The interaction between policy and education using stroke as an example

This paper discusses the interaction between healthcare policy at the European, UK and Scottish levels and the funding of education that underpins specific health policy priorities. Stroke is used throughout to illustrate the relationship between a designated European and UK health priority and the translation of that priority into clinical delivery. The necessity to build a responsive and sustainable culture to address the healthcare education that underpins changing healthcare policies is emphasized

A micro costing of NHS cancer genetic services

This paper presents the first full micro costing of a commonly used cancer genetic counselling and testing protocol used in the UK. Costs were estimated for the Cardiff clinic of the Cancer Genetics Service in Wales by issuing a questionnaire to all staff, conducting an audit of clinic rooms and equipment and obtaining gross unit costs from the finance department. A total of 22 distinct event pathways were identified for patients at risk of developing breast, ovarian, breast and ovarian or colorectal cancer. The mean cost per patient were £97–£151 for patients at moderate risk, £975–£3072 for patients at high risk of developing colorectal cancer and £675–£2909 for patients at high risk of developing breast or ovarian cancer. The most expensive element of cancer genetic services was labour. Labour costs were dependent upon the amount of labour, staff grade, number of counsellors used and the proportion of staff time devoted to indirect patient contact. With the growing demand for cancer genetic services and the growing number of national and regional cancer genetic centers, there is a need for the different protocols being used to be thoroughly evaluated in terms of costs and outcomes

Application of statistical and decision-analytic models for evidence synthesis for decision-making in public health and the healthcare sector

With the awareness that healthcare is a limited resource, decision-makers are challenged to allocate it rationally and efficiently. Health economic methods of evidence synthesis for decision-making are useful to quantify healthcare resource utilisation, critically evaluate different interventions and ensure the implementation of the most effective or cost-effective strategy. The nine studies included in the present cumulative doctoral thesis aim to demonstrate the capability of statistical and decision-analytic modelling techniques to inform and support rational healthcare decision-making in Germany. Five studies apply statistical modelling in analyses of public health and health economic data. They show that the developed models are valuable instruments for examining patterns in the data and generating knowledge from observable data which can further be used in devising disease management and care programs as well as economic evaluations. Further, two health economic evaluations, which adopt the decision-analytic-modelling approach, show that decision-analytic modelling is a powerful tool to represent the epidemiology of infectious and non-infectious diseases on a population level, quantify the burden of the diseases, generalise the outcomes of clinical trials, and predict how the interventions can change the impact of the diseases on the health of the population. Additionally, two literature reviews examine the application of decision-analytic modelling in health economic evaluations. The first study reviews and empirically analyses health technology assessments by the German Institute for Medical Documentation and Information and demonstrates that the application of decision-analytic models improves the evidence produced for policy-making in the healthcare sector in Germany. The second systematic review focuses on methodological choices made in constructing decision-analytic models and explains how critically the structural and parametrical assumptions can influence the final message of the economic evaluations and shows that building a validated, reliable model as well as the transparent reporting is of high priority in facilitating the communication and implementation of the most cost-effective course of action. Overall, the present thesis shows the relevance and advantage of the application of models in synthesising evidence for decision-making. The included studies contribute to the current and future development of the methods used to address the problems of health economic efficiency. Further advances in the computational modelling techniques and data collection, from one side, will ease the decision-making process, but, from another side, will require increasing competence and understanding within the decision-making bodies

Evidence and Value: Impact on DEcisionMaking – the EVIDEM framework and potential applications

<p>Abstract</p> <p>Background</p> <p>Healthcare decisionmaking is a complex process relying on disparate types of evidence and value judgments. Our objectives for this study were to develop a practical framework to facilitate decisionmaking in terms of supporting the deliberative process, providing access to evidence, and enhancing the communication of decisions.</p> <p>Methods</p> <p>Extensive analyses of the literature and of documented decisionmaking processes around the globe were performed to explore what steps are currently used to make decisions with respect to context (from evidence generation to communication of decision) and thought process (conceptual components of decisions). Needs and methodologies available to support decisionmaking were identified to lay the groundwork for the EVIDEM framework.</p> <p>Results</p> <p>A framework was developed consisting of seven modules that can evolve over the life cycle of a healthcare intervention. Components of decision that could be quantified, i.e., intrinsic value of a healthcare intervention and quality of evidence available, were organized into matrices. A multicriteria decision analysis (MCDA) Value Matrix (VM) was developed to include the 15 quantifiable components that are currently considered in decisionmaking. A methodology to synthesize the evidence needed for each component of the VM was developed including electronic access to full text source documents. A Quality Matrix was designed to quantify three criteria of quality for the 12 types of evidence usually required by decisionmakers. An integrated system was developed to optimize data analysis, synthesis and validation by experts, compatible with a collaborative structure.</p> <p>Conclusion</p> <p>The EVIDEM framework promotes transparent and efficient healthcare decisionmaking through systematic assessment and dissemination of the evidence and values on which decisions are based. It provides a collaborative framework that could connect all stakeholders and serve the healthcare community at local, national and international levels by allowing sharing of data, resources and values. Validation and further development is needed to explore the full potential of this approach.</p

Cost-effectiveness of adjuvant therapy for hepatocellular carcinoma during the waiting list for liver transplantation.

Background: Survival after liver transplantation for early hepatocellular carcinoma (HCC) is worsened by the increasing dropout rate while waiting for a donor. Aims: To assess the cost effectiveness of adjuvant therapy while waiting for liver transplantation in HCC patients. Method: Using a Markov model, a hypothetical cohort of cirrhotic patients with early HCC was considered for: (1) adjuvant treatment—resection was limited to Child-Pugh's A patients with single tumours, and percutaneous treatment was considered for Child-Pugh's A and B patients with single tumours unsuitable for resection or with up to three nodules < 3 cm; and (2) standard management. Length of waiting time ranged from six to 24 months. Results: Surgical resection increased the transplantation rate (>10%) and provided gains in life expectancy of 4.8–6.1 months with an acceptable cost ($40 000/ year of life gained) for waiting lists ≥1 year whereas it was not cost effective ($74 000/life of year gained) for shorter waiting times or high dropout rate scenarios. Percutaneous treatment increased life expectancy by 5.2–6.7 months with a marginal cost of approximately $20 000/year of life gained in all cases, remaining cost effective for all waiting times. Conclusions: Adjuvant therapies for HCC while waiting for liver transplantation provide moderate gains in life expectancy and are cost effective for waiting lists of one year or more. For shorter waiting times, only percutaneous treatment confers a relevant survival advantage

Inference for Ecological Dynamical Systems: A Case Study of Two Endemic Diseases

A Bayesian Markov chain Monte Carlo method is used to infer parameters for an open stochastic epidemiological model: the Markovian susceptible-infected-recovered (SIR) model, which is suitable for modeling and simulating recurrent epidemics. This allows exploring two major problems of inference appearing in many mechanistic population models. First, trajectories of these processes are often only partly observed. For example, during an epidemic the transmission process is only partly observable: one cannot record infection times. Therefore, one only records cases (infections) as the observations. As a result some means of imputing or reconstructing individuals in the susceptible cases class must be accomplished. Second, the official reporting of observations (cases in epidemiology) is typically done not as they are actually recorded but at some temporal interval over which they have been aggregated. To address these issues, this paper investigates the following problems. Parameter inference for a perfectly sampled open Markovian SIR is first considered. Next inference for an imperfectly observed sample path of the system is studied. Although this second problem has been solved for the case of closed epidemics, it has proven quite difficult for the case of open recurrent epidemics. Lastly, application of the statistical theory is made to measles and pertussis epidemic time series data from 60 UK cities