A framework to design successful clinical decisionsupport systems

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3 Scopus citations

Abstract

This paper presents seven principles for successful modeling of the clinical process, forming a framework for clinical decision support systems design. Modeling methods should incorporate data interactions during clinical decisions and should mimic the cognitive skills of clinicians. Predictive models need to be interactive, regenerating predictions in response to new clinical information, or clinician feedback. Any decision support method needs to consider trends of physiological measurements. Temporal trends can be stronger predictors of health outcomes, than cross sectional values. Finally, clinical decision support methods should be outcomes based, in an effort to avoid a 'historical decision' bias. These principles, can contribute to optimized modeling methodologies in healthcare settings, improving the response of health systems to decision making challenges.

Original languageEnglish
Title of host publication10th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2017
PublisherAssociation for Computing Machinery
Pages185-188
Number of pages4
ISBN (Electronic)9781450352277
DOIs
StatePublished - Jun 21 2017
Event10th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2017 - Island of Rhodes, Greece
Duration: Jun 21 2017Jun 23 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F128530

Conference

Conference10th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2017
Country/TerritoryGreece
CityIsland of Rhodes
Period06/21/1706/23/17

Keywords

  • Clinical decision support system
  • Decision making
  • Healthcare quality
  • Systems design
  • Theoretical framework

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