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      Emergency Department Visits for Atrial Fibrillation in the United States: Trends in Admission Rates and Economic Burden From 2007 to 2014

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          Atrial fibrillation ( AF) is an increasingly prevalent public health problem and one of the most common causes of emergency department ( ED) visits. We aimed to investigate the trends in ED visits and hospital admissions for AF.

          Methods and Results

          This is a repeated cross‐sectional analysis of ED visit‐level data from the Nationwide Emergency Department Sample for 2007 to 2014. We identified adults who visited EDs in the United States, with a principal diagnosis of AF. A sample of 864 759 ED visits for AF, representing a weighted total of 3 886 520 ED visits, were analyzed. The annual ED visits for AF increased by 30.7% from 411 406 in 2007 (95% confidence interval, 389 819–432 993) to 537 801 (95% confidence interval, 506 747–568 855) in 2014. Patient demographics remained consistent, with an average age of 69 to 70 years and slight female predominance (51%–53%) throughout the study period. Hospital admission rates were stable at ≈70% between 2007 and 2010, after which they gradually declined to 62% in 2014 ( P trend=0.017). Despite the decline in hospital admission rates, AF hospitalizations increased from 288 225 in 2007 to 333 570 in 2014 because of the increase in total annual ED visits during the study. The adjusted annual charges for admitted AF patients increased by 37% from $7.39 billion in 2007 to $10.1 billion in 2014.


          Annual ED visits and hospital admissions for AF increased significantly between 2007 and 2014, despite a reduction in admission rates. These data emphasize the need for widespread implementation of effective strategies aimed at improving the management of patients with AF to reduce hospital admissions and the economic burden of AF.

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          Most cited references 20

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          A population-based study of the long-term risks associated with atrial fibrillation: 20-year follow-up of the Renfrew/Paisley study.

          To describe the effect of atrial fibrillation on long-term morbidity and mortality. The Renfrew/Paisley Study surveyed 7052 men and 8354 women aged 45-64 years between 1972 and 1976. All hospitalizations and deaths occurring during the subsequent 20 years were analyzed by the presence or absence of atrial fibrillation at baseline. Lone atrial fibrillation was defined in the absence of other cardiovascular signs or symptoms. Cox proportional hazards models were used to adjust for age and cardiovascular conditions. After 20 years, 42 (89%) of the 47 women with atrial fibrillation had a cardiovascular event (death or hospitalization), compared with 2276 (27%) of the 8307 women without this arrhythmia. Among men, 35 (66%) of 53 with atrial fibrillation had an event, compared with 3151 (45%) of 6999 without atrial fibrillation. In women, atrial fibrillation was an independent predictor of cardiovascular events (rate ratio [RR] = 3.0; 95% confidence interval [CI]: 2.1-4.2), fatal or nonfatal strokes (RR = 3.2; 95% CI: 1.0-5.0), and heart failure (RR = 3.4; 95% CI: 1.9-6.2). The rate ratios among men were 1.8 (95% CI: 1.3-2.5) for cardiovascular events, 2.5 (95% CI: 1.3-4.8) for strokes, and 3.4 (95% CI: 1.7-6.8) for heart failure. Atrial fibrillation was an independent predictor of all-cause mortality in women (RR = 2.2; 95% CI: 1.5-3.2) and men (RR = 1.5; 95% CI: 1.2-2.2). However, lone atrial fibrillation (which occurred in 15 subjects) was not associated with a statistically significant increase in either cardiovascular events (RR = 1.5; 95% CI: 0.6-3.6) or mortality (RR = 1.8; 95% CI: 0.9-3.8). Atrial fibrillation is associated with an increased long-term risk of stroke, heart failure, and all-cause mortality, especially in women.
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            Estimates of current and future incidence and prevalence of atrial fibrillation in the U.S. adult population.

            Estimates and projections of diagnosed incidence and prevalence of atrial fibrillation (AF) in the United States have been highly inconsistent across published studies. Although it is generally acknowledged that AF incidence and prevalence are increasing due to growing numbers of older people in the U.S. population, estimates of the rate of expected growth have varied widely. Reasons for these variations include differences in study design, covered time period, birth cohort, and temporal effects, as well as improvements in AF diagnosis due to increased use of diagnostic tools and health care awareness. The objective of this study was to estimate and project the incidence and prevalence of diagnosed AF in the United States out to 2030. A large health insurance claims database for the years 2001 to 2008, representing a geographically diverse 5% of the U.S. population, was used in this study. The trend and growth rate in AF incidence and prevalence was projected by a dynamic age-period cohort simulation progression model that included all diagnosed AF cases in future prevalence projections regardless of follow-up treatment, as well as those cases expected to be chronic in nature. Results from the model showed that AF incidence will double, from 1.2 million cases in 2010 to 2.6 million cases in 2030. Given this increase in incidence, AF prevalence is projected to increase from 5.2 million in 2010 to 12.1 million cases in 2030. The effect of uncertainty in model parameters was explored in deterministic and probabilistic sensitivity analyses. Variability in future trends in AF incidence and recurrence rates has the greatest impact on the projected estimates of chronic AF prevalence. It can be concluded that both incidence and prevalence of AF are likely to rise from 2010 to 2030, but there exists a wide range of uncertainty around the magnitude of future trends.
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              Readmissions, Observation, and the Hospital Readmissions Reduction Program.

              The Hospital Readmissions Reduction Program, which is included in the Affordable Care Act (ACA), applies financial penalties to hospitals that have higher-than-expected readmission rates for targeted conditions. Some policy analysts worry that reductions in readmissions are being achieved by keeping returning patients in observation units instead of formally readmitting them to the hospital. We examined the changes in readmission rates and stays in observation units over time for targeted and nontargeted conditions and assessed whether hospitals that had greater increases in observation-service use had greater reductions in readmissions.

                Author and article information

                J Am Heart Assoc
                J Am Heart Assoc
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                20 July 2018
                07 August 2018
                : 7
                : 15 ( doiID: 10.1002/jah3.2018.7.issue-15 )
                [ 1 ] Cardiovascular Institute Baruch Padeh Medical Center Poriya Israel
                [ 2 ] Cardiac Arrhythmia Service Massachusetts General Hospital Harvard Medical School Boston MA
                [ 3 ] Department of Biostatistics Massachusetts General Hospital Boston MA
                Author notes
                [* ] Correspondence to: Jeremy N. Ruskin, MD, Cardiac Arrhythmia Service, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114. E‐mail: jruskin@ 123456mgh.harvard.edu

                Dr Rozen and Dr Hosseini contributed equally to this work.

                © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                Page count
                Figures: 4, Tables: 4, Pages: 12, Words: 7745
                Original Research
                Original Research
                Arrhythmia and Electrophysiology
                Custom metadata
                07 August 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.4 mode:remove_FC converted:07.08.2018


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