Literature DB >> 29857425

Unveiling Originated Stages of Medication Errors: An Automated Pipeline Approach.

Sicheng Zhou1, Hong Kang1, Bin Yao1, Yang Gong1.   

Abstract

Medication error has been a severe patient safety event in the United States. Medication error reports collected by Patient Safety Organizations provide an opportunity to analyze and learn from previous cases. However, the current process of analyzing the reports is labor-intensive and time-consuming. To improve the efficiency, we used automated text classification techniques to develop a pipeline for medication error report pre-analysis. The pipeline was proven functional in two tasks, i.e., identifying the non-preventable adverse drug events from medication error reports, and identifying the error originated stages during the medication distribution process. The proposed pipeline holds promise in helping clinicians understand the nature of medication error in an error report, and locate the potential root causes of the error, which could further facilitate to reduce medication errors in healthcare settings.

Entities:  

Keywords:  Data Mining; Medication Errors; Patient Safety

Mesh:

Year:  2018        PMID: 29857425

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Analyzing Medication Error Reports in Clinical Settings: An Automated Pipeline Approach.

Authors:  Sicheng Zhou; Hong Kang; Bin Yao; Yang Gong
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

2.  An automated pipeline for analyzing medication event reports in clinical settings.

Authors:  Sicheng Zhou; Hong Kang; Bin Yao; Yang Gong
Journal:  BMC Med Inform Decis Mak       Date:  2018-12-07       Impact factor: 2.796

  2 in total

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