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Background: The UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative "unintended consequences" across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system. This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process., Methods: We used participatory system dynamics modelling to develop a qualitative causal theory linking housing, energy and wellbeing. Qualitative interviews were followed by two interactive workshops to develop the model, involving representatives from national and local government, housing industries, non-government organisations, communities and academia., Results: More than 50 stakeholders from 37 organisations participated. The process resulted in a shared understanding of wellbeing as it relates to housing; an agreed set of criteria against which to assess to future policy options; and a comprehensive set of causal loop diagrams describing the housing, energy and wellbeing system. The causal loop diagrams cover seven interconnected themes: community connection and quality of neighbourhoods; energy efficiency and climate change; fuel poverty and indoor temperature; household crowding; housing affordability; land ownership, value and development patterns; and ventilation and indoor air pollution., Conclusions: The collaborative learning process and the model have been useful for shifting the thinking of a wide range of housing stakeholders towards a more integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing.

The allocation problem in health care can be characterised as a mathematical programming problem but attempts to incorporate uncertainty in costs and effect have suffered from important limitations. A two-stage stochastic mathematical programming formulation is developed and applied to a numerical example to explore and demonstrate the implications of this more general and comprehensive approach. The solution to the allocation problem for different budgets, budgetary policies, and available actions are then demonstrated. This analysis is used to evaluate different budgetary policies and examine the adequacy of standard decision rules in cost-effectiveness analysis. The research decision is then considered alongside the allocation problem. This more general formulation demonstrates that the value of further research depends on: (i) the budgetary policy in place; (ii) the realisations revealed during the budget period; (iii) remedial actions that may be available; and (iv) variability in parameters values., (Copyright 2009 Elsevier B.V. All rights reserved.)

Background The Cold Weather Plan (CWP) for England was launched by the Department of Health in 2011 to prevent avoidable harm to health by cold weather by enabling individuals to prepare and respond appropriately. This study sought the views of local decision makers involved in the implementation of the CWP in the winter of 2012/13 to establish the effects of the CWP on local planning. It was part of a multi-component independent evaluation of the CWP. Methods Ten LA areas were purposively sampled which varied in level of deprivation and urbanism. Fifty-two semi-structured interviews were held with health and social care managers involved in local planning between November 2012 and May 2013. Results Thematic analysis revealed that the CWP was considered a useful framework to formalize working arrangements between agencies though local leadership varied across localities. There were difficulties in engaging general practitioners, differences in defining vulnerable individuals and a lack of performance monitoring mechanisms. Conclusions The CWP was welcomed by local health and social care managers, and improved proactive winter preparedness. Areas for improvement include better integration with general practice, and targeting resources at socially isolated individuals in cold homes with specific interventions aimed at reducing social isolation and building community resilience. [ABSTRACT FROM AUTHOR]

Background: The UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative "unintended consequences" across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system. This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process. Methods: We used participatory system dynamics modelling to develop a qualitative causal theory linking housing, energy and wellbeing. Qualitative interviews were followed by two interactive workshops to develop the model, involving representatives from national and local government, housing industries, non-government organisations, communities and academia. Results: More than 50 stakeholders from 37 organisations participated. The process resulted in a shared understanding of wellbeing as it relates to housing; an agreed set of criteria against which to assess to future policy options; and a comprehensive set of causal loop diagrams describing the housing, energy and wellbeing system. The causal loop diagrams cover seven interconnected themes: community connection and quality of neighbourhoods; energy efficiency and climate change; fuel poverty and indoor temperature; household crowding; housing affordability; land ownership, value and development patterns; and ventilation and indoor air pollution. Conclusions: The collaborative learning process and the model have been useful for shifting the thinking of a wide range of housing stakeholders towards a more integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing. [ABSTRACT FROM AUTHOR]

Background Amid the calls for 'more public health evidencé, we also need simple understandable methods of determining when more research really is needed. This paper describes a simple decision aid to help policymakers, researchers and other decision makers assess the potential 'information value' of a new public health randomised controlled trial. Methods The authors developed a flow chart to help make explicit (1) the user's information needs, (2) the intended use of the new information that the study will produce, (3) the added value of the evidence to be derived from the new study and (4) the levels of precision, bias and generalisability required by the user Results The flow chart is briefly illustrated, first in generic form and then in a worked example, showing how it may be used in deciding whether a new study should be commissioned to evaluate the health impact of allowing motorcycles to use bus lanes in London Conclusions In this paper, the authors have presented a flow chart for enacting an informal 'Value-of- Information'-like approach to deciding when a new public health evaluation is needed. The authors do not suggest that the flow chart approach is technically the equivalent of Value-of-Information methods. Nonetheless, it represents a valuable perspective and process to adopt, and this structured approach will be more revealing than an unstructured thought experiment as the basis for decisions about a new study. To aid in its development as an effective tool, we invite users from a variety of perspectives and contexts to review it, to use it in practice and to send us their comments. INSETS: What is already known on this subject;What this study adds. [ABSTRACT FROM AUTHOR]

The authors offer a response to commentaries on their paper which proposed a flowchart that can be used to decide when more evidence is needed for public health policy and practice in line with randomized controlled trials (RCTs). The authors explain that the flowchart is aimed at proposing a way to put the emphasis back on the decision to be taken. They acknowledge their failure to take context into account in line with making real-life decisions.

• We used a MCDA framework to determine robust optimal school building interventions. • Criteria included educational attainment, health, energy performance and costs. • We compared combinations of energy retrofit and Indoor Environment Quality schemes. • MCDA results were sensitive to stakeholder preferences and interventions evaluated. Maintaining good Indoor Environmental Quality (IEQ) in English schools in terms of overheating and air quality is important for the health and educational performance of children. Improving energy efficiency in school buildings is also a key part of UK's carbon emissions reduction strategy. To address the trade-offs between energy efficiency and IEQ, a Multi–Criteria Decision Analysis (MCDA) framework based on an English classroom stock model was used. The aim was to determine robust optimal school building interventions across a set of criteria (including child health, educational attainment and building energy consumption) and settings (comprising different climate scenarios, construction eras, geographical regions and school geographical orientations). Each intervention was made up of the pairwise combination of an energy efficiency retrofit scheme and an IEQ improvement scheme. The MCDA framework was applied to the school building stock in England. This study shows that the framework represents a transparent approach to support decision making in determining the optimal school building intervention from different perspectives. The optimal interventions included measures that improved IEQ and resulting indoor learning environments, such as external shading, or increased albedo and internal blinds, for the particular set of interventions, criteria and stakeholders in this study. The results of the MCDA analysis were sensitive to the preferences elicited from stakeholders on the relative importance of the criteria and to the range of interventions and criteria selected for evaluation. [ABSTRACT FROM AUTHOR]