Mara Eyllon

Bio: Mara Eyllon is an academic researcher. The author has contributed to research in topics: Telemental health. The author has co-authored 1 publications.

The Impact of the Covid-19-Related Transition to Telehealth on Visit Adherence in Mental Health Care: An Interrupted Time Series Study.

Abstract: Covid-19 has led to an unprecedented shift to telemental health (TMH) in mental healthcare. This study examines the impact of this transition on visit adherence for mental health services in an integrated behavioral health department. Monthly visit data for 12,245 patients from January, 2019 to January, 2021 was extracted from the electronic medical record. Interrupted time series (ITS) analysis examined the impact of the Covid-19 transition to TMH on immediate level and trend changes in the percentage of cancelled visits and no shows in the 10 months following the transition. ITS also compared changes across the three largest services types: adult, pediatric, and substance use. Following the TMH-transition, completed visits increased by 10% amounting to an additional 3644 visits. In April, 2020, immediately following the TMH-transition, no shows increased by 1.4%, (95% CI 0.1, 2.7, p < 0.05) and cancellations fell by 13.5% (95% CI − 17.9, − 9.0, p < 0.001). Across the 10-month post-TMH period, 18.2% of visits were cancelled, compared to 28.3% across the 14-month pre-TMH period. The proportion of no-shows remained the same. The pattern was similar for pediatric and adult sub-clinics, but no significant changes in cancellations or no shows were observed in the substance use sub-clinic. TMH during the Covid-19 pandemic is associated with improved visit adherence over time and may be a promising model for improving the efficiency of mental health care delivery once it is safe to resume in person care.

Impact of the COVID-19 pandemic on treatment for mental health needs: a perspective on service use patterns and expenditures from commercial medical claims data

Abstract: Abstract Objective To examine changes in use patterns, cost of healthcare services before and after the outbreak of the COVID-19 pandemic, and their impacts on expenditures for patients receiving treatment for depression, anxiety, eating disorders, and substance use. Methods This cross-sectional study employed statistical tests to analyze claims in MarketScan® Commercial Database in March 2020-February 2021 and quarterly from March 2020 to August 2021, compared to respective pre-pandemic periods. The analysis is based on medical episodes created by the Merative™ Medical Episode Grouper (MEG). MEG is a methodology that groups medical and prescription drug claims to create clinically relevant episodes of care. Results Comparing year-over-year changes, proportion of patients receiving anxiety treatment among all individuals obtaining healthcare services grew 13.7% in the first year of the pandemic (3/2020–2/2021) versus 10.0% in the year before the pandemic (3/2019–2/2020). This, along with a higher growth in price per episode (5.5% versus 4.3%) resulted in a greater increase in per claimant expenditure ($0.61 versus $0.41 per month). In the same periods, proportion of patients receiving treatment for depression grew 3.7% versus 6.9%, but per claimant expenditure grew by same amount due to an increase in price per episode (4.8%). Proportion of patients receiving treatment for anorexia started to increase 21.1% or more in the fall of 2020. Patient proportion of alcohol use in age group 18–34 decreased 17.9% during the pandemic but price per episode increased 26.3%. Patient proportion of opioid use increased 11.5% in March–May 2020 but decreased or had no significant changes in subsequent periods. Conclusions We investigated the changes in use patterns and expenditures of mental health patients before and after the outbreak of the COVID-19 pandemic using claims data in MarketScan®. We found that the changes and their financial impacts vary across mental health conditions, age groups, and periods of the pandemic. Some changes are unexpected from previously reported prevalence increases among the general population and could underlie unmet treatment needs. Therefore, mental health providers should anticipate the use pattern changes in services with similar COVID-19 pandemic disruptions and payers should anticipate cost increases due, in part, to increased price and/or service use.

Healthcare response strategies for the long-COVID era

Abstract: Background: Coronavirus disease (COVID-19), first reported at the end of 2019, is characterized by a broad spectrum of clinical manifestations ranging from asymptomatic to multi-organ dysfunction. These symptoms may persist even after the acute phase has passed. Post-acute COVID-19 syndrome (long-COVID) is a condition characterized by COVID-19 symptoms that persist for longer than two months after infection. Fatigue, muscle and joint pain, dyspnea, cognitive impairment, and anxiety are the most common symptoms of long-COVID. Given the substantial impact of COVID-19 sequelae on the quality of life of its survivors, as well as its socioeconomic burden, proactive measures are required.Current Concepts: Following the identification of long-COVID characteristics and symptoms, patient-centered care based on vaccination, COVID-19 medications, and digital healthcare is recommended. Furthermore, people who are more vulnerable to long-COVID, such as those with respiratory dysfunctions or the older adults, require more specialized and attentive management. Big data and artificial intelligence will hopefully enable a more timely and effective response to this healthcare issue.Discussion and Conclusion: Infectious diseases threaten our lives constantly, as evidenced by the recent COVID-19 pandemic and its lingering consequences. A novel virus can emerge at any time and place, resulting in substantial clinical and economic loss. At this stage, it is crucial to establish prompt and effective strategies against long-COVID, as well as against potential pandemics.

Effects of Virtual Care and Same-Day Access to Integrated Care on Specialty Mental Health Engagement in the Veterans Health Administration

Abstract: Background: In the Veterans Health Administration (VA), Primary Care-Mental Health Integration (PC-MHI) clinics offer mental health services embedded in primary care, a strategy shown to reduce overall specialty mental health clinic burden while facilitating prompt referrals when indicated. Among newly initiated patients, same-day access to PC-MHI from primary care increases subsequent specialty mental health engagement. However, the impact of virtual care on the association between same-day access to PC-MHI and subsequent mental health engagement remains unclear. Objective: To examine the effects of same-day access to PC-MHI and virtual care use on specialty mental health engagement. Methods: We used administrative data from 3066 veterans who initiated mental health care at a large, California VA PC-MHI clinic during 3/1/2018 to 2/28/2022 and had no previous mental health visits for at least 2 years prior to the index appointment. We conducted Poisson regression analyses to examine the effects of same-day access to PC-MHI, virtual access to PC-MHI and their combined effect on subsequent specialty mental health engagement. Results: Same-day access to PC-MHI from primary care was positively associated with specialty mental health engagement (IRR = 1.19; 95% CI 1.14-1.24). Virtual access to PC-MHI was negatively associated with specialty mental health engagement (IRR = 0.83; 95% CI 0.79-0.87). The positive effect of same-day access on specialty mental health engagement was smaller among patients who initiated PC-MHI in a virtual visit (IRR = 1.07) compared to in-person visits (IRR = 1.29; 95% CI 1.22-1.36). Conclusions: Although same-day access to PC-MHI increased overall specialty mental health engagement, the magnitude of this effect varied between in-person and virtual modalities. More research is needed to understand mechanisms of the association between virtual care use, same-day access to PC-MHI, and specialty mental health engagement.