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^*

^*Bu çalışma için yazışmadan sorumlu yazar

Harita Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Bölüm › bilirkişi

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Studies in Big Data
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	141-155
Sayfa sayısı	15
DOI'lar	https://doi.org/10.1007/978-3-319-60255-4_11
Yayın durumu	Yayınlandı - 2018

Yayın serisi

Adı	Studies in Big Data
Hacim	27
ISSN (Basılı)	2197-6503
ISSN (Elektronik)	2197-6511

Bibliyografik not

Publisher Copyright:
© 2018, Springer International Publishing AG.

Finansman

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.

Finansörler	Finansör numarası
Karacadağ Development Agency
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	1059B141400289

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data",

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.",

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

author = "Selman Delil and {\c C}elik, \{Rahmi Nurhan\}",

note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.",

year = "2018",

doi = "10.1007/978-3-319-60255-4\_11",

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TY - CHAP

T1 - Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

AU - Delil, Selman

AU - Çelik, Rahmi Nurhan

PY - 2018

Y1 - 2018

N2 - 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.

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.

KW - Clustering

KW - Data analysis for health-care

KW - Gandy nomogram

KW - Health service delivery

KW - Patient mobility

KW - Patient mobility analysis

KW - Turkish health-care system

UR - https://www.scopus.com/pages/publications/85132852549

U2 - 10.1007/978-3-319-60255-4_11

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

M3 - Chapter

AN - SCOPUS:85132852549

T3 - Studies in Big Data

SP - 141

EP - 155

BT - Studies in Big Data

PB - Springer Science and Business Media Deutschland GmbH

ER -

Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

Özet

Yayın serisi

Bibliyografik not

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap