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Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data

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  • Yuanyuan Gu
  • Sonia García-Pérez
  • John Massie
  • Kees Gool

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. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Yuanyuan Gu & Sonia García-Pérez & John Massie & Kees Gool, 2015. "Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(7), pages 709-717, September.
  • Handle: RePEc:spr:eujhec:v:16:y:2015:i:7:p:709-717
    DOI: 10.1007/s10198-014-0621-5
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    References listed on IDEAS

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    1. Daniela Eidt-Koch & Thomas Wagner & Thomas Mittendorf & J.-Matthias Schulenburg, 2010. "Outpatient medication costs of patients with cystic fibrosis in Germany," Applied Health Economics and Health Policy, Springer, vol. 8(2), pages 111-118, March.
    2. Manning, Willard G. & Basu, Anirban & Mullahy, John, 2005. "Generalized modeling approaches to risk adjustment of skewed outcomes data," Journal of Health Economics, Elsevier, vol. 24(3), pages 465-488, May.
    3. Kees Van Gool & Richard Norman & Martin B Delatycki & Jane Hall & John Massie, 2011. "Understanding the costs of care for cystic fibrosis: an analysis by age and severity. CHERE Working Paper 2011/1," Working Papers 2011/1, CHERE, University of Technology, Sydney.
    4. Clements, Michael P. & Hendry, David F. (ed.), 2011. "The Oxford Handbook of Economic Forecasting," OUP Catalogue, Oxford University Press, number 9780195398649.
    5. Mareike Heimeshoff & Helge Hollmeyer & Jonas Schreyögg & Oliver Tiemann & Doris Staab, 2012. "Cost of Illness of Cystic Fibrosis in Germany," PharmacoEconomics, Springer, vol. 30(9), pages 763-777, September.
    6. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
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    Cited by:

    1. Tomáš Mlčoch & Jiří Klimeš & Libor Fila & Věra Vávrová & Veronika Skalická & Marek Turnovec & Veronika Krulišová & Jitka Jirčíková & Dana Zemková & Klára Vilimovská Dědečková & Alena Bílková & Vladimí, 2017. "Cost-of-illness analysis and regression modeling in cystic fibrosis: a retrospective prevalence-based study," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(1), pages 73-82, January.

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