Experiences of a general practitioner in the daily practice about Digital Health Literacy. The real needs.

Digital Health Literacy (DHL) is a key element to promote patient empowerment. This position paper presents the lessons learnt from the daily activities of a General Practitioner interacting with patients. General Practitioners have a main role in each stage on individual digital health literacy process. They are the first meeting point between patients and the medical knowledge; in the search phase, they are who can prescribe and validate health information; in the comprehension phase, they lead to a full understanding; and in the adoption phase, they assist in the own personal application. Major conclusions are that General Practitioners need a set of tools, organizational resources and knowledge to acquire Digital Health Literacy skills to help patients on their way from the information to the empowerment. Some of these tools and knowledge are identified to draw the future roadmap to get people with Digital Health Literacy skills.

Performance assessment of a closed-loop system for diabetes management.

Telemedicine systems can play an important role in the management of diabetes, a chronic condition that is increasing worldwide. Evaluations on the consistency of information across these systems and on their performance in a real situation are still missing. This paper presents a remote monitoring system for diabetes management based on physiological sensors, mobile technologies and patient/doctor applications over a service-oriented architecture that has been evaluated in an international trial (83,905 operation records). The proposed system integrates three types of running environments and data engines in a single service-oriented architecture. This feature is used to assess key performance indicators comparing them with other type of architectures. Data sustainability across the applications has been evaluated showing better outcomes for full integrated sensors. At the same time, runtime performance of clients has been assessed spotting no differences regarding the operative environment.

From data to the decision: A software architecture to integrate predictive modelling in clinical settings.

The application of statistics and mathematics over large amounts of data is providing healthcare systems with new tools for screening and managing multiple diseases. Nonetheless, these tools have many technical and clinical limitations as they are based on datasets with concrete characteristics. This proposition paper describes a novel architecture focused on providing a validation framework for discrimination and prediction models in the screening of Type 2 diabetes. For that, the architecture has been designed to gather different data sources under a common data structure and, furthermore, to be controlled by a centralized component (Orchestrator) in charge of directing the interaction flows among data sources, models and graphical user interfaces. This innovative approach aims to overcome the data-dependency of the models by providing a validation framework for the models as they are used within clinical settings.

Heart Cycle: facilitating the deployment of advanced care processes.

Current trends in health management improvement demand the standardization of care protocols to achieve better quality and efficiency. The use of Clinical Pathways is an emerging solution for that problem. However, current Clinical Pathways are big manuals written in natural language and highly affected by human subjectivity. These problems make their deployment and dissemination extremely difficult in real practice environments. Furthermore, the intrinsic difficulties for the design of formal Clinical Pathways requires new specific design tools to help making them relly useful and cost-effective. Process Mining techniques can help to automatically infer processes definition from execution samples and, thus, support the automatization of the standardization and continuous control of healthcare processes. This way, they can become a relevant helping tool for clinical experts and healthcare systems for reducing variability in clinical practice and better understand the performance of the system.