Analysis on descriptions of precautionary statements in package inserts of medicines

Keita Nabeta, Masaomi Kimura, Michiko Ohkura, Fumito Tsuchiya

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Background: To prevent medical accidents, users must be informed of the cautions written in medical package inserts. To realize countermeasures by utilizing information systems, we must also implement a drug information database. However, this is not easy to develop, since the descriptions in package inserts are too complex and their information poorly structured. It is necessary to analyze package insert information and propose a data structure. Methods: We analyzed the descriptions of 'precautions for application' in package inserts via text mining methods. In order to summarize statements, we applied dependency analysis to statements and visualized their relations between predicate words and other words. Furthermore, we extracted words representing timing to execute the order. Results: We found that there are four types of statements: direct orders such as (use), causative orders such as (make someone use), direct interdictions such as (do not use), and causative interdictions such as (do not make user use). As for words representing timing, we extracted six groups: "at the time of delivery," "at the time of preparation," "in use," "after use," and "at the time of storage." From these results, we obtained points of consideration concerning the subjects of orders in the statements and timing of their execution. Conclusion: From the obtained knowledge, we can define the information structure used to describe the precautionary statement. It should contain information such as the actions described in the statement, the flag to express an order or interdiction, the subject to be ordered, and the timing.

Original languageEnglish
Pages (from-to)19-25
Number of pages7
JournalDrug, Healthcare and Patient Safety
Volume4
Issue number1
DOIs
Publication statusPublished - 2012 Feb 23

Keywords

  • Drug database
  • Drug information
  • Medical safety
  • Package insert
  • Text mining

ASJC Scopus subject areas

  • Pharmacology
  • Health Policy

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