Performance of long-term care systems in Europe. ENEPRI Policy Brief No. 13, December 2012

The evaluation of long-term care (LTC) systems carried out in Work Package 7 of the ANCIEN project shows which performance criteria are important and – based on the available information – how European countries score on those criteria. This paper summarises the results and discusses the policy implications. An overall evaluation was carried out for four representative countries: Germany, the Netherlands, Spain and Poland. Of the four countries, the Dutch system has the highest scores on quality of life of LTC users, quality of care and equity of the LTC system, and it performs the secondbest after Poland in terms of the total burden of care (consisting of the financial burden and the burden of informal caregiving). The German system has somewhat lower scores than the Dutch on all four dimensions. The Polish system excels in having a low total burden of care, but it scores the lowest on quality of care and equity. The Spanish system has few extreme scores. Some important lessons are the following. The performance of a LTC system is a complex concept where many dimensions have to be included. Specifically, the impact of informal caregiving on the caregivers and on society should not be forgotten. The role of the state in funding and organising LTC versus individual responsibilities is one of the most important differences among countries. Choices concerning private funding and the role of informal care have a large effect not only on the public expenditures but also on the fairness of the system. International research into the relative preferences for the different performance criteria could produce a sound basis for the weights used in the overall evaluation.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Introducing assistive technology into the homes of older people: Some lessons from the Netherlands - A case study

The authors have just completed a study of assistive technology (AT) and how it can be introduced into the existing homes of older people. As part of this empirical study some collaboration with the Netherlands took place for two reasons. First to learn about the use of assistive technology from a country where its creative use was well established and second to learn how older people influence policy. Two Dutch consultants helped the team and a short visit was paid to Eindhoven. As a result of this collaboration new ways of using AT were found and comparisons made with the policy and legislative background. In addition lessons were drawn about the involvement of older people.