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Evaluation of hospital medication inventory policies

Author

Listed:
  • Marek Gebicki
  • Ed Mooney
  • Shi-Jie Chen
  • Lukasz Mazur

Abstract

As supply chain costs constitute a large portion of hospitals’ operating expenses and with $27.7 billion spent by the US hospitals on drugs alone in 2009, improving medication inventory management provides a great opportunity to decrease the cost of healthcare. This study investigates different management approaches for a system consisting of one central storage location, the main pharmacy, and multiple dispensing machines located in each department. Each medication has a specific unit cost, availability from suppliers, criticality level, and expiration date. Event-driven simulation is used to evaluate the performance of several inventory policies based on the total cost and patient safety (service level) under various arrangements of the system defined by the number of drugs and departments, and drugs’ criticality, availability, and expiration levels. Our results show that policies that incorporate drug characteristics in ordering decisions can address the tradeoff between patient safety and cost. Indeed, this study shows that such policies can result in higher patient safety and lower overall cost when compared to traditional approaches. Additional insights from this study allow for better understanding of the medication inventory system’s dynamics and suggest several directions for future research in this topic. Findings of this study can be applied to help hospital pharmacies with managing their inventory. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Marek Gebicki & Ed Mooney & Shi-Jie Chen & Lukasz Mazur, 2014. "Evaluation of hospital medication inventory policies," Health Care Management Science, Springer, vol. 17(3), pages 215-229, September.
  • Handle: RePEc:kap:hcarem:v:17:y:2014:i:3:p:215-229
    DOI: 10.1007/s10729-013-9251-1
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    References listed on IDEAS

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    1. Miragliotta, Giovanni, 2006. "Layers and mechanisms: A new taxonomy for the Bullwhip Effect," International Journal of Production Economics, Elsevier, vol. 104(2), pages 365-381, December.
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    Cited by:

    1. Moons, Karen & Waeyenbergh, Geert & Pintelon, Liliane, 2019. "Measuring the logistics performance of internal hospital supply chains – A literature study," Omega, Elsevier, vol. 82(C), pages 205-217.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Esha Saha & Pradip Kumar Ray, 2019. "Modelling and analysis of healthcare inventory management systems," OPSEARCH, Springer;Operational Research Society of India, vol. 56(4), pages 1179-1198, December.
    4. Meisam Nasrollahi & Jafar Razmi, 2021. "A mathematical model for designing an integrated pharmaceutical supply chain with maximum expected coverage under uncertainty," Operational Research, Springer, vol. 21(1), pages 525-552, March.
    5. Volland, Jonas & Fügener, Andreas & Schoenfelder, Jan & Brunner, Jens O., 2017. "Material logistics in hospitals: A literature review," Omega, Elsevier, vol. 69(C), pages 82-101.

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