2012
Silva, P.; Quintas, C.; Santos, M.; Abelha, A.; Machado, J.
Step towards fault forecasting in hospital information systems Proceedings Article
Em: pp. 1289-1294, Chongqing, 2012, ISBN: 9781467311816, (cited By 0; Conference of 2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012 ; Conference Date: 16 October 2012 Through 18 October 2012; Conference Code:100337).
Resumo | Links | BibTeX | Etiquetas: Database performance; Early warning score; Fault tolerant systems; Forecasting modeling; Hospital information systems; Indispensable tools; Medical informatics; Prediction systems, Database systems, Forecasting; Health care; Hospitals; Information science; Information systems; Medicine
@inproceedings{Silva20121289,
title = {Step towards fault forecasting in hospital information systems},
author = {P. Silva and C. Quintas and M. Santos and A. Abelha and J. Machado},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886397746&doi=10.1109%2fBMEI.2012.6513041&partnerID=40&md5=b12b2c0331dee2ea78784d8895bb0ea0},
doi = {10.1109/BMEI.2012.6513041},
isbn = {9781467311816},
year = {2012},
date = {2012-01-01},
journal = {2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012},
pages = {1289-1294},
address = {Chongqing},
abstract = {Nowadays, many organizations consider databases indispensable tools for their daily tasks. Particularly in healthcare units, databases have a vital role, since they archive very important information about patients' clinical status, therefore, it is crucial that databases are available twenty-four hours a day, seven days per week. Healthcare units have already implemented fault tolerant systems, which intended to ensure the availability, reliability and disaster recovery of data. However, these mechanisms do not allow to take preventive actions in order to avoid the occurrence of faults. In this context, the necessity of the development of faults prevention and prediction systems is emerging. These systems can predict faults with some time in advance and provide taking early action to solve problems. The objectives of this paper are: monitor database performance and adapt a forecasting model used in medicine (Modified Early Warning Score - MEWS) to database reality. © 2012 IEEE.},
note = {cited By 0; Conference of 2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012 ; Conference Date: 16 October 2012 Through 18 October 2012; Conference Code:100337},
keywords = {Database performance; Early warning score; Fault tolerant systems; Forecasting modeling; Hospital information systems; Indispensable tools; Medical informatics; Prediction systems, Database systems, Forecasting; Health care; Hospitals; Information science; Information systems; Medicine},
pubstate = {published},
tppubtype = {inproceedings}
}
Nowadays, many organizations consider databases indispensable tools for their daily tasks. Particularly in healthcare units, databases have a vital role, since they archive very important information about patients' clinical status, therefore, it is crucial that databases are available twenty-four hours a day, seven days per week. Healthcare units have already implemented fault tolerant systems, which intended to ensure the availability, reliability and disaster recovery of data. However, these mechanisms do not allow to take preventive actions in order to avoid the occurrence of faults. In this context, the necessity of the development of faults prevention and prediction systems is emerging. These systems can predict faults with some time in advance and provide taking early action to solve problems. The objectives of this paper are: monitor database performance and adapt a forecasting model used in medicine (Modified Early Warning Score - MEWS) to database reality. © 2012 IEEE.
Silva, P.; Quintas, C.; Duarte, J.; Santos, M.; Neves, J.; Abelha, A.; MacHado, J.
Hospital database workload and fault forecasting Proceedings Article
Em: pp. 63-68, Langkawi, 2012, ISBN: 9781467316668, (cited By 6; Conference of 2012 2nd IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012 ; Conference Date: 17 December 2012 Through 19 December 2012; Conference Code:96763).
Resumo | Links | BibTeX | Etiquetas: Confidential information; Database performance; Database workload; Disaster recovery; Fault tolerant systems; Forecasting models; Hospital information systems; Indispensable tools, Database systems, Forecasting; Health care; Hospitals; Medical computing; Medicine
@inproceedings{Silva201263,
title = {Hospital database workload and fault forecasting},
author = {P. Silva and C. Quintas and J. Duarte and M. Santos and J. Neves and A. Abelha and J. MacHado},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876746497&doi=10.1109%2fIECBES.2012.6498150&partnerID=40&md5=35fa2df9982add8528a17ca52619208a},
doi = {10.1109/IECBES.2012.6498150},
isbn = {9781467316668},
year = {2012},
date = {2012-01-01},
journal = {2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012},
pages = {63-68},
address = {Langkawi},
abstract = {With the growing importance of hospital information systems, databases became indispensable tools for day-to-day tasks in healthcare units. They store important and confidential information about patients clinical status and about the other hospital services. Thus, they must be permanently available, reliable and at high performance. In many healthcare units, fault tolerant systems are used. They ensure the availability, reliability and disaster recovery of data. However, these mechanisms do not allow the prediction or prevention of faults. In this context, it emerges the necessity of developing a fault forecasting system. The objectives of this paper are monitoring database performance to verify the normal workload for the main database of Centro Hospitalar do Porto and adapt a forecasting model used in medicine into the database context. Based on percentiles it was created a scale to represent the severity of situations. It was observe that the critical workload period is the period between 10:00 am and 12:00 am. Moreover, abnormal situations were detected and it was possible to send alerts and to request assistance. © 2012 IEEE.},
note = {cited By 6; Conference of 2012 2nd IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012 ; Conference Date: 17 December 2012 Through 19 December 2012; Conference Code:96763},
keywords = {Confidential information; Database performance; Database workload; Disaster recovery; Fault tolerant systems; Forecasting models; Hospital information systems; Indispensable tools, Database systems, Forecasting; Health care; Hospitals; Medical computing; Medicine},
pubstate = {published},
tppubtype = {inproceedings}
}
With the growing importance of hospital information systems, databases became indispensable tools for day-to-day tasks in healthcare units. They store important and confidential information about patients clinical status and about the other hospital services. Thus, they must be permanently available, reliable and at high performance. In many healthcare units, fault tolerant systems are used. They ensure the availability, reliability and disaster recovery of data. However, these mechanisms do not allow the prediction or prevention of faults. In this context, it emerges the necessity of developing a fault forecasting system. The objectives of this paper are monitoring database performance to verify the normal workload for the main database of Centro Hospitalar do Porto and adapt a forecasting model used in medicine into the database context. Based on percentiles it was created a scale to represent the severity of situations. It was observe that the critical workload period is the period between 10:00 am and 12:00 am. Moreover, abnormal situations were detected and it was possible to send alerts and to request assistance. © 2012 IEEE.
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.