Introduction: This paper is part of the Focus Theme of Methods of Information in MEdicine on "Biosignal Interpretation: Advanced Methods for Neural Signals and Images". Objectives: This paper presents the main concepts of a decision making approach for the remote management of COPD patients based on the early detection of disease exacerbation episodes. Methods: An e-diary card is defined to evaluate a number of physiological variables and clinical parameters acquired remotely by means of wearable and environmental sensors deployed in patients' long-stay settings. The automatic evaluation of the card results in a so-called Chronic Status Index (CSI) whose computation is tailored to patients' specific manifestation of the disease (i.e., patient's phenotype). The decision support method relies on a parameterized analysis of CSI variations so as to early detect worsening changes, identify exacerbation severity and track the patterns of recovery. Results: A preliminary study, carried out in real settings with 30 COPD patients monitored at home, has shown the validity and sensitivity of the method proposed, which was effectively able to timely and correctly identify patients' critical situation. Conclusion: The preliminary results showed that the proposed e-diary card, which presents several novel features with respect to other solutions presented in the literature, can be practically used to remotely monitor COPD patients.

Decision making concepts for the remote, personalized evaluation of COPD patients' health status

Colantonio S;Martinelli M;Salvetti O;
2014

Abstract

Introduction: This paper is part of the Focus Theme of Methods of Information in MEdicine on "Biosignal Interpretation: Advanced Methods for Neural Signals and Images". Objectives: This paper presents the main concepts of a decision making approach for the remote management of COPD patients based on the early detection of disease exacerbation episodes. Methods: An e-diary card is defined to evaluate a number of physiological variables and clinical parameters acquired remotely by means of wearable and environmental sensors deployed in patients' long-stay settings. The automatic evaluation of the card results in a so-called Chronic Status Index (CSI) whose computation is tailored to patients' specific manifestation of the disease (i.e., patient's phenotype). The decision support method relies on a parameterized analysis of CSI variations so as to early detect worsening changes, identify exacerbation severity and track the patterns of recovery. Results: A preliminary study, carried out in real settings with 30 COPD patients monitored at home, has shown the validity and sensitivity of the method proposed, which was effectively able to timely and correctly identify patients' critical situation. Conclusion: The preliminary results showed that the proposed e-diary card, which presents several novel features with respect to other solutions presented in the literature, can be practically used to remotely monitor COPD patients.
2014
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Clinical decision support systems
outpatient monitoring
personalized medicine
chronic obstructive pulmonary disease
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/308891
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