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Background Determinants of long‐term survival after sudden cardiac arrest (SCA) are not fully elucidated. We investigated the impact of patients' socioeconomic status (SES) on long‐term mortality in SCA survivors. Objective To investigate the association between SES, as estimated by median household income by zip code of residence, and long‐term survival after SCA. Methods We analyzed the electronic medical records of patients who presented to our institution with SCA between 2000 and 2012 and were discharged alive. Patients were stratified into quartiles by median household income of their home zip code. Baseline characteristics of patients were compared by income quartiles. The impact of SES on mortality was assessed using a multivariable Cox proportional hazards model incorporating all unbalanced covariates. Results Our cohort consisted of 1420 patients (mean age of 62 years; 41% men; 82% white). Over a 3.6‐year median follow‐up, 47% of patients died. After adjusting for unbalanced baseline covariates, patients in the poorest income quartile had a 25% increase in their risk of death compared to other SCA survivors (hazard ratios = 1.25, 95% confidence interval 1.00‐1.56, P = .046). Conclusion In conclusion, lower SES is an independent predictor of long‐term mortality in survivors of SCA. Designing interventions to improve survival after SCA requires attention to patients' social and economic factors.

We analyzed the association between social vulnerability index (SVI) and healthcare access among patients with atherosclerotic cardiovascular disease (ASCVD). Using cross-sectional data from the Behavioral Risk Factor Surveillance System 2016 to 2019, we identified measures related to healthcare access in individuals with ASCVD, which included healthcare coverage, presence of primary care clinician, duration since last routine checkup, delay in access to healthcare, inability to see doctor because of cost, and cost-related medication nonadherence. We analyzed the association of state-level SVI (higher SVI denotes higher social vulnerability) and healthcare access using multivariable-adjusted logistic regression models. The study population comprised 203,347 individuals aged 18 years or older who reported a history of ASCVD. In a multivariable-adjusted analysis, prevalence odds ratios (95% confidence interval) for participants residing in states in the third tertile of SVI compared with those in the first tertile (used as reference) were as follows: absence of healthcare coverage = 1.03 (0.85 to 1.24), absence of primary care clinician = 1.33 (1.12 to 1.58), >1 year since last routine checkup = 1.09 (0.96 to 1.23), delay in access to healthcare = 1.39 (1.18, 1.63), inability to see a doctor because of cost = 1.21 (1.06 to 1.40), and cost-related medication nonadherence = 1.10 (0.83 to 1.47). In conclusion, SVI is associated with healthcare access in those with pre-existing ASCVD. Due to the ability of SVI to simultaneously and holistically capture many of the factors of social determinants of health, SVI can be a useful measure for identifying high-risk populations.

Background Atrial fibrillation (AF) affects millions of Americans each year and can lead to high levels of resource utilization through emergency department (ED) visits and inpatient stays. Hypothesis We hypothesized that referral of patients to a dedicated Center for AF from the ED would reduce costs of care. Methods The University of Pittsburgh Center for AF serves as a rapid referral center for patients with AF to avoid unnecessary inpatient admissions and provide specialized care. Patients that presented to the ED with AF and met prespecified criteria were directed to rapid outpatient follow‐up instead of inpatient admission. The primary outcome of interest was 30‐day total costs. Secondary outcomes included outpatient costs, inpatient costs, 90‐day costs, and inpatient stay characteristics. Results We identified 96 patients (median age 65, 38% women) referred to the center for AF for a new diagnosis of AF between October 2017 and December 2019 and matched 96 control patients. After 30 days of follow‐up, patients referred to the center for AF had a lower average cost ( $619 vs. $ 1252, p < 0.001) compared to controls, driven by lower costs of ED care tempered by slightly higher outpatient costs. Thirty‐day admissions and lengths of stay were also lower. These differences were persistent at 90 days. Conclusion Directing patients with AF that present to the ED to follow‐up at a dedicated Center for AF significantly reduced overall costs, while reducing subsequent inpatient admissions and total lengths of stay in the hospital.