BACKGROUND:After a disaster, all victims have to be rapidly and accurately identified for locating, tracking and regulating them. The purpose of this study was to summarize people's experiences that how the patients were tracked in past earthquake disasters in Iran. METHODS:A qualitative study was carried out in 2015. This was an interview-based qualitative study using content analysis. The interviewed people included physicians, nurses, emergency medical technicians, disaster managers, Red Crescent Society' first responders and managers. Participants were identified using a snow ball sampling method. Interviews were audiotaped, transcribed, coded, and entered into MAXQDA (version 10) for coding and content analysis. RESULTS:Three main themes and seven categories including content (recoding data), function (identification of victims, identification of the deceased, informing the patients' relatives, patients' evacuation and transfer, and statistical reporting), technology (the state of using technology) were identified that showed the patient tracking status in past earthquakes in Iran. CONCLUSION:Participants believed that to identify and register the data related to patients or the dead, no consistent action plan was available. So developing a consistent patient tracking system could overcome this issue and improve patient safety.

OBJECTIVES: This paper introduces a telemedicine innovation network and reports its implementation in Tehran University of Medical Sciences. The required conditions for the development of future projects in the field of telemedicine are also discussed; such projects should be based on the common needs and opportunities in the areas of healthcare, education, and technology. METHODS: The development of the telemedicine innovation network in Tehran University of Medical Sciences was carried out in two phases: identifying the beneficiaries of telemedicine, and codification of the innovation network memorandum; and brainstorming of three workgroup members, and completion and clustering ideas. The present study employed a qualitative survey by using brain storming method. Thus, the ideas of the innovation network members were gathered, and by using Freeplane software, all of them were clustered and innovation projects were defined. RESULTS: In the services workgroup, 87 and 25 ideas were confirmed in phase 1 and phase 2, respectively. In the education workgroup, 8 new programs in the areas of telemedicine, tele-education and teleconsultation were codified. In the technology workgroup, 101 and 11 ideas were registered in phase 1 and phase 2, respectively. CONCLUSIONS: Today, innovation is considered a major infrastructural element of any change or progress. Thus, the successful implementation of a telemedicine project not only needs funding, human resources, and full equipment. It also requires the use of innovation models to cover several different aspects of change and progress. The results of the study can provide a basis for the implementation of future telemedicine projects using new participatory, creative, and innovative models.
Brain ; Delivery of Health Care ; Education ; Financial Management ; Humans ; Remote Consultation ; Technology Transfer ; Telemedicine*

OBJECTIVES: Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. METHODS: This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. RESULTS: Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. CONCLUSIONS: The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.
Artificial Intelligence ; Follow-Up Studies* ; Health Information Systems ; Health Services ; Heart Failure* ; Heart* ; Home Care Services ; Humans ; Learning ; Negotiating ; Statistics as Topic ; Telemedicine

OBJECTIVES: Given the importance of the follow-up of chronic heart failure (CHF) patients to reduce common causes of re-admission and deterioration of their status that lead to imposing spiritual and physical costs on patients and society, modern technology tools should be used to the best advantage. The aim of this article is to explain key points which should be considered in designing an appropriate multi-agent system to improve CHF management. METHODS: In this literature review articles were searched with keywords like multi-agent system, heart failure, chronic disease management in Science Direct, Google Scholar and PubMed databases without regard to the year of publications. RESULTS: Agents are an innovation in the field of artificial intelligence. Because agents are capable of solving complex and dynamic health problems, to take full advantage of e-Health, the healthcare system must take steps to make use of this technology. Key factors in CHF management through a multi-agent system approach must be considered such as organization, confidentiality in general aspects and design and architecture points in specific aspects. CONCLUSIONS: Note that use of agent systems only with a technical view is associated with many problems. Hence, in delivering healthcare to CHF patients, considering social and human aspects is essential. It is obvious that identifying and resolving technical and non-technical challenges is vital in the successful implementation of this technology.
Artificial Intelligence ; Chronic Disease ; Confidentiality ; Delivery of Health Care ; Disease Management ; Follow-Up Studies ; Heart ; Heart Failure ; Humans ; Imidazoles ; Nitro Compounds