Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. This disorder, in addition to its main symptoms, creates significant difficulties in education, social performance, and personal relationships. Given the importance of rehabilitation for these patients to combat the above issues, the use of virtual reality (VR) technology is helpful. The aim of this study was to highlight the opportunities for VR in the rehabilitation of children with ADHD. This narrative review was conducted by searching for articles in scientific databases and e-Journals, using keywords including VR, children, and ADHD. Various studies have shown that VR capabilities in the rehabilitation of children with ADHD include providing flexibility in accordance with the patients' requirements; removing distractions and creating an effective and safe environment away from real-life dangers; saving time and money; increasing patients' incentives based on their interests; providing suitable tools to perform different behavioral tests and increase ecological validity; facilitating better understanding of individuals' cognitive deficits and improving them; helping therapists with accurate diagnosis, assessment, and rehabilitation; and improving working memory, executive function, and cognitive processes such as attention in these children. Rehabilitation of children with ADHD is based on behavior and physical patterns and is thus suitable for VR interventions. This technology, by simulating and providing a virtual environment for diagnosis, training, monitoring, assessment and treatment, is effective in providing optimal rehabilitation of children with ADHD.

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Clinical decision support systems are interactive computer systems for situational decision making and can improve decision efficiency and safety of care. We investigated the role of these systems in enhancing prehospital care. This narrative review included full-text articles published since 2000 that were available in databases/e-journals including Web of Science, PubMed, Science Direct, and Google Scholar. Search keywords included "clinical decision support system," "decision support system," "decision support tools," "prehospital care," and "emergency medical services." Non-journal articles were excluded. We revealed 14 relevant studies that used such a support system in prehospital emergency medical service. Owing to the dynamic nature of emergency situations, decision timing is critical. Four key factors demonstrated the ability of clinical decision support systems to improve decision-making, reduce errors, and improve the safety of prehospital emergency activity: computer-based, offer support as a natural part of the workflow, provide decision support in the time and place of decision making, and offer practical advice. The use of clinical decision support systems in prehospital care resulted in accurate diagnoses, improved patient triage and patient outcomes, and reduction of prehospital time. By improving emergency management and rescue operations, the quality of prehospital care will be enhanced.

Introduction:In order to better designing of electronic health record system in Iran, integration of health information systems based on a common language must be done to interpret and exchange this information with this system is required.Background:This study provides a conceptual model of radiology reporting system using unified modeling language. The proposed model can solve the problem of integration this information system with the electronic health record system. By using this model and design its service based, easily connect to electronic health record in Iran and facilitate transfer radiology report data.Methods:This is a cross-sectional study that was conducted in 2013. The study population was 22 experts that working at the Imaging Center in Imam Khomeini Hospital in Tehran and the sample was accorded with the community. Research tool was a questionnaire that prepared by the researcher to determine the information requirements. Content validity and test-retest method was used to measure validity and reliability of questioner respectively. Data analyzed with average index, using SPSS. Also Visual Paradigm software was used to design a conceptual model.Result:Based on the requirements assessment of experts and related texts, administrative, demographic and clinical data and radiological examination results and if the anesthesia procedure performed, anesthesia data suggested as minimum data set for radiology report and based it class diagram designed. Also by identifying radiology reporting system process, use case was drawn.Conclusion:According to the application of radiology reports in electronic health record system for diagnosing and managing of clinical problem of the patient, with providing the conceptual Model for radiology reporting system; in order to systematically design it, the problem of data sharing between these systems and electronic health records system would eliminate.

Background: Hospital Information System (HIS) is implemented to provide high-quality patient care. The aim of this study is to identify significant dimensional factors that influence the hospital decision in adopting the HIS. Methods: This study designs the initial integrated model by taking the three main dimensions in adopting HIS technology. Accordingly, DEMATEL was utilized to test the strength of interdependencies among the dimensions and variables. Then ANP approach is adapted to determining how the factors are weighted and prioritized by professionals and main users working in the Iranian public hospitals, involved with the HIS system. Results: The results indicated that "Perceived Technical Competence" is a key factor in the Human dimension. The respondents also believed that "Relative Advantage," "Compatibility" and "Security Concern" of Technology dimension should be further assessed in relation to other factors. With respect to Organization dimension, "Top Management Support" and "Vendor Support" are considered more important than others. Conclusion: Applying the TOE and HOT-fit models as the pillar of our developed model with significant findings add to the growing literature on the factors associated with the adoption of HIS and also shed some light for managers of public hospitals in Iran to successfully adopt the HIS.

Introduction:Lack of proper diagnosis and inadequate treatment of asthma, leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma.Methods:The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson’s coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique.Results:According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different modes was made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases.Conclusion:Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. So considering the data mining approaches due to the nature of medical data is necessary.

Background The present study aimed to determine the prevalence of work-related musculoskeletal symptoms (WMSs), identify potential factors associated with WMSs, and determine the association between WMSs and fatigue among nurses. Methods This cross-sectional study was carried out among 500 Iranian nurses. Data was gathered by the 1) Persian version of the Nordic musculoskeletal questionnaire (P-NMQ) to examine WMSs, and 2) Persian version of the Multidimensional Assessment of Fatigue (P-MAF) Scale to evaluate fatigue among the study population. Then, data was analyzed by SPSS version 21 using the χ2 test, multiple logistic regression for detection of potential factors associated with WMSs, and multiple linear regression for detection of potential factors associated with fatigue. Results Ankles/feet, lower back, knees, and shoulders had the highest prevalence of WMSs among nurses within the last 12 months prior to the study. Independent variables including age, job tenure, gender, smoking, shift work, and type of employment were significantly associated with WMSs in different body regions with odds ratios (ORs) ranging from 1.635–2.835. Moreover, WMSs in some body regions were associated with subscales of fatigue and total fatigue. Conclusions Ergonomic and organizational interventions for fitting the job to the nurses considering demographic/occupational characteristics are highly essential to improve musculoskeletal system health and relieve fatigue.

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