The Potential of ICT in supporting Domiciliary Care in Germany

This report documents the findings of the study on the potential of ICT in supporting the provision of domiciliary care, with particular attention to the case of immigrant care workers and informal caregivers in Germany. This country study was launched by JRC-IPTS in 2008 in parallel with two complementary country studies, assessing the situation in Spain and the UK, with the same focus and objectives. All three studies were prompted by the findings of a previous exploratory study on the use of ICT by immigrant care workers in Italy. In Germany, the use of Information Communication Technologies (ICT) for health and social care is playing an increasingly important role in the context of the demographic changes. As, on the one hand, people are getting older and the need for care is increasing, and, on the other hand, the number of formal and informal caregivers is decreasing, technical devices are seen as a possible solution to this dilemma. At the same time, people in need of care and their relatives have a tendency to informally employ private care assistants, often from migrant backgrounds, to assist those in need of care in their homes with daily tasks, so as to avoid and postpone their transferral into institutional care. This report gives an overview on the situation of domiciliary care in Germany, outlining the current use of ICT in home care and by domiciliary caregivers. It investigates the opportunities for ICT in home care and identifies drivers and barriers for the deployment of ICT by caregivers with a particular focus on migrant care assistants. The research undertaken in this and the other national reports is exploratory in nature. The study employs a triangulation of methods, comprising desk-based analysis of existing reports and scientific publications; analysis of information and service web sites; and field work involving direct questioning of experts, service providers, and a sample of carers and care workers, including immigrants.JRC.DG.J.4-Information Societ

Process-based evaluation of the VALUE perfect predictor experiment of statistical downscaling methods

Statistical downscaling methods (SDMs) are techniques used to downscale and/or bias-correct climate model results to regional or local scales. The European network VALUE developed a framework to evaluate and inter-compare SDMs. One of VALUE's experiments is the perfect predictor experiment that uses reanalysis predictors to isolate downscaling skill. Most evaluation papers for SDMs employ simple statistical diagnostics and do not follow a process-based rationale. Thus, in this paper, a process-based evaluation has been conducted for the more than 40 participating model output statistics (MOS, mostly bias correction) and perfect prognosis (PP) methods, for temperature and precipitation at 86 weather stations across Europe. The SDMs are analysed following the so-called “regime-oriented” technique, focussing on relevant features of the atmospheric circulation at large to local scales. These features comprise the North Atlantic Oscillation, blocking and selected Lamb weather types and at local scales the bora wind and the western Iberian coastal-low level jet. The representation of the local weather response to the selected features depends strongly on the method class. As expected, MOS is unable to generate process sensitivity when it is not simulated by the predictors (ERA-Interim). Moreover, MOS often suffers from an inflation effect when a predictor is used for more than one station. The PP performance is very diverse and depends strongly on the implementation. Although conditioned on predictors that typically describe the large-scale circulation, PP often fails in capturing the process sensitivity correctly. Stochastic generalized linear models supported by well-chosen predictors show improved skill to represent the sensitivities