ALCOHOL BEVERAGE INDUSTRY TAXATION POLICIES IN FUTURE
6. CONCLUSION
In this paper we have described the progression of illnesses and addictions in connection with their treatment as discount functions by considering that the “discounted disease” depends on three possible explanatory variables, viz the level of dose, the frequency of administration and the time to assess the (non)monetary rewards, all other things being the same. The level of disease is superadditive for an interval and subadditive otherwise.
Essentially, if x∗ and x0 denote, respectively, the maximum and the optimal dose of medicine per day, the function representing the progression of the disease behaves as a discount
Figure 5 | Plotting the progression of a disease.
function with a bounded domain [0, x∗] where the x-axis now represents regular doses of the medicine or time frequencies (see Figure 5). If n:= ⌊xx∗0⌋, then the following inequalities hold (for every integer h and k such that k < n):
Fx0
h
Fx0
h
· · · Fx0
h
| {z }
h times
>F(x0)
and
F(x0)F(x0) · · · F(x0)
| {z }
k times
<F(kx0).
As such, despite the fact that in most experiments about illnesses and addiction processes data are fitted to hyperbolic discounting, we propose that the suitable adjustment must be to the so-called exponentiated hyperbolic discount function.
This reasoning can be reinforced by the idea that most medical treatments are designed to follow a regular dosage, and this would justify the shape of the discount function. In this case, the instantaneous discount rate will be increasing up to a level of the independent variable and decreasing otherwise. An explanation of this situation is provided because in most occasions impatience is measured in patients who exhibit two or more addictions, and their impulsiveness is due to two or more diseases. Consequently, if a psychopharmacological treatment for an addiction or disease
is administered based only on the impatience level shown by a patient, there could be a problem of excessive dosage. This is because impatience or excessive discounting is a trans-disease process (as indicated byBickel et al., 2012) underlying addiction and other disorders and disease-related behavior which needs to be correctly assessed.
It should be noted that our study is a complement to the conventional economic theory of addiction (Becker and Murphy, 1988) in that our model proposes more bio-psychologically plausible characteristics for the decay of the biological influences of drug consumption after “cold turkey” (abstinence) proposed as exponential “depreciation” processes in Becker’s model.
AUTHOR CONTRIBUTIONS
All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.
ACKNOWLEDGMENTS
This paper has been partially supported by the project
“La sostenibilidad del sistema nacional de salud: reformas, estrategias y propuestas,” reference: DER2016-76053-R, Ministry of Economy and Competitiveness. We are very grateful for the comments and suggestions provided by two referees.
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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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PERSPECTIVE published: 17 August 2016 doi: 10.3389/fphar.2016.00252
Edited by:
Mihajlo (Michael) Jakovljevic, Faculty of Medical Sciences University of Kragujevac, Serbia Reviewed by:
Domenico Criscuolo, Genovax, Italy Stefano Giovagnoli, University of Perugia, Italy
*Correspondence:
Georgi Iskrov [email protected]
Specialty section:
This article was submitted to Pharmaceutical Medicine and Outcomes Research, a section of the journal Frontiers in Pharmacology Received: 06 June 2016 Accepted: 02 August 2016 Published: 17 August 2016 Citation:
Iskrov G, Dermendzhiev S, Miteva-Katrandzhieva T and Stefanov R (2016) Health Economic Data in Reimbursement of New Medical Technologies: Importance of the Socio-Economic Burden as a Decision-Making Criterion.
Front. Pharmacol. 7:252.
doi: 10.3389/fphar.2016.00252
Health Economic Data in
Reimbursement of New Medical Technologies: Importance of the Socio-Economic Burden as a Decision-Making Criterion
Georgi Iskrov1,2*, Svetlan Dermendzhiev3, Tsonka Miteva-Katrandzhieva1,2and Rumen Stefanov1,2
1Department of Social Medicine and Public Health, Faculty of Public Health, Medical University of Plovdiv, Plovdiv, Bulgaria,
2Institute for Rare Diseases, Plovdiv, Bulgaria,3Section of Occupational Diseases and Toxicology, Second Department of Internal Medicine, Faculty of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria
Background: Assessment and appraisal of new medical technologies require a balance between the interests of different stakeholders. Final decision should take into account the societal value of new therapies.
Objective: This perspective paper discusses the socio-economic burden of disease as a specific reimbursement decision-making criterion and calls for the inclusion of it as a counterbalance to the cost-effectiveness and budget impact criteria.
Results/Conclusions: Socio-economic burden is a decision-making criterion, accounting for diseases, for which the assessed medical technology is indicated. This indicator is usually researched through cost-of-illness studies that systematically quantify the socio-economic burden of diseases on the individual and on the society. This is a very important consideration as it illustrates direct budgetary consequences of diseases in the health system and indirect costs associated with patient or carer productivity losses. By measuring and comparing the socio-economic burden of different diseases to society, health authorities and payers could benefit in optimizing priority setting and resource allocation. New medical technologies, especially innovative therapies, present an excellent case study for the inclusion of socio-economic burden in reimbursement decision-making. Assessment and appraisal have been greatly concentrated so far on cost-effectiveness and budget impact, marginalizing all other considerations. In this context, data on disease burden and inclusion of explicit criterion of socio-economic burden in reimbursement decision-making may be highly beneficial. Realizing the magnitude of the lost socio-economic contribution resulting from diseases in question could be a reasonable way for policy makers to accept a higher valuation of innovative therapies.
Keywords: health technology assessment, reimbursement, decision-making, cost-effectiveness, burden of disease, socio-economic burden, cost-of-illness, rare diseases
Iskrov et al. Socio-Economic Burden as a Decision-Making Criterion
INTRODUCTION
The balance between the value of a health technology and the effective access to it represents an important issue of today’s health policy. Assessment and appraisal of new medical technologies is a debate of political priorities, health system specifics and societal expectations. In all countries, choices in the allocation of resources are necessary. Health technology assessment (HTA) has been introduced as a concept to address rising health care costs and growing fiscal concerns (Iskrov and Stefanov, 2016). Health economic data play a crucial role in this process and the subsequent reimbursement decision-making (Jakovljevic and Getzen, 2016).
Health technology assessment systematically explores the properties and effects of a health technology, evaluating direct, and intended effects, as well as indirect and unintended consequences. These factors include safety, efficacy, effectiveness, cost, cost-effectiveness, as well as expected social, legal, ethical, and political impacts. There is a growing consensus on the importance of balancing all these criteria, which are determining the impact of a health technology on the healthcare system. In this context, the progress in medical research and development requires innovation of HTA process too. HTA should be updated in order to respond to such challenges, as innovative health technologies pose new critical factors, which affect patients, payers and providers (Panzitta et al., 2015).