Analysis on descriptions of dosage regimens in package inserts of medicines

Masaomi Kimura, Kazuhiro Okada, Keita Nabeta, Michiko Ohkura, Fumito Tsuchiya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

To prevent medical accidents caused by mix-up, the confirmation of usage should be the key to determining error. If a computerized order entry system for medicines shows information concerning therapeutic indications to doctors, they can subsequently avoid mix-ups of medicines such as the case in question. To investigate data which can be utilized for a database in such an entry system, we study the description patterns of the sentences in the dosage regimen portion of the SGML formatted package inserts data via a method based on the text mining technique. Based on this result, we also propose the data structure of dosage regimen information, which will be the basis of a drug information database to ensure safe usage.

Original languageEnglish
Title of host publicationHuman Interface and the Management of Information
Subtitle of host publicationInformation and Interaction - Symposium on Human Interface 2009, Held as Part of HCI International 2009, Proceedings
Pages539-548
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2009 Dec 1
EventHuman Interface and the Management of Information: Information and Interaction - Symposium on Human Interface 2009, Held as Part of HCI International 2009, Proceedings - San Diego, CA, United States
Duration: 2009 Jul 192009 Jul 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5618 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceHuman Interface and the Management of Information: Information and Interaction - Symposium on Human Interface 2009, Held as Part of HCI International 2009, Proceedings
Country/TerritoryUnited States
CitySan Diego, CA
Period09/7/1909/7/24

Keywords

  • Data structure
  • Medical safety
  • Text mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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