Availability of Outpatient Child Psychiatric Care During COVID-19: A Simulated-Patient Study in Three U.S. Cities.

OBJECTIVE: In this study, the authors sought to ascertain the availability of outpatient child psychiatric appointments in three U.S. cities. METHODS: Using a simulated-patient methodology, investigators called 322 psychiatrists who were listed in a major insurer's database for three U.S. cities, and they attempted to make appointments for a child with three payment types: Blue Cross-Blue Shield, Medicaid, and self-pay. RESULTS: Initial appointments were available 11% of the time, and it was most difficult to obtain an appointment under Medicaid coverage. Nineteen percent of phone numbers were wrong, and 25% of psychiatrists were not accepting new patients. CONCLUSIONS: These results are concerning given the current mental health crisis among youths and suggest the need for more psychiatrists, higher reimbursement rates for psychiatric services, and continued efforts to increase access to care. This study also highlights the need for insurance companies to maintain accurate information in their databases.

An Optimization Framework to Study the Balance Between Expected Fatalities Due to COVID-19 and the Reopening of U.S. Communities

During the COVID-19 pandemic, communities faced two conflicting objectives: 1) minimizing infections among vulnerable populations with higher risk for severe illness and 2) enabling reopening to revive American livelihoods. The U.S. pandemic strategy myopically considered one objective at a time, with lockdowns that addressed the former, but was detrimental to the latter, and phased reopening that pursued the latter, but lost control over the former. How could we prioritize interventions to simultaneously minimize cases of severe illness and fatalities while reopening? A team of researchers anchored by the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS), The University of Texas at Arlington, has formulated a computationally efficient optimization framework, referred to as COSMOS COVID-19 Linear Programming (CC19LP), to study the delicate balance between the expected fatality rate due to cases of severe illness and the level of normalcy in the community. The key to the CC19LP framework is a focus on “key contacts” that separate individuals at higher risk from the rest of the population. CC19LP minimizes expected fatalities by optimizing the use of available interventions, namely, COVID-19 testing, personal protective equipment (PPE), COVID-19 vaccines, and social precautions, such as distancing, handwashing, and face coverings. A C3.ai award-winning online CC19LP tool is accessible from the COSMOS COVID-19 project site (https://cosmos.uta.edu/projects/covid-19/) and has been tested for all 3142 U.S. county areas. Results are demonstrated for several metropolitan counties with a deeper investigation for Miami-Dade County in Florida. Note to Practitioners—In this article, a computationally fast optimization framework is presented to study the delicate balance between reopening U.S. communities and controlling severe cases of COVID-19 that lead to hospitalizations and fatalities. This framework can provide guidance to decision-makers on optimal intervention strategies for protecting high-risk individuals while reopening communities. This optimization framework demonstrates a practical approach to conduct decision-making in an uncertain environment and can be useful for the prioritization of resources and interventions in the case of future epidemics or pandemics. Resources on understanding and implementing the framework are publicly available, including an award-winning online optimization tool that automatically accesses county-level data from Census, Centers for Disease Control and Prevention (CDC), and Johns Hopkins COVID-19 repositories. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Telehealth Utilization and Follow-Up Visits in Developmental-Behavioral Pediatrics During the COVID-19 Pandemic in 2020.

OBJECTIVE: The goal of this study was to understand the effect of transition to telehealth care on follow-up visit attendance in a developmental-behavioral pediatric (DBP) practice in 2020 versus in-person care in 2019. METHODS: This was a retrospective observational cohort study of follow-up visits occurring in a large DBP practice during a 6-week period in March/April of 2019 and 2020. The primary outcome was follow-up visit adherence, defined as completion of scheduled follow-up visit. The primary exposure was telehealth visit in 2020 versus in-person visit in 2019. Covariates included patient demographics and clinical characteristics. Data were analyzed using descriptive statistics and logistic regression. RESULTS: The cohort included 2142 visits for 1868 unique patients. The patient mean age was 9.2 ± 4.8 years, with 73.4% male, 56.5% non-Hispanic, 51.4% White, and 68.3% commercial insurance. There were 470 telehealth visits from March to April 2020 and 1672 in-person visits from March to April 2019. Compared with in-person visits, telehealth visits were more likely to be completed (75.3% vs 64.4%, p < 0.001). After adjusting for age, sex, race, ethnicity, insurance, and week of visit (weeks 1-3 vs 4-6), odds of having a complete follow-up visit were higher for telehealth visits than for in-person visits (odds ratio = 1.57; 95% confidence interval [1.23-2.00], p < 0.001). CONCLUSION: Follow-up visit attendance was higher for telehealth care in 2020 than in-person care in 2019. This association persisted after adjusting for insurance, age, race, and ethnicity, suggesting that telehealth is associated with increased follow-up visit attendance in DBP care. Further studies are needed to understand the impact of telehealth on DBP clinical outcomes in chronic disease management.

An exploration of instructors' and students' perspectives on remote delivery of courses during the COVID-19 pandemic.

The world-wide pivot to remote learning due to the exogenous shocks of COVID-19 across educational institutions has presented unique challenges and opportunities. This study documents the lived experiences of instructors and students and recommends emerging pathways for teaching and learning strategies post-pandemic. Seventy-one instructors and 122 students completed online surveys containing closed and open-ended questions. Quantitative and qualitative analyses were conducted, including frequencies, chi-square tests, Welch Two-Samples t-tests, and thematic analyses. The results demonstrated that with effective online tools, remote learning could replicate key components of content delivery, activities, assessments, and virtual proctored exams. However, instructors and students did not want in-person learning to disappear and recommended flexibility by combining learning opportunities in in-person, online, and asynchronous course deliveries according to personal preferences. The paper concludes with future directions and how the findings influenced our planning for Fall 2021 delivery. The video abstract for this article is available at https://www.youtube.com/watch?v=F48KBg_d8AE.