A data-driven approach for analyzing healthcare services extracted from clinical records

Manuel Scurti; Ernestina Menasalvas Ruiz; Maria Esther Vidal; Maria Torrente; Dimitrios Vogiatzis; George Paliouras; Mariano Provencio; Alejandro Rodriguez Gonzalez

doi:10.1109/CBMS49503.2020.00044

A data-driven approach for analyzing healthcare services extracted from clinical records

Manuel Scurti
, Ernestina Menasalvas Ruiz
, Maria Esther Vidal
, Maria Torrente
, Dimitrios Vogiatzis
, George Paliouras
, Mariano Provencio
, Alejandro Rodriguez Gonzalez

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

Abstract

Cancer remains one of the major public health challenges worldwide. After cardiovascular diseases, cancer is one of the first causes of death and morbidity in Europe, with more than 4 million new cases and 1.9 million deaths per year. The suboptimal management of cancer patients during treatment and subsequent follows up are major obstacles in achieving better outcomes of the patients and especially regarding cost and quality of life In this paper, we present an initial data-driven approach to analyze the resources and services that are used more frequently by lung-cancer patients with the aim of identifying where the care process can be improved by paying a special attention on services before diagnosis to being able to identify possible lung-cancer patients before they are diagnosed and by reducing the length of stay in the hospital. Our approach has been built by analyzing the clinical notes of those oncological patients to extract this information and their relationships with other variables of the patient. Although the approach shown in this manuscript is very preliminary, it shows that quite interesting outcomes can be derived from further analysis.

Originalsprache	Englisch
Titel des Sammelwerks	Proceedings
Untertitel	2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020
Herausgeber/-innen	Alba Garcia Seco de Herrera, Alejandro Rodriguez Gonzalez, KC Santosh, Zelalem Temesgen, Bridget Kane, Paolo Soda
Herausgeber (Verlag)	Institute of Electrical and Electronics Engineers Inc.
Seiten	193-196
Seitenumfang	4
ISBN (elektronisch)	9781728194295
DOIs	https://doi.org/10.1109/CBMS49503.2020.00044
Publikationsstatus	Veröffentlicht - 2020
Extern publiziert	Ja
Veranstaltung	33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020 - Virtual, Online, USA / Vereinigte Staaten Dauer: 28 Juli 2020 → 30 Juli 2020

Publikationsreihe

Name	Proceedings - IEEE Symposium on Computer-Based Medical Systems
Band	2020-July
ISSN (Print)	1063-7125

Konferenz

Konferenz	33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020
Land/Gebiet	USA / Vereinigte Staaten
Ort	Virtual, Online
Zeitraum	28 Juli 2020 → 30 Juli 2020

UN-Ziele für nachhaltige Entwicklung (SDGs)

2015 einigten sich die UN-Mitgliedstaaten auf 17 globale Ziele für nachhaltige Entwicklung (Sustainable Development Goals, SDGs) zur Beendigung von Armut, zum Schutz des Planeten und zur Förderung des allgemeinen Wohlstands. Hiermit leisten wir einen Beitrag zu folgendem/n Ziel(en) für nachhaltige Entwicklung (SDGs):

SDG 3 Gute Gesundheit und Wohlergehen

ASJC Scopus Sachgebiete

Radiologie, Nuklearmedizin und Bildgebung
Angewandte Informatik

Zugriff auf Dokument

10.1109/CBMS49503.2020.00044

https://zenodo.org/record/3862244/files/Paper%20CBMS%20BigMed%20v0.2.pdfLizenz: Sonstige

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Dieses zitieren

Scurti, M., Menasalvas Ruiz, E., Vidal, M. E., Torrente, M., Vogiatzis, D., Paliouras, G., Provencio, M., & Rodriguez Gonzalez, A. (2020). A data-driven approach for analyzing healthcare services extracted from clinical records. in A. G. S. de Herrera, A. Rodriguez Gonzalez, KC. Santosh, Z. Temesgen, B. Kane, & P. Soda (Hrsg.), Proceedings: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020 (S. 193-196). Artikel 9183213 (Proceedings - IEEE Symposium on Computer-Based Medical Systems; Band 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBMS49503.2020.00044

Scurti, Manuel ; Menasalvas Ruiz, Ernestina ; Vidal, Maria Esther et al. / A data-driven approach for analyzing healthcare services extracted from clinical records. Proceedings: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. Hrsg. / Alba Garcia Seco de Herrera ; Alejandro Rodriguez Gonzalez ; KC Santosh ; Zelalem Temesgen ; Bridget Kane ; Paolo Soda. Institute of Electrical and Electronics Engineers Inc., 2020. S. 193-196 (Proceedings - IEEE Symposium on Computer-Based Medical Systems).

@inproceedings{0c3c7df48fab4ad39ac7e263cf5ea078,

title = "A data-driven approach for analyzing healthcare services extracted from clinical records",

abstract = "Cancer remains one of the major public health challenges worldwide. After cardiovascular diseases, cancer is one of the first causes of death and morbidity in Europe, with more than 4 million new cases and 1.9 million deaths per year. The suboptimal management of cancer patients during treatment and subsequent follows up are major obstacles in achieving better outcomes of the patients and especially regarding cost and quality of life In this paper, we present an initial data-driven approach to analyze the resources and services that are used more frequently by lung-cancer patients with the aim of identifying where the care process can be improved by paying a special attention on services before diagnosis to being able to identify possible lung-cancer patients before they are diagnosed and by reducing the length of stay in the hospital. Our approach has been built by analyzing the clinical notes of those oncological patients to extract this information and their relationships with other variables of the patient. Although the approach shown in this manuscript is very preliminary, it shows that quite interesting outcomes can be derived from further analysis.",

keywords = "Data-driven, EHR, Hospitalization processes, Lung cancer, Patient management",

author = "Manuel Scurti and \{Menasalvas Ruiz\}, Ernestina and Vidal, \{Maria Esther\} and Maria Torrente and Dimitrios Vogiatzis and George Paliouras and Mariano Provencio and \{Rodriguez Gonzalez\}, Alejandro",

note = "Funding information: This work is supported by the EU Horizon 2020 innovation programme under grant agreement No. 780495, project BigMedilytics (Big Data for Medical Analytics). The work is also a result of a Horizon 2020 research and innovation programme under grant agreement No. 727658, project IASIS (Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients). ACKNOWLEDGMENT This work is supported by the EU Horizon 2020 innovation programme under grant agreement No. 780495, project BigMedilytics (Big Data for Medical Analytics). The work is also a result of a Horizon 2020 research and innovation programme under grant agreement No. 727658, project IASIS (Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients).; 33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020 ; Conference date: 28-07-2020 Through 30-07-2020",

year = "2020",

doi = "10.1109/CBMS49503.2020.00044",

language = "English",

series = "Proceedings - IEEE Symposium on Computer-Based Medical Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "193--196",

editor = "\{de Herrera\}, \{Alba Garcia Seco\} and \{Rodriguez Gonzalez\}, Alejandro and KC Santosh and Zelalem Temesgen and Bridget Kane and Paolo Soda",

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}

Scurti, M, Menasalvas Ruiz, E, Vidal, ME, Torrente, M, Vogiatzis, D, Paliouras, G, Provencio, M & Rodriguez Gonzalez, A 2020, A data-driven approach for analyzing healthcare services extracted from clinical records. in AGS de Herrera, A Rodriguez Gonzalez, KC Santosh, Z Temesgen, B Kane & P Soda (Hrsg.), Proceedings: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020., 9183213, Proceedings - IEEE Symposium on Computer-Based Medical Systems, Bd. 2020-July, Institute of Electrical and Electronics Engineers Inc., S. 193-196, 33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020, Virtual, Online, USA / Vereinigte Staaten, 28 Juli 2020. https://doi.org/10.1109/CBMS49503.2020.00044

A data-driven approach for analyzing healthcare services extracted from clinical records. / Scurti, Manuel; Menasalvas Ruiz, Ernestina; Vidal, Maria Esther et al.
Proceedings: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. Hrsg. / Alba Garcia Seco de Herrera; Alejandro Rodriguez Gonzalez; KC Santosh; Zelalem Temesgen; Bridget Kane; Paolo Soda. Institute of Electrical and Electronics Engineers Inc., 2020. S. 193-196 9183213 (Proceedings - IEEE Symposium on Computer-Based Medical Systems; Band 2020-July).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

TY - GEN

T1 - A data-driven approach for analyzing healthcare services extracted from clinical records

AU - Scurti, Manuel

AU - Menasalvas Ruiz, Ernestina

AU - Vidal, Maria Esther

AU - Torrente, Maria

AU - Vogiatzis, Dimitrios

AU - Paliouras, George

AU - Provencio, Mariano

AU - Rodriguez Gonzalez, Alejandro

N1 - Funding information: This work is supported by the EU Horizon 2020 innovation programme under grant agreement No. 780495, project BigMedilytics (Big Data for Medical Analytics). The work is also a result of a Horizon 2020 research and innovation programme under grant agreement No. 727658, project IASIS (Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients). ACKNOWLEDGMENT This work is supported by the EU Horizon 2020 innovation programme under grant agreement No. 780495, project BigMedilytics (Big Data for Medical Analytics). The work is also a result of a Horizon 2020 research and innovation programme under grant agreement No. 727658, project IASIS (Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients).

PY - 2020

Y1 - 2020

N2 - Cancer remains one of the major public health challenges worldwide. After cardiovascular diseases, cancer is one of the first causes of death and morbidity in Europe, with more than 4 million new cases and 1.9 million deaths per year. The suboptimal management of cancer patients during treatment and subsequent follows up are major obstacles in achieving better outcomes of the patients and especially regarding cost and quality of life In this paper, we present an initial data-driven approach to analyze the resources and services that are used more frequently by lung-cancer patients with the aim of identifying where the care process can be improved by paying a special attention on services before diagnosis to being able to identify possible lung-cancer patients before they are diagnosed and by reducing the length of stay in the hospital. Our approach has been built by analyzing the clinical notes of those oncological patients to extract this information and their relationships with other variables of the patient. Although the approach shown in this manuscript is very preliminary, it shows that quite interesting outcomes can be derived from further analysis.

AB - Cancer remains one of the major public health challenges worldwide. After cardiovascular diseases, cancer is one of the first causes of death and morbidity in Europe, with more than 4 million new cases and 1.9 million deaths per year. The suboptimal management of cancer patients during treatment and subsequent follows up are major obstacles in achieving better outcomes of the patients and especially regarding cost and quality of life In this paper, we present an initial data-driven approach to analyze the resources and services that are used more frequently by lung-cancer patients with the aim of identifying where the care process can be improved by paying a special attention on services before diagnosis to being able to identify possible lung-cancer patients before they are diagnosed and by reducing the length of stay in the hospital. Our approach has been built by analyzing the clinical notes of those oncological patients to extract this information and their relationships with other variables of the patient. Although the approach shown in this manuscript is very preliminary, it shows that quite interesting outcomes can be derived from further analysis.

KW - Data-driven

KW - EHR

KW - Hospitalization processes

KW - Lung cancer

KW - Patient management

UR - https://www.scopus.com/pages/publications/85091146969

U2 - 10.1109/CBMS49503.2020.00044

DO - 10.1109/CBMS49503.2020.00044

M3 - Conference contribution

AN - SCOPUS:85091146969

T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems

SP - 193

EP - 196

BT - Proceedings

A2 - de Herrera, Alba Garcia Seco

A2 - Rodriguez Gonzalez, Alejandro

A2 - Santosh, KC

A2 - Temesgen, Zelalem

A2 - Kane, Bridget

A2 - Soda, Paolo

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020

Y2 - 28 July 2020 through 30 July 2020

ER -

Scurti M, Menasalvas Ruiz E, Vidal ME, Torrente M, Vogiatzis D, Paliouras G et al. A data-driven approach for analyzing healthcare services extracted from clinical records. in de Herrera AGS, Rodriguez Gonzalez A, Santosh KC, Temesgen Z, Kane B, Soda P, Hrsg., Proceedings: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. Institute of Electrical and Electronics Engineers Inc. 2020. S. 193-196. 9183213. (Proceedings - IEEE Symposium on Computer-Based Medical Systems). doi: 10.1109/CBMS49503.2020.00044