NURSE SCHEDULING AND RESCHEDULING UNDER UNCERTAINTY

Yıl 2020, Cilt: 38 Sayı: 1, 75 - 95, 31.03.2020

Sakine Batun Ece Karpuz

https://doi.org/10.17065/huniibf.483986

Cited By: 2

Öz

Nurse planning decisions play a critical role on hospital budgeting, quality of nursing services and job satisfaction of nurses. Nurse planning in a hospital is composed of four main phases: nurse budgeting, nurse scheduling (rostering), nurse rescheduling (staffing) and nurse assignment. In this study, the integrated problem of nurse scheduling and rescheduling under demand uncertainty is considered. The problem is formulated and solved as a two-stage stochastic integer program. The value of the stochastic solution is estimated using realistic problem instances over a monthly planning horizon generated based on the data provided by a private healthcare provider in Ankara, Turkey. The computational results show that the value of the stochastic solution can be more than 9% in some problem instances, and hence healthcare providers can benefit from using models that capture uncertainty rather than deterministic models.

Anahtar Kelimeler

Nurse Scheduling, Nurse Rescheduling, Two-Stage Stochastic Programming

BELİRSİZLİK VARKEN HEMŞİRE ÇİZELGELEME PROBLEMİ

Öz

Hemşire planlama, hastane bütçelemesinde, hastalara verilen hizmetin kalitesinde ve hemşirelerin iş memnuniyetinde kilit rol oynar. Bir hastanedeki hemşire planlama süreci temel olarak dört başlıktan oluşur: Bütçeleme, çizelgeleme, çizelgelerin güncellenmesi ve hemşire atama. Bu çalışmada, aylık çizelgelerin oluşturulması ve güncellenmesi problemi talep belirsizliği altında incelenmektedir. Bu entegre problem, iki aşamalı stokastik tamsayılı program olarak modellenmiş ve çözülmüştür. Aylık planlama ufkunu gözeten gerçekçi problem örnekleri kullanılarak gerçekleştirilen sayısal çalışmalarla belirsizliği modellemenin değeri ölçülmüştür. Elde edilen sonuçlar, belirsizliği modellemenin değerinin %9’u geçebileceğini ve bu nedenle stokastik modelleri kullanmanın oluşturulan çizelgelerin performansını önemli ölçüde iyileştirebileceğini göstermektedir.

Anahtar Kelimeler

Hemşire Çizelgeleme, İki Aşamalı Rassal Programlama

Kaynakça

• Atmaca, E., Pehlivan, C., Aydoğdu, C.B., Yakıcı, M. 2012. “Hemşire Çizelgeleme Problemi ve Uygulaması”, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Vol. 28, No. 4, p. 351-358.
• Bard J.F., Purnomo, H.W. 2004. “Real-time scheduling for nurses in response to demand fluctuations and personnel shortages”, Proceedings of the 5th International Conference on the Practice and Theory of Automated Timetabling, p. 67–87, Pittsburgh, PA.
• Belien, J., Demeulemeester, E. 2008. “A Branch and Price Approach for Integrating Nurse and Surgery Scheduling”, European Journal of Operational Research, Vol. 189, 652-668.
• Birge, J.R., Louveaux, F. 1997. Introduction to Stochastic Programming. Springer, USA.Burke, E.K., De Causmaecker, P., Berghe, G.V., Van Landeghem, H. 2004. “The State of the Art of Nurse Rostering”, Journal of Scheduling, Vol. 7, p. 441–499.
• Cheang, B., Lim, B., Rodrigues, B. 2003. “Nurse Rostering Problems – A Bibliographic Survey”, European Journal of Operational Research, Vol. 151, p.447-460.
• Dantzig, G.B. 1955. “Linear Programming Under Uncertainty”, Management Science, Vol. 1, p. 197-206.Ernst, A.T., Jiang, H. and Krishnamoorthy, M., Sier, D. 2004. “Staff Scheduling and Rostering: A Review of Applications”, Methods and Models. European Journal of Operational Research, Vol. 153, p. 3-27.
• Glass, C.A., Knight, R.A. 2010. “The Nurse Rostering Problem: A Critical Appraisal of the Problem Structure”, European Journal of Operational Research, Vol. 202, p. 379-389.
• Kim, K. 2014. “Predictive Modeling and Stochastic Optimization in Healthcare”, PhD Thesis, Field of Industrial Engineering and Management Sciences, Northwestern University.
• Memiş, S.A. 2012. “Son Dönemdeki Sağlık Harcamalarının Analizi, Değerlendirme Notu”, TEPAV.
• Mobasher, A., Lim, G., Bard, J.F., Jordan, V. 2011. “Daily Scheduling of Nurses in Operating Suites”, IIE Transactions on Healthcare Systems Engineering, Vol. 1, No. 4, p. 232-246.
• Punnakitikashem, P. 2007. “Integrated Nurse Staffing and Assignment under Uncertainty”, PhD Thesis, The University of Texas at Arlington, Department of Industrial and Manufacturing Systems Engineering.
• Punnakitikashem, P., Rosenberger, J.M., Behan, D.B. 2008. “Stochastic programming for nurse assignment.” Computational Optimization and Applications, Vol. 40, p. 321-349.
• Rachev, S.T., Höchstötter, M., Fabozzi, F.J., Focardi, S.M. 2010. Probability and Statistics for Finance. John Wiley & Sons, Inc., Canada.
• Tein, L., Ramli, R. 2010. “Recent Advancements of Nurse Scheduling Models and a Potential Path”, 6th IMT-GT Conference on Mathematics, Statistics and Applications (ICMSA), Malaysia.
• Van Slyke , R.M., Wets, R. 1969. “L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming”, SIAM Journal on Applied Mathematics, Vol.