An increasing number of tracheotomised and/or ventilated patients with high-cost out-of-hospital intensive care needs and, at the same time, a decreasing number of healthcare professionals inevitably lead to challenges in the care of this patient population. In addition, little is known about this population, their health restrictions, needs, patient journeys, care structures and processes. The project ‘Needs, requirements and cross-sectoral care pathways of out-of-hospital ventilated intensive care patients’ (ATME) aims to analyse these aspects and explore current care structures to inform further development of care in line with patients’ needs and requirements.

Qualitative and quantitative methods will be used. In preparation of a semistandardised survey, exploratory interviews will be conducted with tracheotomised and/or ventilated patients with out-of-hospital intensive care needs (TVPOI) (n=15), nursing care providers (n=30), outpatient medical centres, as well as outpatient medical, medical technology and therapeutic care providers (n=35). Three semistandardised survey questionnaires for TVPOI (n=2,000) will be developed and conducted with nursing care facilities (n=250) and outpatient medical centres for mechanical ventilation (n=25). Content analyses will be conducted for qualitative data; survey data will be analysed descriptively. In addition, healthcare claims data will be analysed descriptively to provide information on patient journeys. Three result workshops and one consensus conference will be carried out with representatives of the relevant target groups to analyse the suitability of care structures and to develop recommendations for action to improve TVPOI.

The ATME study received a positive vote from the Ethics Committee of the Osnabrück University of Applied Sciences and is registered in ‘Deutsches Register Klinischer Studien (DRKS)’ (registration number: DRKS00030891). The study results will be presented at national conferences and in relevant peer-reviewed journals. Additionally, study results will be published by the funding institution (the Innovation Committee of the Federal Joint Committee) on their website.

Conventional prediction models fail to integrate the constantly evolving nature of critical illness. Alternative modelling approaches to study dynamic changes in critical illness progression are needed. We compare static risk prediction models to dynamic probabilistic models in early critical illness.

We developed models to simulate disease trajectories of critically ill COVID-19 patients across different disease states. Eighty per cent of cases were randomly assigned to a training and 20% of the cases were used as a validation cohort. Conventional risk prediction models were developed to analyse different disease states for critically ill patients for the first 7 days of intensive care unit (ICU) stay. Daily disease state transitions were modelled using a series of multivariable, multinomial logistic regression models. A probabilistic dynamic systems modelling approach was used to predict disease trajectory over the first 7 days of an ICU admission. Forecast accuracy was assessed and simulated patient clinical trajectories were developed through our algorithm.

We retrospectively studied patients admitted to a Cleveland Clinic Healthcare System in Ohio, for the treatment of COVID-19 from March 2020 to December 2022.

5241 patients were included in the analysis. For ICU days 2–7, the static (conventional) modelling approach, the accuracy of the models steadily decreased as a function of time, with area under the curve (AUC) for each health state below 0.8. But the dynamic forecasting approach improved its ability to predict as a function of time. AUC for the dynamic forecasting approach were all above 0.90 for ICU days 4–7 for all states.

We demonstrated that modelling critical care outcomes as a dynamic system improved the forecasting accuracy of the disease state. Our model accurately identified different disease conditions and trajectories, with a

Rises in average life expectancy, increased comorbidities and frailty among older patients lead to higher admission rates to intensive care units (ICU). During an ICU stay, loss of physical and cognitive functions may occur, causing prolonged rehabilitation. Some functions may be lost permanently, affecting quality of life (QoL). There is a lack of understanding regarding how many variables are relevant to health-related outcomes and which outcomes are significant for the QoL of frail, elderly patients following discharge from the ICU. Therefore, this scoping review aims to identify reported variables for health-related outcomes and explore perspectives regarding QoL for this patient group.

The Joanna Briggs Institute guidelines for scoping reviews will be employed and original, peer-reviewed studies in English and Scandinavian languages published from 2013 to 2023 will be included. The search will be conducted from July 2023 to December 2023, according to the inclusion criteria in Embase, MEDLINE, PsycINFO and CINAHL. References to identified studies will be hand-searched, along with backward and forward citation searching for systematic reviews. A librarian will support and qualify the search strategy. Two reviewers will independently screen eligible studies and perform data extraction according to predefined headings. In the event of disagreements, a third reviewer will adjudicate until consensus is achieved. Results will be presented narratively and in table form and discussed in relation to relevant literature.

Ethical approval is unnecessary, as the review synthesises existing research. The results will be disseminated through a peer-reviewed publication in a scientific journal.