Data mining applied to the cognitive rehabilitation of patients with acquired brain injury

Acquired brain injury (ABI) is one of the leading causes of death and disability in the world and is associated with high health care costs as a result of the acute treatment and long term rehabilitation involved. Different algorithms and methods have been proposed to predict the effectiveness of rehabilitation programs. In general, research has focused on predicting the overall improvement of patients with ABI. The purpose of this study is the novel application of data mining (DM) techniques to predict the outcomes of cognitive rehabilitation in patients with ABI. We generate three predictive models that allow us to obtain new knowledge to evaluate and improve the effectiveness of the cognitive rehabilitation process. Decision tree (DT), multilayer perceptron (MLP) and general regression neural network (GRNN) have been used to construct the prediction models. 10-fold cross validation was carried out in order to test the algorithms, using the Institut Guttmann Neurorehabilitation Hospital (IG) patients database. Performance of the models was tested through specificity, sensitivity and accuracy analysis and confusion matrix analysis. The experimental results obtained by DT are clearly superior with a prediction average accuracy of 90.38%, while MLP and GRRN obtained a 78.7% and 75.96%, respectively. This study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients.

Business model for healthcare interoperability services

En la situación actual donde los sistemas TI sanitarios son diversos con modelos que van desde soluciones predominantes, adoptadas y creadas por grandes organizaciones, hasta soluciones a medida desarrolladas por cualquier empresa de la competencia para satisfacer necesidades concretas. Todos estos sistemas se encuentran bajo similares presiones financieras, no sólo de las condiciones económicas mundiales actuales y el aumento de los costes sanitarios, sino también bajo las presiones de una población que ha adoptado los avances tecnológicos actuales, y demanda una atención sanitaria más personalizable a la altura de esos avances tecnológicos que disfruta en otros ámbitos. El objeto es desarrollar un modelo de negocio orientado al soporte del intercambio de información en el ámbito clínico. El objetivo de este modelo de negocio es aumentar la competitividad dentro de este sector sin la necesidad de recurrir a expertos en estándares, proporcionando perfiles técnicos cualificados menos costosos con la ayuda de herramientas que simplifiquen el uso de los estándares de interoperabilidad. Se hará uso de especificaciones abiertas ya existentes como FHIR, que publica documentación y tutoriales bajo licencias abiertas. La principal ventaja que nos encontramos es que ésta especificación presenta un giro en la concepción actual de la disposición de información clínica, vista hasta ahora como especial por el requerimiento de estándares más complejos que solucionen cualquier caso por específico que sea. Ésta especificación permite hacer uso de la información clínica a través de tecnologías web actuales (HTTP, HTML, OAuth2, JSON, XML) que todo el mundo puede usar sin un entrenamiento particular para crear y consumir esta información. Partiendo por tanto de un mercado con una integración de la información casi inexistente, comparada con otros entornos actuales, hará que el gasto en integración clínica aumente dramáticamente, dejando atrás los desafíos técnicos cuyo gasto retrocederá a un segundo plano. El gasto se centrará en las expectativas de lo que se puede obtener en la tendencia actual de la personalización de los datos clínicos de los pacientes, con acceso a los registros de instituciones junto con datos ‘sociales/móviles/big data’.---ABSTRACT---In the current situation IT health systems are diverse, with models varying from predominant solutions adopted and created by large organizations, to ad-hoc solutions developed by any company to meet specific needs. However, all these systems are under similar financial pressures, not only from current global economic conditions and increased health care costs, but also under pressure from a population that has embraced the current technological advances, and demand a more personalized health care, up to those enjoyed by technological advances in other areas. The purpose of this thesis is to develop a business model aimed at the provision of information exchange within the clinical domain. It is intended to increase competitiveness in the health IT sector without the need for experts in standards, providing qualified technical profiles less expensively with the help of tools that simplify the use of interoperability standards. Open specifications, like FHIR, will be used in order to enable interoperability between systems. The main advantage found within FHIR is that introduces a shift in the current conception of available clinical information. So far seen, the clinical information domain IT systems, as a special requirement for more complex standards that address any specific case. This specification allows the use of clinical information through existing web technologies (HTTP, HTML, OAuth2, JSON and XML), which everyone can use with no particular training to create and consume this information. The current situation in the sector is that the integration of information is almost nonexistent, compared to current trends. Spending in IT health systems will increase dramatically within clinical integration for the next years, leaving the technical challenges whose costs will recede into the background. The investment on this area will focus on the expectations of what can be obtained in the current trend of personalization of clinical data of patients with access to records of institutions with ‘social /mobile /big data’.