RESUMEN
Objective: New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for internal use by other surveillance and epidemiology experts. Materials and methods: Existing surveillance databases and systems were leveraged to create daily analytic datasets of COVID-19 case and testing information, aggregated by week and key demographics. The dashboard was developed iteratively using R, and includes interactive graphs, tables, and maps summarizing recent COVID-19 epidemiologic trends. Additional data and interactive features were incorporated to provide further information on the spread of COVID-19 in NYC. Results: The dashboard allows key staff to quickly review situational data, identify concerning trends, and easily maintain granular situational awareness of COVID-19 epidemiology in NYC. Discussion: The dashboard is used to inform weekly surveillance summaries and alleviated the burden of manual report production on infectious disease epidemiologists. The system was built by and for epidemiologists, which is critical to its utility and functionality. Interactivity allows users to understand broad and granular data, and flexibility in dashboard development means new metrics and visualizations can be developed as needed. Conclusions: Additional investment and development of public health informatics tools, along with standardized frameworks for local health jurisdictions to analyze and visualize data in emergencies, are warranted.
RESUMEN
Background Variability in the management of atrial fibrillation (AF) in the emergency department (ED) leads to avoidable hospital admissions and prolonged length of stay (LOS). In a retrospective single-center study, a multidisciplinary AF treatment pathway was associated with a reduced hospital admission rate and reduced LOS. To assess the applicability of the AF pathway across institutions, we conducted a 2-center study. Methods and Results We performed a prospective, 2-stage study at 2 tertiary care hospitals. During the first stage, AF patients in the ED received routine care. During the second stage, AF patients received care according to the AF pathway. The primary study outcome was hospital admission rate. Secondary outcomes included ED LOS and inpatient LOS. We enrolled 104 consecutive patients in each stage. Patients treated using the AF pathway were admitted to the hospital less frequently than patients who received routine care (15% versus 55%; P<0.001). For admitted patients, average hospital LOS was shorter in the AF pathway cohort than in the routine care cohort (64 versus 105 hours, respectively; P=0.01). There was no significant difference in the average ED LOS between AF pathway and routine care cohorts (14 versus 12 hours, respectively; P=0.32). Conclusions In this prospective 2-stage, 2-center study, utilization of a multidisciplinary AF treatment pathway resulted in a 3.7-fold reduction in admission rate and a 1.6-fold reduction in average hospital LOS for admitted patients. Utilization of the AF pathway was not associated with a significant change in ED LOS.