Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective

被引:11
作者
Khazaei, Hamzeh [1 ]
Mench-Bressan, Nadja [2 ,3 ]
McGregor, Carolyn [2 ]
Pugh, James Edward [2 ,3 ,4 ]
机构
[1] Canada Research and Development Center, IBM, Toronto, L3R9Z7, ON
[2] Faculty of Business and Information Technology, University of Ontario, Institute of Technology, Oshawa, L1H7K4, ON
[3] Department of Neonatology, Hospital for Sick Children, Toronto, M5G1X8, ON
[4] Division of Neonatology, Department of Paediatrics, McMaster University, Toronto, L8S4L8, ON
关键词
analytical modeling; capacity planning; Cloud computing; data management; health informatics; real-time analytics;
D O I
10.1109/JTEHM.2015.2485268
中图分类号
学科分类号
摘要
The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children's Hospital in Hamilton. We collect not only physiological data but also the infusion pumps data that are attached to NICU beds. Using the proposed analytical model, we predict the amount of storage, memory, and computation power required for the system. Capacity planning and tradeoff analysis would be more accurate and systematic by applying the proposed analytical model in this paper. Numerical results are obtained using real inputs acquired from McMaster Children's Hospital and a pilot deployment of the system at The Hospital for Sick Children (SickKids) in Toronto. © 2013 IEEE.
引用
收藏
相关论文
共 29 条
  • [1] McGregor C., Big data in neonatal intensive care, Computer, 46, 6, pp. 54-59, (2013)
  • [2] Kramer M.S., Et al., Secular trends in preterm birth: A hospital-based cohort study, J. Amer. Med. Assoc., 280, 21, pp. 1849-1854, (1998)
  • [3] Thommandram A., Eklund J.M., McGregor C., Pugh J.E., James A.G., A rule-based temporal analysis method for online health analytics and its application for real-time detection of neonatal spells, Proc. IEEE Int. Congr. Big Data (BIGDATACONGRESS), pp. 470-477, (2014)
  • [4] De Smet T., Struys M.M., Neckebroek M.M., Vanden Hauwe K., Bonte S., Mortier E.P., The accuracy and clinical feasibility of a new Bayesian-based closed-loop control system for propofol administration using the bispectral index as a controlled variable, Anesthesia Analgesia, 107, 4, pp. 1200-1210, (2008)
  • [5] Hemmerling T.M., Charabati S., Zaouter C., Minardi C., Mathieu P.A., A randomized controlled trial demonstrates that a novel closed-loop propofol system performs better hypnosis control than manual administration, Can. J. Anesthesia, 57, 8, pp. 725-735, (2010)
  • [6] Flower A.A., Moorman J.R., Lake D.E., Delos J.B., Periodic heart rate decelerations in premature infants, Experim. Biol. Med., 235, 4, pp. 531-538, (2010)
  • [7] Blount M., Et al., Real-time analysis for intensive care: Development and deployment of the artemis analytic system, IEEE Eng. Med. Biol. Mag., 29, 2, pp. 110-118, (2010)
  • [8] Cirelli J., McGregor C., Graydon B., James A., Analysis of continuous oxygen saturation data for accurate representation of retinal exposure to oxygen in the preterm infant, Stud. Health Technol. Informat., 183, pp. 126-131, (2013)
  • [9] Khazaei H., McGregor C., Eklund M., El-Khatib K., Thommandram A., Toward a big data healthcare analytics system: A mathematical modeling perspective, Proc. IEEE 10th World Congr. Services (DSS), pp. 208-215, (2014)
  • [10] Zhang Q., Pang C., Mcbride S., Hansen D., Cheung C., Steyn M., Towards health data stream analytics, Proc. IEEE/ICME Int. Conf. Complex Med. Eng. (CME), pp. 282-287, (2010)