CHE Discussion Papers (DPs) began publication in 1983 as a means of making current research material more widely available to health economists and other potential users. So as to speed up the dissemination process, papers were originally published by CHE and distributed by post to a worldwide readership. The new CHE Research Paper series takes over that function and provides access to current research output via web-based publication, although hard copy will continue to be available (but subject to charge). Disclaimer Papers published in the CHE Research Paper (RP) series are intended as a contribution to current research. Work and ideas reported in RPs may not always represent the final position and as such may sometimes need to be treated as work in progress. The material and views expressed in RPs are solely those of the authors and should not be interpreted as representing the collective views of CHE research staff or their research funders. Further copies Copies of this paper are freely available to download from the CHE website www.york.ac.uk/inst/che/pubs. Access to downloaded material is provided on the understanding that it is intended for personal use. Copies of downloaded papers may be distributed to third-parties subject to the proviso that the CHE publication source is properly acknowledged and that such distribution is not subject to any payment. Printed copies are available on request at a charge of £5.00 per copy. Please contact the

Research article Clearing up the hazy road from bench to bedside: A framework for integrating the fourth hurdle into translational medicine

Research article The greatest happiness of the greatest number? Policy actors' perspectives on the limits of economic evaluation as a tool for informing health care coverage decisions in Thailand

Abstract. After many years searching for customers, economic evaluation is now being used explicitly in health service decision making – principally to inform decisions about whether to fund new pharmaceuticals. To what extent are the methods of economic evaluation in health care adequate for this more prominent role? This paper sets out to address this question by considering the alternative theoretical bases for economic evaluation. It argues that a social decision making perspective provides the most appropriate foundation and, from this, a range of necessary analytical features are required in any study. The paper goes on to describe recent methods developments in the field including statistical methods to analyse patient-level data; techniques to handle uncertainty in cost-effectiveness measures; methods to synthesise available data whilst reflecting their imprecision and heterogeneity; decision analytic techniques to identify cost-effective options under conditions of uncertainty; and value of information methods to help prioritise and design future research. The paper argues, that although the methods of cost-effectiveness have progressed markedly over the last decade, these developments also emphasises how far the field still have to go. Two particular methods challenges are discussed which relate to the methods of constrained maximisation and developments and value of information methods.

case study summarised here was developed, in part, for a Technology Assessment Report for the National Institute of Clinical Excellence. Other co-authors to that

Despite the growing number of pharmacoeconomic/health economic studies, very little is known about their use by decision-makers. The objectives of the Task Force were to ensure that the good research practices of PE/HE studies pay attention to the needs of health care decision-makers and to develop a ‘toolbox ’ for the health care decision-maker wishing to interpret and use PE/HE studies. The Task Force report outlines the contexts for health care decision-making and reviews the literature on decision-makers ’ attitudes to PE/HE studies. Issues relating to the reliability and relevance of published studies are discussed. The reporting requirements in 15 published economic guidelines are reviewed and several recommendations made for additional reporting requirements for decisionmakers. Finally, several issues for further discussion and research are raised. This report was published in Value in Health as follows. The citation for this report is: Drummond M, Brown R, Fendrick AM, et al. Use of pharmacoeconomics information-Report of the ISPOR task force on use of pharmacoeconomic/health economic information in health-care decision making. Value Health 2003; 6:40 7-16. 2

The DARE study of relapse prevention in depression: design for a phase 1/2 translational randomised controlled trial involving mindfulness-based cognitive therapy and supported self monitoring Shawyer et al. Shawyer et al. BMC Psychiatry 2012, 12:3

production: a diary study

Research article Prevalence of dry eye syndrome and diabetic retinopathy in type 2 diabetic patients

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: The absence of trial evidence makes it impossible to determine whether or not mass screening for lung cancer would be cost effective and, indeed, whether a clinical trial to investigate the problem would be justified. Attempts have been made to resolve this issue by modelling, although the complex models developed to date have required more real-world data than are currently available. Being founded on unsubstantiated assumptions, they have produced estimates with wide confidence intervals and of uncertain relevance to the United Kingdom. Method: I develop a simple, deterministic, model of a screening regimen potentially applicable to the UK. The model includes only a limited number of parameters, for the majority of which, values have already been established in non-trial settings. The component costs of screening are derived from government guidance and from published audits, whilst the values for test parameters are derived from clinical studies. The expected health gains as a result of screening are calculated by combining published survival data for screened and unscreened cohorts with data from Life Tables. When a degree of uncertainty over a parameter value exists, I use a conservative estimate, i.e. one