Integrating Electronic Health Records in Clinical Decision Support Systems

Authors: Eider Sánchez Herrero Carlos Toro Manuel Graña

Date: 11.09.2015


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Abstract

Electronic Health Records (EHR) are systematic collections of digital
health information about individual patients or populations. They provide readily
access to the complete medical history of the patient, which is useful for
decision-making activities. In this paper we focus on a secondary benefit of EHR:
the reuse of the implicit knowledge embedded in it to improve the knowledge on
the mechanisms of a disease and/or the effectiveness of the treatments. In fact, all
such patient data registries stored in EHR reflect implicitly different clinical decisions
made by the clinical professionals that participated in the assistance of
patients (e.g. criteria followed during decision making, patient parameters taken
into account, effect of the treatments prescribed). This work proposes a methodology
that allows the management of EHR not only as data containers and information
repositories, but also as clinical knowledge repositories. Moreover, we
propose an architecture for the extraction of the knowledge from EHR. Such
knowledge can be fed into a Clinical Decision Support System (CDSS), in a way
that could render benefits for the development of innovations from clinicians, health
managers and medical researchers.

BIB_text

@Article {
title = {Integrating Electronic Health Records in Clinical Decision Support Systems},
pages = {407-416},
volume = {45},
keywds = {

Electronic health record, Clinical decision support system, Knowledge extraction, Semantic model


}
abstract = {

Electronic Health Records (EHR) are systematic collections of digital
health information about individual patients or populations. They provide readily
access to the complete medical history of the patient, which is useful for
decision-making activities. In this paper we focus on a secondary benefit of EHR:
the reuse of the implicit knowledge embedded in it to improve the knowledge on
the mechanisms of a disease and/or the effectiveness of the treatments. In fact, all
such patient data registries stored in EHR reflect implicitly different clinical decisions
made by the clinical professionals that participated in the assistance of
patients (e.g. criteria followed during decision making, patient parameters taken
into account, effect of the treatments prescribed). This work proposes a methodology
that allows the management of EHR not only as data containers and information
repositories, but also as clinical knowledge repositories. Moreover, we
propose an architecture for the extraction of the knowledge from EHR. Such
knowledge can be fed into a Clinical Decision Support System (CDSS), in a way
that could render benefits for the development of innovations from clinicians, health
managers and medical researchers.


}
isi = {1},
date = {2015-09-11},
year = {2015},
}
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