Uncertainty-Adjusted Translation for Preference-Sensitive Decision Support.

In Multi-Criteria Decision Analysis-based decision support for person-centred care, the person's quantitative preferences (as criterion weightings) are combined with quantified evidence and expert assessments (as option performance ratings on all criteria) to produce a personalised quantified opinion (as a set of expected value option scores). In our current decision support tools, we use the best available (central point) estimates for option performance ratings. The uncertainty surrounding the performance rating estimates, routinely reported by researchers as intervals around the means, are ignored. While defensible, this paper responds to questioning of this disregard. Apart from the inappropriate 'inverse variance' method, we find no attempt to integrate parameter uncertainty into decision analyses, simply an emphasis on reporting it fully, leaving decision makers unsupported in the burden of dealing with the separated outputs - e.g. Means and Credible Intervals. The paper suggests that uncertainty can be brought within Multi-Criteria Decision Analysis-based decision support by treating the means and uncertainties of all outcomes and process considerations as separate criteria, having them traded-off in an individually preference-sensitive manner at the point of decision. An empirical proof of method via an online example on bone health medications is provided, involving six options, two considerations and four criteria

Decision by sampling

We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute’s subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We assume that the sample reflects both the immediate distribution of attribute values from the current decision’s context and also the background, real-world distribution of attribute values. DbS accounts for concave utility functions; losses looming larger than gains; hyperbolic temporal discounting; and the overestimation of small probabilities and the underestimation of large probabilities

Cross-sectional study assessing HIV related knowledge, attitudes and behavior in Namibian public sector employees in capital and regional settings

The study objective was to assess the current status of HIV knowledge, attitudes and behavior (KAB) among employees of Namibian ministries. As most HIV campaigning takes place in the capital of Windhoek, an additional aim was to compare Windhoek to four regions (Hardap, Erongo, Oshana, and Caprivi). Between January and March 2011 a cross-sectional survey was conducted in two Namibian ministries, with participants selected randomly from the workforce. Data collection was based on questionnaires. 832 participants were included in the study (51.6% male). Nearly 90% of participants reported to have been tested for HIV before. Knowledge about HIV transmission ranged from 67% to 95% of correct answers, with few differences between the capital and regions. However, a knowledge gap regarding HIV transmission and prevention was seen. In particular, we found significantly lower knowledge regarding transmission from mother-to-child during pregnancy and higher rate of belief in a supernatural role in HIV transmission. In addition, despite many years of HIV prevention activities, a substantial proportion of employees had well-known HIV risk factors including multiple concurrent partnership rates (21%), intergenerational sex (19%), and lower testing rates for men (82% compared to women with 91%)

A Multi-Factorial Risk Prioritization Framework for Food-Borne Pathogens

To lower the incidence of human food-borne disease, experts and stakeholders have urged the development of a science- and risk-based management system in which food-borne hazards are analyzed and prioritized. A literature review shows that most approaches to risk prioritization developed to date are based on measures of health outcomes and do not systematically account for other factors that may be important to decision making. The Multi-Factorial Risk Prioritization Framework developed here considers four factors that may be important to risk managers: public health, consumer risk perceptions and acceptance, market-level impacts, and social sensitivity. The framework is based on the systematic organization and analysis of data on these multiple factors. The basic building block of the information structure is a three-dimensional cube based on pathogen-food-factor relationships. Each cell of the cube has an information card associated with it and data from the cube can be aggregated along different dimensions. The framework is operationalized in three stages, with each stage adding another dimension to decision-making capacity. The first stage is the information cards themselves that provide systematic information that is not pre-processed or aggregated across factors. The second stage maps the information on the various information cards into cobweb diagrams that create a graphical profile of, for example, a food-pathogen combination with respect to each of the four risk prioritization factors. The third stage is formal multi-criteria decision analysis in which decision makers place explicit values on different criteria in order to develop risk priorities. The process outlined above produces a ‘List A’ of priority food-pathogen combinations according to some aggregate of the four risk prioritization factors. This list is further vetted to produce ‘List B’, which brings in feasibility analysis by ranking those combinations where practical actions that have a significant impact are feasible. Food-pathogen combinations where not enough is known to identify any or few feasible interventions are included in ‘List C’. ‘List C’ highlights areas with significant uncertainty where further research may be needed to enhance the precision of the risk prioritization process. The separation of feasibility and uncertainty issues through the use of ‘Lists A, B, and C’ allows risk managers to focus separately on distinct dimensions of the overall prioritization. The Multi-Factorial Risk Prioritization Framework provides a flexible instrument that compares and contrasts risks along four dimensions. Use of the framework is an iterative process. It can be used to establish priorities across pathogens for a particular food, across foods for a particular pathogen and/or across specific food-pathogen combinations. This report provides a comprehensive conceptual paper that forms the basis for a wider process of consultation and for case studies applying the framework.risk analysis, risk prioritization, food-borne pathogens, benefits and costs

Deploying a spreadsheet tool for early economic value assessment of medical device innovations with healthcare decision makers

Early stage evaluation of medical device innovations is important for healthcare decision-makers as much as for manufacturers, meaning that a wider application of a basic cost-effectiveness analysis is becoming necessary outside the usual expert base of health technology assessment specialists. Resulting from an academic-industry-healthcare professional collaboration, a spreadsheet tool is described that was designed to be accessible both to professionals in healthcare delivery organisations and to innovators in the healthcare technology industry who are non-experts in the field of health economics. The tool enables a basic cost-effectiveness analysis to be carried out, using a simplified decision-tree model to compare costs and patient benefit for a new device-related procedure with that of standard care employing an incumbent device or other alternative. Such a tool is useful to healthcare professionals because it enables them to rapidly elucidate the cost-effectiveness of heterogeneous innovations by means of the standard quality adjusted life year (QALY) measure of clinical outcome, which is intended to be broadly comparable across treatments. For the innovator or manufacturer it helps them focus on what is required for future stages of development, in order to fill gaps in the input data and so further strengthen their case from a health economics perspective. Results are presented of first experiences from deploying the tool on three medical device exemplars, in face-to-face meetings of the NHS National Innovation Centre (NIC) along with the innovator or clinical champion. The results show that mapping of device-related innovations to the tool is achievable in a short meeting between the NIC and the innovator using expected costs, outcomes data from the literature and estimates of ranges for unknown input data. Whilst the result of a simplified analysis is not expected to be definitive, the process of reasoning is found to be illuminating for the parties involved, enabling innovators to articulate the benefits of their innovations and for all parties to highlight gaps in data and evidence that will be required to take the innovation forward. The partnership model of the authors’ organisation supports the kind of cooperative design approach that is necessary to produce the kind of tool described.---------------------------7dd39101208fa Content-Disposition: form-data; name="c14_creators_1_name_family" Crave

Linking Weak and Strong Sustainability Indicators: The Case of Global Warming

The aim of this paper is to describe and discuss the weak and strong sustainability approach of assessing climate change and to show reasonable applications, weaknesses, possible improvements and linkages of both approaches. Main features of ?weak? and ?strong? sustainability approaches are characterized. Damage cost studies of global warming representing weak sustainability indicators are discussed. Further, the examples of the ?inverse scenario? approach of the German Advisory Council on Global Change (WBGU) and the environmental space concept of the Dutch Advisory Council for Research on Nature and Environment (RMNO) are described and discussed for illustrating advantages and weaknesses of strong sustainability indicators. Finally, the integration of damage cost modules into a broader methodological framework of strong sustainability is recommended. --weak sustainability,strong sustainability,environmental space,invers scenario,external costs,climate change,global wearming,damage costs

Preference Reversals and the Analysis of Income Distributions

It is known from the literature on uncertainty that in cases where individuals express a preference for a high win-probability bet over a bet with high winnings they nevertheless will bid more to obtain the bet with high winnings. We investigate whether a similar phenomenon applies in the parallel social-choice situation. Here decisions are to be made between a distribution with a small group of very high-income people. Results from a number of experimental designs are analysed.Preference reversals, social welfare, inequality, risk and experiments.