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.

Técnicas de análisis de posproceso en resonancia magnetica para el estudio de la conectividad cerebral / Magnetic resonance imaging postprocessing techniques in the study of brain connectivity

La noción de conectividad cerebral es un aspecto clave para entender el funcionamiento cerebral. Las metodologías para detectar y cuantificar los diferentes tipos de conectividad con técnicas de neuroimagen son en la actualidad un área de estudio fundamental en la comprensión de la fisiopatología de muchos trastornos, tanto neurológicos como psiquiátricos. Con este artículo se pretende realizar una revisión crítica de las técnicas con resonancia magnética para medir la conectividad cerebral dentro del actual contexto del proyecto Conectoma. Las técnicas revisadas se dividen en: a) conectividad estructural b) conectividad funcional (análisis de componentes principales, análisis de componentes independientes, vóxel semilla, meta-análisis) y c) conectividad efectiva (interacciones psicofisiológicas, modelo dinámico causal, modelos autorregresivos multivariantes y modelo estructural de ecuaciones). Estos tres enfoques permiten combinar y utilizar distintas técnicas matemático-estadísticas cuyos resultados proporcionan modelos para intentar predecir la funcionalidad cerebral. Es necesario validar los hallazgos de estas técnicas con otras formas de análisis de la conectividad estructural y funcional. Esta información se integra dentro del proyecto Conectoma donde este conjunto de técnicas convergen para ofrecer una representación de todos los modelos de conectividad (AU)

Brain connectivity is a key concept for understanding brain function. Current methods to detect and quantify different types of connectivity with neuroimaging techniques are fundamental for understanding the pathophysiology of many neurologic and psychiatric disorders. This article aims to present a critical review of the magnetic resonance imaging techniques used to measure brain connectivity within the context of the Human Connectome Project. We review techniques used to measure: a) structural connectivity b) functional connectivity (main component analysis, independent component analysis, seed voxel, meta-analysis), and c) effective connectivity (psychophysiological interactions, causal dynamic models, multivariate autoregressive models, and structural equation models). These three approaches make it possible to combine and use different statistical techniques to elaborate mathematical models in the attempt to understand the functioning of the brain. The findings obtained with these techniques must be validated by other techniques for analyzing structural and functional connectivity. This information is integrated in the Human Connectome Project where all these approaches converge to provide a representation of all the different models of connectivity (AU)

[Magnetic resonance imaging postprocessing techniques in the study of brain connectivity]. / Técnicas de análisis de posproceso en resonancia magnetica para el estudio de la conectividad cerebral.

Brain connectivity is a key concept for understanding brain function. Current methods to detect and quantify different types of connectivity with neuroimaging techniques are fundamental for understanding the pathophysiology of many neurologic and psychiatric disorders. This article aims to present a critical review of the magnetic resonance imaging techniques used to measure brain connectivity within the context of the Human Connectome Project. We review techniques used to measure: a) structural connectivity b) functional connectivity (main component analysis, independent component analysis, seed voxel, meta-analysis), and c) effective connectivity (psychophysiological interactions, causal dynamic models, multivariate autoregressive models, and structural equation models). These three approaches make it possible to combine and use different statistical techniques to elaborate mathematical models in the attempt to understand the functioning of the brain. The findings obtained with these techniques must be validated by other techniques for analyzing structural and functional connectivity. This information is integrated in the Human Connectome Project where all these approaches converge to provide a representation of all the different models of connectivity.

A telemedicine model for integrating point-of-care testing into a distributed health-care environment.

Centralized testing demands costly laboratories, which are inefficient and may provide poor services. Recent advances make it feasible to move clinical testing nearer to patients and the requesting physicians, thus reducing the time to treatment. Internet technologies can be used to create a virtual laboratory information system in a distributed health-care environment. This allows clinical testing to be transferred to a cooperative scheme of several point-of-care testing (POCT) nodes. Two pilot virtual laboratories were established, one in Italy (AUSL Modena) and one in Greece (Athens Medical Centre). They were constructed on a three-layer model to allow both technical and clinical verification. Different POCT devices were connected. The pilot sites produced good preliminary results in relation to user acceptance, efficiency, convenience and costs. Decentralized laboratories can be expected to become cost-effective.