| Title |
Cost-of-illness analysis and regression modeling in cystic fibrosis: a retrospective prevalence-based study
|
|---|---|
| Published in |
HEPAC Health Economics in Prevention and Care, January 2016
|
| DOI | 10.1007/s10198-015-0759-9 |
| Pubmed ID | |
| Authors |
Tomáš Mlčoch, Jiří Klimeš, Libor Fila, Věra Vávrová, Veronika Skalická, Marek Turnovec, Veronika Krulišová, Jitka Jirčíková, Dana Zemková, Klára Vilimovská Dědečková, Alena Bílková, Vladimíra Frühaufová, Lukáš Homola, Zuzana Friedmannová, Radovan Drnek, Pavel Dřevínek, Tomáš Doležal, Milan Macek |
| Abstract |
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. 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. 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). 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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 22% |
| Student > Ph. D. Student | 6 | 16% |
| Researcher | 5 | 14% |
| Student > Bachelor | 3 | 8% |
| Other | 3 | 8% |
| Other | 7 | 19% |
| Unknown | 5 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 7 | 19% |
| Medicine and Dentistry | 6 | 16% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Business, Management and Accounting | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 9 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 January 2016.
All research outputs
#16,046,765
of 25,373,627 outputs
Outputs from HEPAC Health Economics in Prevention and Care
#856
of 1,303 outputs
Outputs of similar age
#218,213
of 400,073 outputs
Outputs of similar age from HEPAC Health Economics in Prevention and Care
#13
of 23 outputs
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