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Ranking the Cities of Sistan and Baluchestan Province Based on Health and Treatment Indices Using the TOPSIS Method
Mohamad Reza Shahraki, Nastaran Abbasi Hasanabadi,
Volume 12, Issue 6 (Feb & Mar 2019)
Abstract
Background and Aim: One of the important dimensions of access to health services is uniform distribution. A survey on the distribution of health and treatment indices in different regions reveals inequalities in order to reduce inequalities. The study aims to rank the cities of Sistan and Baluchestan province from the perspective of access to healthcare services.
Materials and Methods: This is a descriptive-applied and cross-sectional study. The data were collected from the database of Statistical Center of Iran. The studied indices were weighted by Shannon entropy method, and the ranking of cities was done by TOPSIS method. The distribution of health services among the cities was shown by Spearman and Kendall correlation coefficient. Also, with the coefficient of variation, the important indices for creating imbalances were determined.
Results: The results of TOPSIS method showed a significant difference between the levels of access to health services indices. Zabol and Zahedan cities ranked first and second, and the cities of Ghasreghand, Sibsuran and Fanuj were in the last rank, respectively. Among the factors that led to a level difference, the number of PhDs, laboratory sciences doctors and rehabilitation centers caused the greatest difference between the cities. The findings show that there is little correlation between demographic rank and access to healthcare services, and health services are not distributed equitably according to the population.
Conclusion: More attention to cities that are ranked below the level of access to healthcare resources is needed. More healthcare resources should be given to this province because there are few healthcare indices relative to its population.

Evaluation of Data Mining Algorithms for Detection of Liver Disease
Mohammad Reza Shahraki , Mahboubeh Mesgar,
Volume 13, Issue 1 (Apr & May 2019)
Abstract
Background and Aim: The liver, as one of the largest internal organs in the body, is responsible for many vital functions including purifying and purifying blood, regulating the body's hormones, preserving glucose, and the body. Therefore, disruptions in the functioning of these problems will sometimes be irreparable. Early prediction of these diseases will help their early and effective treatment. Regarding the importance of liver diseases and increasing number of patients, the present study, using data mining algorithms, aimed to predict liver disease.
Materials and Methods: This descriptive study was performed using 721 data from liver patient in zahedan. In this study, after preprocessing data, data mining techniques such as SVM: Support Vector Machine, CHAID, Exhaustive CHAID and boosting C5.0, data were analyzed using IBM SPSS Modeler 18 data mining software.
Result: The validity obtained for boosting C5.0 94/09, for Exhaustive CHAID algorithm 88/71, for SVM 87/09, for CHAID algorithm 85/47 prediction of liver disease. the boosting C5.0 algorithm showed a better performance of this algorithm among other algorithms.
Conclusion: According to the rules created by boosting C5.0 algorithm, for a new sample, one can predict the likelihood of a person for developing liver disease with high precision.

The Effect of Socioeconomic Factors on Household Health Expenditures: Heckman Two-Step Method
Mahdi Shahraki, Simin Ghaderi,
Volume 13, Issue 2 (Jun & Jul 2019)
Abstract
Background and Aim: Due to the high level of out-of-pocket payments for health expenditures and the importance of household health expenditure management, this study aimed to investigate socioeconomic factors affecting Iranian urban households’ health expenditures.
Materials and Methods: This descriptive-analytic and applied study was conducted cross-sectionally at national level with microeconomic approach. The sample included 18809 urban households living in Iran's provinces in 2016; they were selected by three-stage sampling method. Data were collected by the household income-expenditure questionnaire of Statistical Center of Iran (SCI). The results were evaluated in Stata 14 software using Heckman two-step method.
Results: The results showed that socioeconomic factors such as increasing of income and insurance expenditures, having insurance, number of employed people, head's literacy, increasing of per capita expenditures of tobacco and education led to an increase in household health expenditures. Mother-headed households had lower health expenditures than others; and head of household’s age, household size, and the presence of elderly persons led to an increase in household health expenditures.
Conclusion: Household socio-economic factors not only affected the decision to enter health market but also influenced the purchase of goods and health services and inequality in health sector. Therefore, certain policies are essential to improve the socio-economic status towards reducing inequality in health sector; such a thing can be achieved through employment creation, growth of income, investment in education, and increase of insurance coverage.

Forecasting of Physicians Supply and Demand in Medical Sciences Universities of Iran
Mahdi Shahraki, Simin Ghaderi,
Volume 14, Issue 4 (Oct & Nov 2020)
Abstract
Background & Aim: Physicians as human capital and resources are one of the main components of health production. The imbalance of physician supply and demand affects the health and economics. Therefore, this study aimed to estimate and forecast the supply and demand of physician working in Iranian medical universities.
Materials and Methods: This a descriptive-analytical and applied study was conducted at national level for Iran during 1991-2017. The statistical population was physicians working in Iranian medical universities. ARIMA method was used to estimate and forecast physician supply and Vector Error Correction Models was used for physician demand. The data is annual time series that was extracted from the statistical yearbooks of the Statistical Center of Iran and the World Bank database. Eviews 10 software was used to estimate the models.
Results: The results showed that physician demand in Iran was affected by Gross Domestic Product, age structure and hospital beds, and according to the forecast of supply and demand of physicians, we will be faced to the physician shortage in the years 2018-2030.
Conclusion: In the coming years, Iran is facing with physician shortage. Therefore, it is recommended to adopt policies to increase physician capacity in medical universities and to increase strong incentives to retain physicians and prevent their migration.

Development of Iranian Provinces in Terms of Health Indicators Using Weighted Centrality and Numerical Taxonomy Methods
Mohammad Reza Shahraki, Motahare Fallah,
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: The healthcare sector plays an important role in the development of communities by ensuring the health of individuals in each community and can have many social and economic effects on the lives of individuals in the community. The purpose of this study was to determine the development of the country’s provinces based on health facilities and the level of access to these facilities, to find solutions to reduce differences between different parts of the country.
Materials and Methods: This study was an applied study with a descriptive-analytical approach. In this study, 31 provinces of the country have been studied in terms of 10 indicators. Data and information of this study were extracted from the national statistical yearbook and ranked using Center-weighted index method by using Excel software. Then, using taxonomy method, the degree of development of the provinces has been determined. 
Results: The results of the study show that South Khorasan province with a centrality index of 45,692 is in the first place, Yazd province with a centrality index of 43,933 is in the second place and Ilam province with a centrality index of 40,668 is in the third place. East Azerbaijan province with a centrality index of 27,375 is ranked 29th, Qom province with a centrality index of 25,417 is ranked 30th and Hormozgan province with a centrality index of 24,286 is ranked 31st. The degree of development of the provinces is between 0.507 to 0.98, which in terms of development of Yazd province is in the first rank and Hormozgan province is in the last rank.
Conclusion: The results show that there is a deep gap between the provinces in terms of development and access to health indicators; Therefore, it needs more attention and adopt the necessary policies and plans to reduce this gap.

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