Full length article Regional clustering of medical imaging technologies Cuma Son  gur, Mehmet Top * Hacettepe University, Faculty of Economics and Administrative Sciences, Department of Health Care Management, Turkey article info Article history: Received 5 October 2015 Received in revised form 15 March 2016 Accepted 16 March 2016 Keywords: Medical imaging technologies Ultrasonography Magnetic resonance imaging Computed tomography Turkish health system Cluster analysis abstract The purpose of this study was to analyze clusters from 12 regions in Turkey in terms of medical imaging technologies' capacity and use. 12 statistical region units were determined by the Ministry of Develop- ment and Turkish Statistical Institute clustered in terms of selected medical imaging indicators regarding capacity and use by using the hierarchical clustering method. This study was based on the Ward's Method, one of the hierarchical clustering methods, and the distance matrix was created by using Euclidean distance measure analysis. When the distance matrix, which was created by using the squared Euclidean distance measure, was analyzed, it was found that the two regions most distant from each other were Southeast Anatolia and Western Anatolia (Euclidean distance ¼ 13.69) two regions which have the least distance from each other were Mediterranean and Aegean regions (Euclidean distance ¼ 0.99) for public, university and private hospitals. When we analyze the dendrogram, which was created by using hierarchical clustering, it was seen that the 12 statistical region units were gathered in four different clusters. This article revealed that there were inequities in medical imaging technologies according to regions in Turkey and hospital ownerships. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction Advanced diagnosis systems (e.g. MRI scanner, CT scanner, and X-Rays) are much more complex and different in nature than other medical technologies. As healthcare organizations are adopting new medical imaging technologies for better patient care, under- standing these technological environment, users, and their con- cerns and perceptions toward these technologies is important for proposing solutions that are context specific to these organizations (Rahman, Ko, Warren, & Carpenter, 2016, p.13). Medical imaging analyses, which are significantly used in the healthcare sector, enable the imaging of the functioning and structure of the human body by taking photographs without performing any medical intervention and thus, provide general information on the human body, organs, and cells (James & Dasarathy, 2014; CIHI, 2008). Medical imaging can play a central role in the healthcare systems as it contributes to improved patient outcome and more cost-efficient healthcare in all major disease entities (Cappellaro, Ghislandi, & Anessi-Pessina, 2011; European Science Foundation, 2007; Finoc- chiaro et al., 2014; Hillman & Schwartz, 2014; Oh, Imanaka, & Evans, 2005; Packer, Simpson, & Stevens, 2006; Silva & Viana, 2011). Medical imaging has grown exponentially in the last three de- cades with the development of many promising and often nonin- vasive diagnostic studies and therapeutic modalities in health care services; especially in evidence based practice and medicine. Although the roots of evidence-based medicine are in fields other than radiology and medical imaging, in recent years, a number of radiologists and medical imaging professionals/academicians have emerged to assume leadership roles in evidence based medicine. Today medical imaging medicine has its own evidence based practice as in named evidence based medical imaging (Medina & Blackmore, 2006a, 2006b). “Medical imaging refers to several different technologies that are used to view the human body in order to diagnose, monitor , or treat medical conditions. Each type of technology gives different information about the area of the body being studied or treated, related to possible disease, injury, or the effectiveness of medical treatment” (Haidekker, 2013, p. 1). In Evidence Based Im- aging, basic science, and medical knowledge has been translated into patient-centered clinical research, which determines the ac- curacy and role of the diagnostic and therapeutic imaging in patient care in complex diseases. Evidence based imaging may make both current diagnostic tests obsolete and new ones more accurate, less invasive, safer, and less costly in health care services (Medina & Blackmore, 2006a, 2006b). “The evidence based imaging process * Corresponding author. E-mail addresses: Cuma.songur@hacettepe.edu.tr (C. Son gur), mtop@hacettepe. edu.tr (M. Top). Contents lists available at ScienceDirect Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh http://dx.doi.org/10.1016/j.chb.2016.03.056 0747-5632/© 2016 Elsevier Ltd. All rights reserved. Computers in Human Behavior 61 (2016) 333e343