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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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