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Cost-of-illness analysis and regression modeling in cystic fibrosis: a retrospective prevalence-based study

T. Mlčoch, J. Klimeš, L. Fila, V. Vávrová, V. Skalická, M. Turnovec, V. Krulišová, J. Jirčíková, D. Zemková, KV. Dědečková, A. Bílková, V. Frühaufová, L. Homola, Z. Friedmannová, R. Drnek, P. Dřevínek, T. Doležal, M. Macek,

. 2017 ; 18 (1) : 73-82. [pub] 20160107

Jazyk angličtina Země Německo

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc17031874

Grantová podpora
NT13770 MZ0 CEP - Centrální evidence projektů

Digitální knihovna NLK
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NLK ProQuest Central od 2001 do Před 1 rokem
Medline Complete (EBSCOhost) od 2002-03-01 do Před 1 rokem
Health & Medicine (ProQuest) od 2001 do Před 1 rokem
Health Management Database (ProQuest) od 2001 do Před 1 rokem
Public Health Database (ProQuest) od 2001 do Před 1 rokem

BACKGROUND: Economic data pertaining to cystic fibrosis (CF), is limited in Europe generally, and completely lacking in Central and Eastern Europe. We performed an analysis of all direct costs associated with CF relative to key disease features and laboratory examinations. METHODS: A retrospective prevalence-based cost-of-illness (COI) study was performed in a representative cohort of 242 CF patients in the Czech Republic, which represents about 65 % of all Czech CF patients. Medical records and invoices to health insurance companies for reference year 2010 were analyzed. RESULTS: The mean total health care costs were €14,486 per patient, with the majority of the costs going towards medicinal products and devices (€10,321). Medical procedures (€2676) and inpatient care (€1829) represented a much smaller percentage of costs. A generalized linear model showed that the strongest cost drivers, for all cost categories, were associated with patient age and lung disease severity (assessed using the FEV1 spirometric parameter), when compounded by chronic Pseudomonas aeruginosa airway infections. Specifically, maximum total costs are around the age 16 years; a FEV1 increase of 1 % point represented a cost decrease of: 0.9 % (medicinal products), 1.7 % (total costs), 2.8 % (procedures) and 7.0 % (inpatient care). CONCLUSIONS: COI analysis and regression modeling using the most recent data available can provide a better understanding of the overall economic CF burden. A comparison of our results with other methodologically similar studies demonstrates that although overall costs may differ, FEV1 can nonetheless be utilized as a generally transferrable indicator of the relative economic impact of CF.

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