Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

  • Selman Delil
  • Rahmi Nurhan ÇelikEmail author
Part of the Studies in Big Data book series (SBD, volume 27)


This research aims to identify and analyze mobility patterns and trends across eighty-one provinces in Turkey to understand spatio-temporal characteristics of health-service areas at the national level. In the study we focus on classification of mobility characteristics of different health administration areas with a comprehensive spatial and temporal perspective. We identified four major clusters in addition to several smaller and isolated ones. Statistical tests show that groups identified by clustering patient mobility data correlate, in a statistically significant manner, with all but one of the basic health-care indicators considered. Our analysis identifies several important patterns revealing the level of effectiveness of Turkish health-care delivery in certain regions.


Data analysis for health-care Patient mobility Patient mobility analysis Health service delivery Turkish health-care system Clustering Gandy nomogram 



This research was sponsored by the Scientific and Technological Research Council of Turkey (TUBITAK) under the International Doctoral Research Fellowship Programme (Grant number: 1059B141400289). The content is solely the responsibility of the authors and does not necessarily represent the official views of TUBITAK.

We would like to express our sincere thanks and appreciation to both the Republic of Turkey Social Security Institution and the Karacadağ Development Agency for providing us the patient mobility data for our research.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Informatics InstituteIstanbul Technical UniversityIstanbulTurkey

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