Leveraging Digital Medicine to Support Providers and Their Patients in Managing Serious Mental Illness.

Recent national statistics show that an estimated 11.2 million American adults live with serious, chronic forms of mental illness. The burden of mental illness is considerable for these individuals, their families, and communities. Effective medical treatment for serious mental illness (SMI) requires a patient-centered approach that engages patients in shared decision-making and supports the therapeutic alliance. Information regarding medication-taking behavior is essential for making treatment decisions, particularly in the instance of suboptimal therapeutic response. However, the evidence suggests that the probability of nonconformity with prescribed medication is elevated for individuals with SMI and that clinicians often overestimate their patients' adherence to medication-taking behaviors. In patients with SMI, unidentified problems with adherence may lead to unnecessary changes in treatment regimen and increased rates of hospitalization. Although various approaches have been used to assess medication ingestion with greater accuracy, none are without limitation. The growing field of digital medicine has introduced tools that engage patients for clinical purposes, gather and organize clinical data, and help measure care quality. Physician surveys show an appreciable increase in physician adoption of digital clinical tools, and studies suggest that a significant population of patients with SMI own and are comfortable using digital devices and tools. Digital tools designed to help people with SMI have the potential to transform the support and care available to people with mental health disorders, bridging a technology gap in mental health services.

System-Level Variation in Multiple Sclerosis Disease-Modifying Therapy Utilization: Findings From the Multiple Sclerosis Continuous Quality Improvement Research Collaborative.

BACKGROUND: The Multiple Sclerosis Continuous Quality Improvement (MS-CQI) Collaborative is the first multicenter improvement research collaborative for multiple sclerosis (MS). The main objective of this study is to describe baseline system-level variation in disease-modifying therapy (DMT) utilization across 4 MS centers participating in MS-CQI. METHODS: Electronic health record data from the first year of the 3-year MS-CQI study were analyzed. Participants were adults ≥ 18 years with MS presenting to any of the 4 MS-CQI centers. DMT utilization was categorized into oral, infusion, and injection types. Multinomial logistic regression was used to investigate associations between centers and DMT utilization. RESULTS: Overall, 2,029 patients were included in the analysis. Of those patients, 75.1% were female, mean age was 50 years, and 87.4% had relapsing-remitting MS. Overall, 32.7% were on an oral DMT, 23.5% on an infusion DMT, and 43.9% on an injection DMT. Overall, statistically significant differences (p < 0.01) were observed across centers for proportions of patients who received oral, infusion, and no DMTs. There were also overall significant differences (p < 0.01) across MS types for proportions of encounters who received oral, infusion, injection, no DMTs, and mean age varied significantly across centers. CONCLUSION: System-level effects on MS treatment and outcomes have not been previously studied and our findings contribute initial evidence concerning system-level variation in DMT utilization. Results suggest system-level variation in DMT utilization (ie, after adjusting for individual level factors, MS center or location of care a person with MS engages in care influences DMT treatment choices), resulting in a lack of standardization in DMT management. Continued research and improvement efforts targeting system-level performance could improve outcomes for people with MS.

The Evolution of Disease State Management: Historical Milestones and Future Directions.

Twenty-five years ago, the Journal of Managed Care Pharmacy introduced its readers to disease state management, which attempted to break the siloed culture of the U.S. health care system. Disease state management has been transformed, in part, to population health management. This shift was marked by 3 main inflection points: the rise of the web-enabled smartphone, the Patient Protection and Affordable Care Act (ACA), and the adoption of artificial intelligence (AI). The introduction of smartphones filled the communication gap through improved patient engagement and accessible mobile applications, giving patients access to their clinical data. In addition, through the ACA, bundled payment models moved away from a volume-based to a value-based payment approach and attempted to incorporate population health concerns, such as the social determinants of health. The advancement of AI will allow the health care system to collect comprehensive health data and to predict the population at higher risk. Despite these advancements, some challenges from 25 years ago remain, yet rapid technology advancements may expedite the next wave of change. DISCLOSURES: No funding contributed to the writing of this article. The authors have nothing to disclose with respect to research, authorship, and/or publication of this article.

Perceived Needs for Adolescent Mental Health in an Urban Community.

INTRODUCTION: Stressors in urban communities are detrimental to adolescents' psychological health. Key factors for success are a community-academic partnership in which researchers and stakeholders in the community work together on program development and research practices. This study elicited students', parents', and teachers' perceived needs for psychological well-being in urban-dwelling adolescents. METHODS: Focus groups were conducted with teachers, family members, and students in an urban middle school. Individuals who did not speak English were excluded. Focus group interviews were recorded and transcribed and underwent content analysis to identify key themes. Two investigators independently reviewed and coded the data, with a third expert available if there was disagreement. RESULTS: Six focus groups, two from each stakeholder group, were conducted with a total of 29 participants. Approximately 70% of participants were female, ranging in age from 11 to 68 years. Participants were primarily African American (n = 22), and the remainder were multiracial (n = 4), White (n = 2), and Latino (n = 1). Emergent themes were educational support, social skills, and community landscape. DISCUSSION: Participants identified gaps and approaches to education and clinical care, strengthening social skills, and changing the community landscape as possible effective targets for future interventions.