Encouraging nurses to take the lead on the information agenda.

This is the final in a series of four articles that discuss issues relating to the UK's growing reliance on health information technology. It is becoming increasingly clear that information and communication technologies are increasing the availability of health care, and improving the management, sharing and understanding of health care at a local and national level. This article explores the role of senior nurses in the management, delivery and support of care.

Measuring the nursing contribution using electronic records.

This article is the third in a series of four, looking at the impact on the nursing profession of the increasing demand to demonstrate the nursing contribution to patient care in terms of quality and performance. Information management processes and indicators for the measurement of care are described. The necessary improvements that need to be made to patient records to support integrated care in the future and examples of nursing classifications are also provided. The article examines the roles and responsibilities of nurses as data collectors and concludes that strong nursing leadership in the field of informatics is needed to influence and shape the data collected and ensure that nurses' professional contribution to patient care is captured.

Health care's response to climate change: a carbon footprint assessment of the NHS in England.

BACKGROUND: Climate change threatens to undermine the past 50 years of gains in public health. In response, the National Health Service (NHS) in England has been working since 2008 to quantify and reduce its carbon footprint. This Article presents the latest update to its greenhouse gas accounting, identifying interventions for mitigation efforts and describing an approach applicable to other health systems across the world. METHODS: A hybrid model was used to quantify emissions within Scopes 1, 2, and 3 of the Greenhouse Gas Protocol, as well as patient and visitor travel emissions, from 1990 to 2019. This approach complements the broad coverage of top-down economic modelling with the high accuracy of bottom-up data wherever available. Available data were backcasted or forecasted to cover all years. To enable the identification of measures to reduce carbon emissions, results were disaggregated by organisation type. FINDINGS: In 2019, the health service's emissions totalled 25 megatonnes of carbon dioxide equivalent, a reduction of 26% since 1990, and a decrease of 64% in the emissions per inpatient finished admission episode. Of the 2019 footprint, 62% came from the supply chain, 24% from the direct delivery of care, 10% from staff commute and patient and visitor travel, and 4% from private health and care services commissioned by the NHS. INTERPRETATION: This work represents the longest and most comprehensive accounting of national health-care emissions globally, and underscores the importance of incorporating bottom-up data to improve the accuracy of top-down modelling and enabling detailed monitoring of progress as health systems act to reduce emissions. FUNDING: Wellcome Trust.

Supply versus use designs of environmental extensions in input-output analysis: Conceptual and empirical implications for the case of energy.

Input-output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input-output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply-use dataset and apply them to the same single-region input-output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi-regional input-output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product-level results can vary by several orders of magnitude. The GMRIO-based comparison further reveals that for a few countries the supply-extension result can be twice the size of the use-extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life-cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting.

The impacts of data deviations between MRIO models on material footprints: A comparison of EXIOBASE, Eora, and ICIO.

In various international policy processes such as the UN Sustainable Development Goals, an urgent demand for robust consumption-based indicators of material flows, or material footprints (MFs), has emerged over the past years. Yet, MFs for national economies diverge when calculated with different Global Multiregional Input-Output (GMRIO) databases, constituting a significant barrier to a broad policy uptake of these indicators. The objective of this paper is to quantify the impact of data deviations between GMRIO databases on the resulting MF. We use two methods, structural decomposition analysis and structural production layer decomposition, and apply them for a pairwise assessment of three GMRIO databases, EXIOBASE, Eora, and the OECD Inter-Country Input-Output (ICIO) database, using an identical set of material extensions. Although all three GMRIO databases accord for the directionality of footprint results, that is, whether a countries' final demand depends on net imports of raw materials from abroad or is a net exporter, they sometimes show significant differences in level and composition of material flows. Decomposing the effects from the Leontief matrices (economic structures), we observe that a few sectors at the very first stages of the supply chain, that is, raw material extraction and basic processing, explain 60% of the total deviations stemming from the technology matrices. We conclude that further development of methods to align results from GMRIOs, in particular for material-intensive sectors and supply chains, should be an important research priority. This will be vital to strengthen the uptake of demand-based material flow indicators in the resource policy context.

Soil sensitivity to acidification in Asia: status and prospects.

Exceedance of steady-state critical loads for soil acidification is consistently found in southern China and parts of SE Asia, but there is no evidence of impacts outside of China. This study describes a methodology for calculating the time to effects for soils sensitive to acidic deposition in Asia under potential future sulfur (S), nitrogen (N), and calcium (Ca) emission scenarios. The calculations are matched to data availability in Asia to produce regional-scale maps that provide estimates of the time (y) it will take for soil base saturation to reach a critical limit of 20% in response to acidic inputs. The results show that sensitive soil types in areas of South, Southeast, and East Asia, including parts of southern China, Burma, Hainan, Laos, Thailand, Vietnam, and the Western Ghats of India, may acidify to a significant degree on a 0-50 y timescale, depending on individual site management and abiotic and biotic characteristics. To make a clearer assessment of risk, site-specific data are required for soil chemistry and deposition (especially base cation deposition); S and N retention in soils and ecosystems; and biomass harvesting and weathering rates from sites across Asia representative of different soil and vegetation types and management regimes. National and regional assessments of soils using the simple methods described in this paper can provide an appreciation of the time dimension of soil acidification-related impacts and should be useful in planning further studies and, possibly, implementing measures to reduce risks of acidification.

Improving the policy application of footprint indicators to support Europe's transition to a one planet economy: the development of the EUREAPA tool.

Environmentally extended multi-regional input-output (EE-MRIO) models provide us with a wealth of data relating to consumption-based environmental impacts at a national level. The results can identify the categories of consumption and sectors of production that contribute most to environmental impact allowing policy makers to prioritise intervention into particular areas. However, these data are not readily accessible to policy makers and civil society, making it difficult to extract and communicate the important messages it contains. The web-based tool - EUREAPA - was created as a usable, task-oriented interface to improve access to environmental and economic data held within a complex EE-MRIO model and make it more relevant to policy makers and civil society. The project team of scientists and IT specialists used an iterative, agile and participatory approach to engage potential end-users in the specification and testing of the tool. The engagement process identified two principal functions that were essential for the EUREAPA tool: viewing data and creating scenarios. The viewing data function allows users to analyse the wealth of data held within the model and present results from a range of perspectives. This helps to understand the causes of environmental pressure and identify priorities for policy intervention. The scenario function helps to communicate how changes in consumption and production might affect the future environmental impact of citizens of the EU, and facilitates long-term planning. Through this dialogue process the project has been able to ensure EUREAPA is relevant, user-friendly and fit-for-purpose. It is intended that EUREAPA will be adopted by policy makers and civil society as an important policy planning and assessment aid in the complex field of sustainable consumption and production.

Bioinformatics on the cloud computing platform Azure.

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development.

Identifying the impact of G-quadruplexes on Affymetrix 3' arrays using cloud computing.

A tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips. In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3' arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google. We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3' arrays.