Costs associated with heart failure with preserved versus reduced ejection fraction a retrospective population-based cohort study in Sweden

• Published in: European journal of heart failure Vol. 19; no. S1; p. 346
• Main Authors: Boman, Kurt, Lindmark, K., Stalhammar, J., Wikstrom, G., Bergman, G. J., Tornblom, M., Costa-Scharplatz, M., Wirta, S. Bruce, Olofsson, Mona
• Format: Journal Article
• Language: English
• Published: 2017
• ISSN: 1879-0844; 1388-9842
• DOI: 10.1002/ejhf.833

Background and purpose: To implement cost-effective management programmes, it is important to understand the costs associated with heart failure (HF) with preserved (HFpEF) versus reduced (HFrEF) ejection fraction. We aimed to estimate direct costs associated with HFpEF and HFrEF using population data from two Swedish counties. Methods: Patients with HF were identified via electronic medical records (EMRs) from primary and/or secondary care in Västerbotten, linked via unique identifiers to data from the National Patient Register and Swedish Prescribed Drug Register. Local echocardiography data were used to identify HFpEF (defined as ejection fraction ≥50%) and HFrEF (defined as <50%). Patients aged ≥18 years with ≥2 diagnoses of HF between 01/01/2010 and 31/03/2015 and an ICD-10 diagnostic code of I50 (inclusive of all granular codes), I42.0, I42.6, I42.7, I42.9, I110, I130 or I132 in any position were included. Patients were followed from date of first diagnosis (index date) to end of study period or EMR collection, date of death or loss to follow-up for other reasons, whichever came first. Unadjusted all-cause and cardiovascular disease (CVD)-related (defined by ICD-10 codes) costs associated with secondary care were estimated based on diagnosis-related group codes and price lists. Costs of drug use and comorbidities were available in Uppsala only; impact of the latter on total costs was assessed using a multiple Gamma regression model. Results: In total, 8702 patients with HF were identified. HF phenotype was known in 3167 patients: 35.4% had HFpEF and 64.6% had HFrEF. Patients with HFpEF were older (mean±SD: 74.2±12.6 vs 69.9±13.7 years) and had a higher Charlson comorbidity index (1.83 vs 1.65) than those with HFrEF. Total all-cause costs dropped substantially after 1 year after diagnosis. CVD-related costs followed the same pattern, and comprised 85.9% and 89.6% of total costs over 4 years after diagnosis for patients with HFpEF and HFrEF, respectively. Inpatient costs, which accounted for ˜90% of total costs, generally decreased over time, whereas outpatient all-cause and CVD-related costs (accounting for ˜10%) tended to increase over time, especially for patients with HFpEF (Figure). In Uppsala, drug use in the year after diagnosis cost SEK 18171.0 and 11109.7 per patient with HFpEF and HFrEF, respectively. Furthermore, anaemia, cancer, chronic kidney disease, chronic obstructive pulmonary disease, diabetes, hypotension and aortic insufficiency were significant drivers of all-cause costs in the year after diagnosis (all p<0.05) in the Uppsala cohort. Conclusions: This analysis highlights the substantial economic burden of HFpEF and HFrEF. Costs were highest in the first year after diagnosis, and were driven by inpatient costs due to CVD and other comorbidities.