The Integration of RFID Information System Programs Based on Grey Multi-Attribute Decision Making Analysis– Taking Chemotherapy Infusion Dispensing Procedures for Example

Article Preview

Abstract:

This study intended to investigate the effect of integrating RFID information systems into cancer chemotherapy infusion dispensing procedures on the efficiency of patient care. After the ad hoc committee selected the improvement program based on grey multi-attribute decision-making, improvements were made to the information system and infusion dispensing procedures, and relevant professionals fully communicated with one another to apply the RFID information system to the improvement program. After the RFID information system was integrated with the infusion dispensing procedures, the average total operating time for dispensing chemotherapy infusions was reduced from 24.55 minutes to 12.2 minutes, which was a decrease of 50.3%. The objective of requiring less time than the standard (16 minutes) was achieved, verifying that the integration of better RFID information system programs indeed can reduce the time required for providing patients with service. The improvement program can both increase operating efficiency and patient safety, and can be provided as a reference to relevant industries.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

2050-2053

Citation:

Online since:

November 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] J.L. Deng: Control problems of grey systems, System and Control Letters, Vol. 1-5 (1982), pp.288-294.

Google Scholar

[2] C.F. Chian: Decision Making Analysis and Management: Overall Decision Making Quality Improvement Structure and Method, Shuang Yeh Books (2007).

Google Scholar

[3] R.J. Cody: Anticipating risk for human subjects participating in clinical research: application of failure mode and effects analysis, Cancer investigation, Vol. 24-2 (2006), pp.209-214.

DOI: 10.1080/07357900500524678

Google Scholar

[4] H. K. H. Chow, K.L. Choy and W.B. Lee: A dynamic logistics process knowledge-based system – An RFID multi-agent approach, Knowledge-Based Systems, Vol. 20-4 (2007), pp.357-372.

DOI: 10.1016/j.knosys.2006.08.004

Google Scholar

[5] Y. Zhang, P. Jiang, G. Huang: RFID-based smart Kanbans for Just-In-Time manufacturing, International Journal of Materials and Product Technology, Vol. 33-1-2 (2008), pp.170-184.

DOI: 10.1504/ijmpt.2008.019780

Google Scholar

[6] F. Palacio, X. Cano, J.M. Gomez, C. Vilar, A. Scorzoni, M. Cicioni, E. Abad, A. Juarros, D. Gómez, M. Nuin, A. Gonzalez, T. Becker and S. Marco: Radio Frequency Identification Semi-Active Tag with Sensing Capabilities for the Food Logistic Chain, Sensor Letters, Vol. 7-5 (2009).

DOI: 10.1166/sl.2009.1178

Google Scholar

[7] H. A. Linstone and M. Turoff: The Delphi Method: Techniques and applications, Addison-Wesley, Massachusetts (2002).

Google Scholar

[8] T. H. Lin, S. L. Hung, M. Chavali, R. J. Wu, H. N. Luk and Q. Fei: Towards Development of Wireless Sensor System for Monitoring Anesthetic Agents, Sensor Letters, Vol. 8-6 (2010), pp.767-776.

DOI: 10.1166/sl.2010.1344

Google Scholar