Citclops: Data Interpretation and Knowledge-based Systems Integration

Measuring the optical properties of water bodies (as indicators of, e.g., sewage impact, dissolved organic matter, sediment load or gross biological activity) is a way to assess their environmental status. The Citclops European project, in 2012-2015, developed systems to retrieve and use data on natural-water colour, transparency and fluorescence, using low-cost sensors combined with contextual information, taking into account existing experiences. This paper describes the general interpretation of data and delivery of information as carried out via the development of a decision support system named 'Citclops Data Explorer' and available from the main portal of the project

Clinical decision support system to enhance quality control of spirometry using information and communication technologies

BACKGROUND: We recently demonstrated that quality of spirometry in primary care could markedly improve with remote offline support from specialized professionals. It is hypothesized that implementation of automatic online assessment of quality of spirometry using information and communication technologies may significantly enhance the potential for extensive deployment of a high quality spirometry program in integrated care settings. OBJECTIVE: The objective of the study was to elaborate and validate a Clinical Decision Support System (CDSS) for automatic online quality assessment of spirometry. METHODS: The CDSS was done through a three step process including: (1) identification of optimal sampling frequency; (2) iterations to build-up an initial version using the 24 standard spirometry curves recommended by the American Thoracic Society; and (3) iterations to refine the CDSS using 270 curves from 90 patients. In each of these steps the results were checked against one expert. Finally, 778 spirometry curves from 291 patients were analyzed for validation purposes. RESULTS: The CDSS generated appropriate online classification and certification in 685/778 (88.1%) of spirometry testing, with 96% sensitivity and 95% specificity. CONCLUSIONS: Consequently, only 93/778 (11.9%) of spirometry testing required offline remote classification by an expert, indicating a potential positive role of the CDSS in the deployment of a high quality spirometry program in an integrated care setting

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems

Protocol for regional implementation of collaborative lung function testing

The potential of forced spirometry (FS) testing for diagnosis, monitoring and management of chronic respiratory patients is well established1-3 such that FS is a pivotal test in both respiratory medicine and primary care. Moreover, it also shows potential in the informal care scenario: that is, in pharmacy offices for case-finding purposes4,5 and for self-management in selected patients.6,7 We acknowledge that well-designed studies8 have failed to show practical benefits of FS for asthma and COPD diagnosis and management in primary care. However, it has been demonstrated that historical limitations for extensive use of FS in primary care, because of suboptimal quality of testing, can be overcome by offline remote support by specialised professionals.9,10 Large-scale deployment of this type of setting has generated evidence of cost-effectiveness.

Workforce preparation: the Biohealth computing model for Master and PhD students

Abstract The article addresses the strategic role of workforce preparation in the process of adoption of Systems Medicine as a driver of biomedical research in the new health paradigm. It reports on relevant initiatives, like CASyM, fostering Systems Medicine at EU level. The chapter focuses on the BioHealth Computing Program as a reference for multidisciplinary training of future systems-oriented researchers describing the productive interactions with the Synergy-COPD project

Workforce preparation: the Biohealth computing model for Master and PhD students

Abstract The article addresses the strategic role of workforce preparation in the process of adoption of Systems Medicine as a driver of biomedical research in the new health paradigm. It reports on relevant initiatives, like CASyM, fostering Systems Medicine at EU level. The chapter focuses on the BioHealth Computing Program as a reference for multidisciplinary training of future systems-oriented researchers describing the productive interactions with the Synergy-COPD project

Workforce preparation: the Biohealth computing model for Master and PhD students

The article addresses the strategic role of workforce preparation in the process of adoption of Systems Medicine as a driver of biomedical research in the new health paradigm. It reports on relevant initiatives, like CASyM, fostering Systems Medicine at EU level. The chapter focuses on the BioHealth Computing Program as a reference for multidisciplinary training of future systems-oriented researchers describing the productive interactions with the Synergy-COPD project

Clinical decision support for screening, diagnosis and assessment of respiratory diseases: chronic obstructive pulmonary disease as a use case

In this thesis we propose a framework for designing, developing, a clinical decision support systems (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), and then demonstrate how these services can be integrated into the work-flow of healthcare providers. Furthermore, we focus on supporting spirometry, one of the main diagnostic tools in respiratory disease assessment. We present two methods to offer decision support in assuring the quality of a spirometry test that can be easily embedded into the CDSS framework. The first method is a novel algorithm that relies on a set of rules operating on 23 new parameters to define a high quality test. The second is a machine-learning approach, where we optimise the distinction between a good quality spirometry test and a poor one using a set of supervised-learning classifiers and hyper-parametersEn esta tesis proponemos un marco para el diseño y desarrollo de un Sistema de Soporte de Decisión Clínica (SSDC) que ofrezca un conjunto de herramientas para el diagnóstico y la evaluación de las enfermedades pulmonares. Al mismo tiempo demostramos como estos servicios se pueden integrar en el flujo de trabajo del personal sanitario. Además, nos centramos en la ayuda en espirometría, una de las herramientas de diagnóstico principales en la evaluación de enfermedades pulmonares. Presentamos dos métodos de SSDC que tienen como objetivo asegurar la calidad de las pruebas de espirometría, y que se pueden integrar en el marco del SSDC. El primero es un nuevo algoritmo basado en un conjunto de reglas que definen lo que es considerado como una prueba de alta calidad. El segundo es un enfoque de aprendizaje supervisado donde se optimiza la distinción entre una prueba correcta de espirometría y una de mala calida

Development of an algorithm to automatic forced spirometry quality assessment

We hypothesized that the implementation of automatic real-time assessment of quality of forced spirometry (FS) may significantly enhance the potential for extensive deployment of a FS program in the community. Recent studies have demonstrated that the application of quality criteria defined by the ATS/ERS (American Thoracic Society/European Respiratory Society) in commercially available equipment with automatic quality assessment can be markedly improved. To this end, an algorithm for assessing quality of FS automatically was reported. The current research describes the mathematical developments of the algorithm. An innovative analysis of the shape of the spirometric curve, adding 23 new metrics to the traditional 4 recommended by ATS/ERS, was done. The algorithm was created through a two-step iterative process including: (1) an initial version using the standard FS curves recommended by the ATS; and, (2) a refined version using curves from patients. In each of these steps the results were assessed against one expert's opinion. Finally, an independent set of FS curves from 291 patients was used for validation purposes. The novel mathematical approach to characterize the FS curves led to appropriate FS classification with high specificity (95%) and sensitivity (96%). The results constitute the basis for a successful transfer of FS testing to non-specialized professionals in the community

Teenagers' usage of a mobile-wearable-cloud platform to promote healthy lifestyles ::the PEGASO experience

In contemporary society, non-communicable diseases linked to unhealthy lifestyles, such as obesity, are on the rise with a major impact on global deaths. Prevention is the new frontier, promising to increase life expectancy and quality, while reducing costs related to healthcare. The PEGASO project developed a mobile ecosystem where the digital Companion aims at empowering teenagers in the adoption of healthy lifestyles. The pilot study conducted in three European countries (Spain, UK and Italy) shows a good acceptance of the system and that teenagers are keen to use mobile technology to improve their lifestyle, although wearable devices did not engage the young user