2013
Portela, F.; Gago, P.; Santos, M. F.; Machado, J.; Abelha, A.; Silva, Á.; Rua, F.
Implementing a pervasive real-time intelligent system for tracking critical events with intensive care patients Journal Article
Em: International Journal of Healthcare Information Systems and Informatics, vol. 8, não 4, pp. 1-16, 2013, ISSN: 15553396, (cited By 11).
Resumo | Links | BibTeX | Etiquetas: Artificial intelligence; Decision making; Decision support systems; Intelligent systems; Nursing; Tracking (position), Critical events; Data collection; Decision-making process; Intelligent decision support systems; Intensive-care patients; Nursing records; Technology acceptance model; Tracking system, Intensive care units
@article{Portela20131b,
title = {Implementing a pervasive real-time intelligent system for tracking critical events with intensive care patients},
author = {F. Portela and P. Gago and M. F. Santos and J. Machado and A. Abelha and Á. Silva and F. Rua},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903153312&doi=10.4018%2fijhisi.2013100101&partnerID=40&md5=ddeb5aa9b2f510e714c7bb50d8123b62},
doi = {10.4018/ijhisi.2013100101},
issn = {15553396},
year = {2013},
date = {2013-01-01},
journal = {International Journal of Healthcare Information Systems and Informatics},
volume = {8},
number = {4},
pages = {1-16},
publisher = {IGI Global},
abstract = {Nowadays, it is increasingly important to utilize intelligent systems to support the decision making process (DMP) in challenging areas such as Intensive Medicine. In Intensive Care Units (ICU), some of the biggest challenges relate both to the number and the different types of available data sources. Even though in such a setting the values for some variables are easy to collect, data collection is still performed manually in particular instances. In order to improve the DMP in ICU, a Pervasive Intelligent Decision Support System, called INTCare was deployed in the ICU of Centro Hospitalar do Porto in Portugal. This system altered the way information is collected and presented. Moreover, the tracking system deployed as a specific module of INTCare - Electronic Nursing Record (ENR) is made accessible anywhere and anytime. The system allows for the calculation of the critical events regarding fve variables that are typically monitored in an ICU. Specifically, the INTCare tracking system characterizes a grid that shows the events by type and duration, empowers a warning system to alert the doctors and promotes intuitive graphics that allow care providers to follow the patient care journey. User acceptance was measured through a questionnaire designed in accordance with the Technology Acceptance Model (TAM) and results of implementing the INTCare tracking system, and its interface are reported. Copyright © 2013, IGI Global.},
note = {cited By 11},
keywords = {Artificial intelligence; Decision making; Decision support systems; Intelligent systems; Nursing; Tracking (position), Critical events; Data collection; Decision-making process; Intelligent decision support systems; Intensive-care patients; Nursing records; Technology acceptance model; Tracking system, Intensive care units},
pubstate = {published},
tppubtype = {article}
}
Nowadays, it is increasingly important to utilize intelligent systems to support the decision making process (DMP) in challenging areas such as Intensive Medicine. In Intensive Care Units (ICU), some of the biggest challenges relate both to the number and the different types of available data sources. Even though in such a setting the values for some variables are easy to collect, data collection is still performed manually in particular instances. In order to improve the DMP in ICU, a Pervasive Intelligent Decision Support System, called INTCare was deployed in the ICU of Centro Hospitalar do Porto in Portugal. This system altered the way information is collected and presented. Moreover, the tracking system deployed as a specific module of INTCare - Electronic Nursing Record (ENR) is made accessible anywhere and anytime. The system allows for the calculation of the critical events regarding fve variables that are typically monitored in an ICU. Specifically, the INTCare tracking system characterizes a grid that shows the events by type and duration, empowers a warning system to alert the doctors and promotes intuitive graphics that allow care providers to follow the patient care journey. User acceptance was measured through a questionnaire designed in accordance with the Technology Acceptance Model (TAM) and results of implementing the INTCare tracking system, and its interface are reported. Copyright © 2013, IGI Global.