IMPORTANCE As coronavirus disease 2019 (COVID-19) spread throughout the US in the early months of 2020, acute care delivery changed to accommodate an influx of patients with a highly contagious infection about which little was known. OBJECTIVE To examine trends in emergency department (ED) visits and visits that led to hospitalizations covering a 4-month period leading up to and during the COVID-19 outbreak in the US. DESIGN, SETTING, AND PARTICIPANTS This retrospective, observational, cross-sectional study of 24 EDs in 5 large health care systems in Colorado (n = 4), Connecticut (n = 5), Massachusetts (n = 5), New York (n = 5), and North Carolina (n = 5) examined daily ED visit and hospital admission rates from January 1 to April 30, 2020, in relation to national and the 5 states' COVID-19 case counts. EXPOSURES Time (day) as a continuous variable. MAIN OUTCOMES AND MEASURES Daily counts of ED visits, hospital admissions, and COVID-19 cases. RESULTS A total of 24 EDs were studied. The annual ED volume before the COVID-19 pandemic ranged from 13 000 to 115 000 visits per year; the decrease in ED visits ranged from 41.5% in Colorado to 63.5% in New York. The weeks with the most rapid rates of decrease in visits were in March 2020, which corresponded with national public health messaging about COVID-19. Hospital admission rates from the ED were stable until new COVID-19 case rates began to increase locally; the largest relative increase in admission rates was 149.0% in New York, followed by 51.7% in Massachusetts, 36.2% in Connecticut, 29.4% in Colorado, and 22.0% in North Carolina. CONCLUSIONS AND RELEVANCE From January through April 2020, as the COVID-19 pandemic intensified in the US, temporal associations were observed with a decrease in ED visits and an increase in hospital admission rates in 5 health care systems in 5 states. These findings suggest that practitioners and public health officials should emphasize the importance of visiting the ED during the COVID-19 pandemic for serious symptoms, illnesses, and injuries that cannot be managed in other settings.

were grouped into primary care, medical, and surgical specialties (eTable 2 in the Supplement).Variables were compared before (March 2018 to February 2020) and during (March 2020 to June 2021) the COVID-19 pandemic. To assess whether the onset of the pandemic was an inflection point in PMARs, message volume per physician per day was modeled by piecewise linear regression using a spline for month with a single knot at March 2020 and Huber-White SEs. Three months of inbox message data were missing (3 of 40 months [7.5%]) and excluded from the analysis. To test for significance (P < .05), we used a 2-sided Wald test for equivalence of the coefficients. We used Stata statistical software version 16 (StataCorp) for data analyses. ResultsForty months of inbox messages were analyzed, including 10 850 401 messages to 419 unique physicians from 38 specialties across 141 practice sites (Figure). Overall, primary care, medical, and surgical physicians received 49.3, 33.4, and 20.7 messages per day, respectively. Between March 2020 and June 2021, mean (SD) total messages per day increased from 45.0 (27.4) to 46.0 (27.4) messages per day for primary care physicians, from 29.3 (20.7) to 32.0 (20.8) messages per day for medical physicians, and from 16.6 (11.9) to 23.3 (17.9) messages per day for surgical physicians.Patient-originated messages also increased, including PMARs (from a mean [SD] of 1.8 [1.8] to 3.9 [3.2] messages per day for primary care physicians; from 1.0 [1.7] to 2.2 [2.9] messages per day for medical physicians; and from 0.4 [0.5] to 1.1 [1.3] messages per day for surgical physicians), patient calls, and time in the inbox (from 21.7 [12.7] to 25.1 [13.7] minutes per day for primary care physicians;

People with opioid use disorder are vulnerable to disruptions in access to addiction treatment and social support during the COVID-19 pandemic. Our study objective was to understand changes in emergency department (ED) utilization following a nonfatal opioid overdose during COVID-19 compared to historical controls in 6 healthcare systems across the United States.Methods: Opioid overdoses were retrospectively identified among adult visits to 25 EDs in Alabama, Colorado, Connecticut, North Carolina, Massachusetts, and Rhode Island from January 2018 to December 2020. Overdose visit counts and rates per 100 allcause ED visits during the COVID-19 pandemic were compared with the levels predicted based on 2018 and 2019 visits using graphical analysis and an epidemiologic outbreak detection cumulative sum algorithm.Results: Overdose visit counts increased by 10.5% (n¼3486; 95% confidence interval [CI] 4.18% to 17.0%) in 2020 compared with the counts in 2018 and 2019 (n¼3020 and n¼3285, respectively), despite a 14% decline in all-cause ED visits. Opioid overdose rates increased by 28.5% (95% CI 23.3% to 34.0%) from 0.25 per 100 ED visits in 2018 to 2019 to 0.32 per 100 ED visits in 2020. Although all 6 studied health care systems experienced overdose ED visit rates more than the 95th percentile prediction in 6 or more weeks of 2020 (compared with 2.6 weeks as expected by chance), 2 health care systems experienced sustained outbreaks during the COVID-19 pandemic. Conclusion:Despite decreases in ED visits for other medical emergencies, the numbers and rates of opioid overdose-related ED visits in 6 health care systems increased during 2020, suggesting a widespread increase in opioid-related complications during the COVID-19 pandemic. Expanded community-and hospital-based interventions are needed to support people with opioid use disorder and save lives during the COVID-19 pandemic.

Objective To derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time. Materials and Methods A cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time. Results Five out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P &lt; .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month −0.01 hours; practicing cardiology −1.30 hours; medical subspecialties −0.89 hours (except gastroenterology, P = .002); neurology/psychiatry −2.60 hours; obstetrics/gynecology −1.88 hours; pediatrics −1.05 hours (P = .001); sports/physical medicine and rehabilitation −3.25 hours; and surgical specialties −3.65 hours. Conclusions For every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.

Objectives To measure nurse-perceived electronic health records (EHR) usability with a standardized metric of technology usability and evaluate its association with professional burnout. Methods A cross-sectional survey of a random sample of US nurses was conducted in November 2017. EHR usability was measured with the System Usability Scale (SUS; range 0–100) and burnout with the Maslach Burnout Inventory. Results Among the 86 858 nurses who were invited, 8638 (9.9%) completed the survey. The mean nurse-rated EHR SUS score was 57.6 (SD 16.3). A score of 57.6 is in the bottom 24% of scores across previous studies and categorized with a grade of “F.” On multivariable analysis adjusting for age, gender, race, ethnicity, relationship status, children, highest nursing-related degree, mean hours worked per week, years of nursing experience, advanced certification, and practice setting, nurse-rated EHR usability was associated with burnout with each 1 point more favorable SUS score and associated with a 2% lower odds of burnout (OR 0.98; 95% CI, 0.97–0.99; P &lt; .001). Conclusions Nurses rated the usability of their current EHR in the low marginal range of acceptability using a standardized metric of technology usability. EHR usability and the odds of burnout were strongly associated with a dose-response relationship.