Health Policy Model: Long-term Predictive Results Associated With The Management Of HCV-Induced Diseases In Italy

Francesco Saverio Mennini, Andrea Marcellusi (), Massimo Andreoni (), Antonio Gasbarrini (), Salvatore Salomone () and Antonio Craxì ()
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Massimo Andreoni: School of Medicine, University of Rome Tor Vergata, Rome
Antonio Gasbarrini: Catholic University of the Sacred Heart of Rome
Salvatore Salomone: University of Catania
Antonio Craxì: University of Palermo

No 308, CEIS Research Paper from Tor Vergata University, CEIS

Abstract: Background: This study is aimed at describing the epidemiological and economic burden that HCV will generate in the next few years in Italy. Furthermore, the impact that future anti-HCV treatments may have on the burden of disease was considered. The analysis has been developed over the period 2013-2030 from the Italian National Health Service (NHS) perspective. Methods: A published system dynamic model was adapted for Italy in order to quantify the HCV-infected population, the disease progression and the associated cost from 1950 to 2030. The model structure was based on transition probabilities reflecting the natural history of the disease. In order to estimate the efficacy of current anti-HCV treatment strategies for different Genotypes, it was estimated the sustained virological response (SVR) rate in registration clinical trials for both Boceprevir and Telaprevir. It was assumed that the efficacy for patients treated with peginterferon+ribavirin was equal to the placebo arm of randomized clinical trial (RCT) relating to Boceprevir and Telaprevir. According to the aim of the study, only direct healthcare costs (hospital admissions, drugs, treatment and care of patients) incurred by the Italian NHS have been included in the model. Costs have been extrapolated by the published scientific literature available in Italy and actualized at 2011 ISTAT Price Index system for monetary revaluation. Three different scenario was assumed in order to evaluate the impact of future anti-HCV treatments may have on the burden of disease. Results: Overall, in Italy 1.2 million infected subjects were estimated in 2012. Out of these, about 211 thousand patients were diagnosed, while about 11,800 subjects are actually being treated with anti-HCV drugs. A reduction of healthcare costs is associated with a prevalence decrease. Indeed, once the spending peak is reached during this decade (about € 527 million), the model predicts a cost reduction in the following 18 years. In 2030, due to the more effective treatments currently available, the direct healthcare cost associated with the management of HCV patients HCV may reach € 346 million (-34.3% compared to 2012). The first scenario (new treatment in 2015 with SVR = 90% and same number of treated patients) was associated with a significant reduction in HCV-induced clinical consequences (prevalence = -3%) and a decrease in healthcare direct expenses corresponding to € 11.1 million. The second scenario (increasing treated patients until 12,790) produced an incremental cost reduction of € 7.3 million, reaching a net decrease equal to € 18.4 million. In the third scenario (treated patients = 16,770), a higher net healthcare direct cost decrease vs the base-case (€ 44.0 million ) was estimated. Conclusions: This study does not have the pretension of being or creating a model of epidemiological projection. Its primary objective is to supply data and a careful consideration for a encourage dialogue among the different professionals fully involved in the management of patients with HCV-induced chronic infection, and to suggest a valuable tool for future health policy strategy. Running head: Long-term predictive HCV-induced diseases cost in Italy

Keywords: Cost of Illness; Chronic Hepatitis; Forecast; New HCV treatment (search for similar items in EconPapers)
JEL-codes: H68 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2014-02-17, Revised 2014-02-17
New Economics Papers: this item is included in nep-hea
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Citations: View citations in EconPapers (3)

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