title: Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data.
abstract: Cystic fibrosis (CF) is a progressive disease with treatments intensifying as patients get older and severity worsens. To inform policy makers about the cost burden in CF, it is crucial to understand what factors influence the costs and how they affect the costs. Based on 1,060 observations (from 731 patients) obtained from the Australian Data Registry, individual annual health care costs were calculated and a regression analysis was carried out to examine the impact of multiple variables on the costs. A method of retransformation and a hypothetical patient were used for cost analysis. We show that an additional one unit improvement of FEV1pp (i.e., forced expiratory volume in 1 s as a percentage of predicted volume) reduces the costs by 1.4%, or for a hypothetical patient whose FEV1pp is 73 the cost reduction is A$252. The presence of chronic infections increases the costs by 69.9-163.5% (A$12,852-A$30,047 for the hypothetical patient) depending on the type of infection. The type of CF genetic mutation and the patient's age both have significant effects on the costs. In particular, being homozygous for p.F508del increases the costs by 26.8% compared to all the other gene mutations. We conclude that bacterial infections have a very strong influence on the costs, so reducing both the infection rates and the severity of the condition may lead to substantial cost savings. We also suggest that the patient's genetic profile should be considered as an important cost determinant.
authors.affiliation: Centre for Health Economics, Monash University, Level 2, Building 75, Clayton, Melbourne, VIC, 3800, Australia, yuanyuan.gu@monash.edu.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Gu
authors.forename: Sonia
authors.initials: S
authors.lastname: García-Pérez
authors.forename: John
authors.initials: J
authors.lastname: Massie
authors.forename: Kees
authors.initials: K
authors.lastname: van Gool
mesh_terms: D000328:Adult; D000367:Age Factors; D001315:Australia; D001424:Bacterial Infections / Q000150:complications / Q000191:economics; D002908:Chronic Disease / Q000191:economics; D003198:Computer Simulation; D003550:Cystic Fibrosis / Q000191:economics* / Q000235:genetics / Q000382:microbiology; D005260:Female; D005541:Forced Expiratory Volume; D017048:Health Care Costs / Q000706:statistics & numerical data; D006760:Hospitalization / Q000191:economics; D006801:Humans; D008297:Male; D055624:Methicillin-Resistant Staphylococcus aureus; D012042:Registries; D012044:Regression Analysis; D013203:Staphylococcal Infections / Q000150:complications / Q000191:economics; D055815:Young Adult
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