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A Simulation Approach for Scheduling Patients in the Department of Radiation Oncology

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Abstract

Physical therapy, hemodialysis and radiation oncology departments in which patients go through lengthy and periodic treatments need to utilize their limited and expensive equipment and human resources efficiently. In such departments, it is an important task to continue to treat current patients without any interruption along with incoming patients. In this study, a patient scheduling approach for a university radiation oncology department is introduced to minimize delays in treatments due to potential prolongations in treatments of current patients and to maintain efficient use of the daily treatment capacity. A simulation analysis of the scheduling approach is also conducted to assess its efficiency under different environmental conditions and to determine appropriate scheduling policy parameter values. Also, the simulation analysis of the suggested scheduling approach enables to determine appropriate scheduling parameters under given circumstances. Therefore, the system can perform more efficiently.

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References

  1. Babes, M., and Sarma, G. V., Out-patient queues at the Ibni-Roche Health Centre. J. Oper. Res. Soc. 42:10845–855, 1991.

    Article  MATH  Google Scholar 

  2. Brahimi, M., and Worthington, D. J., Queuing models for out-patient appointment systems—a case study. J. Oper. Res. Soc. 42:9731–745, 1991.

    Google Scholar 

  3. Fetter, R. B., and Thampson, J. D., The simulation of hospital systems. Oper. Res. 13:5609–711, 1965.

    Article  Google Scholar 

  4. Ho, C. H., and Lau, H. S., Minimizing total cost in scheduling outpatient appointments. Manage. Sci. 38:121750–1764, 1992.

    Article  MATH  Google Scholar 

  5. Ho, C. H., and Lau, H. S., Evaluating the impact of operating conditions on the performance of appointment scheduling rules in service systems. Eur. J. Oper. Res. 112:3542–553, 1999, doi:10.1016/S0377-2217(97)00393-7.

    Article  MATH  Google Scholar 

  6. Jeang, A., Inpatient admission system model using SIMAN software. J. Med. Syst. 14:6365–374, 1990, doi:10.1007/BF00996716.

    Article  Google Scholar 

  7. Paulussen, T. O., Jennings, N. R., Decker, K. S., and Heinzl, A., Distributed patient scheduling in hospitals. Proceedings of 18th International Joint Conference on Artificial Intelligence. 1224–1229, Acapulco: Mexico, 2003.

  8. Paulussen, T. O., Zöller, A., Heinzl, A., Braubach, L., Pokahr, A., and Lamersdorf, W., Patient scheduling under uncertainty. Proceedings of the 2004 ACM Symposium on Applied computing (SAC2004). Nicosia: Cyprus, 2004.

  9. Paulussen, T. O., Zöller, A., Heinzl, A., Braubach, L., Pokahr, A., and Lamersdorf, W., Dynamic patient scheduling in hospitals. Coordination and agent technology in value networks. GITO, Berlin, 2004.

    Google Scholar 

  10. Perez, C. A., and Brady, L. W., Principles and practice of radiation oncology. Lippincott-Raven, Philadelphia, p. 2341, 1998.

    Google Scholar 

  11. Podgorelec, V., and Kokol, P., Genetic algorithm based system for patient scheduling in highly constrained situations. J. Med. Syst. 21:6417–427, 2004.

    Article  Google Scholar 

  12. Rising, E. J., Baron, R., and Averil, B., A systems analysis of a university-health-service out-patient clinic. Oper. Res. 21:51030–1047, 1973.

    Article  Google Scholar 

  13. Rohleder, T. R., and Klassen, K. J., Using client-variance information to improve dynamic appointment scheduling performance. Omega-International J. Manage. Sci. 28:3293–302, 2000, doi:10.1016/S0305-0483(99)00040-7.

    Article  Google Scholar 

  14. Soriano, A., Comparisons of two scheduling systems. Oper. Res. 14:1338–397, 1966.

    MathSciNet  Google Scholar 

  15. Su, S., and Shih, C. L., Managing a mixed-registration-type appointment system in outpatient clinics. Int. J. Med. Inform. 70:31–40, 2003, doi:10.1016/S1386-5056(03)00008-X.

    Article  Google Scholar 

  16. Standridge, C. R., Using expert systems for simulation modeling of patient scheduling. Simulation. 75:3148–156, 2000, doi:10.1177/003754970007500303.

    Article  MATH  Google Scholar 

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Correspondence to Esra Koyuncu.

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Ogulata, S.N., Cetik, M.O., Koyuncu, E. et al. A Simulation Approach for Scheduling Patients in the Department of Radiation Oncology. J Med Syst 33, 233–239 (2009). https://doi.org/10.1007/s10916-008-9184-2

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  • DOI: https://doi.org/10.1007/s10916-008-9184-2

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