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Synergy-COPD: a systems approach for understanding and managing chronic diseases.

Gomez-Cabrero D, Lluch-Ariet M, Tegnér J, Cascante M, Miralles F, Roca J, Synergy-COPD consorti - J Transl Med (2014)

Bottom Line: The challenges posed by the epidemics of CD have triggered a novel health paradigm with major consequences on the traditional concept of disease and with a profound impact on key aspects of healthcare systems.The current manuscript describes main features of the project design and the strategies put in place for its development, as well the expected outcomes during the project life-span.Moreover, the manuscript serves as introductory and unifying chapter of the different papers associated to the Supplement describing the characteristics, tools and the objectives of Synergy-COPD.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Chronic diseases (CD) are generating a dramatic societal burden worldwide that is expected to persist over the next decades. The challenges posed by the epidemics of CD have triggered a novel health paradigm with major consequences on the traditional concept of disease and with a profound impact on key aspects of healthcare systems. We hypothesized that the development of a systems approach to understand CD together with the generation of an ecosystem to transfer the acquired knowledge into the novel healthcare scenario may contribute to a cost-effective enhancement of health outcomes. To this end, we designed the Synergy-COPD project wherein the heterogeneity of chronic obstructive pulmonary disease (COPD) was addressed as a use case representative of CD. The current manuscript describes main features of the project design and the strategies put in place for its development, as well the expected outcomes during the project life-span. Moreover, the manuscript serves as introductory and unifying chapter of the different papers associated to the Supplement describing the characteristics, tools and the objectives of Synergy-COPD.

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Patient information collected through the Personal Health Folder (PHF, Informal Care) and through the Electronic Health Record (EHR, formal healthcare) will be used to feed the biomedical research platform wherein subject-specific predictive modeling will be generated using the knowledge-base and tools for data analysis. Predictive modeling will generate rules to feed Clinical Decision Support Systems (CDSS) embedded into clinical processes to support health professionals. Moreover, it will also help to generate Patient Decision Support Systems (PDSS) embedded into the PHF aiming at patient empowerment for self-management of his/her condition. Interoperability of the three steps indicated in the figure constitutes the Digital Health Framework (DHF) extensively described in Chapter 10 [37].
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Figure 3: Patient information collected through the Personal Health Folder (PHF, Informal Care) and through the Electronic Health Record (EHR, formal healthcare) will be used to feed the biomedical research platform wherein subject-specific predictive modeling will be generated using the knowledge-base and tools for data analysis. Predictive modeling will generate rules to feed Clinical Decision Support Systems (CDSS) embedded into clinical processes to support health professionals. Moreover, it will also help to generate Patient Decision Support Systems (PDSS) embedded into the PHF aiming at patient empowerment for self-management of his/her condition. Interoperability of the three steps indicated in the figure constitutes the Digital Health Framework (DHF) extensively described in Chapter 10 [37].

Mentions: The project hypothesizes that a systems analysis of COPD heterogeneity may facilitate the identification of combined biomarkers with predictive power of disease progress. The elaboration of subject-specific predictive modeling as initially addressed in the project only relied on the analysis of biological phenomena, but further enrichment with other types of input data, namely: patient adherence profile, life-style, clinical and social factors involving frailty risk, etc...) must be considered, as shown in Figure 3. Efforts on personalized modeling, such as the integrated use of bayesian and mechanistic models, are described in Chapter 4 [32].


Synergy-COPD: a systems approach for understanding and managing chronic diseases.

Gomez-Cabrero D, Lluch-Ariet M, Tegnér J, Cascante M, Miralles F, Roca J, Synergy-COPD consorti - J Transl Med (2014)

Patient information collected through the Personal Health Folder (PHF, Informal Care) and through the Electronic Health Record (EHR, formal healthcare) will be used to feed the biomedical research platform wherein subject-specific predictive modeling will be generated using the knowledge-base and tools for data analysis. Predictive modeling will generate rules to feed Clinical Decision Support Systems (CDSS) embedded into clinical processes to support health professionals. Moreover, it will also help to generate Patient Decision Support Systems (PDSS) embedded into the PHF aiming at patient empowerment for self-management of his/her condition. Interoperability of the three steps indicated in the figure constitutes the Digital Health Framework (DHF) extensively described in Chapter 10 [37].
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4255903&req=5

Figure 3: Patient information collected through the Personal Health Folder (PHF, Informal Care) and through the Electronic Health Record (EHR, formal healthcare) will be used to feed the biomedical research platform wherein subject-specific predictive modeling will be generated using the knowledge-base and tools for data analysis. Predictive modeling will generate rules to feed Clinical Decision Support Systems (CDSS) embedded into clinical processes to support health professionals. Moreover, it will also help to generate Patient Decision Support Systems (PDSS) embedded into the PHF aiming at patient empowerment for self-management of his/her condition. Interoperability of the three steps indicated in the figure constitutes the Digital Health Framework (DHF) extensively described in Chapter 10 [37].
Mentions: The project hypothesizes that a systems analysis of COPD heterogeneity may facilitate the identification of combined biomarkers with predictive power of disease progress. The elaboration of subject-specific predictive modeling as initially addressed in the project only relied on the analysis of biological phenomena, but further enrichment with other types of input data, namely: patient adherence profile, life-style, clinical and social factors involving frailty risk, etc...) must be considered, as shown in Figure 3. Efforts on personalized modeling, such as the integrated use of bayesian and mechanistic models, are described in Chapter 4 [32].

Bottom Line: The challenges posed by the epidemics of CD have triggered a novel health paradigm with major consequences on the traditional concept of disease and with a profound impact on key aspects of healthcare systems.The current manuscript describes main features of the project design and the strategies put in place for its development, as well the expected outcomes during the project life-span.Moreover, the manuscript serves as introductory and unifying chapter of the different papers associated to the Supplement describing the characteristics, tools and the objectives of Synergy-COPD.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Chronic diseases (CD) are generating a dramatic societal burden worldwide that is expected to persist over the next decades. The challenges posed by the epidemics of CD have triggered a novel health paradigm with major consequences on the traditional concept of disease and with a profound impact on key aspects of healthcare systems. We hypothesized that the development of a systems approach to understand CD together with the generation of an ecosystem to transfer the acquired knowledge into the novel healthcare scenario may contribute to a cost-effective enhancement of health outcomes. To this end, we designed the Synergy-COPD project wherein the heterogeneity of chronic obstructive pulmonary disease (COPD) was addressed as a use case representative of CD. The current manuscript describes main features of the project design and the strategies put in place for its development, as well the expected outcomes during the project life-span. Moreover, the manuscript serves as introductory and unifying chapter of the different papers associated to the Supplement describing the characteristics, tools and the objectives of Synergy-COPD.

Show MeSH
Related in: MedlinePlus