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J Am Med Inform Assoc 2004;11:285-293 doi:10.1197/jamia.M1425
  • Focus on Electronic Prescribing
  • Model Formulation

Structured Representation of the Pharmacodynamics Section of the Summary of Product Characteristics for Antibiotics: Application for Automated Extraction and Visualization of Their Antimicrobial Activity Spectra

  1. Catherine Duclos,
  2. Gian Luigi Cartolano,
  3. Michael Ghez,
  4. Alain Venot
  1. Affiliations of the authors: Laboratoire d'informatique médicale et de bioinformatique (LIM&BIO), UFR Santé, Médecine, Biologie Humaine, Université Paris 13, Bobigny, France (CD, MG, AV); Laboratoire de microbiologie, CHI Saint Germain/Poissy, Saint Germain en Laye, France (GLC)
  1. Correspondence and reprints: Catherine Duclos, PharmD, PhD, LIM&BIO, UFR de Santé, Médecine et Biologie Humaine Léonard de Vinci, 74 rue Marcel Cachin 93017 Bobigny cedex, France; e-mail: <catherine.duclos{at}avc.ap-hop-paris.fr>
  • Received 15 July 2003
  • Accepted 4 February 2004

Abstract

Objective The aim of this study was to construct automatically a knowledge base concerning the pharmacodynamic properties of antibiotics and a visualization tool.

Design The authors studied the various guidelines used to write the pharmacodynamics section of the Summary of Product Characteristics (SPC) for antibiotics and constructed a conceptual model of the information. Particular words, syntagms, and punctuation elements were marked in the SPC texts, and automatic extraction was then used to build a knowledge base. This base was used to create dynamic HTML tables displaying the activity spectra of the antibiotics.

Measurements The authors analyzed the performances of automatic extraction (recall and precision).

Results The conceptual pharmacodynamics model dealt with antibiotics, pathogens, susceptibility tests, and the prevalence of resistance. Automatic extraction had a recall rate of 97.9% and a precision of 96.2%. The tool displaying antibiotic spectra and resistance prevalences used color codes to identify differences in susceptibility.

Conclusion This tool can provide an overview of the prevalence of resistance as expressed in SPC in primary care settings. Its potential impact should be evaluated.

Footnotes

  • The authors thank Jean François Forget for making the Vidal Drug Database available for this study.

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