Impact of Atrial Fibrillation Burden on Health Care Costs and Utilization.

BACKGROUND: Integrating patient-specific cardiac implantable electronic device (CIED)-detected atrial fibrillation (AF) burden with measures of health care cost and utilization allows for an accurate assessment of the AF-related impact on health care use. OBJECTIVES: The goal of this study was to assess the incremental cost of device-recognized AF vs no AF; compare relative costs of paroxysmal atrial fibrillation (pAF), persistent atrial fibrillation (PeAF), and permanent atrial fibrillation (PermAF) AF; and evaluate rates and sources of health care utilization between cohorts. METHODS: Using the de-identified Optum Clinformatics U.S. claims database (2015-2020) linked with the Medtronic CareLink database, CIED patients were identified who transmitted data ≥6 months postimplantation. Annualized per-patient costs in follow-up were analyzed from insurance claims and adjusted to 2020 U.S. dollars. Costs and rates of health care utilization were compared between patients with no AF and those with device-recognized pAF, PeAF, and PermAF. Analyses were adjusted for geographical region, insurance type, CHA2DS2-VASc score, and implantation year. RESULTS: Of 21,391 patients (mean age 72.9 ± 10.9 years; 56.3% male) analyzed, 7,798 (36.5%) had device-recognized AF. The incremental annualized increased cost in those with AF was $12,789 ± $161,749 per patient, driven by increased rates of health care encounters, adverse clinical events associated with AF, and AF-specific interventions. Among those with AF, PeAF was associated with the highest cost, driven by increased rates of inpatient and outpatient hospitalization encounters, heart failure hospitalizations, and AF-specific interventions. CONCLUSIONS: Presence of device-recognized AF was associated with increased health care cost. Among those with AF, patients with PeAF had the highest health care costs. Mechanisms for cost differentials include both disease-specific consequences and physician-directed interventions.

Geographic Variation in Influenza Vaccination Disparities Between Hispanic and Non-Hispanic White US Nursing Home Residents.

Background: Disparities in influenza vaccination exist between Hispanic and non-Hispanic White US nursing home (NH) residents, but the geographic areas with the largest disparities remain unknown. We examined how these racial/ethnic disparities differ across states and hospital referral regions (HRRs). Methods: This retrospective cohort study included >14 million short-stay and long-stay US NH resident-seasons over 7 influenza seasons from October 1, 2011, to March 31, 2018, where residents could contribute to 1 or more seasons. Residents were aged ≥65 years and enrolled in Medicare fee-for-service. We used the Medicare Beneficiary Summary File to ascertain race/ethnicity and Minimum Data Set assessments for influenza vaccination. We calculated age- and sex-standardized percentage point (pp) differences in the proportions vaccinated between non-Hispanic White and Hispanic (any race) resident-seasons. Positive pp differences were considered disparities, where the proportion of non-Hispanic White residents vaccinated was greater than the proportion of Hispanic residents vaccinated. States and HRRs with ≥100 resident-seasons per age-sex stratum per racial/ethnic group were included in analyses. Results: Among 7 442 241 short-stay resident-seasons (94.1% non-Hispanic White, 5.9% Hispanic), the median standardized disparities in influenza vaccination were 4.3 pp (minimum, maximum: 0.3, 19.2; n = 22 states) and 2.8 pp (minimum, maximum: -3.6, 10.3; n = 49 HRRs). Among 6 758 616 long-stay resident-seasons (93.7% non-Hispanic White, 6.5% Hispanic), the median standardized differences were -0.1 pp (minimum, maximum: -4.1, 11.4; n = 18 states) and -1.8 pp (minimum, maximum: -6.5, 7.6; n = 34 HRRs). Conclusions: Wide geographic variation in influenza vaccination disparities existed across US states and HRRs. Localized interventions targeted toward areas with high disparities may be a more effective strategy to promote health equity than one-size-fits-all national interventions.