An analysis of the logistics of supplying and processing sterilized items in hospitals

doi:10.1016/0305-0548(78)90017-5

Computers & Operations Research

Volume 5, Issue 1, 1978, Pages 47-54

https://doi.org/10.1016/0305-0548(78)90017-5 Get rights and content

Abstract

This paper presents an analysis of the logistics of supplying and processing sterile medical/surgical supplies and materials for hospitals. The analysis slightly modifies classical inventory theory to take into consideration the special needs and requirements of hospitals, particularly the need to allow for the possibility of being ‘cut off from supplies’ and to take into consideration the effects of single-use vs multiple-use items [1,2,4,6].

The analysis breaks out total sterile stock requirements into two components—processing stock and replacement stock. The processing stock component is the multiple-use and single-use, non-prepackaged kern stock required to ‘support’ the processing cycle. For the case of continuous processing, continuous constant demand, the processing component is equal to the product of the daily demand times the processing cycle in days. For the case of discrete, evenly spaced demand, it is described by a range of values, the lower limit of which is a linear function of demand and processing time and the upper limit of which is a disjointed linear function of demand and processing time.

The replacement stock component is the stock that is required to replace items thȧt wear out or are lost, damaged, pilfered, and the like. The replacement stock component is broken out into two components: a working stock—the stock required to replace items that wear out, etc., during the normal time between arrival of supplies; and a safety stock—the stock required for replacements during the time when a hospital could be cut off from supplies. The analysis shows that, for fixed replenishment intervals, the replacement stock component is equal to the daily demand multiplied by the sum of the replenishment and cut-off periods, and the product is divided by the number of times the item in question can be used. At economical order quantities, the working stock component is proportional to the square root of the annual demand times the cost to order items divided by the number of uses possible for the item in question times the annual cost to inventory items.

An example demonstrates the combined effects of processing and replacement stock on total sterile stock requirements for a hospital. The example shows that single-use, non-prepackaged items require the greatest level of supply, single-use prepackaged items the next level of supply, multiple-use slowly processed items an intermediate level of supply, and multiple-use quickly processed items the lowest level of supply.

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There are more references available in the full text version of this article.

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Although some papers have proposed general methods to determine inventory control parameters, i.e., reorder point and order quantity, in a healthcare setting, there is limited quantified research that considers the unique characteristics of the OR. The body of literature in inventory management in healthcare can generally be grouped into four categories: (1) operations research methods to optimize inventory control parameters in central storage (CS) [23,24]; (2) inventory management in department storerooms [8,25–34]; (3) investigations of both CS and department store rooms [35–38]; (4) work that incorporated MRP and JIT concepts [9,39–42]. All these papers tried to optimize reorder point and order quantity and have not dealt with the allocation of supplies between different possible locations.
In a hospital, surgical supplies can be stored in multiple locations, each of which has limited space and different associated costs. The locations include central storage, where items are retrieved to build a cart of supplies for each procedure; sterile storage adjacent to the operating rooms; and within the operating rooms themselves. In practice, the decision on allocating items to these locations is often based on the staff’s experience, rather than through optimization methods. In this research, we have identified the costs associated with each location to determine where each item should be stored and in what quantities. These costs include the cost of building the case cart, the cost of returning unused items to storage, the cost of picking items during a procedure, the cost of restocking and the cost of reviewing items to determine what needs to be replenished. Since the number of supplies required to perform a procedure is uncertain, we have developed a robust stochastic mixed-integer programming model to make the inventory allocation decision. The model also enables a hospital to assess the potential cost saving from optimization of the preference cards, which are used by surgeons to specify the requested supplies available on the case carts. The performance of the proposed model is evaluated through a case study. Three alternatives to the current configuration of the system are presented and reduction of inventory expenditure within each alternative is discussed. Finally, sensitivity analyses are performed to determine which cost parameters contribute to the model more significantly and how the model behaves against different levels of risk coefficient.
Material logistics in hospitals: A literature review
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The handling of sterile medical items is a distinct field of research within hospital distribution and scheduling. Fineman and Kapadia [46] were among the first to address this problem in the OR literature. For a brief introduction into sterilization logistics, see Di Mascolo and Gouin [107].
Hospital material management has been identified as one key cost containment lever to cope with steadily increasing healthcare costs in industrialized countries. The purpose of this work is to present the state-of-the-art of research on material logistics management in hospitals. Particular focus is given to articles that apply quantitative methods. Our contribution is threefold: First, we provide research guidance through categorizing literature and identifying major research streams. Second, we discuss applied methodologies and third, we identify future research directions. A systematic approach is undertaken in order to identify the relevant literature from 1998 to 2014. Applicable publications are categorized thematically and methodologically and future research opportunities are worked out. In total, 145 publications are identified and discussed in this work. The literature is categorized into four streams, i.e., (1) Supply and procurement, (2) Inventory management, (3) Distribution and scheduling, and (4) Holistic supply chain management. The use of optimization techniques is constantly gaining importance. The number of respective publications has continually grown and has peaked over the last three years. Optimization has been successfully applied in research streams (1), (2), and (3). Category (4) comprises a rather qualitative research field of literature dealing with supply chain management issues.
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^∗: Stephen J. Fineman is an independent management consultant in the health services field. He has served medical centers, hospitals, group practices, as well as government and private agencies, in the areas of long-range planning, organization and staffing, and operations analysis. Prior to becoming an independent management consultant, he was associated with Cresap, McCormick and Paget Inc., Arthur D. Little, Inc., The MITRE Corporation, and Dasol Corporation. He holds a B.S. degree from Cornell University and an M.S. degree from Princeton University, where he was a Guggenheim Fellow. He also did graduate work in management at Massachusetts Institute of Technology.

^†

Asha S. Kapadia is an Associate Professor of Biometry and Health Services Administration at The University of Texas School of Public Health in Houston. Prior to joining the University of Texas she was an Associate Professor of Quantitative Management Science at the College of Business Administration in the University of Houston. She has also worked at Arthur D. Little, Inc. as a management consultant for two years. She holds a S.M. degree in industrial Management from Massachusetts Institute of Technology and a Ph.D. in Statistics/Operations Research from Harvard University.

The analysis presented in this paper was developed by the senior author, Mr. Fineman, while he was with the staff of Arthur D. Little, Inc. The analysis is based on work performed for the U.S. Army Medical Research and Development Command under Contract No. DADA17-70-0072. The findings presented here are not to be construed as an official Department of the Army position unless so designated by other authorized documents.

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An analysis of the logistics of supplying and processing sterilized items in hospitals

Abstract

Decision Rules for Inventory Management

Analysis of Inventory Systems

Yale J. biol. Med.