2012
Silva, P.; Quintas, C.; Goncalves, P.; Pontes, G.; Santos, M.; Abelha, A.; Machado, J.
Intelligent systems based in hospital database malfunction scenarios Proceedings Article
Em: pp. 846-850, IEEE Computer Society, Hong Kong, 2012, ISSN: 21573611, (cited By 1; Conference of 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012 ; Conference Date: 10 December 2012 Through 13 December 2012; Conference Code:106121).
Resumo | Links | BibTeX | Etiquetas: Confidential information; Database performance; Disaster recovery; Fault tolerant systems; Forecasting modeling; Mathematical tools; Performance level; Preventive action, Database systems, Health care; Industrial engineering; Intelligent systems
@inproceedings{Silva2012846,
title = {Intelligent systems based in hospital database malfunction scenarios},
author = {P. Silva and C. Quintas and P. Goncalves and G. Pontes and M. Santos and A. Abelha and J. Machado},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903826869&doi=10.1109%2fIEEM.2012.6837859&partnerID=40&md5=941aed69ef0d4695f9541c1b9e0059cb},
doi = {10.1109/IEEM.2012.6837859},
issn = {21573611},
year = {2012},
date = {2012-01-01},
journal = {IEEE International Conference on Industrial Engineering and Engineering Management},
pages = {846-850},
publisher = {IEEE Computer Society},
address = {Hong Kong},
abstract = {Databases are indispensable for everyday tasks in organizations, particularly in healthcare units. Databases archive important and confidential information about patient's clinical status. Therefore, they must always be available, reliable and at high performance level. In healthcare units, fault tolerant systems ensure the availability, reliability and disaster recovery of data. However, these mechanisms do not allow taking preventive actions in order to avoid fault occurrence. In this context, it emerges the necessity of developing a fault prevention system. It can predict database malfunction in advance and provides early decision taken to solve problems. The objectives of this paper are: monitoring database performance and adapt a forecasting model used in medicine (MEWS) to the database context. Based on mathematical tools it was created a scale that assesses the severity of abnormal situations. In this way, it is possible to define the scenarios where database symptoms must trigger alerts and assistance request. © 2012 IEEE.},
note = {cited By 1; Conference of 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012 ; Conference Date: 10 December 2012 Through 13 December 2012; Conference Code:106121},
keywords = {Confidential information; Database performance; Disaster recovery; Fault tolerant systems; Forecasting modeling; Mathematical tools; Performance level; Preventive action, Database systems, Health care; Industrial engineering; Intelligent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Databases are indispensable for everyday tasks in organizations, particularly in healthcare units. Databases archive important and confidential information about patient's clinical status. Therefore, they must always be available, reliable and at high performance level. In healthcare units, fault tolerant systems ensure the availability, reliability and disaster recovery of data. However, these mechanisms do not allow taking preventive actions in order to avoid fault occurrence. In this context, it emerges the necessity of developing a fault prevention system. It can predict database malfunction in advance and provides early decision taken to solve problems. The objectives of this paper are: monitoring database performance and adapt a forecasting model used in medicine (MEWS) to the database context. Based on mathematical tools it was created a scale that assesses the severity of abnormal situations. In this way, it is possible to define the scenarios where database symptoms must trigger alerts and assistance request. © 2012 IEEE.