IDEAS home Printed from
   My bibliography  Save this paper

On the design of custom packs: Grouping of medical disposable items for surgical procedures






Custom packs group medical disposable items into a single sterile package that is used for surgical procedures. Although custom packs constitute a well-known concept in the hospital setting, little is known on methodologies to configure them, especially if the number of medical items, procedures and surgeons is large. In this paper we propose a mathematical programming approach to guide hospitals in developing or reconfiguring their custom packs. In particular, we optimize the configuration process so that the number of material touch points, the number of configured packs and the cost of waste is optimized. We develop an intuitive integer non-linear programming model which we eventually linearize and apply to real data of a medium-sized Belgian hospital. We report on the crucial data gathering phase and the problems we encountered in retrieving accurate information. A computational experiment compares the optimized results with the performance of the current configuration settings and indicates how to improve the custom pack usage. Multiple scenarios are listed and evaluated, such as the development of surgeon-specific or discipline-wide custom packs. We point at some interesting insights that can be taken up by the hospital management to guide the configuration and accompanying negotiation processes, both internally (surgeons) and externally (vendors).

Suggested Citation

  • B. Cardoen & M. Vanhoucke & J. Beliën, 2011. "On the design of custom packs: Grouping of medical disposable items for surgical procedures," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/751, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:11/751

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    Health care services; combinatorial optimization; integer linear programming; decision analysis;

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rug:rugwps:11/751. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nathalie Verhaeghe). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.