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The Optimization of Total Laboratory Automation by Simulation of a Pull-Strategy

  • Systems-Level Quality Improvement
  • Published:
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Abstract

Laboratory results are essential for physicians to diagnose medical conditions. Because of the critical role of medical laboratories, an increasing number of hospitals use total laboratory automation (TLA) to improve laboratory performance. Although the benefits of TLA are well documented, systems occasionally become congested, particularly when hospitals face peak demand. This study optimizes TLA operations. Firstly, value stream mapping (VSM) is used to identify the non-value-added time. Subsequently, batch processing control and parallel scheduling rules are devised and a pull mechanism that comprises a constant work-in-process (CONWIP) is proposed. Simulation optimization is then used to optimize the design parameters and to ensure a small inventory and a shorter average cycle time (CT). For empirical illustration, this approach is applied to a real case. The proposed methodology significantly improves the efficiency of laboratory work and leads to a reduction in patient waiting times and increased service level.

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Acknowledgments

The authors thank the anonymous medical center for providing the case study. This work was partially supported by the National Science Council of Taiwan, Republic of China, under grants NSC-101-2221-E-006 -137 -MY3 and MOST-103-2622-E-006 -025 -CC3.

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Authors and Affiliations

  1. Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan

    Taho Yang, Teng-Kuan Wang & Chia-Lo Su

  2. Department of Business Administration, National Chiayi University, Chiayi City, Taiwan

    Vincent C. Li

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  1. Taho Yang
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  2. Teng-Kuan Wang
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  3. Vincent C. Li
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  4. Chia-Lo Su
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Correspondence to Taho Yang.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Yang, T., Wang, TK., Li, V.C. et al. The Optimization of Total Laboratory Automation by Simulation of a Pull-Strategy. J Med Syst 39, 162 (2015). https://doi.org/10.1007/s10916-014-0162-6

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  • DOI: https://doi.org/10.1007/s10916-014-0162-6

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