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Inferencing Strategies for Automated Alerts on Critically Abnormal Laboratory and Blood Gas Data

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Decision Support Systems in Critical Care

Part of the book series: Computers and Medicine ((C+M))

Abstract

A relatively insignificant amount of human thought is required to recognize critically abnormal events. After a few weeks of training on the ward, most medical students can recognize seriously abnormal results of common laboratory tests and take some definitive action, such as calling a supervising physician. The “gestalt” by which laboratory results are appreciated as clinically dangerous is complex and challenging to duplicate in a modern digital computer.

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References

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Authors
  1. M. Michael Shabot
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  2. Mark LoBue
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  3. Beverley J. Leyerle
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  4. Stuart B. Dubin
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Editor information

Editors and Affiliations

  1. Cedars-Sinai Medical Center, 90048-1865, Los Angeles, CA, USA

    M. Michael Shabot M.D. (Associate Director of Surgery Director of Surgical Intensive Care Clinical Associate Professor of Surgery and Anesthesiology) (Associate Director of Surgery Director of Surgical Intensive Care Clinical Associate Professor of Surgery and Anesthesiology)

  2. UCLA School of Medicine, 90048, Los Angeles, CA, USA

    M. Michael Shabot M.D. (Associate Director of Surgery Director of Surgical Intensive Care Clinical Associate Professor of Surgery and Anesthesiology) (Associate Director of Surgery Director of Surgical Intensive Care Clinical Associate Professor of Surgery and Anesthesiology)

  3. Medical Computing, LDS Hospital, 84143, Salt Lake City, UT, USA

    Reed M. Gardner Ph.D. (Co-Director Professor of Medical Informatics) (Co-Director Professor of Medical Informatics)

  4. University of Utah, 84112, Salt Lake City, UT, USA

    Reed M. Gardner Ph.D. (Co-Director Professor of Medical Informatics) (Co-Director Professor of Medical Informatics)

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© 1994 Springer-Verlag New York Inc.

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Shabot, M.M., LoBue, M., Leyerle, B.J., Dubin, S.B. (1994). Inferencing Strategies for Automated Alerts on Critically Abnormal Laboratory and Blood Gas Data. In: Shabot, M.M., Gardner, R.M. (eds) Decision Support Systems in Critical Care. Computers and Medicine. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2698-7_10

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  • DOI: https://doi.org/10.1007/978-1-4612-2698-7_10

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97799-7

  • Online ISBN: 978-1-4612-2698-7

  • eBook Packages: Springer Book Archive

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