mental illnesses and the need for services beyond those delivered in face-to-face visits. These services have been referred to by different and confusing names with over 40 definitions of care coordination concepts in the literature. Kilbourne et al. in a recent article in this journal divided these tasks into three groups: care coordination, care management and case management with associated definitions provided as used in the veterans affairs system. In this commentary, while drawing on over a decade of experience in implementing care management models in the Mayo clinic system of care, I will suggest we need to be even more specific with these definitions. I propose these terms be linked to critical and measurable tasks in the management of chronic conditions, thus allowing those administrating or researching these interventions to better assess fidelity, processes and outcomes when a model is applied to a population of patients with chronic conditions in an integrated setting.