Seasonal Variation of Atrial Fibrillation Admission and Quality of Care in the United States.
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ABSTRACT: Background Currently, little is known regarding seasonal variation for atrial fibrillation (AF) in the United States and whether quality of care for AF varies between seasons. Methods and Results The GWTG-AFib (Get With The Guidelines-AFib) registry was initiated by the American Heart Association to enhance national guideline adherence for treatment and management of AF. Our analyses included 61 291 patients who were admitted at 141 participating hospitals from 2014 to 2018 across the United States. Outcomes included numbers of AF admissions and quality-of-care measures (defect-free care, defined as a patient's receiving all eligible measures). For quality-of-care measures, generalized estimating equations accounting for within-site correlations were used to estimate odds ratios (ORs) with 95% CIs, adjusting patient and hospital characteristics. The proportion of AF admissions for each season was similar, with the highest percentage of AF admissions being observed in the fall (spring 25%, summer 25%, fall 27%, and winter 24%). Overall, AF admissions across seasons were similar, with no seasonal variation observed. No seasonal variation was observed for incident AF. There were no seasonal differences in care quality (multivariable adjusted ORs and 95% CIs were 0.93 (0.87-1.00) for winter, 1.09 (1.01-1.18) for summer, and 1.08 (0.97-1.20) for fall, compared with spring). Conclusions In a nationwide quality improvement registry, no seasonal variation was observed in hospital admissions for AF or quality of care for AF.
Project description:BackgroundPrevious studies conflict on whether seasonal variability exists in atrial fibrillation (AF) admissions, and contemporary studies are lacking.MethodsWe identified admissions for AF or atrial flutter in the Midwest and Northeast regions of the US from the National Inpatient Database for 2016 to 2020, grouped them into the four seasons (spring, summer, fall, winter), and compared the number of admissions. Subgroup analyses were performed stratified to sex, age, race, AF alone, and geographical regions.ResultsA total of 955,320 admissions for AF or atrial flutter occurred. The number of admissions was highest during winter (243,990, 25.5% of the total), followed by fall (239,250, 25.0% of the total), summer (236,910, 24.8% of the total), and spring (235,170, 24.6% of the total). The differences were statistically significant (P < 0.001). An increasing trend in the number of admissions was observed from March to February of the next year (P trend <0.001). Admissions were most common in the winter and least common in the spring in subgroups of both sexes, age ≥65 years, Whites, non-Whites, AF alone, Northeast region, and Midwest region.ConclusionContemporary analysis of a national database demonstrates seasonal variability in the number of admissions for AF, with a slight increase observed during the winter.
Project description:ObjectiveCertain neurologic diseases have been noted to vary by season, and this is important for understanding disease mechanisms and risk factors, but seasonality has not been systematically examined across the spectrum of neurologic disease, and methodologic guidance is also lacking.MethodsUsing nationally representative data from the National Inpatient Sample, a stratified 20% sample of all non-federal acute care hospitalizations in the United States, we calculated the monthly rate of hospitalization for 14 neurologic diseases from 2016 to 2018. For each disease, we assessed seasonality of hospitalization using chi-squared, Edward, and Walter-Elwood tests and seasonal time series regression models. Statistical tests were adjusted for multiple hypothesis testing using Bonferroni correction.ResultsMeningitis, encephalitis, ischemic stroke, intracerebral hemorrhage, Guillain-Barre syndrome, and multiple sclerosis had statistically significant seasonality according to multiple methods of testing. Subarachnoid hemorrhage, status epilepticus, myasthenia gravis, and epilepsy had significant seasonality according to Edwards and Walter-Elwood tests but not chi-square tests. Seasonal time series regression illustrated seasonal variation in all 14 diseases of interest, but statistical testing for seasonality within these models using the Kruskal-Wallis test only achieved statistical significance for meningitis.InterpretationSeasonal variation is present across the spectrum of acute neurologic disease, including some conditions for which seasonality has not previously been described, and can be examined using multiple different methods. ANN NEUROL 2023;93:743-751.
Project description: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. 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 (Ptrend=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.
Project description:RationaleThe extent to which geographic variability in ICU admission across the United States is driven by patients with lower risk of death is unknown.ObjectivesTo determine whether patients at low to moderate risk of death contribute to geographic variation in ICU admission.MethodsRetrospective cohort of hospitalizations among Medicare beneficiaries (age > 64 years) admitted for ten common medical and surgical diagnoses (2004 to 2009). We examined population-adjusted rates of ICU admission per 100 hospitalizations in 304 health referral regions (HRR), and estimated the relative risk of ICU admission across strata of regional ICU and risk of death, adjusted for patient and regional characteristics.Measurement and main resultsICU admission rates varied nearly two-fold across HRR quartiles (quartile 1 to 4: 13.6, 17.3, 20.0, and 25.2 per 100 hospitalizations, respectively). Observed mortality for patients in regions (quartile 4) with the greatest ICU use was 17% compared to 21% in regions with lowest ICU use (quartile 1) (p<0.001). After adjusting for patient and regional characteristics, including regional differences in ICU, skilled nursing, and long-term acute care bed capacity, individuals' risk of death modified the relationship between regional ICU use and an individual's risk of ICU admission (p for interaction<0.001). Region was least important in predicting ICU admission among patients with high (quartile 4) risk of death (RR 1.27, 95% CI 1.22-1.31, for high versus low ICU use regions), and most important for patients with moderate (quartile 2; RR 1.63, 95% CI 1.53-1.72, quartile 3; RR 1.56 95% CI 1.47-1.65) and low (quartile 1) risk of death (RR 1.50, 95% CI 1.41-1.59).ConclusionsThere is wide variation in in ICU use by geography, independent of ICU beds and physician supply, for patients with low and moderate risks of death.
Project description:Despite increasing attention on reducing relatively costly hospital practices while maintaining the quality of care, few studies have examined how hospitals use the intensive care unit (ICU), a high-cost setting, for patients admitted with heart failure (HF). We characterized hospital patterns of ICU admission for patients with HF and determined their association with the use of ICU-level therapies and patient outcomes.We identified 166 224 HF discharges from 341 hospitals in the 2009-2010 Premier Perspective database. We excluded hospitals with <25 HF admissions, patients <18 years old, and transfers. We defined ICU as including medical ICU, coronary ICU, and surgical ICU. We calculated the percent of patients admitted directly to an ICU. We compared hospitals in the top quartile (high ICU admission) with the remaining quartiles. The median percentage of ICU admission was 10% (interquartile range, 6%-16%; range, 0%-88%). In top-quartile hospitals, treatments requiring an ICU were used less often; the percentage of ICU days receiving mechanical ventilation was 6% for the top quartile versus 15% for the others; noninvasive positive pressure ventilation, 8% versus 19%; vasopressors and/or inotropes, 9% versus 16%; vasodilators, 6% versus 12%; and any of these interventions, 26% versus 51%. Overall HF in-hospital risk-standardized mortality was similar (3.4% versus 3.5%; P=0.2).ICU admission rates for HF varied markedly across hospitals and lacked association with in-hospital risk-standardized mortality. Greater ICU use correlated with fewer patients receiving ICU interventions. Judicious ICU use could reduce resource consumption without diminishing patient outcomes.
Project description:With the introduction of novel oral anticoagulants (NOACs), the factors driving anticoagulant selection in atrial fibrillation (AF) in real-world practice are unclear. The goal was to examine whether and to what extent utilization has been driven by predictions of stroke risk (treatment benefit), bleeding risk (treatment harm), or prescription benefits' coverage. We extracted a cohort of patients with nonvalvular AF initiating anticoagulation from October 2010 to December 2012 from a large US database of commercial and Medicare supplement claims. Multivariable regression examined associations between ischemic stroke (CHA2DS2-VASc) and bleeding (Anticoagulation and Risk Factors in Atrial Fibrillation [ATRIA]) risk scores and benefits' generosity (proportion of costs covered by patients relative to total) with warfarin and novel oral anticoagulant (NOAC) selection and also between dabigatran and rivaroxaban. C-statistics and partial chi-square statistics were used to assess the variation explained. Of 70,498 patients initiating anticoagulation, 29.9% and 7.9% used dabigatran and rivaroxaban, respectively. Compared with warfarin, patients were less likely to receive an NOAC with high ischemic stroke risk (CHA2DS2-VASc ?2; adjusted relative risk [aRR] 0.75, 95% confidence interval [CI] 0.72 to 0.77) and high bleeding risk (ATRIA ?5; aRR 0.66, 95% CI 0.64 to 0.69) but more likely with good benefits' generosity (?20% of costs borne by patient; aRR 2.03, 95% CI 1.92 to 2.16). Prescription generosity explained almost twice the model variation as either risk score. Compared with dabigatran, patients were more likely to fill rivaroxaban with high bleeding risk (aRR 1.16, 95% CI 1.09 to 1.24). In conclusion, patients with greater bleeding and ischemic stroke risk were more likely to initiate warfarin, but generous benefits more strongly predicted NOAC usage and drove more selection.
Project description:BACKGROUND:Cardiovascular outcomes vary between urban and rural hospitals, with worse outcomes in rural settings. OBJECTIVE:The purpose of this study was to examine whether in-hospital mortality for hospitalization for atrial fibrillation (AF) varied between urban and rural hospitals. METHODS:A cross-sectional examination of patients who were hospitalized for AF was performed in the National Inpatient Sample between 2012 and 2014 to compare in-hospital mortality in patients admitted to urban vs rural hospitals. Patients with a principal International Classification of Diseases, Ninth Revision discharge diagnosis of AF were included. Hospitals were classified as urban or rural on the basis of core-based statistical areas. In-hospital mortality was defined as death due to any cause during hospitalization. RESULTS:A total of 248,731 (mean age 69 years; 78% white; 48% women) admissions for AF were identified. Of these, 218,946 (88%) were from urban hospitals and 29,785 (12%) were from rural hospitals. Patients admitted to rural hospitals had a 17% increased risk of death as compared with those admitted to urban hospitals in a multivariable model, which accounted for differences in patient characteristics and potential confounders (odds ratio 1.17; 95% confidence interval 1.04-1.32). Similar results were obtained in a propensity score-matched analysis and in subgroup analyses by sex, race, and region. CONCLUSION:In-hospital mortality of AF is higher in rural hospitals than in urban hospitals. Further research is needed to understand this finding and to develop targeted strategies to reduce mortality in patients admitted for AF in rural hospitals.
Project description:BackgroundAtrial fibrillation (AF) prevalence estimates vary and have been based on cohorts with clinically established or diagnosed disease. Undiagnosed AF prevalence estimates are less certain as they are based on nongeneralizable convenience samples.HypothesisBecause AF is often asymptomatic, it my remain undiagnosed until the development of complications such as stroke or heart failure. Consequently, the observed prevalence of diagnosed AF from the literature may underestimate total disease burden. We therefore sought to estimate the total prevalence of both diagnosed and undiagnosed AF.MethodsWe performed a retrospective cohort study from 2012 to 2017 using data from five US medical claims data sets. Undiagnosed AF prevalence was estimated based on the observed incidence of ischemic stroke, systemic embolism (SE), and AF incidence after a stroke/SE. The diagnosed AF cohort included AF patients between Q1 2014 and Q3 2015. The undiagnosed AF cohort were patients with assumed undiagnosed AF in the year before a stroke/SE and who were newly diagnosed with AF in the 3-month poststroke/SE. Stroke/SE incidence was calculated among all AF patients and the ratio of number of undiagnosed AF patients to stroke rate was created. Age- and sex-adjusted estimates were stratified by period of assumed undiagnosed AF before poststroke/SE AF diagnosis (1 or 2 years).ResultsThe estimated US prevalence of AF (diagnosed and undiagnosed) in Q3 2015 was 5 628 000 cases, of which 591 000 cases (11%) were undiagnosed. The assumed 2-year undiagnosed AF prevalence was 23% (1 531 000) of the total prevalent patients with AF (6 568 000). Undiagnosed (vs. diagnosed) AF patients were older and had higher CHA2DS2-VASc scores. Of undiagnosed AF, 93% had CHA2DS2-VASc ≥2 and met OAC criteria.ConclusionsThese contemporary estimates demonstrate the high prevalence of undiagnosed AF in the United States. Undiagnosed AF patients are composed of primarily elderly individuals who if diagnosed, would meet criteria for stroke prevention therapy.
Project description:BACKGROUND: Despite warfarin's marked efficacy, not all eligible patients receive it for stroke prevention in AF. The aim of this meta-analysis was to evaluate the association between prescriber and/or patient characteristics and subsequent prescription of warfarin for stroke prevention in patients with atrial fibrillation (AF). METHODS: Observational studies conducted in the US using multivariate analysis to determine the relationship between characteristics and the odds of receiving warfarin for stroke prevention were identified in MEDLINE, EMBASE and a manual review of references. Effect estimates of prescriber and/or patient characteristics from individual studies were pooled to calculate odds ratios (ORs) with 95% confidence intervals. RESULTS: Twenty-eight studies reporting results of 33 unique multivariate analyses were identified. Warfarin use across studies ranged from 9.1%-79.8% (median=49.1%). There was a moderately-strong correlation between warfarin use and year of study (r=0.60, p=0.002). Upon meta-analysis, characteristics associated with a statistically significant increase in the odds of warfarin use included history of cerebrovascular accident (OR=1.59), heart failure (OR=1.36), and male gender (OR=1.12). Those associated with a significant reduction in the odds of warfarin use included alcohol/drug abuse (OR=0.62), perceived barriers to compliance (OR=0.87), contraindication(s) to warfarin (OR=0.81), dementia (OR=0.32), falls (OR=0.60), gastrointestinal hemorrhage (OR=0.47), intracranial hemorrhage (OR=0.39), hepatic (OR=0.59), and renal impairment (OR=0.69). While age per 10-year increase (OR=0.78) and advancing age as a dichotomized variable (cut-off varied by study) (OR=0.57) were associated with significant reductions in warfarin use; qualitative review of results of studies evaluating age as a categorical variable did not confirm this relationship. CONCLUSIONS: Warfarin use has increased somewhat over time. The decision to prescribe warfarin for stroke prevention in atrial fibrillation is based upon multiple prescriber and patient characteristics. These findings can be used by family practice prescribers and other healthcare decision-makers to target interventions or methods to improve utilization of warfarin when it is indicated for stroke prevention.