A sequential data analysis approach to electronic health record workflow

David R. Kaufman, Stephanie K. Furniss, Maria Adela Grando, David Larson, Matthew M. Burton

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

2 Scopus citations


Failure to understand clinical workflow across electronic health record (EHR) tasks is a significant contributor to usability problems. In this paper, we employed sequential data analysis methods with the aim of characterizing patterns of 5 clinicians' information-gathering across 66 patients. Two analyses were conducted. The first one characterized the most common sequential patterns as reflected in the screen transitions. The second analysis was designed to mine and quantify the frequency of sequence occurrence. We observed 27 screen-transition patterns that were employed from 2 to 7 times. Documents/Images and Intake/Output screens were viewed for nearly all patients indicating the importance of these information sources. In some cases, they were viewed more than once which may show that users are following inefficient patterns in the information gathering process. New quantitative methods of analysis as applied to interaction data can yield critical insights in robust designs that better support clinical workflow.

Original languageEnglish (US)
Title of host publicationStudies in Health Technology and Informatics
PublisherIOS Press
Number of pages6
ISBN (Print)9781614995739
StatePublished - 2015
EventContext Sensitive Health Informatics Conference, CSHI 2015 - Curitiba, Brazil
Duration: Aug 15 2015Aug 16 2015

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)09269630
ISSN (Electronic)18798365


OtherContext Sensitive Health Informatics Conference, CSHI 2015


  • Electronic health records
  • process mining
  • sequential pattern analysis
  • usability

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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