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Electronic Drug Prescribing and Administration - Bedside Medical Decision Making

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  • First Online:
Artificial Intelligence in Medicine (AIMDM 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1620))

Abstract

A rules-based electronic drug prescribing system is described, which by means of radio-linked mobile terminals allows bedside entry of drug prescription and administration data to be evaluated in real-time against wide-ranging clinical data including interactions and allergies. Results of a questionnaire assessing the acceptability of the system are summarised, and preliminary analysis of data gathered as part of routine operation is presented, showing doctors' responses to warning messages of differing severity.

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References

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Author information

Authors and Affiliations

  1. Wolfson Computer Laboratory, Queen Elizabeth Hospital, Edgbaston, Birmingham, B15 2TH, UK

    I. R. Clark, B. A. McCauley, I. M. Young, P. G. Nightingale & M. Peters

  2. Department of Nephrology, Queen Elizabeth Hospital, Edgbaston, Birmingham, B15 2TH, UK

    N. T. Richards & D. Adu

Authors
  1. I. R. Clark
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  2. B. A. McCauley
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  3. I. M. Young
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  4. P. G. Nightingale
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  5. M. Peters
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  6. N. T. Richards
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  7. D. Adu
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Editor information

Editors and Affiliations

  1. Austrian Research Institute for Artificial Intelligence, Schottengasse 3, A-1010, Vienna, Austria

    Werner Horn

  2. Department of Medicine and Computer Science, Stanford University, 251 Campus Drive, Stanford, CA, 94305-5479, USA

    Yuval Shahar

  3. Department of Medicine Karolinska Institutet, Huddinge University Hospital, Sweden

    Greger Lindberg

  4. Department of Medical Informatics and Image Analysis, Aalborg University, Fredrik Bajers Vej 7D, DK-9000, Aalborg, Denmark

    Steen Andreassen

  5. School of Public Policy, University College London, 29/30 Tavistock Square, London, WC1H 9EZ, UK

    Jeremy Wyatt

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© 1999 Springer-Verlag Berlin Heidelberg

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Cite this paper

Clark, I.R. et al. (1999). Electronic Drug Prescribing and Administration - Bedside Medical Decision Making. In: Horn, W., Shahar, Y., Lindberg, G., Andreassen, S., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIMDM 1999. Lecture Notes in Computer Science(), vol 1620. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48720-4_14

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  • DOI: https://doi.org/10.1007/3-540-48720-4_14

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66162-7

  • Online ISBN: 978-3-540-48720-3

  • eBook Packages: Springer Book Archive

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