Augmenting EHR interfaces for enhanced nurse communication and decision making

Alessandro Chetta, Jane M Carrington, Angus Graeme Forbes

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

Abstract

The use of electronic health records (EHRs) in clinical environments provides new opportunities for nurses to integrate data analyses into their practice. While having access to these records has many benefits, the act of recording, retrieving, and analyzing this data can nonetheless introduce communication issues, as navigating and interpreting large amounts of heterogeneous data can be difficult, and conclusions can be hard to validate. In this paper, we describe a series of integrated visual interfaces to help nurses document and reason about patient data and about clinicians' understanding of patient data. The interfaces present the output of a predictive algorithm that makes use of historical EHR data, patient vital signs, and nurse handoff reports in order to classify a patient in terms of their likelihood of experiencing clinical events. Furthermore, the interfaces enable the nurses to quickly explore the original data and to examine other nurses' interpretation of patient activity during previous shifts. We present a series of usage scenarios that introduce our interactive visualization tools in the context of real-world healthcare situations.

Original languageEnglish (US)
Title of host publicationProceedings of the 2015 Workshop on Visual Analytics in Healthcare, VAHC 2015 - in conjunction with IEEE VIS 2015
PublisherAssociation for Computing Machinery
Volume25-October-2015
ISBN (Electronic)9781450336710
DOIs
StatePublished - Oct 25 2015
Event2015 Workshop on Visual Analytics in Healthcare, VAHC 2015 - Chicago, United States
Duration: Oct 25 2015 → …

Other

Other2015 Workshop on Visual Analytics in Healthcare, VAHC 2015
CountryUnited States
CityChicago
Period10/25/15 → …

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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