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Hepatology. 2016 Oct;64(4):1331-42. doi: 10.1002/hep.28527. Epub 2016 Apr 4.

Effective but costly: How to tackle difficult trade-offs in evaluating health improving technologies in liver diseases.

Author information

1
Research Center on Public Health, University of Milan-Bicocca, Monza, Italy. lorenzo.mantovani@unimib.it.
2
Research Center on Public Health, University of Milan-Bicocca, Monza, Italy.
3
Section of Digestive Diseases, International Center for Digestive Health, Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.
4
Liver Center & Section of Digestive Diseases, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT.

Abstract

In the current context of rising health care costs and decreasing sustainability, it is becoming increasingly common to resort to decision analytical modeling and health economics evaluations. Decision analytic models are analytical tools that help decision makers to select the best choice between alternative health care interventions, taking into consideration the complexity of the disease, the socioeconomic context, and the relevant differences in outcomes. We present a brief overview of the use of decision analytical models in health economic evaluations and their applications in the area of liver diseases. The aim is to provide the reader with the basic elements to evaluate health economic analysis reports and to discuss some limitations of the current approaches, as highlighted by the case of the therapy of chronic hepatitis C. To serve its purpose, health economics evaluations must be able to do justice to medical innovation and the market while protecting patients and society and promoting fair access to treatment and its economic sustainability.

CONCLUSION:

New approaches and methods able to include variables such as prevalence of the disease, budget impact, and sustainability into the cost-effectiveness analysis are needed to reach this goal. (Hepatology 2016;64:1331-1342).

PMID:
26926906
DOI:
10.1002/hep.28527
[Indexed for MEDLINE]

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