Practice-Based Implementation Network: Behavioral Health Technician Optimization Pilot Lessons Learned.

INTRODUCTION: Between June 2021 and December 2022, the Practice-Based Implementation (PBI) Network conducted a pilot to study the optimization of behavioral health technicians (BHTs) within military behavioral health (BH) care system specialty BH clinics. Behavioral health technicians are paraprofessionals found in all branches of the military, and with training across a variety of clinic functions. Behavioral health technicians support BH specialty providers in many clinic functions (i.e., administrative, case management, clinical, and outreach). The primary aim of the BHT optimization pilot was to increase BHTs' involvement in clinical care. MATERIALS AND METHODS: Four military BH outpatient clinics participated in the BHT optimization pilot. Participants from the 4 clinics included 12 BHTs, 3 providers, 3 internal facilitators, and 3 dual-role providers/internal facilitators. The pilot asked each clinic to assess their BHT utilization needs, and then barriers and facilitators to BHT optimization were addressed by creating site-specific BHT optimization plans. RESULTS: The degree to which clinic optimization of BHTs impacts provider workload, clinic capability or capacity, and patient access to evidence-based care could not be determined during the BHT optimization pilot. However, individualized clinic BHT optimization plans and strategies appeared to be feasible and acceptable methods for military health system BH clinics to optimize BHTs' clinical skills. Lessons learned from this pilot included that: (1) clinics should consider establishing and maintaining action plans with specific, actionable goals for use of BHTs, and (2) BHT supervision, training, and clinic processes supporting optimization should be prioritized despite time constraints. CONCLUSION: Overall, individualized clinic BHT optimization plans and strategies appear to be feasible and acceptable methods for military health system BH clinics to optimize BHTs' clinical skills.

Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.

Longitudinal clinical studies traditionally require in-person study visits which are well documented to pose barriers to participation and contribute challenges to enrolling representative samples. Remote trial models may reduce barriers to research engagement, improve retention, and reach a more representative cohort. As remote trials become more common following the COVID-19 pandemic, a critical evaluation of this approach is imperative to optimize this paradigm shift in research. The TestBoston study was launched to understand prevalence and risk factors for COVID-19 infection in the greater Boston area through a fully remote home-testing model. Participants (adults, within 45 miles of Boston, MA) were recruited remotely from patient registries at Brigham and Women's Hospital and the general public. Participants were provided with monthly and "on-demand" at-home SARS-CoV-2 RT-PCR and antibody testing using nasal swab and dried blood spot self-collection kits and electronic surveys to assess symptoms and risk factors for COVID-19 via an online dashboard. Between October 2020 and January 2021, we enrolled 10,289 participants reflective of Massachusetts census data. Mean age was 47 years (range 18-93), 5855 (56.9%) were assigned female sex at birth, 7181(69.8%) reported being White non-Hispanic, 952 (9.3%) Hispanic/Latinx, 925 (9.0%) Black, 889 (8.6%) Asian, and 342 (3.3%) other and/or more than one race. Lower initial enrollment among Black and Hispanic/Latinx individuals required an adaptive approach to recruitment, leveraging connections to the medical system, coupled with community partnerships to ensure a representative cohort. Longitudinal retention was higher among participants who were White non-Hispanic, older, working remotely, and with lower socioeconomic vulnerability. Implementation highlighted key differences in remote trial models as participants independently navigate study milestones, requiring a dedicated participant support team and robust technology platforms, to reduce barriers to enrollment, promote retention, and ensure scientific rigor and data quality. Remote clinical trial models offer tremendous potential to engage representative cohorts, scale biomedical research, and promote accessibility by reducing barriers common in traditional trial design. Barriers and burdens within remote trials may be experienced disproportionately across demographic groups. To maximize engagement and retention, researchers should prioritize intensive participant support, investment in technologic infrastructure and an adaptive approach to maximize engagement and retention.