Software for data analysis in the intensive care service

Authors

Keywords:

software design, data analysis, health information management, Intensive care service, monitoring, physiologic, artificial intelligence, intensive care units

Abstract

Introduction: at present, when the use of information and technology is essential for decision making, the data has become a resource of a lot of value to boost the success of hospital entities and improve the quality of life of the people.
Objective: describe the “Dynamic data set generator for intensive care service” software.
Methods: technological development iesearch in the Intensive Care Service of the “Arnaldo Milián Castro” Hospital in the 2017 to 2022 period. The defined population were all the specialists (12) of the intensive therapy room that used the system since January of January 2017 to December 2022.
Results: it allows to collect clinical data of patients from the intensive therapy room and generate dynamic data sets for intensive care specialists and data analysis.
Conclusions: system in exploitation since 2017, the data sets generated have been used for the application of automatic learning techniques, which has enhanced medical research and timely decision making.

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Author Biographies

Marcos Díaz Bastida, Hospital Provicnicial Clínico Quirúrgico Universitario "Arnaldo Milián Castro"

Licenciado en Matemática-Computación. Máster Computación Aplicada.

Armando Caballero López, Hospital Provicnicial Clínico Quirúrgico Universitario "Arnaldo Milián Castro"

Especialistas de II Grado en Medicina Intensiva y Emergencias. Especialista de II Grado en Anestesiología y Reanimación. Máster en Urgencias Médicas. Doctor en Ciencias Médicas. Profesor Titular en la Universidad de Ciencias Médicas de Villa Clara. Investigador Titular.

Armando Caballero Font, Hospital Provicnicial Clínico Quirúrgico Universitario "Arnaldo Milián Castro"

Especialistas de II Grado en Medicina Intensiva y Emergencias. Máster en en Urgencias Médicas. Profesor Auxiliar en la Universidad de Ciencias Médicas de Villa Clara. Investigador Agregado.

References

1.Dräger.com [Internet]. Alemania: Drägerwerk AG & Co.; 2023 [citado 02/09/2023]. Vista 120; [aprox. 3 pantallas]. Disponible en: https://www.draeger.com/es_csa/Products/Vista-120

2.GE HealthCare [Internet]. Chicago: GE HealthCare; 2023 [citado 02/09/2023]. Aspectos destacados del ventilador CARESCAPE R860; [aprox. 2 pantallas]. Disponible en: https://www.gehealthcare.es/products/ventilators/carescape-r860

3.PHILIPS [Internet]. Ámsterdam: Koninklijke Philips N.V.; 2004-2023 [citado 02/09/2023]. IntelliVue MX800 Monitor de paciente al lado de la cama; [aprox. 4 pantallas]. Disponible en: https://www.philips.es/healthcare/product/HC865240/intellivue-mx800-bedside-patient-monitor

4.GE HealthCare [Internet]. Chicago: GE HealthCare; 2023 [citado 02/09/2023]. Centricity™ High Acuity Critical Care; [aprox. 1 pantalla]. Disponible en: https://www.gehealthcare.es/products/healthcare-digital/centricity-high-acuity-critical-care

5.PHP.net [Internet]. The PHP Group; 2001-2023 [citado 02/09/2023]. ¿Qué es PHP?; [aprox. 2 pantallas]. Disponible en: https://www.php.net/manual/es/intro-whatis.php

6.W3Schools [Internet]. Sandnes, Noruega: W3schools; 1999-2023 [citado 02/09/2023]. HTML Tutorial; [aprox. 4 pantallas]. Disponible en: https://www.w3schools.com/html/

7.jQuery.com [Internet]. San Francisco: Open JS Foundation; 2023 [citado 02/09/2023]. What is jQuery?; [aprox. 1 pantalla]. Disponible en: https://jquery.com/

8.OpenWebinars.net [Internet]. Sevilla: OpenWebinars S.L.; 2023 [actualizado 24/09/2019; citado 02/09/2023].Robledano A. Qué es MySQL: Características y ventajas; [aprox. 10 pantallas]. Disponible en: https://openwebinars.net/blog/que-es-mysql/

9.GeeksforGeeks.org [Internet]. Noida, India: GeeksforGeeks; 2023 [actualizado 18/04/2023; citado 02/09/2023]. One Hot Encoding in Machine Learning; [aprox. 9 pantallas]. Disponible en: https://www.geeksforgeeks.org/ml-one-hot-encoding-of-datasets-in-python/

10.PhysioNet [Internet]. Bethesda: PhysioNet; 2023 [actualizado 17/01/2019; citado 02/09/2023]. About PhysioNet; [aprox. 3 pantallas]. Disponible en: https://archive.physionet.org/about.shtml

11.PhysioNet [Internet]. Bethesda: PhysioNet; 2023 [actualizado 04/09/2016; citado 02/09/2023]. Johnson A, Pollard T, Mark R. MIMIC-III Clinical Database Version 1.4; [aprox. 10 pantallas]. Disponible en: https://physionet.org/content/mimiciii/1.4/

12.PhysioNet [Internet]. Bethesda: PhysioNet; 2023 [actualizado 18/02/2021; citado 02/09/2023]. Faltys M, Zimmermann M, Lyu X, Hüser M, Hyland S, Rätsch G, et al. HiRID, a high time-resolution ICU dataset Version 1.1.1; [aprox. 6 pantallas]. Disponible en: https://www.physionet.org/content/hirid/1.1.1/

Published

2024-02-15

How to Cite

1.
Díaz Bastida M, Caballero López A, Caballero Font A. Software for data analysis in the intensive care service. Acta Méd Centro [Internet]. 2024 Feb. 15 [cited 2025 Jul. 13];18(1):e1910. Available from: https://revactamedicacentro.sld.cu/index.php/amc/article/view/1910

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Section

Original Articles