Drivers of hospitalisation trends for non-valvular atrial fibrillation in Western Australia, 2000-2013. 2019

Courtney Weber, and Joseph Hung, and Siobhan Hickling, and Ian Li, and Brendan McQuillan, and Tom Briffa
School of Population and Global Health, The University of Western Australia, Crawley, Western Australia, Australia. Electronic address: Courtney.weber@uwa.edu.au.

OBJECTIVE To determine if increasing hospitalisations for non-valvular atrial fibrillation (NVAF) in Western Australia (WA) was due to incident (first-ever) or repeat hospitalisations, an ageing population structure, changing procedural practice or a combination of these factors. METHODS We conducted a longitudinal retrospective population study on all WA residents aged 25-94 years between 2000 and 2013, with a principal hospital discharge diagnosis of NVAF. Person-linked hospital morbidity and mortality records were used to measure annual rate ratios (RRs) and 95% confidence intervals (CIs) in the total and incident NVAF (25-94 years) hospitalisations, further stratified by sex and by age-specific standardised groups (25-44, 45-64, 65-75, 75-84, 85-94 years). RESULTS There were 55,532 total hospitalisations for NVAF between 2000 and 2013, patient mean age 68.3 years, and 58% male. Annual age- and sex- standardised rates for total NVAF hospitalisation increased by 3.0%/year (RR 1.030; 95%CI; 1.028, 1.038), and in both men and women. The largest absolute increase in hospitalisation rate occurred in those aged 85-94 years (∆613/100,000 men and women combined). Incident NVAF hospitalisations showed a borderline decline of 0.5%/year (RR 0.99; 95%CI; 0.99, 1.0) with a statistically significant trend in women but not men. The rate of AF admissions associated with a catheter ablation increased by 13%/year (95%CI; 13.1%, 15.3%). CONCLUSIONS The increasing rates of total hospitalisation for NVAF is driven more by repeat than incident admissions, escalating hospitalisations in the very elderly, and more frequent interventional procedures. These drivers have major economic and healthcare planning implications.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D011159 Population Surveillance Ongoing scrutiny of a population (general population, study population, target population, etc.), generally using methods distinguished by their practicability, uniformity, and frequently their rapidity, rather than by complete accuracy. Surveillance, Population
D005260 Female Females
D005500 Follow-Up Studies Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease. Followup Studies,Follow Up Studies,Follow-Up Study,Followup Study,Studies, Follow-Up,Studies, Followup,Study, Follow-Up,Study, Followup
D006760 Hospitalization The confinement of a patient in a hospital. Hospitalizations
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D000369 Aged, 80 and over Persons 80 years of age and older. Oldest Old

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