BackgroundSpecialist palliative care teams are consulted during hospital admission for advice on complex palliative care. These consultations need to be timely to prevent symptom burden and maintain quality of life. Insight into specialist palliative care teams may help improve the outcomes of palliative care.MethodsIn this retrospective observational study, we analyzed qualitative and quantitative data of palliative care consultations in a six-month period (2017 or 2018) in four general hospitals in the northwestern part of the Netherlands. Data were obtained from electronic medical records.ResultsWe extracted data from 336 consultations. The most common diagnoses were cancer (54.8%) and organ failure (26.8%). The estimated life expectancy was less than three months for 52.3% of all patients. Within two weeks after consultation, 53.2% of the patients died, and the median time until death was 11 days (range 191) after consultation. Most patients died in hospital (49.4%) but only 7.5% preferred to die in hospital. Consultations were mostly requested for advance care planning (31.6%). End-of-life preferences focused on last wishes and maintaining quality of life.ConclusionThis study provides detailed insight into consultations of palliative care teams and shows that even though most palliative care consultations were requested for advance care planning, consultations focus on end-of-life care and are more crisis-oriented than prevention-oriented. Death often occurs too quickly after consultation for end-of-life preferences to be met and these preferences tend to focus on dying. Educating healthcare professionals on when to initiate advance care planning would promote a more prevention-oriented approach. Defining factors that indicate the need for timely palliative care team consultation and advance care planning could help timely identification and consultation.
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The aim of this qualitative study was 1) to investigate how generalist PTs, OTs and ETs provide work-focused healthcare and 2) to obtain insight into their perceived barriers and needs that afect their ability to address occupa- tional factors. Methods: An exploratory qualitative study using three focus groups.
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Objective: The aim of the study was to assess the effectiveness of intensive care unit (ICU)–initiated transitional care interventions for patients and families on elements of post-intensive care syndrome (PICS) and/or PICS-family (PICS–F). Review method used: This is a systematic review and meta-analysis Sources: The authors searched in biomedical bibliographic databases including PubMed, Embase (OVID), CINAHL Plus (EBSCO), Web of Science, and the Cochrane Library and included studies written in English conducted up to October 8, 2020. Review methods: We included (non)randomised controlled trials focussing on ICU-initiated transitional care interventions for patients and families. Two authors conducted selection, quality assessment, and data extraction and synthesis independently. Outcomes were described using the three elements of PICS, which were categorised into (i) physical impairments (pulmonary, neuromuscular, and physical function), (ii) cognitive impairments (executive function, memory, attention, visuo-spatial and mental processing speed), and (iii) psychological health (anxiety, depression, acute stress disorder, post-traumatic stress disorder, and depression). Results: From the initially identified 5052 articles, five studies were included (i.e., two randomised controlled trials and three nonrandomised controlled trials) with varied transitional care interventions. Quality among the studies differs from moderate to high risk of bias. Evidence from the studies shows no significant differences in favour of transitional care interventions on physical or psychological aspects of PICS-(F). One study with a nurse-led structured follow-up program showed a significant difference in physical function at 3 months. Conclusions: Our review revealed that there is a paucity of research about the effectiveness of transitional care interventions for ICU patients with PICS. All, except one of the identified studies, failed to show a significant effect on the elements of PICS. However, these results should be interpreted with caution owing to variety and scarcity of data. Prospero registration: CRD42020136589 (available via https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020136589).
Veel ouderen ervaren tijdens en na ziekenhuisopname functieverlies. ‘Function Focused Care in Hospital’, ook wel bekend als bewegingsgerichte zorg, is een interventie gericht op het voorkomen en verminderen van functieverlies bij ouderen tijdens een ziekenhuisopname. Verpleegkundigen moedigen patiënten aan tot actieve betrokkenheid in de dagelijkse zorgmomenten.
Veel ouderen ervaren tijdens en na ziekenhuisopname functieverlies. ‘Function Focused Care in Hospital’, ook wel bekend als bewegingsgerichte zorg, is een interventie gericht op het voorkomen en verminderen van functieverlies bij ouderen tijdens een ziekenhuisopname. Verpleegkundigen moedigen patiënten aan tot actieve betrokkenheid in de dagelijkse zorgmomenten.Doel Doel van dit project is de effectiviteit bepalen van Function Focused Care in Hospital op het fysiek functioneren van patiënten die opgenomen zijn in de Nederlandse ziekenhuizen. Resultaten Nederlandstalig scholingsprogramma en handboek van de Function Focused Care in Hospital-benadering voor de ziekenhuissetting; Een evaluatie van het proces en de uitkomsten van de Function Focused Care-benadering. Looptijd 01 november 2020 - 31 oktober 2025 Aanpak Er is een haalbaarheidsstudie uitgevoerd, die uitwees dat de interventie geschikt is voor de Nederlandse praktijk. Op de neurologische en geriatrische afdelingen van drie ziekenhuizen is Function Focused Care in Hospital in de dagelijkse zorg geïmplementeerd en geëvalueerd op effectiviteit. Over de interventie Function Focused Care (FFC) is een zorgbenadering waarin verpleegkundigen patiënten actief betrekken bij alle zorgmomenten om hun fysiek functioneren te optimaliseren. Eerder onderzoek heeft laten zien dat FFC een positief effect heeft op fysieke activiteit, mobiliteit en ADL bij ouderen in de wijk en de langdurige zorg. Ook laten studies in de acute zorg belovende resultaten zien van FFC op fysieke activiteit en mobiliteit bij ouderen opgenomen in het ziekenhuis. Voorbeelden van zorg volgens de FFC-benadering zijn met de patiënt naar de badkamer lopen in plaats van wassen op bed, of de maaltijd aan tafel nuttigen in plaats van zittend in bed eten. De essentie van FFC is het behouden of, indien mogelijk, verbeteren van het fysieke functioneren. Tijdens de hele ziekenhuisopname wordt de patiënt aangemoedigd meer tijd te laten besteden aan fysieke activiteit op een op de patiënt aangepast niveau. Co-financiering Het project wordt mede gefinancierd door ZonMW, projectnummer 520002003.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
