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The COVID-19 pandemic is causing world-wide social dislocation, operational and economic dysfunction, and high rates of morbidity and mortality. Medical practices are responding by developing, disseminating, and implementing unprecedented changes in health care delivery. Telemedicine has rapidly moved to the frontline of clinical practice due to the need for prevention and mitigation strategies; these have been encouraged, facilitated, and enabled by changes in government rules and regulations and payer-driven reimbursement policies. We describe our neurology department's situational transformation from in-person outpatient visits to a largely virtual neurology practice in response to the COVID-19 pandemic. Two key factors enabled our rapid deployment of virtual encounters in neurology and its subspecialties. The first was a well-established robust information technology infrastructure supporting virtual urgent care services at our institution; this connected physicians directly to patients using both the physician's and the patient's own mobile devices. The second is the concept of one patient, one chart, facilitated by a suite of interconnected electronic medical record (EMR) applications on several different device types. We present our experience with conducting general teleneurology encounters using secure synchronous audio and video connections integrated with an EMR. This report also details how we perform virtual neurologic examinations that are clinically meaningful and how we document, code, and bill for these virtual services. Many of these processes can be used by other neurology providers, regardless of their specific practice model. We then discuss potential roles for teleneurology after the COVID-19 global pandemic has been contained., (© 2020 American Academy of Neurology.)

Background: Although the national obesity epidemic has been well documented, less is known about obesity at the U.S. state level. Current estimates are based on body measures reported by persons themselves that underestimate the prevalence of obesity, especially severe obesity., Methods: We developed methods to correct for self-reporting bias and to estimate state-specific and demographic subgroup-specific trends and projections of the prevalence of categories of body-mass index (BMI). BMI data reported by 6,264,226 adults (18 years of age or older) who participated in the Behavioral Risk Factor Surveillance System Survey (1993-1994 and 1999-2016) were obtained and corrected for quantile-specific self-reporting bias with the use of measured data from 57,131 adults who participated in the National Health and Nutrition Examination Survey. We fitted multinomial regressions for each state and subgroup to estimate the prevalence of four BMI categories from 1990 through 2030: underweight or normal weight (BMI [the weight in kilograms divided by the square of the height in meters], <25), overweight (25 to <30), moderate obesity (30 to <35), and severe obesity (≥35). We evaluated the accuracy of our approach using data from 1990 through 2010 to predict 2016 outcomes., Results: The findings from our approach suggest with high predictive accuracy that by 2030 nearly 1 in 2 adults will have obesity (48.9%; 95% confidence interval [CI], 47.7 to 50.1), and the prevalence will be higher than 50% in 29 states and not below 35% in any state. Nearly 1 in 4 adults is projected to have severe obesity by 2030 (24.2%; 95% CI, 22.9 to 25.5), and the prevalence will be higher than 25% in 25 states. We predict that, nationally, severe obesity is likely to become the most common BMI category among women (27.6%; 95% CI, 26.1 to 29.2), non-Hispanic black adults (31.7%; 95% CI, 29.9 to 33.4), and low-income adults (31.7%; 95% CI, 30.2 to 33.2)., Conclusions: Our analysis indicates that the prevalence of adult obesity and severe obesity will continue to increase nationwide, with large disparities across states and demographic subgroups. (Funded by the JPB Foundation.)., (Copyright © 2019 Massachusetts Medical Society.)