TY - GEN
T1 - Run-time support to comorbidities in GLARE-SSCPM
AU - Bottrighi, Alessio
AU - Piovesan, Luca
AU - Terenziani, Paolo
N1 - Publisher Copyright:
© 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
PY - 2019
Y1 - 2019
N2 - Comorbidities play a relevant role in healthcare, so that, in the last years, several approaches Medical Informatics and Artificial Intelligence have developed software tools to support physicians in the treatment of comorbid patients. Computer Interpretable Guidelines (CIGs) are consolidated decision support tools to help physicians, but they are devoted to provide evidence-based recommendations for one specific disease. In order to support the treatment of patient affected by multiple diseases, challenging additional problems have to be addressed, such as (i) the detection of the interactions between CIG actions, (ii) their management, and, finally, (ii) the "merge" of CIGs. Several CIG approaches have been recently extended in order to face (at least one of) such challenging problems, and one of them is GLARE (GuideLine Acquisition Representation and Execution). However, such approaches have mostly focused on the "apriori" treatment of such problems, while addressing them "run-time" (i.e., to support physicians during the execution of the CIGs on a specific patient) involves additional challenges, and requires additional methodologies. In this paper we take advantage of previous extensions of GLARE (to cope with issues (i), (ii), (iii)), and propose a new knowledge-based, "focused" and interactive management of comorbid patients.
AB - Comorbidities play a relevant role in healthcare, so that, in the last years, several approaches Medical Informatics and Artificial Intelligence have developed software tools to support physicians in the treatment of comorbid patients. Computer Interpretable Guidelines (CIGs) are consolidated decision support tools to help physicians, but they are devoted to provide evidence-based recommendations for one specific disease. In order to support the treatment of patient affected by multiple diseases, challenging additional problems have to be addressed, such as (i) the detection of the interactions between CIG actions, (ii) their management, and, finally, (ii) the "merge" of CIGs. Several CIG approaches have been recently extended in order to face (at least one of) such challenging problems, and one of them is GLARE (GuideLine Acquisition Representation and Execution). However, such approaches have mostly focused on the "apriori" treatment of such problems, while addressing them "run-time" (i.e., to support physicians during the execution of the CIGs on a specific patient) involves additional challenges, and requires additional methodologies. In this paper we take advantage of previous extensions of GLARE (to cope with issues (i), (ii), (iii)), and propose a new knowledge-based, "focused" and interactive management of comorbid patients.
KW - Clinical Guidelines
KW - Comorbid Patients
KW - Interaction Analysis and Management
UR - https://www.scopus.com/pages/publications/85064669788
U2 - 10.5220/0007685004980505
DO - 10.5220/0007685004980505
M3 - Conference contribution
AN - SCOPUS:85064669788
T3 - HEALTHINF 2019 - 12th International Conference on Health Informatics, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019
SP - 498
EP - 505
BT - HEALTHINF 2019 - 12th International Conference on Health Informatics, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019
A2 - Moucek, Roman
A2 - Fred, Ana
A2 - Gamboa, Hugo
PB - SciTePress
T2 - 12th International Conference on Health Informatics, HEALTHINF 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019
Y2 - 22 February 2019 through 24 February 2019
ER -