Linked Life Data

20841779

Source:http://linkedlifedata.com/resource/pubmed/id/20841779

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 1
pubmed:dateCreated
2010-9-15
pubmed:abstractText
Information technology has the potential to greatly streamline healthcare and reduce the chance of human error. However, there is a growing literature indicating that if systems are not designed adequately they may actually increase the possibility of error in the complex interaction between clinician and machine in healthcare (i.e. they may lead to technology-induced errors). In other domains the study of error has been guided by a variety of theories, models and frameworks for understanding human error. In this paper we argue for the need to consider and extend this work to the study of technology-induced error in healthcare. Insights from the software engineering, human factors and organizational behaviour literature will be described, including a set of models and frameworks that we have been using to guide our work in detecting and preventing technology-induced error in healthcare.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
T
pubmed:status
MEDLINE
pubmed:issn
0926-9630
pubmed:author
pubmed:issnType
Print
pubmed:volume
160
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
714-8
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Theories, models and frameworks for diagnosing technology-induced error.
pubmed:affiliation
School of Health Information Science, University of Victoria, Victoria, British Columbia, Canada. emb@uvic.ca
pubmed:publicationType
Journal Article