TRANSFUSION PRACTICE

The role of failure modes and effects analysis in showing the benefits of automation in the blood bank

  1. Tae Hee Han,
  2. Moon Jung Kim,
  3. Shinyoung Kim,
  4. Hyun Ok Kim,
  5. Mi Ae Lee,
  6. Ji Seon Choi,
  7. Mina Hur,
  8. Andrew St John*

Article first published online: 25 SEP 2012

DOI: 10.1111/j.1537-2995.2012.03883.x

Issue

Transfusion

Transfusion

Volume 53, Issue 5, pages 1077–1082, May 2013

Additional Information

How to Cite

Han, T. H., Kim, M. J., Kim, S., Kim, H. O., Lee, M. A., Choi, J. S., Hur, M. and St John, A. (2013), The role of failure modes and effects analysis in showing the benefits of automation in the blood bank. Transfusion, 53: 1077–1082. doi: 10.1111/j.1537-2995.2012.03883.x

Author Information

  1. From the Department of Laboratory Medicine, Sanggye Paik Hospital, Inje University, Seoul, Korea; the Department of Laboratory Medicine, College of Medicine, Yonsei University, Seoul, Korea; the Department of Laboratory Medicine, School of Medicine, Ewha Womans University, Seoul, Korea; the Department of Laboratory Medicine, Korea University College of Medicine, Seoul, Korea; the Department of Laboratory Medicine, Konkuk University College of Medicine, Seoul, Korea; and Ortho Clinical Diagnostics, Perth, Australia.

*Andrew St John, Scientific and Clinical Affairs, Ortho Clinical Diagnostics Asia Pacific, 14 Learoyd Street, Mt Lawley, WA 6050, Australia; e-mail: astjohn@its.jnj.com.

Publication History

  1. Issue published online: 9 MAY 2013
  2. Article first published online: 25 SEP 2012
  3. Received for publication June 21, 2012; revision received July 23, 2012, and accepted July 24, 2012.

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

View Full Article (HTML) Get PDF (111K)

BACKGROUND: Failure modes and effects analysis (FMEA) is a risk management tool used by the manufacturing industry but now being applied in laboratories.

STUDY DESIGN AND METHODS: Teams from six South Korean blood banks used this tool to map their manual and automated blood grouping processes and determine the risk priority numbers (RPNs) as a total measure of error risk.

RESULTS: The RPNs determined by each of the teams consistently showed that the use of automation dramatically reduced the RPN compared to manual processes. In addition, FMEA showed where the major risks occur in each of the manual processes and where attention should be prioritized to improve the process. Despite no previous experience with FMEA, the teams found the technique relatively easy to use and the subjectivity associated with assigning risk numbers did not affect the validity of the data.

CONCLUSION: FMEA should become a routine technique for improving processes in laboratories.

View Full Article (HTML) Get PDF (111K)