Cost of illness of cystic fibrosis in Germany: results from a large cystic fibrosis centre

Pharmacoeconomics. 2012 Sep 1;30(9):763-77. doi: 10.2165/11588870-000000000-00000.


Background: Cystic fibrosis (CF) is the most common life-shortening genetic disorder among Whites worldwide. Because many of these patients experience chronic endobronchial colonization and have to take antibiotics and be treated as inpatients, societal costs of CF may be high. As the disease severity varies considerably among patients, costs may differ between patients.

Objectives: Our objectives were to calculate the average total costs of CF per patient and per year from a societal perspective; to include all direct medical and non-medical costs as well as indirect costs; to identify the main cost drivers; to investigate whether patients with CF can be grouped into homogenous cost groups; and to determine the influence of specific factors on different cost categories.

Methods: Resource utilization data were collected for 87 patients admitted to an inpatient unit at a CF treatment centre during the first 6 months of 2004 and 125 patients who visited the centre's CF outpatient unit during the entire year. Fifty-four patients were admitted to the hospital and also visited the outpatient unit. Since all patients were exclusively treated at the centre, data could be aggregated. Costs that varied greatly between patients were measured per patient. The remaining costs were summarized as overhead costs and allocated on the basis of days of treatment or contacts per patient. Costs of the outpatient and inpatient units and costs for drugs patients received at the outpatient pharmacy were summarized as direct medical costs. Direct non-medical costs (i.e. travel expenses), as well as indirect costs (i. e. absence from work, productivity losses), were also included in the analysis. Main cost drivers were detected by the analysis of different cost categories. Patients were classified according to a diagnosis-related severity model, and median comparison tests (Wilcoxon-Mann-Whitney tests) were performed to investigate differences between the severity groups. Generalized least squares (GLS) regressions were used to identify variables influencing different cost categories. A sensitivity analysis using Monte Carlo simulation was performed.

Results: The mean total cost per patient per year was &U20AC;41 468 (year 2004 values). Direct medical costs accounted for more than 90% of total costs and averaged &U20AC;38 869 (&U20AC;3876 to &U20AC;88 096), whereas direct non-medical costs were minimal. Indirect costs amounted to &U20AC;2491 (6% of total costs). Costs for drugs patients received at the outpatient pharmacy were the main cost driver. Costs rose with the degree of severity. Patients with moderate and severe disease had significantly higher direct costs than the relatively milder group. Regression analysis revealed that direct costs were mainly affected by the diagnosis-related severity level and the expiratory volume; the coefficient indicating the relationship between costs for mild CF patients and other patients rose with the degree of severity. A similar result was obtained for drug costs per patient as the dependent variable. Monte Carlo simulation suggests that there is a 90% probability that annual costs will be lower than &U20AC;37 300.

Conclusions: The share of indirect costs as a percentage of total costs for CF was rather low in this study. However, the relevance of indirect costs is likely to increase in the future as the life expectancy of CF patients increases, which is likely to lead to a rising work disability rate and thus increase indirect costs. Moreover we found that infection with Pseudomonas aeruginosa increases costs substantially. Thus, a decrease of the prevalence of P. aeruginosa would lead to substantial savings for society.

MeSH terms

  • Adolescent
  • Adult
  • Ambulatory Care / economics
  • Child
  • Child, Preschool
  • Cystic Fibrosis / drug therapy
  • Cystic Fibrosis / economics*
  • Cystic Fibrosis / therapy*
  • Drug Costs / statistics & numerical data
  • Economics, Pharmaceutical
  • Female
  • Germany
  • Health Care Costs* / statistics & numerical data
  • Hospitalization / economics
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Young Adult