ABSTRACT
Background: Drastic increases in the rates of maternal depression and anxiety have been reported since the COVID-19 pandemic began. Most programs aim to improve maternal mental health or parenting skills separately, despite it being more effective to target both concurrently. The Building Emotional Awareness and Mental health (BEAM) program was developed to address this gap. BEAM is a mobile health program aiming to mitigate the impacts of pandemic stress on family well-being. Since many family agencies lack infrastructure and personnel to adequately treat maternal mental health concerns, a partnership will occur with Family Dynamics (a local family agency) to address this unmet need. The study’s objective is to examine the feasibility of the BEAM program when delivered with a community partner to inform a larger randomized controlled trial (RCT). Methods: A pilot randomized controlled trial will be conducted with mothers who have depression and/or anxiety with a child 6-18 months old living in Manitoba, Canada. Mothers will be randomized to the 10 weeks of the BEAM program or a standard of care. Back-end App data (collected via Google Analytics and Firebase) will be used to examine feasibility, engagement, and accessibility of the BEAM program; cost-effectiveness will also be examined. Implementation elements (e.g., maternal depression [Patient Health Questionnaire-9] and anxiety [Generalized Anxiety Disorder-7]) will be piloted to estimate the effect size and variance for future sample size calculations. Discussion: In partnership with a local family agency, BEAM holds the potential to promote maternal-child health via a cost-effective and easily accessible program designed to scale. Results will provide insight into the feasibility of the BEAM program and will inform future RCTs of the BEAM program. Trial Registration: This trial was retrospectively registered with ClinicalTrial.gov (NCT05398107) on May 31st, 2022. https://clinicaltrials.gov/ct2/show/NCT05398107
Subject(s)
Anxiety Disorders , Depressive Disorder , COVID-19ABSTRACT
Background: Due to COVID-19's significant morbidity and mortality, identifying the most cost-effective pharmacologic treatment strategy is critical. As such, we determined the most cost-effective strategy for moderate to severe COVID-19 respiratory infections using the United States health care system as a representative model. Methods: A decision analytic model modelled a base case scenario of a 60-year-old patient admitted to hospital with COVID-19. Patients requiring oxygen were considered moderate severity, and patients with severe COVID-19 required intubation with intensive care. Strategies modelled included giving remdesivir to all patients, remdesivir in severe infections, remdesivir in moderate infections, dexamethasone to all patients, dexamethasone in severe infections, remdesivir in moderate/dexamethasone in severe infections, and best supportive care. Data for the model came from the published literature. The time horizon was 28 days; no discounting was performed due to the short duration. The perspective was of the payer in the United States health care system. Results: Supportive care for moderate/severe COVID-19 cost $11,112.98/0.8256 QALY. Remdesivir in moderate/dexamethasone in severe infections was the most cost-effective with an incremental cost-effectiveness ratio of $19,764.56/QALY gained compared to supportive care. Probabilistic sensitivity analyses showed remdesivir for moderate/dexamethasone for severe COVID-19 infection was most cost-effective in 88.6% of scenarios and dexamethasone in moderate-severe infections in 11.4% of scenarios. With lower willingness to pay thresholds ($250-$37,500), dexamethasone for severe infections was favoured. Conclusions: Remdesivir for moderate/dexamethasone for severe COVID-19 infections was the most cost-effective strategy. Further data is required for remdesivir to better assess its cost effectiveness in treatment of COVID-19.