AimTo evaluate healthcare professionals' performance and treatment fidelity in the Cardiac Care Bridge (CCB) nurse‐coordinated transitional care intervention in older cardiac patients to understand and interpret the study results.DesignA mixed‐methods process evaluation based on the Medical Research Council Process Evaluation framework.MethodsQuantitative data on intervention key elements were collected from 153 logbooks of all intervention patients. Qualitative data were collected using semi‐structured interviews with 19 CCB professionals (cardiac nurses, community nurses and primary care physical therapists), from June 2017 until October 2018. Qualitative data‐analysis is based on thematic analysis and integrated with quantitative key element outcomes. The analysis was blinded to trial outcomes. Fidelity was defined as the level of intervention adherence.ResultsThe overall intervention fidelity was 67%, ranging from severely low fidelity in the consultation of in‐hospital geriatric teams (17%) to maximum fidelity in the comprehensive geriatric assessment (100%). Main themes of influence in the intervention performance that emerged from the interviews are interdisciplinary collaboration, organizational preconditions, confidence in the programme, time management and patient characteristics. In addition to practical issues, the patient's frailty status and limited motivation were barriers to the intervention.ConclusionAlthough involved healthcare professionals expressed their confidence in the intervention, the fidelity rate was suboptimal. This could have influenced the non‐significant effect of the CCB intervention on the primary composite outcome of readmission and mortality 6 months after randomization. Feasibility of intervention key elements should be reconsidered in relation to experienced barriers and the population.ImpactIn addition to insight in effectiveness, insight in intervention fidelity and performance is necessary to understand the mechanism of impact. This study demonstrates that the suboptimal fidelity was subject to a complex interplay of organizational, professionals' and patients' issues. The results support intervention redesign and inform future development of transitional care interventions in older cardiac patients.
Aim: To evaluate healthcare professionals' performance and treatment fidelity in the Cardiac Care Bridge (CCB) nurse-coordinated transitional care intervention in older cardiac patients to understand and interpret the study results. Design: A mixed-methods process evaluation based on the Medical Research Council Process Evaluation framework. Methods: Quantitative data on intervention key elements were collected from 153 logbooks of all intervention patients. Qualitative data were collected using semi-structured interviews with 19 CCB professionals (cardiac nurses, community nurses and primary care physical therapists), from June 2017 until October 2018. Qualitative data-analysis is based on thematic analysis and integrated with quantitative key element outcomes. The analysis was blinded to trial outcomes. Fidelity was defined as the level of intervention adherence. Results: The overall intervention fidelity was 67%, ranging from severely low fidelity in the consultation of in-hospital geriatric teams (17%) to maximum fidelity in the comprehensive geriatric assessment (100%). Main themes of influence in the intervention performance that emerged from the interviews are interdisciplinary collaboration, organizational preconditions, confidence in the programme, time management and patient characteristics. In addition to practical issues, the patient's frailty status and limited motivation were barriers to the intervention. Conclusion: Although involved healthcare professionals expressed their confidence in the intervention, the fidelity rate was suboptimal. This could have influenced the non-significant effect of the CCB intervention on the primary composite outcome of readmission and mortality 6 months after randomization. Feasibility of intervention key elements should be reconsidered in relation to experienced barriers and the population. Impact: In addition to insight in effectiveness, insight in intervention fidelity and performance is necessary to understand the mechanism of impact. This study demonstrates that the suboptimal fidelity was subject to a complex interplay of organizational, professionals' and patients' issues. The results support intervention redesign and inform future development of transitional care interventions in older cardiac patients.
Background In a large randomized trial, Utrecht PROactive Frailty Intervention Trial (U‐PROFIT), we evaluated the effectiveness of an integrated program on the preservation of daily functioning in older people in primary care that consisted of a frailty identification tool and a multicomponent nurse‐led care program. Examination of treatment fidelity is critical to successful translation of evidence‐based interventions into practice. Aims To assess treatment delivery, dose and content of nursing care delivered within the nurse‐led care program, and to explore if the delivery may have influenced the trial results. Methods A mixed‐methods study was conducted. Type and dose of nursing care were collected during the trial. Shortly after the trial, a focus group with nurses was conducted to explore reasons for the observed differences between the type and dose of nursing care delivered. Results A total of 835 older persons were included in the nurse‐led care program. The mean age was 75 years, 64% were female and 53.5% were living alone. The most frequent self‐reported conditions were loneliness (60.8%) and cognitive problems (59.4%). One‐third of the patients with a geriatric condition received an additional assessment (e.g., Mini‐Mental State Examination), and the majority of these patients received at least one nurse intervention (>85%). Most nursing care was delivered to patients at risk of falling and to those with urinary incontinence. Patients with nutrition problems seldom received nursing interventions. The nurses explained that differences in type and dose were influenced by the preference of the patient, the type of geriatric problem, and the time required to apply a nurse intervention. Linking Evidence to Action All intervention components were delivered; however, differences were observed in the type and dose of nursing care delivered across geriatric conditions. The findings better explain the treatment fidelity and suggest that there is room for improvement that may result in more beneficial patient outcomes.
Communicatieprofessionals geven aan dat organisaties geconfronteerd worden met een almaar complexere samenleving en daarmee het overzicht verloren hebben. Zo’n overzicht, een ‘360 graden blik’, is echter onontbeerlijk. Dit vooral, aldus diezelfde communicatieprofessionals, omdat dan eerder kan worden opgemerkt wanneer de legitimiteit van een organisatie ter discussie staat en zowel tijdiger als adequater gereageerd kan worden. Op dit moment is het echter nog zo dat een reactie pas op gang komt als zaken reeds in een gevorderd stadium verkeren. Onderstromen blijven onderbelicht, als ze niet al geheel onzichtbaar zijn. Een van de verklaringen hiervoor is de grote rol van sociale media in de publieke communicatie van dit moment. Die media produceren echter zoveel data dat communicatieprofessionals daartegenover machteloos staan. De enige oplossing is automatisering van de selectie en analyse van die data. Helaas is men er tot op heden nog niet in geslaagd een brug te slaan tussen het handwerk van de communicatieprofessional en de vele mogelijkheden van een datagedreven aanpak. Deze brug dan wel de vertaling van de huidige praktijk naar een hogere technisch niveau staat centraal in dit onderzoeksproject. Daarbij gaat het in het bijzonder om een vroegtijdige herkenning van potentiële issues, in het bijzonder met betrekking tot geruchtvorming en oproepen tot mobilisatie. Met discoursanalyse, AI en UX Design willen we interfaces ontwikkelen die zicht geven op die onderstromen. Daarbij worden transcripten van handmatig gecodeerde discoursanalytische datasets ingezet voor AI, in het bijzonder voor de clustering en classificatie van nieuwe data. Interactieve datavisualisaties maken die datasets vervolgens beter doorzoekbaar terwijl geautomatiseerde patroon-classificaties de communicatieprofessional in staat stellen sociale uitingen beter in te schatten. Aldus wordt richting gegeven aan handelingsperspectieven. Het onderzoek voorziet in de oplevering van een high fidelity ontwerp en een handleiding plus training waarmee analisten van newsrooms en communicatieprofessionals daadwerkelijk aan de slag kunnen gaan.
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.
The key goal was to further develop, secure and disseminate knowledge and concepts concerning the role of high realism in Virtual Reality. It followed the Digital Media Concept professorship to create and examine the effects of high quality worlds and characters in VR. Key focus was on the effect of high versus low realism in (existing and non-existing) digital environments as well as digital characters and avatars (digital representations of human users) and embodied agents (digital representations of computer programs that have been designed to interact with, or on behalf of, a human). This means on the one hand getting better equipment and skills to digitize and create high realistic avatars in VR. And on the other hand this means that a better understanding of the concept of realism and quality is needed. This encompasses a whole range of terms that varies from realistic resemblance, to high fidelity appearance and (real-time interactive and authentic) behaviour based on high AI programming. Research showed that very important is congruency in realism between elements within a VR world. Furthermore it showed that high realism is not always needed to stimulate ‘real’ (VR) behaviour. High immersive experiences and impulse behaviour also functions in virtual environments that have lower levels of realism. Studies have been conducted within the field of health, entertainment, advertising, architecture and journalism. An example is the VR game Descend, see link (used to examine the effect of realism through resemblance).Partners: Radboud University, Enversed, Stanford University, University of Oregon, Cornell University, several companies
