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Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the
potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate
change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as
follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential.
Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several
methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most
vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573
lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological
habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that
the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to
be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on
enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater
ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate
change provide preliminary targets for development of climate change conservation management and mitigation
strategies.
Objectives: eHealth and innovation are often regarded as synonyms - not least because eHealth technologies and applications are new to their users. This position paper challenges this view and aims at exploring the nature of eHealth innovation against the background of common definitions of innovation and facts from the biomedical and health informatics literature. A good understanding of what constitutes innovative eHealth developments allows the degree of innovation to be measured and interpreted.
Methods: To this end, relevant biomedical and health informatics literature was searched mainly in Medline and ACM digital library. This paper presents seven facts about implementing and applying new eHealth developments hereby drawing on the experience published in the literature.
Results: The facts are: 1. eHealth innovation is relative. 2. Advanced clinical practice is the yardstick. 3. Only used and usable eHealth technology can give birth to eHealth innovatio. 4. One new single eHealth function does not make a complex eHealth innovation. 5. eHealth innovation is more evolution than revolution. 6. eHealth innovation is often triggered behind the scenes; and 7. There is no eHealth innovation without sociocultural change.
Conclusions: The main conclusion of the seven facts is that eHealth innovations have many ingredients: newness, availability, advanced clinical practice with proven outcomes, use and usability, the supporting environment, other context factors and the stakeholder perspectives. Measuring eHealth innovation is thus a complex matter. To this end we propose the development of a composite score that expresses comprehensively the nature of eHealth innovation and that breaks down its complexity into the three dimensions: i) eHealth adoption, ii) partnership with advanced clinical practice, and iii) use and usability of eHealth. In order to better understand the momentum and mechanisms behind eHealth innovation the fourth dimension, iv) eHealth supporting services and means, needs to be studied. Conceptualising appropriate measurement instruments also requires eHealth innovation to be distinguished from eHealth sophistication, performance and quality, although innovation is intertwined with these concepts. The demanding effort for defining eHealth innovation and measuring it properly seem worthwhile and promise advances in creating better systems. This paper thus intends to stimulate the necessary discussion.
Background: We see a growing number of older adults receiving long-term care in industrialized countries. The Healthcare Utilization Model by Andersen suggests that individual need characteristics influence utilization. The purpose of this study is to analyze correlations between need characteristics and service utilization in home care arrangements.
Methods: 1,152 respondents answered the questionnaire regarding their integration of services in their current and future care arrangements. Care recipients with high long-term care needs answered the questionnaire on their own, the family caregiver assisted the care recipient in answering the questions, or the family caregiver responded to the questionnaire on behalf of the care recipient. They were asked to rank specific needs according to their situation. We used descriptive statistics and regression analysis.
Results: Respondents are widely informed about services. Nursing services and counseling are the most used services. Short-term care and guidance and training have a high potential for future use. Day care, self-help groups, and mobile services were the most frequently rejected services in our survey. Women use more services than men and with rising age utilization increases. Long waiting times and bad health of the primary caregiver increases the chance of integrating services into the home care arrangements.
Conclusion: The primary family caregiver has a high impact on service utilization. This indicates that the whole family should be approached when offering services. Professionals should react upon the specific needs of care dependents and their families.
The study addresses staffing and workforce issues for home‐ and community‐based long‐term care in Germany. It is based on a study aimed at developing staffing recommendations for home‐care provider organisations. The study was commissioned within the regulation of the German long‐term care act. Following an exploratory literature search on staffing issues in home‐ and community‐based care qualitative interviews with 30 experts in home care were conducted. In addition, time needed for different interventions in homes of people in need of care (n = 129) was measured. Ethical approval for the study was obtained. The literature on the topic is limited. In Germany, no fixed staff‐to‐client ratio exists, but staffing is determined primarily by reimbursement policies, not by care recipients’ needs. The results of the interviews indicated that staffing ratios are not the main concern of home‐care providers. Experts stressed that general availability of staff with different qualification levels and the problems of existing regulation on services and their reimbursement are of higher concern. The measurement of time needed for selected interventions reveals the huge heterogeneity of home‐care service delivery and the difficulty of using a task‐based approach to determine staffing levels. Overall, the study shows that currently demand for home‐care exceeds supply. Staff shortage puts a risk to home care in Germany. Existing approaches of reimbursement‐driven determination of staffing levels have not been sufficient. A new balance between staffing, needs and reimbursement policies needs to be developed.