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Imperial College researchers have developed methods and indicators for highlighting potential variations in healthcare performance and safety using routinely collected health data. Analytical tools based on our methodological research are used by managers and clinicians in over two thirds of NHS hospital trusts, and hospitals throughout the world. The results of our analyses helped detect problems at Mid Staffordshire NHS Foundation Trust and triggered the initial investigation and subsequent public inquiry with wide ranging recommendations based on the recognition of their value and their use in enhancing the safety of healthcare.
The Variable Life-Adjusted Display (VLAD) is a graphical tool for monitoring clinical outcomes. It has been widely adopted by UK cardiac surgery centres, and has helped a shift in culture towards more open outcome assessment in adult cardiac surgery, which has been credited with reduced mortality rates. VLAD is also being used for a broad range of other clinical outcomes by regulatory bodies worldwide. For example, Queensland Health uses VLAD as a major part of its Patient Safety and Quality Improvement Service to monitor 34 outcomes across 64 public hospitals, and NHS Blood and Transplant uses VLAD to monitor early outcomes of all UK transplants.
Events in the UK NHS have shown the need for a robust understanding of hospital mortality rates.
Surrey's research produced "a unique web-enabled pattern analysis system that is specifically designed to enable clinicians and their teams to view in detail their in-house mortality patterns in the national context" (a).
Launched on a national scale in Ireland in 2013, it has already identified `mortality outliers' and been described as a `game changer' for improving service quality at national level. The tool's impact stems from its ability to translate statistical patterns into a form readily usable by health professionals to improve care quality and sharing best practice.
This case study describes a significant new index used to monitor death rates in hospitals. The Summary Hospital Mortality Index (SHMI) was developed as a direct result of research carried out at the School of Health and Related Research (ScHARR). This was implemented nationally in October 2011 and the SHMI is now the main mortality indicator used by the NHS. Following publication of the high profile Francis Inquiry on Mid Staffordshire in February 2013, set up to investigate excess mortality in the Trust, the Government has used the SHMI to identify and target 8 further hospitals for investigation.
This case study concerns the research of Professor David Spiegelhalter on `funnel plot' methodology for comparing institutions. This system has now become the standard method within the National Health Service for comparing clinical outcomes, including hospital Trusts with apparently `outlying' mortality rates. In particular, mortality following children's heart surgery is analysed and presented using funnel plots, and Professor Spiegelhalter's work has been instrumental in handling high-profile cases such as surgery at Oxford Radcliffe Infirmary and Leeds General Infirmary.
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.
There is growing evidence that official population statistics based on the decennial UK Census are inaccurate at the local authority level, the fundamental administrative unit of the UK. The use of locally-available administrative data sets for counting populations can result in more timely and geographically more flexible data which are more cost-effective to produce than the survey-based Census. Professor Mayhew of City University London has spent the last 13 years conducting research on administrative data and their application to counting populations at local level. This work has focused particularly on linking population estimates to specific applications in health and social care, education and crime. Professor Mayhew developed a methodology that is now used as an alternative to the decennial UK Census by a large number of local councils and health care providers. They have thereby gained access to more accurate, detailed and relevant data which have helped local government officials and communities make better policy decisions and save money. The success of this work has helped to shape thinking on statistics in England, Scotland and Northern Ireland and has contributed to the debate over whether the decennial UK Census should be discontinued.
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.
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.