Farahnaz Sadoughi; Khadijeh Moulaei
Abstract
Introduction: Health care systems are known as complex systems, which are difficult to analyze and reengineer. Health system engineers often rely on Unified Modeling Language (UML) to model and simulate various parts of these systems. The purpose of the current study was to identify the most widely used ...
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Introduction: Health care systems are known as complex systems, which are difficult to analyze and reengineer. Health system engineers often rely on Unified Modeling Language (UML) to model and simulate various parts of these systems. The purpose of the current study was to identify the most widely used and least-practicable UML diagrams as well as the range of applications of this language in the field of health care for documenting, analyzing, and designing an efficient system.Methods: The study was a systematize review. All the articles related to UML applications in the field of health care were extracted from March 2010 to July 2017 using valid keywords from the Web of Science, PubMed, ProQuest, and Elsevier Scopus databases. After screening, 48 articles were selected and analyzed via two 12-hours concurrent sessions.Results: Three diagrams of class, activity, and use case were the most usable UML diagrams, and four diagrams of component, collaboration, object, and profile were the least used diagrams in designing and modeling in various fields of health care, respectively. In addition, in the domain of applications, infrastructure group, disease management, and knowledge discovery had the highest use of UML, respectively.Conclusion: Considering the fact that UML applications scopes over all aspects of the system in three areas of disease management, knowledge discovery, and health care infrastructure both in software and hardware systems, designing and modeling this application domain with UML will facilitate the reengineering and promotion of organizations, and develop interactive systems to support the linkages between different parts of the health care system and collaboration between project partners.
Hamed Samadpour; Farahnaz Sadoughi
Volume 12, Issue 4 , August 2015, , Pages 416-425
Abstract
Introduction: Currently, the important role of personal health record (PHR) system is underlined due to increasing global concentration on the concept of patient-centered healthcare. Generating national standards and data sets as well as its advertisement by health providers will increase the wide-spread ...
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Introduction: Currently, the important role of personal health record (PHR) system is underlined due to increasing global concentration on the concept of patient-centered healthcare. Generating national standards and data sets as well as its advertisement by health providers will increase the wide-spread acceptance of PHR systems. The aim of this study was to determine optimal data set of electronic PHR system for Iranian students of medical sciences.Methods: The study was conducted in three steps, i.e. qualitative comparison of data sets in USA, Australia, and UK; quantitative-descriptive assessment among 301 subjects, who was the students of Tehran University of Medical Sciences and their healthcare providers; and finally qualitative Delphi technique to take the outcomes of the comments of 60 specialists and experts in six classified field, i.e. management, medicine, dentistry, nursing, rehabilitation, and mental health, in 2014. Data collection questionnaire was arranged based on the common data sets of emerging countries and the available national student health records, approved by the Ministry of Health and Sciences. Its content validity has been approved by three experts and its reliability was confirmed with Cronbach's alpha value of 0.97 using internal consistency through SPSS20 software. The requirements assessment of stakeholders to achieve the required data collection and descriptive analysis was performed by calculating the distribution function of its frequency through Excel software. The questionnaire was prepared based on the results of the requirements assessment phase and Its content validity were approved by three experts in the field of clinical and management, Reliability analysis of research tool at this step of research was not possible, because in Delphi method respondents could completely change Its reply In each round. Descriptive analysis was performed based on the average through Excel software. The data elements those were higher than 4 in averages have been considered in proposed Data Set.Results: 344 data elements were evaluated, 280 items among them was resulted from the requirements assessment step and 64 items among them were added in Delphi step. 271 data elements are approved, which five items were approved with perfect (100%) agreement. Finally, the data set and its subsets were determined.Conclusion: Modifications and evolutions of data set elements over the study period underlined the important role the comments of both stakeholders and the experts for determining optimal data set among diverse range of possible fields. It can be concluded from the results of this study that more details, such as mental health, can be added to the PHR data set. Moreover, Student Health Certificate, which is used in most universities of Iran is incomplete and it has to be modified.
Farahnaz Sadoughi; Kamal Ebrahimi
Volume 11, Issue 5 , October 2014, , Pages 581-592
Abstract
Introduction: Scientific trend analysis can help inform Research topic trend, challenges, and solve these challenges. The purpose of this study is to identify World current Status in the field of health information management and informatics.Methods: In this Content analysis and scientometric ...
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Introduction: Scientific trend analysis can help inform Research topic trend, challenges, and solve these challenges. The purpose of this study is to identify World current Status in the field of health information management and informatics.Methods: In this Content analysis and scientometric study, 1502 articles published in the Health Information Management and Health informatics were analyzed from 2008-2012 . Data were analyzed using Histcite ,SPSS, Bibexcel, VOSviewer . Data were categorized in to 14 conceptual fields by Health information management professionals . Results: In this research four main clusters were identified from 100 most cited articles in health information management. Data were collected by Health information management in to 14 subfields. with most papers classified in the information systems, information technology, interoperability and security and safety. Social networking, web-based systems and mobile phone technology, new approaches in the literature of health information management. Conclusions: The diversity of research, innovation in research, applied research or implementation experience of being a major feature articles in the field of information management in the world.Keywords: Health Information Management; Electronic Health Record; Medical Informatics.
