Showing 5 results for Health
Dr Abolfazl Shahabadi, Dr Mohamad Kazem Naziri, Nima Nilforoushan,
Volume 3, Issue 9 (10-2012)
Abstract
Parties and candidates in the election campaign try to raise the community to vote for them by offering a variety of social policies. However, the public health expenditures have been raised among the candidates as one of the most important tools to attract votes. Thus, this study uses panel data to investigate whether the components of electoral cycle have affected the growth of public health expenditures in both developed and developing countries over the period of 1994-2010. Using the related tests, two methods of static panel (random effects) and dynamic panel estimation were selected. According to the results, the presence of electoral cycles could not be rejected in both types of countries. Based on these results, politicians in every country increase the public health expenditures before the election in hopes of gaining a greater share of people's votes.
Narges Samadpoor, Mostafa Emadzade, Homayoun Rangbar, Firozeh Azizi,
Volume 5, Issue 15 (3-2014)
Abstract
The growth of non-communicable diseases, and the enormous costs of health care, has led policy makers to focus on “education”, as an effective instrument to improve the public health. Recent empirical studies show that education can improve health and increase life expectancy via ameliorating the life style. The main objective of this paper is to investigate the effect of education on health in Iran over the period of 1974- 2010. Health production function is defined based on the Grossman (1972) model. The empirical model has been estimated by using co-integration technique and error correction model. Separation of short and long-term effects and estimate of impact by education’s temporary and permanent lag time changes on health is considered the innovation aspect of this research. The results of model estimation indicate that there is a positive and long-term equilibrium relationship between health and education. Based on evidence obtained, education plays a key role in health improvement. Empowering people by investment in their education can prevent many non-communicable diseases. Diseases that are imposed by our incorrect life style. Today we believe that an active participation of elementary and high schools, higher education, and mass media can ameliorate the health statue of society.
Hosein Panahi, Firouz Fallahu, Ali Imani, Sima Nasibparast,
Volume 9, Issue 31 (3-2018)
Abstract
In recent decades, unnecessary growth in health expenditures of developing countries, and the importance of physicians' behavior in health market, have made investigating determinants of health expenditure on the one hand and the theory of physician induced demand (PID) on the other, as two of the most important issues in health economics. Therefore, using data collected through filling out information collection forms by psychiatrists and patients of East Azarbayjan in 2016 and employing hierarchical linear modeling methods (HLM), this study, examines the determinants of the average expenditure of each visit to a doctor and investigates the theory of PID within psychiatrists in the East Azarbayjan province. The results show that in psychiatry, although psychiatrists are “doctors tend to profit”, there is no physician induced demand. Results also indicate that patiant’s income, patiant’s education level, and condition of illness have significant effects on the average expenditure of each visit to a doctor. According to these results, it is suggested that in order to reduce unnecessary health expenditure, patient information on medical care should be increased, and government monitoring and control over the national health system must be increased.
Zahra Mehranfard, Amirhossein Mozayani, Abbas Asari Arani, Lotfali Agheli,
Volume 13, Issue 47 (5-2022)
Abstract
The corona pandemic is a phenomenon that has caused a crisis in the world due to its rapid spread and unstoppable nature. This crisis, however, seems to have a purely medical and health-related nature. But it is a multidimensional phenomenon which effects and consequences can be studied and evaluated in various fields.The purpose of this study is to propose an appropriate approach in implementing the choice experiment method from the perspective of heterogeneity expressed in individuals’ preferences. In the present study, using the choice experiment method, the factors influencing the selection of individuals from the options of the selection sets (including mental illness, unemployment, change in social activities, family problems, concerns about social discriminations) have been identified. Because in choice experiment some respondents may not consider all the features or levels provided; This causes heterogeneity in the behavior of respondents. To investigate the effect of this heterogeneity on the selection process of different individuals in the sample population (Tehran), in this study, a new approach of endogenous attribute attendance in the logit model was used. The information required for the research was obtained by completing 384 questionnaires completely randomly by different people in 2021. The results of estimating the two logit models in terms of endogenous attribute attendance (EAA) and conditional logit indicate that the average tendency to Payment for features defined in the model (EAA) is higher than the conditional logit model.
Because the EAA model considers the probabilities of the absence of certain features in individuals' preferences, it will have reliable results for estimating the willingness to pay.
, Abbas Khandan,
Volume 14, Issue 52 (9-2023)
Abstract
Purpose: The aim of this study is to identify and classify insurance customers in order to identify the target population for increasing the profitability of insurance companies, achieving a balance in premium payments, and examining the health questionnaire as an indicator of policyholders' preferences. Moreover, designing a marketing strategy to optimize advertising efficiency.
Method: In this paper, five machine learning algorithms, namely Decision Tree, Random Forest, Support Vector Machine, Naive Bayes, and Logistic Regression, are used to classify customers into two categories: profit-generating and loss-generating. Data from a private insurance company is utilized, consisting of 2,897 observations collected from December 1400 to December 1401.
Findings: By utilizing machine learning methods and focusing on the target population, the chances of success can be increased. The presence of a small number of individuals who significantly reduce the profitability of insurance companies is evident. The pre-existing medical conditions of individuals have a considerable impact on their insurance usage and the damage caused to insurance companies.
Conclusion: Machine-learning methods can provide a comprehensive understanding of insurance customers and their needs. By identifying the target population, insurance companies can increase their profitability and satisfy their customers by addressing their specific demands
