My Publications: Google scholar
Informatics for more efficient research with primary care databases
Routinely collected electronic medical record (EMR) databases are rich sources of data for health reearch. Although lacking the rigour of Randomised controlled trials (RCTs) and potentially affected by bias from uncontrolled factors, these databases allow the investigation of research questions which may not be feasible to address by other means. For example, some population groups are often excluded from RCTs for ethical and other reasons (e.g. children, pregnant women, people with severe mental illness). These groups, however will often receive these interventions in clinical practice. Trials are in addition frequently insufficiently powered to study less common outcomes, e.g. mortality, or unintended beneficial or adverse effects of interventions and are often limited by short duration of follow up. These datasets are also increasingly used in health services research, particularly for investigating the impacts of nationally-implemented NHS policies where control groups are not possible.
The UK leads the world in Primary care databases (PCDs), which collate data from the EMRs of patients registered with a large number of practices. This project focuses on three problematic or under-developed aspects of PCD-based research:
- Reducing duplication of effort – I am developing open source software tools to facilitate the manipulation and analysis of PCD data.
- Improving validity and reproducibility of clinical code lists – I have built and am maintaining the ClinicalCodes.org online repository for clinical code lists.
- Improving data quality – We are working on developing methods to address missing data and outliers in complex and messy PCD datasets.
- Springate DA, Kontopantelis E, Ashcroft DA, Olier I, Parisi R, Chamapiwa E, Reeves, D 2014 ClinicalCodes: An online clinical codes repository to improve the validity and reproducibility of research using electronic medical records. PLoS ONE (in press).
Validity of PCD effectiveness studies
Evidence from Primary care databases (PCDs) is traditionally given less weight than evidence from bespoke cohort studies and RCTs. The reasons for this include uncertainties areound issues of data quality, completeness and confounding factors. In this project, we attempt to to establish the extent to which results derived from PCD studies are valid and reproducible.
- D Reeves, David Springate, D Ashcroft, R Ryan, T Doran, R Morris, I Ollier, E Kontopantelis (2014) Can analyses of electronic patient records be independently and externally validated? The effect of statins on the mortality of patients with Ischaemic heart disease: a cohort study with nested case-control analysis. BMJ Open,;4:e004952.
- E Kontopantelis, David Springate and D Reeves (2013) A re-analysis of the Cochrane library data: the dangers of unobserved heterogeneity in meta-analyses PLoS ONE 8(7):e69930.
An investigation of the NHS Quality and Outcomes Framework using the Clinical Practice Research Datalink
In the UK, GPs are paid for treating patients with certain conditions according to clinical evidence in a large and expensive par-for-performance scheme which is adjusted every year. using a large Electronic Medical Records database, we examined what happens when payment for a particular activity was stopped, whether some patients should be excluded from the scheme and how payments can be more closely aligned to health gains.
- E Kontopantelis, David Springate, D Reeves, D Ashcroft, M Rutter, I Buchan T Doran (2014) Predictors of survivals and complications in type 2 diabetes: a retrospective cohort study. Submitted.
- E Kontopantelis,David Springate, D Reeves, D Ashcroft, J Valderas, T Doran (2014) Withdrawing Performance Indicators: Retrospective Analysis of General Practice Performance Under the UK’s Quality and Outcomes Framework. British Medical Journal;348:g330. DOI
PhD Thesis: Plastic and Genetic Responses to Environmental changes
Human activity is causing climates to change more rapidly than at any time in the last 10,000 years. If populations of organisms are unable to effectively respond to changing environments, they will be at risk of extinction. In plants, two of the most important mechanisms of response to environmental change are phenotypic plasticity, where the same genotype expresses different phenotypes in different environments, and adaptation, which requires changes in allele frequency in populations as exposed individuals show variable survival and reproduction. Although most researchers accept the importance of both of these mechanisms, they are most commonly considered in isolation in models of response and persistence to climate change. Here, I use the model species Arabidopsis thaliana to investigate the interaction of plasticity and selection in fitness and phenology response to simulated climate warming, the effect of artificial selection on variation for plastic response and cross-generational effects of environmentally induced variation in flowering time. I also study the effects of varying rates of environmental fluctuation on evolvability on populations of self-replicating computer programs using the artificial life platform Avida. I find that a small increase in ambient temperature, in line with predictions for the next few decades, is able to elicit significant plastic responses and that these responses have the potential to alter population genetic structure and affect future evolution. I also find that selection on flowering time can reduce variation for plastic response and that non-genetic effects on flowering time can significantly alter germination in the next generation. Lastly, I find that rapidly changing environments in the long term can select for more evolvable populations and genotypes. These results highlight the importance of considering plasticity and evolution together if we are going to make accurate predictions of climate change response.
- David Springate and P Kover (2013) Plant responses to elevated temperatures: a field study on phenological sensitivity and fitness responses to simulated climate warming. Global Change Biology 20(2) 456-465
- David Springate, N Scarcelli, J Rowntree, P Kover (2011) Correlated response in plasticity to selection for early flowering in Arabidopsis thaliana. Journal of Evolutionary Biology 08/2011; 24(10):2280-8.
Other Collaborations and smaller projects
- P Hadjipantelis, N Jones, J Moriarty, David Springate, C Knight (2012) Function-valued traits in Evolution. Journal of the Royal Society Interface 01/2013; 10(82):20121032.
- Oldekop, A Bebbington, K Hennermann, J Mcmorrow, David Springate, B Torres, N Truelove, N Tysklind, S Villamarn, R Preziosi (2012) Evaluating the effects of common-pool resource institutions and market forces on species richness and forest cover in Ecuadorian indigenous Kichwa communities. Conservation Letters 01/2013
- V Savolainen, M Anstett, C Lexer, I Hutton, J Clarkson, M Norup, M Powell, David Springate, N Salamin, W Baker (2006) Sympatric speciation in palms on an oceanic island. Nature 06/2006; 441(7090):210-3. DOI:10.1038/nature04566
- A Paton, David Springate, S Suddee, D Otieno, R Grayer, M Harley, F Willis, M Simmonds, M Powell, V Savolainen (2003) Phylogeny and evolution of basils and allies (Ocimeae, Labiatae) based on three plastid DNA regions. Molecular Phylogenetics and Evolution 05/2004; 31(1):277-99.