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Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis

Healthcare systems are challenged to deliver high-quality and efficient care. Studying patient flow in a hospital is particularly fundamental as it demonstrates effectiveness and efficiency of a hospital. Since hospital is a collection of physically nearby services under one administration, its perf...

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Autores principales: Abuhay, Tesfamariam M., Nigatie, Yemisrach G., Metsker, Oleg G., Yakovlev, Aleksey N., Kovalchuk, Sergey V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303685/
http://dx.doi.org/10.1007/978-3-030-50423-6_32
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author Abuhay, Tesfamariam M.
Nigatie, Yemisrach G.
Metsker, Oleg G.
Yakovlev, Aleksey N.
Kovalchuk, Sergey V.
author_facet Abuhay, Tesfamariam M.
Nigatie, Yemisrach G.
Metsker, Oleg G.
Yakovlev, Aleksey N.
Kovalchuk, Sergey V.
author_sort Abuhay, Tesfamariam M.
collection PubMed
description Healthcare systems are challenged to deliver high-quality and efficient care. Studying patient flow in a hospital is particularly fundamental as it demonstrates effectiveness and efficiency of a hospital. Since hospital is a collection of physically nearby services under one administration, its performance and outcome are shaped by the interaction of its discrete components. Coordination of processes at different levels of organizational structure of a hospital can be studied using network analysis. Hence, this article presents a data-driven static and temporal network of departments. Both networks are directed and weighted and constructed using seven years’ (2010–2016) empirical data of 24902 Acute Coronary Syndrome (ACS) patients. The ties reflect an episode-based transfer of ACS patients from department to department in a hospital. The weight represents the number of patients transferred among departments. As a result, the underlying structure of network of departments that deliver healthcare for ACS patients is described, the main departments and their role in the diagnosis and treatment process of ACS patients are identified, the role of departments over seven years is analyzed and communities of departments are discovered. The results of this study may help hospital administration to effectively organize and manage the coordination of departments based on their significance, strategic positioning and role in the diagnosis and treatment process which, in-turn, nurtures value-based and precision healthcare.
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spelling pubmed-73036852020-06-19 Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis Abuhay, Tesfamariam M. Nigatie, Yemisrach G. Metsker, Oleg G. Yakovlev, Aleksey N. Kovalchuk, Sergey V. Computational Science – ICCS 2020 Article Healthcare systems are challenged to deliver high-quality and efficient care. Studying patient flow in a hospital is particularly fundamental as it demonstrates effectiveness and efficiency of a hospital. Since hospital is a collection of physically nearby services under one administration, its performance and outcome are shaped by the interaction of its discrete components. Coordination of processes at different levels of organizational structure of a hospital can be studied using network analysis. Hence, this article presents a data-driven static and temporal network of departments. Both networks are directed and weighted and constructed using seven years’ (2010–2016) empirical data of 24902 Acute Coronary Syndrome (ACS) patients. The ties reflect an episode-based transfer of ACS patients from department to department in a hospital. The weight represents the number of patients transferred among departments. As a result, the underlying structure of network of departments that deliver healthcare for ACS patients is described, the main departments and their role in the diagnosis and treatment process of ACS patients are identified, the role of departments over seven years is analyzed and communities of departments are discovered. The results of this study may help hospital administration to effectively organize and manage the coordination of departments based on their significance, strategic positioning and role in the diagnosis and treatment process which, in-turn, nurtures value-based and precision healthcare. 2020-05-23 /pmc/articles/PMC7303685/ http://dx.doi.org/10.1007/978-3-030-50423-6_32 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Abuhay, Tesfamariam M.
Nigatie, Yemisrach G.
Metsker, Oleg G.
Yakovlev, Aleksey N.
Kovalchuk, Sergey V.
Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis
title Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis
title_full Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis
title_fullStr Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis
title_full_unstemmed Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis
title_short Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis
title_sort investigating coordination of hospital departments in delivering healthcare for acute coronary syndrome patients using data-driven network analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303685/
http://dx.doi.org/10.1007/978-3-030-50423-6_32
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