OBJECTIVES: The aim of this study was to examine a predictive model using features related to the diabetes type 2 risk factors. METHODS: The data were obtained from a database in a diabetes control system in Tabriz, Iran. The data included all people referred for diabetes screening between 2009 and 2011. The features considered as “Inputs” were: age, sex, systolic and diastolic blood pressure, family history of diabetes, and body mass index (BMI). Moreover, we used diagnosis as “Class”. We applied the “Decision Tree” technique and “J48” algorithm in the WEKA (3.6.10 version) software to develop the model. RESULTS: After data preprocessing and preparation, we used 22,398 records for data mining. The model precision to identify patients was 0.717. The age factor was placed in the root node of the tree as a result of higher information gain. The ROC curve indicates the model function in identification of patients and those individuals who are healthy. The curve indicates high capability of the model, especially in identification of the healthy persons. CONCLUSIONS: We developed a model using the decision tree for screening T2DM which did not require laboratory tests for T2DM diagnosis.

This review study aimed to compare the electronic prescription systems in five selected countries (Denmark, Finland, Sweden, England, and the United States). Compared developed countries were selected by the identified selection process from the countries that have electronic prescription systems. Required data were collected by searching the valid databases, most widely used search engines, and visiting websites related to the national electronic prescription system of each country and also sending E-mails to the related organizations using specifically designed data collection forms. The findings showed that the electronic prescription system was used at the national, state, local, and area levels in the studied countries and covered the whole prescription process or part of it. There were capabilities of creating electronic prescription, decision support, electronically transmitting prescriptions from prescriber systems to the pharmacies, retrieving the electronic prescription at the pharmacy, electronic refilling prescriptions in all studied countries. The patient, prescriber, and dispenser were main human actors, as well as the prescribing and dispensing providers were main system actors of the Electronic Prescription Service. The selected countries have accurate, regular, and systematic plans to use electronic prescription system, and health ministry of these countries was responsible for coordinating and leading the electronic health. It is suggested to use experiences and programs of the leading countries to design and develop the electronic prescription systems.

Introduction: Mobile health is an emerging technology around the world that can be effective in cancer screening. This study aimed to examine the effectiveness of mobile health applications on cancer screening. Methods: We conducted a systematic literature review of studies related to the use of mobile health applications in cancer screening. We also conducted a comprehensive search of articles on cancer screening related to the use of mobile health applications in journals published between January 1, 2008, and January 31, 2019, using 5 databases: IEEE, Scopus, Web of Science, Science Direct and PubMed. Results: A total of 23 articles met the inclusion criteria and were included in the present review. All studies have identified positive effects of applications on cancer screening and clinical health outcomes. Furthermore, more than half of mobile applications had multiple functions such as providing information, planning and education. Moreover, most of the studies, which examined the satisfaction of patients and quality improvement, showed healthcare application users have significantly higher satisfaction of living and it leads to improving quality. Conclusion: This study found that the use of mobile health applications has a positive impact on health-related behaviours and outcomes. Application users were more satisfied with applying mobile health applications to manage their health condition in comparison with users who received conventional care.