The development and evaluation of delirium assessment and nursing care decision-making assistant mobile application for intensive care unit

Fangyu Yang, Meihua Ji, Shu Ding, Ying Wu, Polun Chang, Chiawei Lin, Xin Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

Delirium is a common complication among patients in ICU settings. Although it has been repeatedly confirmed that Confusion Assessment Model for Intensive Care Unit (CAM-ICU), one of the most commonly used ICU delirium assessment tool, is highly accurate in validation studies, it's sensitivity and specificity is relatively low during routine practice among bedside nurses. The aim of this study is to develop a mobile application (app) to detect delirium and to test its reliability and validity both by research nurses and among ICU bedside nurses. The app was programmed with Java and installed on a mobile device with Android system. After completion of reliability and validity testing, the app will be integrated into the existing Hospital Information System in order to automatically retrieve essential information for risk factor identification and formulation of care plan accordingly to prevent or manage ICU delirium.

Original languageEnglish
Title of host publicationNursing Informatics 2016 - eHealth for All
Subtitle of host publicationEvery Level Collaboration - From Project to Realization
EditorsWalter Sermeus, Patrick Weber, Paula M. Procter
PublisherIOS Press
Pages668-672
Number of pages5
ISBN (Electronic)9781614996576
DOIs
StatePublished - 2016
Event13th International Conference on Nursing Informatics, NI 2016 - Geneva, Switzerland
Duration: 25 Jun 201629 Jun 2016

Publication series

NameStudies in Health Technology and Informatics
Volume225
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference13th International Conference on Nursing Informatics, NI 2016
Country/TerritorySwitzerland
CityGeneva
Period25/06/1629/06/16

Keywords

  • Confusion assessment model for intensive care unit
  • Diagnostic test study
  • ICU delirium
  • Mobile application
  • Usability evaluation

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