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Preparation of chemotherapy drugs: Planning policy for reduced waiting times

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  • Masselink, Inge H.J.
  • van der Mijden, Thomas L.C.
  • Litvak, Nelly
  • Vanberkel, Peter T.
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    Abstract

    This study investigates the impact of pharmacy policies on patient waiting time in the Chemotherapy Day Unit of the Netherlands Cancer Institute--Antoni van Leeuwenhoek hospital. The project evaluated whether a reduction in waiting time resulting from medication orders being prepared in advance of patient appointments was justified, given that medications prepared in advance are wasted when patients arrive too sick for treatment. Within this context, we derive analytic expressions to approximate patient waiting times and wastage costs, allowing management to see the tradeoff between these two metrics for different policies. Using a case study and a simulation model, the approximations are evaluated. The use of analytic expressions allows the analysis to be easily repeated when medication costs change or when new medications/protocols are introduced. In the same vein, other hospitals with different patient case mixes can easily complete the analysis in their settings. Finally, the outcome from this study resulted in a new policy at the cancer center which is expected to decrease the waiting time by half, while only increasing pharmacy's costs by 1-2%.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 40 (2012)
    Issue (Month): 2 (April)
    Pages: 181-187

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    Handle: RePEc:eee:jomega:v:40:y:2012:i:2:p:181-187

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    Related research

    Keywords: Stochastic modeling Queueing systems Pharmacy Chemotherapy;

    References

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    1. Robbins, Matthew J. & Jacobson, Sheldon H., 2011. "Pediatric vaccine procurement policy: The monopsonist's problem," Omega, Elsevier, Elsevier, vol. 39(6), pages 589-597, December.
    2. A. Federgruen & H. Groenevelt, 1988. "M/G/c Queueing Systems with Multiple Customer Classes: Characterization and Control of Achievable Performance Under Nonpreemptive Priority Rules," Management Science, INFORMS, INFORMS, vol. 34(9), pages 1121-1138, September.
    3. Litvak, Nelly & van Rijsbergen, Marleen & Boucherie, Richard J. & van Houdenhoven, Mark, 2008. "Managing the overflow of intensive care patients," European Journal of Operational Research, Elsevier, Elsevier, vol. 185(3), pages 998-1010, March.
    4. Harper, P. R. & Shahani, A. K. & Gallagher, J. E. & Bowie, C., 2005. "Planning health services with explicit geographical considerations: a stochastic location-allocation approach," Omega, Elsevier, Elsevier, vol. 33(2), pages 141-152, April.
    5. Syam, Siddhartha S. & Côté, Murray J., 2010. "A location-allocation model for service providers with application to not-for-profit health care organizations," Omega, Elsevier, Elsevier, vol. 38(3-4), pages 157-166, June.
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