Background and Objectives: The transition from home to a nursing home is a stressful event for both older persons and informal caregivers. Currently, this transition process is often fragmented, which can create a vicious cycle of health carerelated events. Knowledge of existing care interventions can prevent or break this cycle. This project aims to summarize existing interventions for improving transitional care, identifying their effectiveness and key components. Research Design and Methods: A scoping review was performed within the European TRANS-SENIOR consortium. The databases PubMed, EMBASE (Excerpta Medica Database), PsycINFO, Medline, and CINAHL (Cumulated Index to Nursing and Allied Health Literature) were searched. Studies were included if they described interventions designed to improve the transition from home to a nursing home. Results: 17 studies were identified, describing 13 interventions. The majority of these interventions focused on nursing home adjustment with 1 study including the entire transition pathway. The study identified 8 multicomponent and 5 single-component interventions. From the multicomponent interventions, 7 main components were identified: education, relationships/communication, improving emotional well-being, personalized care, continuity of care, support provision, and ad hoc counseling. The study outcomes were heterogeneous, making them difficult to compare. The study outcomes varied, with studies often reporting nonsignificant changes for the main outcome measures. Discussion and Implications: There is a mismatch between the theory on optimal transitional care and current transitional care interventions, as they often lack a comprehensive approach. This research is the first step toward a uniform definition of optimal transitional care and a tool to improve/develop (future) transitional care initiatives on the pathway from home to a nursing home.
Bridging the gap between hospital and primary care is important as transition from one healthcare setting to another increases the risk on drug-related problems and consequent readmissions. To reduce those risks, pharmacist interventions during and after hospitalization have been frequently studied, albeit with variable effects. Therefore, in this manuscript we propose a three phase approach to structurally address post-discharge drug-related problems. First, hospitals need to transfer up-todate medication information to community pharmacists. Second, the key phase of this approach consists of adequate follow-up at the patients’ home. Pharmacists need to apply their clinical and communication skills to identify and analyze drug-related problems. Finally, to prevent and solve identified drug related problems a close collaboration within the primary care setting between pharmacists and general practitioners is of utmost importance. It is expected that such an approach results in improved quality of care and improved patient safety.
Background: Patients with heart failure (HF) need long-term and complex care delivered by healthcare professionals in primary and secondary care. Although guidelines on optimal HF care exist, no specific description of components that are applied for optimal HF care at home exist. The objective of this review was to describe which components of HF (home) care are found in research studies addressing homecare interventions in the HF population. Methods: The Pubmed, Embase, Cinahl, and Cochrane databases were searched using HF-, homecare services-, and clinical trial-related search terms. Results: The literature search identified 703 potentially relevant publications, out of which 70 articles were included. All articles described interventions with two or more of the following components: multidisciplinary team, continuity of care and care plans, optimized treatment according to guidelines, educational and counselling of patients and caregivers, and increased accessibility to care. Most studies (n=65, 93%) tested interventions with three components or more and 20 studies (29%) used interventions including all five components. Conclusions: There a several studies on HF care at home, testing interventions with a variety in number of components. Comparing the results to current standards, aspects such as collaboration between primary care and hospital care, titration of medication, and patient education can be improved. © 2012 The European Society of Cardiology.
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
In de faculteit ‘Science en Engineering’ van de Rijksuniversiteit Groningen is kennis ontwikkeld op het gebied van verduurzaming en vergroening in de chemie. De ambitie is om toe te werken naar de transitie van synthetische chemische processen naar biobased chemische processen. Een expertisegebied betreft de inzet van biotechnologische enzymconversies als alternatief voor klassieke (fossiele) chemische omzettingen. De vakgroep ‘Product and Processes for Biotechnology’ heeft expertise op het gebied van de opschaling van enzymatische conversies. Het MKB-bedrijf CarbExplore Research B.V. werkt aan procesontwikkeling van enzymatische glucosylering. De methode kan worden toegepast bij de (duurzame) productie van ingrediënten (w.o. zoetstoffen en surfactanten) die nodig zijn voor zogenaamde Home & Personal care producten van de toekomst. Bij de opschaling van de technologie, ontstaan innovatievragen. Inzet van het praktijkgerichte onderzoek tussen de RUG en CarbExplore is het vinden van een efficiënte enzymatische opschalingsroute voor deze groene grondstoffen. In de relatie met CarbExplore wordt gewerkt aan de conversie van een Stevia zoetstof. In het vervolg kan de universiteit deze enzymatische opschalingsmethode toepassen in andere bioconversies, andere producten, en bij andere bedrijven. Zowel voor de universiteit, als voor het bedrijf CarbExplore, wordt een economisch potentieel gecreëerd. De uiteindelijke visie en einddoel is het toewerken naar een vergroening van de chemie door middel van enzymatische conversies.
