When planning a study measuring the effects of a neurodevelopmental treatment (NDT), we were confronted with the methodological problem that while measuring the effects of NDT, a rival hypothesis is that the decision to implement the NDT might be related to the quality of nursing care. Therefore, we measured the quality of nursing care as a possible confounding variable in relation to this outcome study. The quality of nursing care was measured on 12 wards participating in the experimental and control groups of the outcome study. Data were collected from 125 patients and 71 nurses and patients' records. The findings showed no significant differences in the quality of nursing care between the 2 groups of wards (P = .49). This method may be useful to other researchers conducting outcome research and who are confronted with a similar methodological problem.
BACKGROUND: Recent evidence suggests that an increase in baccalaureate-educated registered nurses (BRNs) leads to better quality of care in hospitals. For geriatric long-term care facilities such as nursing homes, this relationship is less clear. Most studies assessing the relationship between nurse staffing and quality of care in long-term care facilities are US-based, and only a few have focused on the unique contribution of registered nurses. In this study, we focus on BRNs, as they are expected to serve as role models and change agents, while little is known about their unique contribution to quality of care in long-term care facilities. METHODS: We conducted a cross-sectional study among 282 wards and 6,145 residents from 95 Dutch long-term care facilities. The relationship between the presence of BRNs in wards and quality of care was assessed, controlling for background characteristics, i.e. ward size, and residents' age, gender, length of stay, comorbidities, and care dependency status. Multilevel logistic regression analyses, using a generalized estimating equation approach, were performed. RESULTS: 57% of the wards employed BRNs. In these wards, the BRNs delivered on average 4.8 min of care per resident per day. Among residents living in somatic wards that employed BRNs, the probability of experiencing a fall (odds ratio 1.44; 95% CI 1.06-1.96) and receiving antipsychotic drugs (odds ratio 2.15; 95% CI 1.66-2.78) was higher, whereas the probability of having an indwelling urinary catheter was lower (odds ratio 0.70; 95% CI 0.53-0.91). Among residents living in psychogeriatric wards that employed BRNs, the probability of experiencing a medication incident was lower (odds ratio 0.68; 95% CI 0.49-0.95). For residents from both ward types, the probability of suffering from nosocomial pressure ulcers did not significantly differ for residents in wards employing BRNs. CONCLUSIONS: In wards that employed BRNs, their mean amount of time spent per resident was low, while quality of care on most wards was acceptable. No consistent evidence was found for a relationship between the presence of BRNs in wards and quality of care outcomes, controlling for background characteristics. Future studies should consider the mediating and moderating role of staffing-related work processes and ward environment characteristics on quality of care.
Staffing practices in long-term care lack a clear evidence base and often seem to be guided by opinions instead of evidence. While stakeholders believe intuitively that there is a positive relationship between staffing levels and quality in nursing homes, the research literature is contradictory (1). In this editorial we consider the evidence found in a literature study that we conducted for the Dutch Ministry of Health, Welfare and Sports (VWS). The aim of this study was to summarize all available evidence on the relationship between staffing and quality in nursing homes. Specifically, we focused on the quantity and the educational background of staff and quality in nursing homes. The literature study has contributed to the recent Dutch quality framework for nursing homes (Kwaliteitskader verpleeghuiszorg in Dutch) of the National Health Care Institute. This quality framework was published in January 2017 and provides norms – among other quality aspects – for nursing home staffing. As well as a description of the main findings of the literature study, we present implications for different stakeholders charged with staffing issues in nursing homes.
The project aims to improve palliative care in China through the competence development of Chinese teachers, professionals, and students focusing on the horizontal priority of digital transformation.Palliative care (PC) has been recognised as a public health priority, and during recent years, has seen advances in several aspects. However, severe inequities in the access and availability of PC worldwide remain. Annually, approximately 56.8 million people need palliative care, where 25.7% of the care focuses on the last year of person’s life (Connor, 2020).China has set aims for reaching the health care standards of the developed countries by 2030 through the Healthy China Strategy 2030, where one of the improvement areas in health care includes palliative care, thus continuing the previous efforts.The project provides a constructive, holistic, and innovative set of actions aimed at resulting in lasting outcomes and continued development of palliative care education and services. Raising the awareness of all stakeholders on palliative care, including the public, is highly relevant and needed. Evidence based practice guidelines and education are urgently required for both general and specialised palliative care levels, to increase the competencies for health educators, professionals, and students. This is to improve the availability and quality of person-centered palliative care in China. Considering the aging population, increase in various chronic illnesses, the challenging care environment, and the moderate health care resources, competence development and the utilisation of digitalisation in palliative care are paramount in supporting the transition of experts into the palliative care practice environment.General objective of the project is to enhance the competences in palliative care in China through education and training to improve the quality of life for citizens. Project develops the competences of current and future health care professionals in China to transform the palliative care theory and practice to impact the target groups and the society in the long-term. As recognised by the European Association for Palliative Care (EAPC), palliative care competences need to be developed in collaboration. This includes shared willingness to learn from each other to improve the sought outcomes in palliative care (EAPC 2019). Since all individuals have a right to health care, project develops person-centered and culturally sensitive practices taking into consideration ethics and social norms. As concepts around palliative care can focus on physical, psychological, social, or spiritual related illnesses (WHO 2020), project develops innovative pedagogy focusing on evidence-based practice, communication, and competence development utilising digital methods and tools. Concepts of reflection, values and views are in the forefront to improve palliative care for the future. Important aspects in project development include health promotion, digital competences and digital health literacy skills of professionals, patients, and their caregivers. Project objective is tied to the principles of the European Commission’s (EU) Digital Decade that stresses the importance of placing people and their rights in the forefront of the digital transformation, while enhancing solidarity, inclusion, freedom of choice and participation. In addition, concepts of safety, security, empowerment, and the promotion of sustainable actions are valued. (European Commission: Digital targets for 2030).Through the existing collaboration, strategic focus areas of the partners, and the principles of the call, the PalcNet project consortium was formed by the following partners: JAMK University of Applied Sciences (JAMK ), Ramon Llull University (URL), Hanze University of Applied Sciences (HUAS), Beijing Union Medical College Hospital (PUMCH), Guangzhou Health Science College (GHSC), Beihua University (BHU), and Harbin Medical University (HMU). As project develops new knowledge, innovations and practice through capacity building, finalisation of the consortium considered partners development strategy regarding health care, (especially palliative care), ability to create long-term impact, including the focus on enhancing higher education according to the horizontal priority. In addition, partners’ expertise and geographical location was also considered important to facilitate long-term impact of the results.Primary target groups of the project include partner country’s (China) staff members, teachers, researchers, health care professionals and bachelor level students engaging in project implementation. Secondary target groups include those groups who will use the outputs and results and continue in further development in palliative care upon the lifetime of the project.
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 the Netherlands, 125 people suffer a stroke every day, which annually results in 46.000 new stroke patients Stroke patients are confronted with combinations of physical, psychological and social consequences impacting their long term functioning and quality of live. Fortunately many patients recover to their pre-stroke level of functioning, however, almost half of them never will. Consequently, rehabilitation often means that patients need to adapt to a new reality in their lives, requiring not only physical but also psychosocial adjustments. Nurses play a key role during rehabilitation of stroke patients. However, when confronted with psychosocial problems, they often feel insecure about identifying the specific psycho-social needs of the individual patient and providing adequate care. In our project ‘Early Detection of Post-Stroke Depression’, (SIA RAAK; 2010-12-36P), we developed a toolkit focusing on early identification of depression after stroke continued with interventions nurses can use during hospitalisation. During this project it became clear that evidence regarding possible interventions is scarce and inclusive. Moreover feasibility of interventions is often not confirmed. Our project showed that during the period of hospital admission patients and health care providers strongly focus on surviving the stroke and on the physical rehabilitation. Therefore, we concluded that to make one step beyond we first have to go one step back. To strengthen psychosocial care for patients after stroke we have to add, reconsider and shape knowledge in context of health care practices in a systematic way, resulting in evidence based and practice informed stepping stones. With this project we aim to collect these stepping stones and develop a nursing care programme that improves psychosocial well-being of patients after stroke, is tailored to the particular concerns and needs of patients, and is considered feasible for use in the usual care process of nurses in the stroke rehabilitation pathway.
