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Preliminary Processing and Analysis of an Adverse Event Dataset for Detecting Sepsis-Related Events

Abstract

Adverse event (AE) reports contain notes detailing procedural and guideline deviations, and unwanted incidents that can bring harm to patients. Available datasets mainly focus on vigilance or post-market surveillance of adverse drug reactions or medical device failures. The lack of clinical-related AE datasets makes it challenging to study healthcare-related AEs. AEs affect 10% of hospitalized patients, and almost half are preventable. Having an AE dataset can assist in identifying possible patient safety interventions and performing quality surveillance to lower AE rates. The free-text notes can provide insight into the cause of incidents and lead to better patient care. The objective of this study is to introduce a Norwegian AE dataset and present preliminary processing and analysis for sepsis-related events, specifically peripheral intravenous catheter-related bloodstream infections. Therefore, the methods focus on performing a domain analysis to prepare and better understand the data through screening, generating synthetic free-text notes, and annotating notes.
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Category

Academic chapter

Language

English

Author(s)

  • Melissa Yan
  • Lise Husby Høvik
  • André Pedersen
  • Lise Tuset Gustad
  • Øystein Nytrø

Affiliation

  • SINTEF Digital / Health Research
  • St. Olavs Hospital, Trondheim University Hospital
  • Norwegian University of Science and Technology

Year

2021

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Book

2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

ISBN

9781665401265

Page(s)

1605 - 1610

View this publication at Norwegian Research Information Repository