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Information Literacy Among Undergraduate Students Of Health Services Administration In Ahvaz Jundishapur University Of Medical Sciences Based On SCONUL Seven Pillars Model: 2013
Farzad Faraji Khiavi , Mansour Zahiri , Kambiz Ahmadi Angali , Bahareh Mirzaei , Mohammad Veisi, Marjan Arab Rahmatipour ,
Volume 8, Issue 2 (7-2014)
Abstract

 Background and Aim: Information literacy is a set of skills required to identify rightful information resources and access to them. These skills are empowering goal oriented use of information resources. This study aimed to determine the ability rate of information literacy among health services administration students in Jundishapur University of Medical Sciences based on SCONUL seven pillars model.  

 Materials and Methods: This cross-sectional descriptive-analytic study was conducted using a questionnaire developed based on SCONUL information literacy seven pillars model. Validity of the questionnaire was confirmed through content analysis and coefficient of Chronbach’s alpha was 0.93. The study population included students of health services administration in Ahvaz Jundishapur University of Medical Sciences in 2013. The sample size included 40 cases collected randomly. Data analyzed through SPSS descriptive statistics and non-parametric statistical tests.

 Results: The mean score for the studied components of information literacy abilities among the study population was 0.5±0.43. Information Literacy score among freshmen was significantly different from other students (P<0.03). Students who passed Computer Basics and Research Methodology educational courses showed significant differences from other students in the information management (P<0.01).

 Conclusion: Given the increasing development in information technology, the need to develop information literacy skills is considerable especially among those who are going to be engaged in the health sector. Although studied students’ information literacy estimated relatively well, it seems necessary to take measures to improve their information literacy in all components.

 


Medical Laboratory Director Competencies: State of the Basic Medical Sciences and Global Perspective
Mohammad Erfan Zare, Reza Meshkani, Mojtaba Abbasi, Farhad Shaveisi Zadeh, Atefeh Nasir Kansestani ,
Volume 11, Issue 3 (Supplement 1 2017)
Abstract
Background and Aim: There has been a long-lasting debate among medical laboratory-associated specialists about required competencies and educational background to qualify for directing medical laboratories in Iran. The aim of this study was to provide a comprehensive review regarding required training and competencies for becoming a medical laboratory director in Iran and all around the world.
Materials and Methods: A thorough search of the literature was carried out in scientific databases including Web of Science, Science Direct, Springer Link, Wiley Online, PubMed, Scopus, SID and web-based search engines such as Google and Google Scholar.
Results: The results revealed detailed required competencies for directing medical laboratories in the United States of America, Canada, European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and its many affiliated European countries.
Conclusion: Our results indicate that in all assessed countries, specialists of basic medical sciences and also physicians, after passing certifying examinations, are equally qualified to direct medical laboratories. Indeed, Iran is the only country within the evaluated ones, in which basic medical sciences specialists (which have their own specific curriculum and are educated as clinical majors) have been eliminated from directing medical laboratory and the position has almost exclusively been available for graduates of pathology and it is important to revise this approach.

Educational Needs Assessment of Health Information Technology Professionals: A Cross-Sectional Study in Hospitals in Western Iran
Taleb Khodaveisi, Hamid Bouraghi, Tooba Mehrabi, Javad Faradmal, Mahdiye Shojaei Baghini, Ali Mohammadpour,
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: Identifying the educational needs of health information technology staff is essential before implementing any continuous education programs. This comprehensive study investigates these needs among health information technology personnel working in hospitals in the Hamadan province, considering both the general and specialized aspects of the field.
Materials and Methods: This descriptive cross-sectional study was conducted across 11 hospitals affiliated with Hamadan University of Medical Sciences. The study population comprised staff from the reception, medical records, statistics, and coding departments. Data were gathered using a validated and reliable standardized questionnaire. Collection methods included both in-person and remote approaches. Data analysis was performed using SPSS software, with results reported through descriptive and inferential statistics, specifically utilizing the Kruskal-Wallis test.
Results: The results of this study showed that among the generally accepted needs, items such as information technology (96.7%), legal aspects of medical records (87.6%), and communication skills (76.7%) had the highest percentage. Additionally, educational needs varied across different units: Coding unit staff required more training in the principles of diagnosis documentation (92.9%), familiarity with the coding guidelines for causes of death (85.7%), and familiarity with the coding guidelines for procedures (85.7%), statistics unit staff needed training in statistical software, and reception and medical records staff required education on relevant regulations. There was also a significant correlation between educational needs and certain individual characteristics such as work experience, education level, gender, and field of study.
Conclusion: The study results indicate that designing effective educational programs for health information technology staff requires consideration of individual characteristics, such as gender, work experience, and education level. Additionally, the training should be continuous, tailored to the distinct needs of each group, and delivered at appropriate intervals.

Applications and Role of Artificial Intelligence in the Management of Cardiac Diseases: A Systematic Review of Persian Research Studies
Mozhgan Farazmand, Mandana Asgari, Hamid Bouraghi, Taleb Khodaveisi, Ali Mohammadpour, Soheila Saeedi,
Volume 19, Issue 3 (9-2025)
Abstract
Background and Aim: Cardiovascular diseases have a very high prevalence globally and are recognized as one of the main causes of mortality worldwide. Artificial intelligence, as a novel technology, has garnered attention in recent years in Iran and other parts of the world for the management of a wide variety of diseases. The present study aimed to systematically review research studies conducted in the field of applying artificial intelligence in cardiovascular diseases.
Materials and Methods: To investigate research studies conducted in the field of cardiovascular diseases utilizing artificial intelligence, the Persian language databases SID, Google Scholar, and Magiran were searched. This search was conducted without time limitations on April 3, 2024 and included all research studies that, up to this date, had used various artificial intelligence methods in the field of cardiovascular diseases in the present systematic review.
Results: The results of the search in the aforementioned three databases led to the retrieval of 17,819 research studies, of which 46 research studies met the inclusion and exclusion criteria of the study. These research studies had used artificial intelligence in three areas: prediction, treatment, and diagnosis. Neural networks (n=22), support vector machines (n=20), and decision trees (n=16) were the algorithms that were used more than other techniques. The data sources of the included research studies were mainly patient medical records and the UCI database. Additionally, MATLAB software was used more than other software. The most frequently mentioned limitations in the research studies included not considering all factors, limited access to data, insufficient data, the presence of noise in signals or images, and the presence of outliers, missing values, and non-normality of data.
Conclusion: The systematic review of research studies conducted in the field of cardiovascular diseases utilizing artificial intelligence showed that this technology has been used in a wide range of cardiovascular diseases, and most of the conducted research studies confirmed its effectiveness and successful performance.

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