Volume 5, Issue 4 (Winter 2019)                   jhbmi 2019, 5(4): 423-434 | Back to browse issues page

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Rashidi Khazaee P, Bagherzadeh J, Niazkhani Z, Prinejad H. Proposing an Appropriate Architecture for Decision Support Systems in the Field of Complex Chronic Care: Micro-Services Based Software Architecture in Kidney Transplant Care. jhbmi 2019; 5 (4) :423-434
URL: http://jhbmi.ir/article-1-335-en.html
Ph.D. in Medical Informatics, Associate Professor, Health Information Technology Dept., Urmia University of Medical Sciences, Urmia, Iran
Abstract:   (6523 Views)
Introduction: Development and successfully implementation of knowledge based clinical decision support system (KBCDSS) in kidney transplantation (KT) could support decision-making, reduce cost and improve quality of care. For practical use of these systems, however, many challenges have to be met.  Besides to well-recognized challenges of design and implementation of information systems in healthcare domain, designing an appropriate architecture for KBCDSS that can address requirements of complex and multidisciplinary chronic care, is a new growing challenge.
Method: This case study was done based on the experience achieved in design of kidney transplantation management system in Urmia. Then, considering main applications and challenges of development and implementation of KBCDSS in Kidney transplantation and using the latest advancements in software technology field, appropriate software architecture based on micro-services has been proposed.
Results: For each function (process) of the KBCDSS, three different micro-services of data gathering, optimal model designing and its application were proposed. These services, through implementation on provided backgrounds, can respond to different requests of patients and provide them with adequate knowledge and information.
Conclusion: Use of this architecture makes it possible for different research teams with different skills and knowledge throughout the country to focus on designing a specific function and doing it in a best way. The proposed architecture can be extended and scaled. Moreover, in spite of increase in size and type of data, users and requests, it can respond well.
 
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Type of Study: Original Article | Subject: Clinical Decision Support Systems
Received: 2018/05/12 | Accepted: 2018/09/6

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