5,246 research outputs found

    Does the National Institute for Health and Clinical Excellence take account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services? A binary choice experiment

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    Background: NICE is an independent organisation responsible for providing national guidance on the promotion of good health and the prevention and treatment of ill health in England and Wales. One of NICE’s main roles is to produce national guidance on the use of health technologies within the NHS. Despite the Institute’s recent efforts to clarify the way in which its Appraisal Committees reach their recommendations concerning the use of health technologies, there remains ambiguity about how cost-effectiveness evidence is interpreted alongside other considerations such as the degree of clinical need within the patient population, and the degree of uncertainty surrounding cost-effectiveness estimates. Objective: To explore whether the NICE takes account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services. Methods: A binary choice experiment was undertaken using NICE’s three Appraisal Committees. The experiment included five attributes: (1) Incremental cost-effectiveness (2) Degree of economic uncertainty (3) Age of the target population (4) Baseline health-related quality of life (5) Availability of other therapies A choice questionnaire detailing 18 scenarios was administered to NICE’s Appraisal Committees. For each scenario, respondents were asked to indicate whether they would recommend the intervention under consideration or not. The stated preference data obtained from respondents were analysed using a random effects logit regression model. Results: A response rate of 46% was obtained from the Appraisal Committees. The regression model suggests that increases in cost-effectiveness, economic uncertainty, and the availability of other therapies are associated with statistically significant reductions in the odds of adoption (p<0.05). The transition from a very low to a comparatively high level of health-related quality of life is also associated with a statistically significant reduction in the odds of a positive recommendation. Smaller changes in health-related quality of life, and the age of the target population are not associated with a statistically significant reduction in the odds of a positive recommendation. Analysis of revealed preference data indicates that the model is capable of distinguishing between those technologies which the Appraisal Committees would be highly likely to recommend, and those technologies which appear to be less attractive, although further external validation is warranted. Conclusion: The modelling suggests that cost-effectiveness, uncertainty and certain equity concerns influence the NICE Appraisal Committees’ recommendations on the use of health technologies. The modelling results appear to support Rawlins and Culyer’s notion of a probabilistic cost-effectiveness threshold approach; the "mythical" £30,000 per QALY gained threshold assumed within the literature is not supported by this stated preference modelling analysis

    Does the National Institute for Health and Clinical Excellence take account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services? A binary choice experiment

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    Background NICE is an independent organisation responsible for providing national guidance on the promotion of good health and the prevention and treatment of ill health in England and Wales. One of NICE’s main roles is to produce national guidance on the use of health technologies within the NHS. Despite the Institute’s recent efforts to clarify the way in which its Appraisal Committees reach their recommendations concerning the use of health technologies, there remains ambiguity about how cost-effectiveness evidence is interpreted alongside other considerations such as the degree of clinical need within the patient population, and the degree of uncertainty surrounding cost-effectiveness estimates. Objective To explore whether the NICE takes account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services. Methods A binary choice experiment was undertaken using NICE’s three Appraisal Committees. The experiment included five attributes: (1) Incremental cost-effectiveness (2) Degree of economic uncertainty (3) Age of the target population (4) Baseline health-related quality of life (5) Availability of other therapies A choice questionnaire detailing 18 scenarios was administered to NICE’s Appraisal Committees. For each scenario, respondents were asked to indicate whether they would recommend the intervention under consideration or not. The stated preference data obtained from respondents were analysed using a random effects logit regression model. Results A response rate of 46% was obtained from the Appraisal Committees. The regression model suggests that increases in cost-effectiveness, economic uncertainty, and the availability of other therapies are associated with statistically significant reductions in the odds of adoption (puncertainty; equity; cost-effectiveness; public health

    GEEQBOX: A MATLAB Toolbox for Generalized Estimating Equations and Quasi-Least Squares

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    The GEEQBOX toolbox analyzes correlated data via the method of generalized estimating equations (GEE) and quasi-least squares (QLS), an approach based on GEE that overcomes some limitations of GEE that have been noted in the literature. GEEQBOX is currently able to handle correlated data that follows a normal, Bernoulli or Poisson distribution, and that is assumed to have an AR(1), Markov, tri-diagonal, equicorrelated, unstructured or working independence correlation structure. This toolbox is for use with MATLAB.

    Scalable quantum computation with fast gates in two-dimensional microtrap arrays of trapped ions

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    We theoretically investigate the use of fast pulsed two-qubit gates for trapped ion quantum computing in a two-dimensional microtrap architecture. In one dimension, such fast gates are optimal when employed between nearest neighbours, and we examine the generalisation to a two-dimensional geometry. We demonstrate that fast pulsed gates are capable of implementing high-fidelity entangling operations between ions in neighbouring traps faster than the trapping period, with experimentally demonstrated laser repetition rates. Notably, we find that without increasing the gate duration, high-fidelity gates are achievable even in large arrays with hundreds of ions. To demonstrate the usefulness of this proposal, we investigate the application of these gates to the digital simulation of a 40-mode Fermi-Hubbard model. This also demonstrates why shorter chains of gates required to connect arbitrary pairs of ions makes this geometry well suited for large-scale computation

    Estimation of a preference based single index from the sexual quality of life questionnaire (SQOL) using ordinal data

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    There is increasing interest in using ordinal methods to estimate cardinal values for health states to calculate quality adjusted life years. This paper reports the estimation of models of rank data and discrete choice experiment (DCE) data to derive a preference-based index from a condition specific measure relating to sexual health and to compare the results to values generated from time trade-off valuation (TTO). The DCE data were analysed using a random effects probit model and the DCE predicted values were rescaled according to the highest and lowest predicted TTO values corresponding to the best and worst SQOL health states respectively. The rank data were analysed using a rank ordered logit model and re-scaled using two alternative methods. Firstly, re-scaling the rank predicted values using identical methods to those employed for DCE and secondly, re-scaling the rank model coefficients by dividing each level coefficient by the coefficient relating to death. The study raises some important issues about the use of ordinal data to produce cardinal health state valuations

    Older people, regeneration and health and well-being. Case study of Salford Partnership Board for Older People

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    This study sat within a national project aimed at demonstrating that expert knowledge housed within universities can make a positive impact in urban communities around four themes: Community Cohesion, Crime, Enterprise and Health & Wellbeing. It involved the Universities of Salford, Northumbria, Central Lancashire, Manchester Metropolitan University and Bradford. The project aimed to address key urban regeneration challenges in the North of England through inter-disciplinary collaboration between partner universities and practitioner organisations. It also sought to build a long term strategic alliance between core university partners. Within each of the four project areas there were a number of smaller projects each focusing on the relationship between the theme and urban regeneration. This study sought to establish how partnership boards for older people address the health and well being needs of people over 50 years of age including how health and wellbeing are defined; strategies older people adopt to change service providers' actions; learning by service providers about the involvement of older people on Boards; and how this influences practice. The main activity within this study was to interview Salford Partnership Board members. The findings informed further development of the Board

    Restorative practice and behaviour management in schools: discipline meets care.

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    The history of restorative practices in New Zealand schools is directly related to projects such as the Suspension Reduction Initiative (SRI) and the more recent Student Engagement Initiative (SEI); thus the origins of restorative practices in schools are linked with behaviour management and school discipline. During the same period, teachers' work has become more complex: They are working with an increasingly diverse range of students, which in turn requires epistemologically diverse teaching and relationship-building approaches to ensure maximum participation for all. Teachers are looking for new and better ways to interact with students in their classrooms, and those responsible for disciplinary systems are looking to restorative practice for new ways to resolve the increasing range and number of difficulties between teachers and students, students and other students, and between the school and parents. Restorative practices (RP) are currently seen as a way of achieving all this, so they carry a huge burden of hope. Relationship skills are a key competency in the new curriculum, and the philosophy of restoration offers both a basis for understanding and a process for putting this agenda into practice. In effect, it means educating for citizenship in a diverse world, including teaching the skills of conflict resolution. If we accept this philosophy, the curriculum for teacher education will require significant changes in what students are taught about behaviour and classroom management

    Estimation of a preference based single index from the sexual quality of life questionnaire (SQOL) using ordinal data

    Get PDF
    There is increasing interest in using ordinal methods to estimate cardinal values for health states to calculate quality adjusted life years. This paper reports the estimation of models of rank data and discrete choice experiment (DCE) data to derive a preference-based index from a condition specific measure relating to sexual health and to compare the results to values generated from time trade-off valuation (TTO). The DCE data were analysed using a random effects probit model and the DCE predicted values were rescaled according to the highest and lowest predicted TTO values corresponding to the best and worst SQOL health states respectively. The rank data were analysed using a rank ordered logit model and re-scaled using two alternative methods. Firstly, re-scaling the rank predicted values using identical methods to those employed for DCE and secondly, re-scaling the rank model coefficients by dividing each level coefficient by the coefficient relating to death. The study raises some important issues about the use of ordinal data to produce cardinal health state valuations.sexual health, quality of life, preference-based measures

    Estimation of a preference based single index from the sexual quality of life questionnaire (SQOL) using ordinal data

    Get PDF
    There is increasing interest in using ordinal methods to estimate cardinal values for health states to calculate quality adjusted life years. This paper reports the estimation of models of rank data and discrete choice experiment (DCE) data to derive a preference-based index from a condition specific measure relating to sexual health and to compare the results to values generated from time trade-off valuation (TTO). The DCE data were analysed using a random effects probit model and the DCE predicted values were rescaled according to the highest and lowest predicted TTO values corresponding to the best and worst SQOL health states respectively. The rank data were analysed using a rank ordered logit model and re-scaled using two alternative methods. Firstly, re-scaling the rank predicted values using identical methods to those employed for DCE and secondly, re-scaling the rank model coefficients by dividing each level coefficient by the coefficient relating to death. The study raises some important issues about the use of ordinal data to produce cardinal health state valuations
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