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IJAT Vol.3 No.2 pp. 174-184
doi: 10.20965/ijat.2009.p0174
(2009)

Paper:

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Dynamic Scheduling in Inpatient Nursing

Mingang Cheng*1,*3, Hiromi Itoh Ozaku*2,*3, Noriaki Kuwahara*3,*4, Kiyoshi Kogure*3, and Jun Ota*1,*3

*1Department of Precision Engineering, the University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

*2National Institute of Information and CommunicationsTechnology
4-2-1, Nukui-Kitamachi, Koganei, Tokyo 184-8795, Japan

*3Knowledge Science Laboratories, Advanced Telecommunications Research Institute International (ATR)
2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan

*4Department of Advanced Fibro-Science, Kyoto Institute of Technology
1 Hashigami-cho, Matsugasaki, Sakyo-ku, Kyoto 606-8585, Japan

Received:
December 30, 2008
Accepted:
February 4, 2009
Published:
March 5, 2009
Creative Commons License
Keywords:
inpatient nursing care, dynamic scheduling, optimization, work overload, overtime work
Abstract
To shorten the notoriously long waits for service in hospitals in Japan and to improve efficiency, we propose a scheduling algorithm with a 2-layer local search based on simulated annealing -- permutating (switching) (i) tasks among nurses and (ii) subtasks on each nurse. The scheduling algorithm generates a solution initializing our proposed dynamic scheduling to iteratively generate new, feasible schedules based on the scheduling algorithm to accommodate interruptions while preventing nurses' work hours from increasing. To verify the effectiveness of our proposed scheduling, we executed a set of nursing scheduling problems taken from those actually observed and focused on those that featuring frequent interruptions.
Cite this article as:
M. Cheng, H. Ozaku, N. Kuwahara, K. Kogure, and J. Ota, “Dynamic Scheduling in Inpatient Nursing,” Int. J. Automation Technol., Vol.3 No.2, pp. 174-184, 2009.
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References
  1. [1] Japanese Nursing Association, Statistical Data on Nursing Servicein Japan: 2006, http://www.nurse.or.jp/toukei/index.html, 2007.
  2. [2] National Institute of Population and Social Security Research, Populationprojection for Japan: 2006-2055, http://www.ipss.go.jp/ppnewest/j/newest03/newest03point.pdf, 2007.
  3. [3] N. Ilhan, E. Durukan, E. Aras, S. Tukcuoglu, and R. Aygun, “Longworking hours increase the risk of sharp and needlestick injury innurses: the need for new policy implication,” Journal of AdvancedNursing, Vol.56, No.5, pp. 563-568, 2006.
  4. [4] J. Needleman, P. Buerhaus, S. Mattke, M. Stewart, and K. Zelevinsky,“Nurse-staffing levels and the quality of care in hospitals,” theNew England Journal of Medicine, Vol.346, No.22, pp. 1715-1722,2002.
  5. [5] P. Benner, “From novice to expert: Excellence and power in clinicalnursing practice,” Menlo Park, CA: Addison-Wesley, 1984.
  6. [6] S. Lauri and S. Salantera, “Decision-making models in differentfields of nursing,” Research in Nursing & Health, Vol.21, pp. 443-452, 1998.
  7. [7] M. Yokouchi, Y. Ohno, S. Kasahara, H. Numasaki, and A. Ishii,“Development of medical task classification for job scheduling,”Transactions of the Japanese Society for Medical and BiologicalEngineering, Vol.43, No.4, pp. 762-768, 2005 (in Japanese).
  8. [8] J. F. Bard and H. W. Purnomo, “Real-time scheduling for nursesin response to demand fluctuations and personnel shortages,” Proc.of the 5th Int. Conf. on the Practice and Theory of AutomatedTimetabling, Pittsburgh, pp. 67-87, 2004.
  9. [9] P. Brucker, R. Qu, E. Burke, and G. Post, “A decomposition, constructionand post-processing approach for nurse rostering,” Proc.of the 2nd Multidisciplinary Int. Conf. on Scheduling: Theory &Applications (MISTA' 05), pp. 397-406, 2005.
  10. [10] D. M. Ferrin, M. J. Miller, S. Wininger, and M. S. Neuendorf,“ Analysing incentives and scheduling in a major metropolitan hospitaloperating room through simuation,” Proc. of the 2004 Winter Simulation Conf., pp. 1975-1980, 2004.
  11. [11] Vermeulen, S. Bohte, K. Somefun, and H. L. Poutre, “Improvingpatient activity schedules by multi-agent Pareto appointment exchanging,” Proc. of the 8th IEEE Conf. on E-Commerce Technology(CEC' 06), 2006.
  12. [12] T. O. Paulussen, N. R. Jennings, K. S. Decker, and A. Heinzl, “Distributedpatient scheduling in hospitals,” Proc. of the 18th Int. Joint Conference on Artificial Intelligence, pp. 1224-1229, 2003.
  13. [13] R. Ramasesh, “Dynamic job shop scheduling: A survey of simulation research,” Int. Journal of Management Science, Vol.18, No.1,pp. 43-57, 1990.
  14. [14] K. Kogure, “ About the E-nightingale project,” the Report of the Institute of Image Information and Television Engineers, Vol.30,No.27, pp. 17-22, 2006 (in Japanese).
  15. [15] H. I. Ozaku, A. Abe, N. Kuwahara, F. Naya, K. Kogure, and K.Sagara, “Building dialogue corpora for nursing activity analysis,” Proc. of the 6th Int.Workshop on Linguistically Interpreted Corpora (LINC2005), pp. 41-48, 2005.
  16. [16] R. L. Rardin and R. Uzsoy, “Experimental evaluation of heuristicoptimization algorithms: a tutorial,” Journal of Heuristics, Vol.7,pp. 261-304, 2001.
  17. [17] T. Yamada and R. Nakano, “Job-shop scheduling by simulated annealing combined with deterministic local search,” Meta-heuristics: theory & applications, pp. 237-248, 1996.
  18. [18] A. L Tucker and S. J. Spear, “Operational failures and interruptionsin hospital nursing,” Health Services Research, Vol.41, pp. 643-662, 2006.
  19. [19] S. S. Panwalkar and W. Iskander,“ A survey of scheduling rules,”Operations Research, Vol.25, pp. 45-61, 1977.
  20. [20] M. Cheng, H. I. Ozaku, N. Kuwahara, K. Kogure, and J. Ota, “Analysisof daily nursing care: an nursing care scheduling algorithm,”Proc. of the 17th IEEE Int. Symposium on Robot and Human Interactive Communication (IEEE RO-MAN2008), pp. 193-200, 2008.

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