Search published articles


Showing 3 results for Maleki
Investigating the Effect of Having Health Insurance on the Utilization of Outpatient Services Provided by Physicians Based on the Data of the Utilization of Health Services Survey
Zhaleh Abdi, Iraj Harirchi, Mahshad Goharimehr, Elham Ahmadnezhad, Rezvaneh Alvandi, Elham Abdalmaleki,
Volume 1, Issue 3 (12-2018)
Abstract
Introduction: One of the most important measures to ensure achieving Universal Health Coverage (UHC) is expanding health insurance coverage to all population. Accordingly, the present study was conducted with the aim of investigating the effect of having health insurance on the utilization of outpatient services provided by physicians using the data of the utilization of health services survey (2015).
Methods: This study is a secondary analysis of the utilization of health services survey data that was conducted in two groups of the insured and uninsured to examine the differences between these two groups in outpatient healthcare utilization provided by physicians. The variables were insurance status as an independent variable and the number of physician visit as a dependent variable. This analysis was disaggregated by place of residence and income.
Results: The visit per capita for outpatient services was lower in all uninsured groups. The visit per capita in insured people was almost two times more than that of uninsured individuals, which was 4.25 and 2.61 among insured and uninsured individuals, respectively. Therefore, the lack of basic health insurance decreased the utilization of outpatient services by 50 percent. General physician visits per capita for insured people living in urban and rural areas were 11.2 and 0.35, respectively.
Conclusions: Based on the results of this study, the visit per capita is directly related to the insurance status of the individuals. Therefore, it is necessary to ensure the equity in utilization of outpatient services provided by the physicians among various groups of population.

Futures Study of Corporate Governance With the Scenario Planning Approach Focusing on Healthcare Companies
Rohollah Esmaeili, Mohammad Hasan Maleki, Reza Gholami Jamkarani, Azadeh Maddahi,
Volume 6, Issue 4 (Winter 2024)
Abstract
Introduction: The current study seeks to identify drivers and future scenarios of corporate governance in health companies.
Methods: The current research is practical in terms of orientation and its methodology is mixed. The theoretical community of the research are active experts in the capital market and corporate governance. The sampling method was done in a judgmental manner according to the expertise. The number of samples was equal to 10 people. The drivers of the research were obtained through literature review and interviews with experts. Screening and prioritization of drivers was done using two questionnaires, expert assessment and prioritization. These questionnaires were analyzed with two methods, fuzzy Delphi and Marcus.
Results: 24 drivers were obtained through literature review and 7 drivers were obtained through interviews with experts. Among the drivers of the research, 10 drivers had a diffusion number higher than 0.7 and were selected for the final ranking. The degree of priority of drivers screened with Marcus and considering three indicators of experts' expertise, severity of importance and degree of certainty was determined. The drivers, policies of governments regarding economic corruption and monitoring regulations of the TSE were respectively the most important drivers and were used to formulate research scenarios. To strengthen the research scenarios, the components of the root definition tool were used. The scenarios were: glass room, weak mechanisms, scattered world and dark room.
Conclusion: The practical proposals of the research were presented according to the ideal scenario (glass room). In this context, suggestions such as improving the organizational culture, strengthening the administrative organization, developing decision support systems for ranking health companies and continuously revising the corporate governance rules according to the necessities of business will help to improve corporate governance in the long term.

Early Detection of Autism Spectrum Disorder Using Machine Learning
Shabnam Akhoundi Yazdi, Amin Janghorbani Poudeh, Ali Maleki,
Volume 7, Issue 3 (Autumn 2024)
Abstract
Introduction: Autism is classified as a developmental disorder and primarily disrupts social interactions and communication. This disorder has no definitive treatment, making early diagnosis crucial for mitigating its effects. The purpose of this study is to identify autistic individuals based on the recorded information of their walking pattern by Kinect sensor.
Methods: In this research, the machine learning method was employed to identify autistic individuals based on recorded joint position data during walking, recorded by the Kinect sensor. First, a group of statistical features was extracted from the Kinect data, which included joint positions and the angles between them. Then, the extracted features were evaluated using the statistical test of analysis of variance, and the optimal features were selected. Finally, classification was performed by decision tree classifier.
Results: In this research, the classification of healthy and autistic individuals was done by the decision tree classification and 42 optimal features selected based on statistical analysis, and the accuracy of classification was 85%. The sensitivity and specificity obtained in this classification are 88 and 82%, respectively.
Conclusion: According to the classification results, this research was able to achieve acceptable accuracy by using the low dimension feature vector obtained by statistical analysis. This research, shows autistic individuals can be classified from healthy people only by having the position of several joints. It is suggested researches in future, using this method for measurement the recovery rate or control autism in patient after performing treatment methods.

Page 1 from 1     

© 2025 CC BY-NC 4.0 | Iranian Journal of Health Insurance

Designed & Developed by : Yektaweb