Quality Indices in Medical Alert Systems
Juan-Pablo Suarez-Coloma, Christine Verdier, Claudia Roncancio
2014
Abstract
Numerous alert systems exist in healthcare domains but most of them produce too many false alerts leading to bad usage or disinterest. The need of better alert systems motivates the development of context-aware alert systems. The alert system Tempas is a help-decision tool based on personalized alerts. It is adaptable to business environment, target population, expert user needs, and customized in real-time for immediate needs by end users. The adaptability is defined during the alert creation process. The customization is defined during the alert management process. It is based on the population targeted, activation conditions, and the alert behavior. It is supported by two quality indices: the applicability index expresses how much a patient is concerned by the alert and the confidence index expresses how much the user can trust the alert. Both indices are used during the alert creation process (minimal thresholds for the population) and during the management process (minimal personalized threshold). The paper presents a summarized view of Tempas and focuses on the quality indices.
References
- Agrawal, R., Imielinski, T. & Swami, A., 1993. Mining association rules between sets of items in large databases. International conference on Management of data - SIGMOD, 22(2), pp. 207-216.
- Alsubhi, K., Aib, I. & Boutaba, R., 2012. FuzMet: a fuzzy-logic based alert prioritization engine for intrusion detection systems. International Journal of Network Management, 22(4), pp. 263-284.
- Anliker, U. et al., 2004. AMON: a wearable multiparameter medical monitoring and alert system. IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society, 8(4), pp. 415-427.
- Atzema, C. et al., 2006. ALARMED: adverse events in low-risk patients with chest pain receiving continuous electrocardiographic monitoring in the emergency department. A pilot study. The American Journal of Emergency Medicine, 24(1), pp. 62-67.
- Bai, Y. & Wang, D., 2006. Fundamentals of Fuzzy Logic Control - Fuzzy Sets, Fuzzy Rules and Defuzzifications. In: Y. Bai, H. Zhuang & D. Wang, eds. Advanced Fuzzy Logic Technologies in Industrial Applications. London: Springer , pp. 17-36.
- Borowski, M., Siebig, S., Wrede, C. & Imhoff, M., 2011. Reducing False Alarms of Intensive Care OnlineMonitoring Systems: An Evaluation of Two Signal Extraction Algorithms. Computational and Mathematical Methods in Medicine.
- Clark, T., 2006. American College of Clinical Engineering. Impact of clinical alarms on patient safety. (Online) Available at: www.accehtf.org/White%20Paper.pdf (Accessed 20 10 2013).
- Cvach, M., 2012. Monitor Alarm Fatigue: An Integrative Review. Biomedical instrumentation & technology / Association for the Advancement of Medical Instrumentation, 46(4), pp. 268-277.
- Gee, T. & Moorman, B. A., 2011. Reducing Alarm Hazards: Selection and Implementation of Alarm Notification Systems. Patient Safety & Quality Healthcare, 8(2), pp. 14-17.
- Haimowitz, I. J. & Kohane, I. S., 1996. Managing temporal worlds for medical trend diagnosis. Artificial Intelligence in Medicine, 8(3), pp. 199-321.
- Hudson, D. & Cohen, M., 2010. Diagnostic Models Based on Personalized Analysis of Trends (PAT). Information Technology in Biomedicine, IEEE Transactions on, 14(4), pp. 941-948.
- Iskio, J. et al., 2006. Improving Acceptance of Computerized Prescribing Alerts in Ambulatory Care. Journal of the American Medical Informatics Association:JAMIA, 13(1), pp. 5-11.
- King, A. et al., 2012. Evaluation of a smart alarm for intensive care using clinical data. Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pp. 166-169.
- Korniewicz, D. M., Clark, T. & David, Y., 2008. A national online survey on the effectiveness of clinical alarms.. American journal of critical care : an official publication, American Association of Critical-Care Nurses, 17(1), pp. 36-41.
- Krall, M. A. & Sittig, D. F., 2002. Clinician's assessments of outpatient electronic medical record alert and reminder usability and usefulness requirements.. American Medical Informatics Association (AMIA) Annual Symposium, pp. 400-404.
- Leung, C. W.-k., Chan, S. C.-f. & Chung, F.-l., 2006. A Collaborative Filtering Framework Based on Fuzzy Association Rules and Multiple-Level Similarity. Knowledge and Information Systems, 10(3), pp. 357-381.
- Manzi de Arantes Junior, W. & Verdier, C., 2010. Defining quality-measurable medical alerts from incomplete data through fuzzy linguistic variables and modifiers. IEEE Transactions on Information Technology in Biomedicine, 14(4), pp. 916-922.
- Phansalkar, S. et al., 2010. A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems. Journal of the American Medical Informatics Association:JAMIA, 17(5), pp. 493-501.
- Suarez-Coloma, J.-P., Verdier, C. & Roncancio, C., 2013. Personalized temporal medical alert system. 2nd International Conference on Advances in Biomedical Engineering (ICABME), pp. 69-72.
- Wyckoff, M., 2009. Improving how we use and respond to clinical alarms. American Nurse Today, 4(9), pp. 37- 39.
- Zadeh, L., 1965. Fuzzy sets. Information and Control, 8(3), pp. 338-353.
- Zwieg, F. H. et al., 1998. Arrhythmia detection and response in a monitoring technician and pocket paging system.. Progress in cardiovascular nursing, 13(1), pp. 16-22, 33.
Paper Citation
in Harvard Style
Suarez-Coloma J., Verdier C. and Roncancio C. (2014). Quality Indices in Medical Alert Systems . In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-027-7, pages 81-89. DOI: 10.5220/0004893900810089
in Bibtex Style
@conference{iceis14,
author={Juan-Pablo Suarez-Coloma and Christine Verdier and Claudia Roncancio},
title={Quality Indices in Medical Alert Systems},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2014},
pages={81-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004893900810089},
isbn={978-989-758-027-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Quality Indices in Medical Alert Systems
SN - 978-989-758-027-7
AU - Suarez-Coloma J.
AU - Verdier C.
AU - Roncancio C.
PY - 2014
SP - 81
EP - 89
DO - 10.5220/0004893900810089