Mapping the way: functional modelling for community-based integrated care for older people.

Background: Healthcare system sustainability is challenged by several critical issues; one of the most pressing is the ageing population. Traditional, episodic care delivery models are not designed for older people who are medically complex and frail. These individuals would benefit from health and social care that is more comprehensive, coordinated, person-centred and accessible in the communities in which they live.

A knowledge elicitation study to inform the development of a consequence model for Arctic ship evacuations: Qualitative and quantitative data.

Expert knowledge was elicited to develop a life-safety consequence severity model for Arctic ship evacuations (Browne et al., 2021). This paper presents the associated experimental design and data.

The Functional Resonance Analysis Method as a health care research methodology: a scoping review.

Objective: The objective of this review was to examine and map the literature on the use of the Functional Resonance Analysis Method (FRAM) in health care research.

Introduction: The FRAM is a resilient health care tool tat offers an approach to deconstruct complex systems by mapping health care processes to identify essential activities, how they are interrelated, and the variability that emerges, which can strengthen or compromise outcomes. Insight into how the FRAM has been operationalized in health care can help researchers and policy-makers understand how this method can be used to strengthen health care systems.

A dynamic version of the FRAM for capturing variability in complex operations.

Functional Resonance Analysis Method (FRAM) is a function-based approach to model complex socio-technical systems and to manage variability. The current FRAM related tools are unable to capture qualitative and quantitative characteristics of variability as well as temporal variations. This study presents in detail a dynamic FRAM-based tool, which is called DynaFRAM.

A food chain-based ecological risk assessment model for oil spills in the Arctic environment.

This paper investigates the linkage between the acute impacts on apex marine mammals with polar cod responses to an oil spill. It proposes a Bayesian network-based model to link these direct and indirect effects on the apex marine mammals. The model predicts a recruitment collapse (for the scenarios considered), causing a higher risk of mortality of polar bears, beluga whales, and Narwhals in the Arctic region.

Modeling and analyzing hospital to home transition processes of frail older adults using the functional resonance analysis method (FRAM).

The main purpose of this study was to model and analyze hospital to home transition processes of frail older adults in order to identify the challenges within this process. A multi-phase, multi-sited and mixed methods design was utilized, in which, Phase 1 included collecting semi-structured interviews and focus group data, and Phase 2 consisted of six patient/caregiver dyad prospective case studies. This study was conducted in three hospitals in three cities in a single province in Canada.

The functional resonance analysis method as a health care research methodology: a scoping review protocol.

Objective: The objective of this review is to examine and map the literature on the use of the functional resonance analysis method in health care research.

Introduction: Health care systems are highly complex and involve interrelated functions, organizations, individuals, and technologies. Understanding how these elements interact and impact health care processes is difficult because of inherent contextual and human variables.

Risk assessment of Arctic aquatic species using ecotoxicological biomarkers and Bayesian network.

The risk to Arctic aquatic species due to accidental oil spills is not well studied. One of the key reasons for this limitation is the lack of understanding of the dose-response relations for the species in the Arctic region. The present study addresses this knowledge gap.

Dynamic ecological risk modelling of hydrocarbon release scenarios in Arctic waters.

The Arctic is an ecologically diverse area that is increasingly vulnerable to damages from oil spills associated with commercial vessels traversing newly open shipping lanes. The significance of such accidents on Arctic marine habitats and the potential for recovery can be examined using ecological risk assessment (ERA) coupled with a dynamic object-oriented Bayesian network (DOOBN). A DOOBN approach is useful to represent the probabilistic relationships inherent in the interactions between key events associated with an oil spill, including oil dispersion from the source, ice-oil slick interactions, seawater-oil slick formation, sedimentation, and exposures to different aquatic life.

Arctic marine fish 'biotransformation toxicity' model for ecological risk assessment.

Oil and gas exploration and marine transport in the Arctic region have put the focus on the ecological risk of the possibly exposed organisms. In the present study, the impacts of sea ice, extreme light regime, various polar region-specific physiological characteristics in polar cod (Boreogadus saida) and their effects on xenobiotic distribution and metabolism are studied. A Bayesian belief network is used to model individual fish toxicity.

Assessment of changes in neural activity during acquisition of spatial knowledge using EEG signal classification.

Objective: This study explored the classification of electroencephalography (EEG) signals to assess changes in neural activity as individuals performed a training task in a virtual environment simulator. Commonly, task behavior and perception are used to assess a trainee's ability to perform a task, however, changes in cognition are not usually measured and could be important to provide a true indication of an individual's level of knowledge or skill.

Approach: In this study, 15 participants acquired spatial knowledge via 60 navigation trials (divided into ten blocks) in a novel virtual environment.

Human performance data collected in a virtual environment.

This data article describes the experimental data used in the research article "Incorporating individual differences in human reliability analysis: an extension to the virtual experimental technique" (Musharraf et al., 2017) [1]. The article provides human performance data for 36 individuals collected using a virtual environment.

Aquatic ecotoxicological models and their applicability in Arctic regions.

Dose-response modeling is one of the most important steps of ecological risk assessment. It requires concentration-effects relationships for the species under consideration. There are very limited studies and experimental data available for the Arctic aquatic species.

A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents.

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation-based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information.

Dynamic fugacity model for accidental oil release during Arctic shipping.

Improved understanding of ecological risk associated with Arctic shipping would help advance effective oil spill prevention, control, and mitigation strategies. Ecological risk assessment involves analysis of a release (oil), its fate, and dispersion, and the exposure and intake of the contaminant to different receptors. Exposure analysis is a key step of the detailed ecological risk assessment, which involves the evaluation of the concentration and persistence of released pollutants in the media of contact.

Modeling oil weathering and transport in sea ice.

This paper presents a model of oil weathering and transport in sea ice. It contains a model formulation and scenario simulation to test the proposed model. The model formulation is based on state-of-the-art models for individual weathering and transport processes.

Fault and event tree analyses for process systems risk analysis: uncertainty handling formulations.

Quantitative risk analysis (QRA) is a systematic approach for evaluating likelihood, consequences, and risk of adverse events. QRA based on event (ETA) and fault tree analyses (FTA) employs two basic assumptions. The first assumption is related to likelihood values of input events, and the second assumption is regarding interdependence among the events (for ETA) or basic events (for FTA).

Evaluation of generic types of drilling fluid using a risk-based analytic hierarchy process.

The composition of drilling muds is based on a mixture of clays and additives in a base fluid. There are three generic categories of base fluid--water, oil, and synthetic. Water-based fluids (WBFs) are relatively environmentally benign, but drilling performance is better with oil-based fluids (OBFs).

Distribution of arsenic and copper in sediment pore water: an ecological risk assessment case study for offshore drilling waste discharges.

Due to the hydrophobic nature of synthetic based fluids (SBFs), drilling cuttings are not very dispersive in the water column and settle down close to the disposal site. Arsenic and copper are two important toxic heavy metals, among others, found in the drilling waste. In this article, the concentrations of heavy metals are determined using a steady state "aquivalence-based" fate model in a probabilistic mode.

Patient sources of drug information and attitudes to their provision: a corticosteroid model.

Aim: To determine patient's preferred sources of drug information and their attitudes to how this is provided.

Design: A quantitative evaluation via personal interviews using a formal questionnaire. SUBJECT AND SETTINGS: A group of 101 in-patients in a chest ward at the Royal Devon & Exeter Healthcare NHS Trust.