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

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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.

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Notes

  1. These studies were identified through a snowballing approach which started from a list of papers identified in the literature reviews conducted by Krauth et al. [19], van Gool et al. [34], and Heimeshoff et al. [12]. Several rounds of searching were conducted until no extra studies could be found.

  2. The Shapiro–Wilk test tends to reject normality when the sample size is large and our study is based on a relatively large sample (n = 1,060). Visualisation of the residuals did not show significant deviation from normality.

  3. The hypothetical patient was created based on the sample means of independent variables.

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Acknowledgments

This project was funded by an Early Career Research Grant at the University of Technology Sydney and a National Health and Medical Research Council Health Services Research Capacity Building Grant (No. 571926). We would like to thank the patients, their parents, and Cystic Fibrosis Australia for providing access to the registry data. We would also like to thank Geoff Sims for facilitating access. The use of the Australian Cystic Fibrosis Data Registry was approved by the Sydney South West Area Health Service Ethics Review Committee.

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None of the authors have any conflict of interests that are relevant to the content of the paper.

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Correspondence to Yuanyuan Gu.

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Gu, Y., García-Pérez, S., Massie, J. et al. Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data. Eur J Health Econ 16, 709–717 (2015). https://doi.org/10.1007/s10198-014-0621-5

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  • DOI: https://doi.org/10.1007/s10198-014-0621-5

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