Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

Selman Delil; Rahmi Nurhan Çelik

doi:10.1007/978-3-319-60255-4_11

Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

Selman Delil, Rahmi Nurhan Çelik^*

^*Corresponding author for this work

Department of Geomatics Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

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.

Original language	English
Title of host publication	Studies in Big Data
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	141-155
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-319-60255-4_11
Publication status	Published - 2018

Publication series

Name	Studies in Big Data
Volume	27
ISSN (Print)	2197-6503
ISSN (Electronic)	2197-6511

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG.

Funding

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.

Funders	Funder number
Karacadağ Development Agency
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	1059B141400289

Keywords

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

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10.1007/978-3-319-60255-4_11

Cite this

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abstract = "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.",

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AB - 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.

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KW - Data analysis for health-care

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ER -

Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

Abstract

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Keywords

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