Studying the HIT-complexity interchange

Craig E. Kuziemsky*, Elizabeth M. Borycki, Andre W. Kushniruk

*Corresponding author for this work

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

5 Citations (Scopus)
12 Downloads (Pure)

Abstract

The design and implementation of health information technology (HIT) is challenging, particularly when it is being introduced into complex settings. While complex adaptive system (CASs) can be a valuable means of understanding relationships between users, HIT and tasks, much of the existing work using CASs is descriptive in nature. This paper addresses that issue by integrating a model for analyzing task complexity with approaches for HIT evaluation and systems analysis. The resulting framework classifies HIT-user tasks and issues as simple, complicated or complex, and provides insight on how to study them.

Original languageEnglish
Title of host publicationNursing Informatics 2016
Subtitle of host publicationeHealth for all : every level collaboration - from project to realization
EditorsWalter Sermeus, Paula M. Procter, Patrick Weber
Place of PublicationAmsterdam
PublisherIOS Press
Pages38-42
Number of pages5
ISBN (Electronic)9781614996583
ISBN (Print)9781614996576
DOIs
Publication statusPublished - 2016
Externally publishedYes
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

Other

Other13th International Conference on Nursing Informatics, NI 2016
CountrySwitzerland
CityGeneva
Period25/06/1629/06/16

Bibliographical note

Copyright 2016 IMIA and IOS Press. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Clinical simulation
  • Complexity
  • Health information technology
  • Naturalistic observations
  • Technology-induced errors
  • Usability testing

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