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The statistical analysis of large datasets has contributed to the rehabilitation of the Ross procedure (the replacement of a failing aortic valve with the patient's own pulmonary valve) for specific patient groups, such as those above 50 years old who want to avoid daily anticoagulation treatment, and those with a reduced life span, especially patients on dialysis. The results of the research have (a) contributed to changes in the current practice guidelines of the European Society of Cardiologists and (b) have shown that, in contrast to previous beliefs, the Ross procedure can still be safely performed when the aortic valve malfunctions.
Professor Hutton's research considers the biasing effect of selection of data due to consent procedures or selective reporting, and its consequences for the validity of conclusions and reliability of results. This research has had impacts on patients directly; on health and legal professionals by informing and influencing national and international guidelines for the treatment of epilepsy used by healthcare professionals and practitioners; and has provided expert evidence to legal professionals for the conclusion of civil litigations and a General Medical Council professional misconduct trial. Hutton's research also informs ethical debate associated with the validity and robustness of study results. This work has determined guidelines for ethical conduct of research, and requirements for publications, which are significant for all biomedical researchers.
The National Institute for health Care Excellence (NICE) in England and Wales makes timely and equitable decisions regarding the use of health technologies (medical devices and pharmaceuticals) within the NHS in order to improve patient care. Such decisions are reliant on Health Technology Assessment (HTA) — the processes of evidence generation and synthesis, and the methods that underpin these. Methods pioneered and developed at Leicester over the last 15 years are now used routinely in HTA both by NICE and the pharmaceutical industry and healthcare consultancy companies who make submissions to NICE. Internationally, these methods are also now being adopted in the US by Agency for Healthcare Research and Quality (AHRQ), as well as in rapidly developing countries such as Brazil and Colombia.
Research on novel statistical methods for disease surveillance and influenza vaccine effectiveness has led to the development of a suite of automatic systems for detecting outbreaks of infectious diseases at Health Protection Scotland (HPS). This work has improved the public health response and helped to reduce costs in Scotland and also in the wider UK and EU by providing real-time early warning of disease outbreaks and timely estimates of the effectiveness of the influenza vaccine. This research, commissioned by the Scottish Government, through HPS, and also the UK National Institute for Health Research (NIHR) and the European Centres for Disease Control (ECDC), but used in a wider context by many others, formed the basis for the HPS response to the H1N1 Influenza Pandemic and monitoring of the effects of Influenza Vaccines.
This research has profoundly influenced the practice of pharmacoepidemiology in 2008-13. The self-controlled case series (SCCS) method is particularly well-suited for working with computerised databases, which are increasingly used in epidemiology. The method has been recommended by international agencies (WHO, ECDC) and is now widely used by health practitioners within national public health agencies, including the CDC (USA), Public Health England (UK) and many other national and regional public health bodies. It has influenced practice within the private sector (notably the pharmaceutical and the healthcare industries). Use of the SCCS method has impacted on health by reducing costs, improving timeliness and improving the quality of evidence upon which policy decisions are based.
The WinBUGS software (and now OpenBUGS software), developed initially at Cambridge from 1989-1996 and then further at Imperial from 1996-2007, has made practical MCMC Bayesian methods readily available to applied statisticians and data analysts. The software has been instrumental in facilitating routine Bayesian analysis of a vast range of complex statistical problems covering a wide spectrum of application areas, and over 20 years after its inception, it remains the leading software tool for applied Bayesian analysis among both academic and non-academic communities internationally. WinBUGS had over 30,000 registered users as of 2009 (the software is now open-source and users are no longer required to register) and a Google search on the term `WinBUGS' returns over 205,000 hits (over 42,000 of which are since 2008) with applications as diverse as astrostatistics, solar radiation modelling, fish stock assessments, credit risk assessment, production of disease maps and atlases, drug development and healthcare provider profiling.
Novel statistical methods were developed in order to address the needs of Federal-Mogul Corporation (FM), an innovative and diversified $6.9bn global component supplier to vehicle manufacturers, with a broad range of customers in the industrial sector. During 2012, the research underpinned the production of new disc brake pad products for Audi, BMW, Ford, GM, Mercedes Benz and VW. The research has already resulted in significant benefits for the company by improving the manufacturing process, allowing it to be optimised to a mean specification, and by reducing the production cycle time by 30%.
Reversible Jump Markov chain Monte Carlo, introduced by Peter Green [1] in 1995, was the first generic technique for conducting the computations necessary for joint Bayesian inference about models and their parameters, and it remains by far the most widely used, 18 years after its introduction. The paper has been (by September 2013) cited over 3800 times in the academic literature, according to Google Scholar, the vast majority of the citing articles being outside statistics and mathematics. This case study, however, focusses on substantive applications outside academic research altogether, in the geophysical sciences, ecology and the environment, agriculture, medicine, social science, commerce and engineering.
Age Related Macular Degeneration (AMD) is by far the leading cause of blindness in older people in the developed world, affecting 30% of those aged over 65, and is set to increase. The naturally-occurring carotenoids lutein (L) and zeaxanthin (Z) are located in the central retina (macula) and are collectively called the macular pigment (MP). High MP levels confer protection from AMD. Murray and colleagues have developed a new instrument, the Macular Pigment Screener (MPS), which allows regular, non-invasive monitoring of MP in ophthalmic practice. This means that, for the first time, the MPS can show the effect of intervention on the MP, providing a management strategy for AMD patients, and allowing early identification of those at risk of developing AMD. Over 750 instruments have been sold to date, with more than 1M patients in the US alone estimated to be benefiting from routine MP testing.
Since 2008, statistical research at the University of Bristol has significantly influenced policies, practices and tools aimed at evaluating and promoting the quality of institutional and student learning in the education sector in the UK and internationally. These developments have also spread beyond the education sector and influence the inferential methods employed across government and other sectors. The underpinning research develops methodologies and a much-used suite of associated software packages that allows effective inference from complicated data structures, which are not well-modelled using traditional statistical techniques that assume homogeneity across observational units. The ability to analyse complicated data (such as pupil performance measures when measured alongside school, classroom, context and community factors) has resulted in a significant transformation of government and institutional policies and their practices in the UK, and recommendations in Organisation for Economic Co-operation and Development (OECD) policy documents. These techniques for transforming complex data into useful evidence are well-used across the UK civil service, with consequent policy shifts in areas such as higher education admissions and the REF2014 equality and diversity criteria.