How to prioritize health policies by understanding a spectrum of complete health to death
Anita Taft 1, H. Rahavi 2, Alexander S Taft 3 *
1 Basis Independent Silicon Valley CA, USA2 Pediatrician, Alborz University of Medical Sciences, Karaj, IRAN3 Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA, USA
* Corresponding Author
  • Article Type: Research Article
  • Eurasian Journal of Biosciences, 2020 - Volume 14 Issue 1, pp. 105-110
  • Published Online: 29 Feb 2020
  • Article Views: 63 | Article Download: 70
  • Open Access Full Text (PDF)
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Taft A, Rahavi H, Taft AS. How to prioritize health policies by understanding a spectrum of complete health to death. Eurasia J Biosci. 2020;14(1), 105-110.

APA 6th edition
In-text citation: (Taft et al., 2020)
Reference: Taft, A., Rahavi, H., & Taft, A. S. (2020). How to prioritize health policies by understanding a spectrum of complete health to death. Eurasian Journal of Biosciences, 14(1), 105-110.

Chicago
In-text citation: (Taft et al., 2020)
Reference: Taft, Anita, H. Rahavi, and Alexander S Taft. "How to prioritize health policies by understanding a spectrum of complete health to death". Eurasian Journal of Biosciences 2020 14 no. 1 (2020): 105-110.

Harvard
In-text citation: (Taft et al., 2020)
Reference: Taft, A., Rahavi, H., and Taft, A. S. (2020). How to prioritize health policies by understanding a spectrum of complete health to death. Eurasian Journal of Biosciences, 14(1), pp. 105-110.

MLA
In-text citation: (Taft et al., 2020)
Reference: Taft, Anita et al. "How to prioritize health policies by understanding a spectrum of complete health to death". Eurasian Journal of Biosciences, vol. 14, no. 1, 2020, pp. 105-110.

Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Taft A, Rahavi H, Taft AS. How to prioritize health policies by understanding a spectrum of complete health to death. Eurasia J Biosci. 2020;14(1):105-10.

Abstract

The effect of various health and illness status on society, has always been a matter of interest to public health researchers and policy makers. Specific mortality rate is a simple image of overall burden of a disease, but it only considers the fatality of a disease. Regarding this lack of representativeness, other indices are developed to investigate the burden of various diseases. Two of the most commonly used include Quality Adjusted Life Years (QALY) and Disability Adjusted Life Years (DALY). In both indices, in addition to mortality, other effects of a disease are introduced. Death is considered as zero quality or maximal disability but Weighting is used to quantify the non fatal effects of disease. QALY was developed earlier than DALY. This index is mostly used in cost utility studies to determine the necessity of a desired intervention. DALY index was introduced later to clarify calculations. DALY is calculated at the national and global level by the support of World Health Organization (WHO) regularly. However there are some different ways to calculate DALY, WHO promotes its standard method which has gone through some changes in years. QALY is an index of expected health (higher is better) but DALY is an index showing distance to an ideal health (lower is better). In this study we aim to investigate and compare the use of these two indices in public health studies.

Keywords

quality adjusted life years disability adjusted life years burden of disease

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