The treatment of comorbid patients is one of the main challenges of modern health care, and many Medical Informatics approaches have been devoted to it in the last years. In this paper, we propose the first approach in the literature that analyses the conformance of execution traces with multiple Computer-Interpretable Guidelines (CIGs), as needed in the treatment of comorbid patients. This is a fundamental task, to support physicians in an a-posteriori analysis of the treatments that have been provided. Notably, the conformance problem is very complex in this context, since CIGs may have negative interactions, so that in specific circumstances full conformance to individual CIGs may be dangerous for patients. We thus complement our conformance analysis with an explanation approach, aimed at justifying deviations in case they can be explained in terms of interaction management, e.g., some possible undesired interaction has been avoided. Our approach is based on Answer Set Programming, and, to face realistic problems, devotes specific attention to the temporal dimension.

Temporal Conformance Analysis and Explanation on Comorbid Patients

Piovesan, Luca
;
Terenziani, Paolo;Theseider Dupré, Daniele
2018-01-01

Abstract

The treatment of comorbid patients is one of the main challenges of modern health care, and many Medical Informatics approaches have been devoted to it in the last years. In this paper, we propose the first approach in the literature that analyses the conformance of execution traces with multiple Computer-Interpretable Guidelines (CIGs), as needed in the treatment of comorbid patients. This is a fundamental task, to support physicians in an a-posteriori analysis of the treatments that have been provided. Notably, the conformance problem is very complex in this context, since CIGs may have negative interactions, so that in specific circumstances full conformance to individual CIGs may be dangerous for patients. We thus complement our conformance analysis with an explanation approach, aimed at justifying deviations in case they can be explained in terms of interaction management, e.g., some possible undesired interaction has been avoided. Our approach is based on Answer Set Programming, and, to face realistic problems, devotes specific attention to the temporal dimension.
2018
978-989-758-281-3
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11579/93791
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? ND
social impact