Virtual Behavioral Health for Army Soldiers: Soldier Perspectives and Patterns of Treatment.

Delivery of high-quality behavioral health (BH) care is essential to supporting the readiness of the U.S. armed forces and their families. The coronavirus disease 2019 (COVID-19) pandemic led to a dramatic expansion of virtual behavioral health (VBH) care: remote patient access to BH care using technology such as a computer or cellular phone. The U.S. Army asked RAND Arroyo Center to examine the use of VBH to inform recommendations on the role of VBH care in the future of BH care in the Military Health System. The authors analyzed administrative data on VBH and in-person BH care from prior to the pandemic through March 2022 and surveyed soldiers who received BH care to assess their perceptions of VBH care. Administrative data analyses showed that direct care providers were less likely to deliver VBH care than private-sector providers and relied heavily on audio rather than video VBH. In addition, soldiers who received VBH care typically received a mix of VBH and in-person visits. Survey respondents who used VBH care had similar perceptions of the quality of their care and more-positive views of VBH than respondents who did not use VBH care. Few respondents had declined VBH care in favor of in-person care. Using these findings, the authors make recommendations on the role of VBH care in overall BH delivered by the military.

Assessing the state of care for Huntington disease in the United States: Results from a survey of practices treating Huntington disease patients.

Background: No study to date has thoroughly examined US Huntington disease (HD) care delivery in a variety of clinic settings by HD specialists and non-specialists. Objective: To obtain a clearer understanding of current care structure and delivery of care through a survey of representative US physicians treating HD patients. Methods: We designed and fielded a survey of 40 closed-ended evaluative items and one open-ended item to a sample of 339 US practices. Unique to this survey was the inclusion of non-specialists. Results: Responses were received from 156 practices (overall response rate 46.02 %), with 52.6 % from academic sites, 35.3 % from private practices, and 12.2 % from the VA. More than half (63.5 %) of the practice leads were movement disorder trained or Directors of HDSA Centers of Excellence and 58.3 % had an HD or multidisciplinary care clinic. However, 48.7 % of the practices saw 1-25 HD patients, 28.2 % saw 26-100 HD patients, and 23.1 % served over 100 HD patients annually. Most practices (>69 %) reported having difficulty providing social work, genetic counseling, care coordination and psychologists/psychiatrists. Increased HD practice size was associated with higher rates of pre-visit screenings, care navigator/care coordinators, routine monitoring of weight, and provision of genetic counseling by genetic counselors. Conclusions: Not surprisingly, we found that HD care was inconsistently applied across the US. Practices led by neurologists trained in movement disorders, and higher HD volume practices, tended to be better equipped to provide multi-disciplinary staffing and procedures as compared to those with fewer numbers of HD patients.

Nonparametric Estimation of Population Average Dose-Response Curves using Entropy Balancing Weights for Continuous Exposures.

Weighted estimators are commonly used for estimating exposure effects in observational settings to establish causal relations. These estimators have a long history of development when the exposure of interest is binary and where the weights are typically functions of an estimated propensity score. Recent developments in optimization-based estimators for constructing weights in binary exposure settings, such as those based on entropy balancing, have shown more promise in estimating treatment effects than those methods that focus on the direct estimation of the propensity score using likelihood-based methods. This paper explores recent developments of entropy balancing methods to continuous exposure settings and the estimation of population dose-response curves using nonparametric estimation combined with entropy balancing weights, focusing on factors that would be important to applied researchers in medical or health services research. The methods developed here are applied to data from a study assessing the effect of non-randomized components of an evidence-based substance use treatment program on emotional and substance use clinical outcomes.