The National Institute for Health and Clinical Excellence (NICE) is responsible for making recommendations about which treatments are available on the NHS. An important part of the decision making process is to estimate the cost effectiveness of a treatment, measured in cost per QALY gained. If a treatment costs more than £30000 per QALY the NHS does not consider it to be cost effective. QALYs are calculated using life years and QALY weights. which represent the quality of life of a condition. An example of a QALY weight is a utility. which is a measure of preference for a health condition. A utility is measured on a scale between 0 and 1, where 0 is the utility of death and 1 is the utility of perfect health. This thesis uses discrete choice modelling to estimate utilities for health states defined using the Asthma quality of life questionnaire. A Bayesian approach is used to estimate the utilities in order to quantify utility. A probit and legit model are considered for the likelihood where the parameters represent the decrease in utility associated with increasing levels of the attributes of the asthma quality of life questionnaire. An MCMC is run using three prior distributions on the parameters: Gamma(l.lO). Gamma(5.15) and Uniform(O. 1). The model is also extended to include a multiplicative random effect. Bayes factors are used as a model comparison in the standard model, Results from both the standard model and random effects model are also compared with maximum likelihood estimates.

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Due to limited budgets and tight financial control of budget within the NHS, policy makers are faced with difficult decisions. Recent Governmental White Papers have turned the NHS full circle and it has returned to where it started in the 1990's. The primary care health sector is increasingly responsible not only for managing their own budgets but for providing services which need to be economically evaluated. In order to achieve this various goal, sources of evidence stemming from evidence based medicine, involving various evaluations are/paramount. Policy makers need to base their decisions on sources of evidence which have been subject to economic evaluation. This thesis attempts to illustrate where the best sources of evidence can.be obtained, either from Randomised Controlled Trials of Observational Studies when making choices involving cost-effective treatments and investigations and ensuring to appropriately use the relevant economic evaluation technique. Heart failure represents a major problem not only for society but also for the NHS. Many treatments have been developed for this condition and have been proven to be not only beneficial for the morbidity and mortality of patients but have also been shown to be cost-effective for the NHS. Their prescription however needs assessment via echocardiography. There are a large proportion of patients not receiving the optimal treatment and management. Such crucial issues make heart failure one of the best targets for a high yield, low health care intervention. Due to the advances of a primary care led NHS, the viability of a primary care service involving echocardiography was economically evaluated and compared via cost minimisation analysis, to a secondary echocardiography service. Results demonstrated not only the costs of patients to the NHS but also how echocardiography could assist in reducing this burden. Primary care echocardiography has also been demonstrated to be cost-effective compared with secondary care provision and recommendations for further research should consider the expansion of similar echocardiographic service encompassing a larger patient population in a multi health care centre. This would provide further evidence combined with the recent advances in technology for the necessary resources for funding such an expansion of schemes where the biggest impact will be achieved. Issues of equality of provision inherent with this expansion must also be addressed before any introduction.

Aim: To develop a process guide to support the novice modeller in developing a methodologically sound decision analytic cost effectiveness model from start to finish. Methods: An outline of the guide was constructed based on a systematic review of health economic guidelines. The content of the guide was developed according to a review of best practice methods. The draft guide was subject to two rounds of the nominal group technique method of consensus agreement. After revision, the usability of the final guide was tested by the researcher, and validated by two independent novice modellers. Results: Thirty-two health economic guidelines met the selection criteria and were data extracted, synthesized, critically evaluated and formed the outline of the guide. The guide was structured according to the model building process, and the content was developed based on review of best practice methods. Agreement was reached on the key content of the draft guide. The final guide consists of 142 components divided over five modules aligned to the process of model building. Conclusion: A step by step process guide to decision analytic cost effectiveness modelling has been constructed. The content has been agreed upon using concensus methods and has been independantly validated. The guide aims to explicitly capture each step required in the process of model development. In contrast to guidelines and best practice recommendations already available, the guide is uniquely arranged according to the process of model building and consists of five modules composed of multiple components, each representing the tasks which constitute the model building process. The guide is designed to facilitate the novice modeller in the process of model development with the aim of improving model quality and transparency, thereby improving the decision making process for which modelling is an increasingly important source of evidence.

This thesis investigates the problem of treatment crossover – where patients randomised to the control group of a clinical trial are permitted to cross over onto the experimental treatment at some point during follow-up. Methods commonly used to adjust for treatment crossover within health technology assessments are known to be prone to bias, and these may lead to inconsistent resource allocation decisions. The objective of the thesis is to identify which methods are most appropriate for adjusting for treatment crossover in an economic evaluation context. If control group patients cross over and benefit from the experimental treatment, an intention to treat analysis will underestimate the “true” survival benefit associated with the new treatment – that is, the benefit that would have been observed had treatment crossover not been allowed. Simple methods for adjusting for crossover, such as excluding or censoring crossover patients, will lead to substantial bias when crossover is associated with prognosis. More complex crossover adjustment methods have been described in the literature and previous research has shown that some of these, such as the Rank Preserving Structural Failure Time Model, perform very well when their key methodological assumptions are satisfied. However, a full comparison of all relevant methods across a range of realistic scenarios – including scenarios where key assumptions are not satisfied – has not previously been undertaken. Approaches for incorporating these methods within an economic evaluation – specifically their use in combination with extrapolation modelling – have also not previously been investigated. In this thesis I demonstrate the importance of the treatment crossover problem, review and assess relevant crossover adjustment methods, and provide an analysis framework to enable the most appropriate method to be identified on a case-by-case basis. Importantly, it is shown that no single method will be satisfactory in all circumstances. In order to identify the method that is likely to provide least bias, consideration must be given to the crossover mechanism, the available trial data, disease and patient characteristics, and the nature of the treatment effect.

The purpose of this study was to explore and describe the knowledge of student nurses regarding the cost concepts in health economics, specifically the efficient allocation of resources and determining the cost of interventions, in order to prepare them to deliver cost-effective yet quality nursing care. An explorative and descriptive quantitative design was used. A structured self-administered questionnaire was used for data collection. Respondents were student nurses studying towards becoming professional nurses in their final year of study (comprehensive programme). The results revealed an apparent lack of knowledge among student nurses regarding cost concepts in health economics, although respondents agreed that knowledge of health economics is essential for nursing practice. The results led the researcher to draw a strong conclusion that there is a need for the inclusion of a module regarding health economics in the nursing curriculum and in continuous professional development (CPD) workshops and in-service training. / Health Studies / M.A. (Health Studies)