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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Iranian Journal of Medical Sciences
- نوع مقاله: Journal Article
- کلمات کلیدی: Informatics,Telemedicine,Warfare,Stress Disorders, Traumatic
- چکیده:
- چکیده انگلیسی: Background: Physical limitations, distance, and time are major obstacles to access to mental health services for veterans and soldiers. This study was aimed at comparing the efficacy of telepsychiatry and face-to-face consultation as methods of treating post-traumatic stress disorder (PTSD). The comparison was based on treatment costs, access to health services, completion of therapy sessions, and patient satisfaction as variables.Methods: This research was a double blinded clinical trial supported by Tabriz University of Medical Sciences and conducted in 2015 to 2016 in Tabriz, Iran. Totally, 60 patients were included in the study. Through simple randomization, the patients were divided into experimental and control groups, both of whom were treated through face-to-face consultations for the first 3 sessions. Six follow-up sessions were then held remotely with the experimental group and face to face with the control group. Data were collected using a self-designed and reliable questionnaire and entered in SPSS, version 16. Intergroup comparisons were performed using descriptive statistical measures. Finally, the results were tested using the t test method. Results: A significant relationship was found between the use of information technology and increased patient satisfaction, completion of therapy sessions, and reduction in treatment costs; however, no significant difference was found between the groups in terms of reduction in waiting time and access to a psychiatrist.Conclusion: Telepsychiatry is an effective means of delivering mental health services to psychiatric outpatients living in remote areas with limited resources. The results provide preliminary support for the use of telepsychiatry in treating PTSD and improving access to care.Trial Registration Number: IRCT2016020826449N1
- انتشار مقاله: 04-05-1396
- نویسندگان: Yousef Haghnia,Taha Samad-Soltani,Mahmood Yousefi,Habib Sadr,Peyman Rezaei-Hachesu
- مشاهده
- جایگاه : پژوهشی
- مجله: Iranian Journal of Medical Sciences
- نوع مقاله: Journal Article
- کلمات کلیدی: Iran,Drug resistance,Microbial,Global Health,Dataset,Biosurveillance
- چکیده:
- چکیده انگلیسی: Background: Success of infection treatment depends on the availability of accurate, reliable, and comprehensive data, information, and knowledge at the point of therapeutic decision-making. The identification of a national minimum data set will support the development and implementation of an effective surveillance system. The goal of this study was to develop a national antimicrobial resistance surveillance minimum data set. Methods: In this cross-sectional and descriptive study, data were collected from selected pioneering countries and organizations which have national or international antimicrobial resistance surveillance systems. A minimum data set checklist was extracted and validated. The ultimate data elements of the minimum data set were determined by applying the Delphi technique.Results: Through the Delphi technique, we obtained 80 data elements in 8 axes. The resistance data categories comprised basic, clinical, electronic reporting, infection control, microbiology, pharmacy, World Health Organization-derived, and expert-recommended data. Relevance coding was extracted based on the Iranian electronic health record coding system. Conclusion: This study provides a set of data elements and a schematic framework for the implementation of an antimicrobial resistance surveillance system. A uniform minimum data set was created based on key informants’ opinions to cover essential needs in the early implementation of a global antimicrobial resistance surveillance system in Iran.
- انتشار مقاله: 22-11-1395
- نویسندگان: Reza Safdari,Marjan Ghazi Saeedi,Hossein Masoumi-Asl,Peyman Rezaei-Hachesu,Kayvan Mirnia,Niloofar Mohammadzadeh,Taha Samad-Soltani
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: cancer,Data mining,Knowledge,lung neoplasms,Informatics
- چکیده:
- چکیده انگلیسی:
Background: Data mining, a new concept introduced in the mid-1990s, can help researchers to gain new, profound insights and facilitate access to unanticipated knowledge sources in biomedical datasets. Many issues in the medical field are concerned with the diagnosis of diseases based on tests conducted on individuals at risk. Early diagnosis and treatment can provide a better outcome regarding the survival of lung cancer patients. Researchers can use data mining techniques to create effective diagnostic models. The aim of this study was to evaluate patterns existing in risk factor data of for mortality one year after thoracic surgery for lung cancer. Methods: The dataset used in this study contained 470 records and 17 features. First, the most important variables involved in the incidence of lung cancer were extracted using knowledge discovery and datamining algorithms such as naive Bayes, maximum expectation and then, using a regression analysis algorithm, a questionnaire was developed to predict the risk of death one year after lung surgery. Outliers in the data were excluded and reported using the clustering algorithm. Finally, a calculator was designed to estimate the risk for one-year post-operative mortality based on a scorecard algorithm. Results: The results revealed the most important factor involved in increased mortality to be large tumor size. Roles for type II diabetes and preoperative dyspnea in lower survival were also identified. The greatest commonality in classification of patients was Forced expiratory volume in first second (FEV1), based on levels of which patients could be classified into different categories. Conclusion: Development of a questionnaire based on calculations to diagnose disease can be used to identify and fill knowledge gaps in clinical practice guidelines.- انتشار مقاله: 19-11-1395
- نویسندگان: Peyman Rezaei Hachesu,Nazila Moftian,Mahsa Dehghani,Taha Samad-Soltani
- مشاهده