Modeling information flows in clinical decision support: key insights for enhancing system effectiveness
Author(s) -
Stephanie Medlock,
Jeremy C Wyatt,
Vimla L. Patel,
Edward H. Shortliffe,
Ameen AbuHanna
Publication year - 2016
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocv177
Subject(s) - clinical decision support system , decision support system , computer science , r cast , key (lock) , clinical decision making , decision system , knowledge management , field (mathematics) , evidential reasoning approach , decision engineering , business decision mapping , artificial intelligence , medicine , operations research , intensive care medicine , computer security , engineering , mathematics , pure mathematics
A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the systems to support them. This article outlines such a framework. We present a two-stream model of information flow within clinical decision-support systems (CDSSs): reasoning about the patient (the clinical stream), and reasoning about the user (the cognitive-behavioral stream). We propose that CDSS "effectiveness" be measured not only in terms of a system's impact on clinical care, but also in terms of how (and by whom) the system is used, its effect on work processes, and whether it facilitates appropriate decisions by clinicians and patients. Future research into which factors improve the effectiveness of decision support should not regard CDSSs as a single entity, but should instead differentiate systems based on their attributes, users, and the decision being supported.
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