Implementation of an integrated drug information system for inpatients to reduce medication errors in administrating stage

Tun Yang Lawrence Sung, Fei Hung Hung, Hung Wen Chiu

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

Abstract

In hospitals, computerized provider order entry (CPOE) with Clinical Decision Support System (CDSS) would decrease respectable amount of medication errors in prescribing stage. However, medication errors occur not only in prescribing stage, but also in administrating stage. In this study we constructed an integrated drug information system (IDIS) for inpatients. To reduce medication errors in administrating stage, IDIS is constructed on a computerized drug cart and could provide patients' data, drug information with drug images, drug administration routes, drug interactions, and intravenous drug compatibility information. By offering these helpful information, care workers in Taiwan could easily find medication errors as well. IDIS have been constructed and been demonstrated by patients' information from a medical center in Taipei. The primary results showed that 16.3% of inpatients still had drug interaction concerns, i.e. every patient suffered approximately 0.35 drug interaction in average. It seems that except for CPOE with CDSSs, it could be helpful using such a system to prevent medication errors.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
Pages743-746
Number of pages4
Publication statusPublished - 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: Aug 20 2008Aug 25 2008

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period8/20/088/25/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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