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

verfasst von

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

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.

Externe Organisation(en)

Universidad Politécnica de Madrid (UPM)
Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
Universidad Autónoma de Madrid (UAM)
National Centre For Scientific Research Demokritos (NCSR Demokritos)
The American College of Greece (ACG)

Typ

Aufsatz in Konferenzband

Seiten

193-196

Anzahl der Seiten

4

Publikationsdatum

2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Radiologie, Nuklearmedizin und Bildgebung, Angewandte Informatik

Ziele für nachhaltige Entwicklung

SDG 3 – Gute Gesundheit und Wohlergehen

Elektronische Version(en)

https://zenodo.org/record/3862244/files/Paper%20CBMS%20BigMed%20v0.2.pdf (Zugang: Offen)
https://doi.org/10.1109/CBMS49503.2020.00044 (Zugang: Geschlossen)