Biomedical Informatics
Biomedical Informatics Research Group is a multidisciplinary group of informaticians, clinicians, psychologists and computer scientists, researching the role of data and knowledge in medical research and practice. Our core area of interest is the concept of the Learning Health System (LHS) which is a part of a growing field of ‘learning systems’ where knowledge acquisition and process improvement become at least semi-automated tasks of the human-cyber-social infrastructure. Thus, applications such as clinical trials, diagnostic support and epidemiological studies, are all redefined in terms of data and knowledge flows through the health system. Through our work, we are committed to improving the quality and safety of clinical care and efficiency and effectiveness of research it is based on.
Current Research Projects
CONSULT: Collaborative Mobile Decision Support for Managing Multiple Morbidities, EPSRC, £1.4M, 2017-2020
CONSULT will combine wireless wellness sensors with intelligent software running on mobile devices, to support patient decision making, and thus actively engage patients in managing their healthcare.
ProvTemp: Provenance templates as a method for facilitating provenance capture and simulating provenance data, EPSRC, £100K, 2016-2017
Developing a provenance infrastructure for non-computational domains with a use case in clinical trial informatics. The project will establish a roadmap for a future research programme in the area.
https://twitter.com/ProvTempProject
EmProv: Using provenance to embed trust in visual analytics of health data, InnovateUK, £135K, 2016-2018
Using data provenance technology to implement reproducibility features for Face Ltd.’s iMoLYTICS product, giving it a competitive advantage.
Ancestry and biological Informative Markers for stratification of HYpertension (AIM HY), MRC, £3.5M, 2015-2020
Hypertension is recognised as the biggest contributor to the global burden of disease, a burden that is particularly great in ethnic minorities in the UK and in lower and middle- income countries (LMIC). AIM HY is looking to personalize the selection of established drugs to provide a more effective treatment of hypertension for ethnic minority groups in the UK and in LMIC populations such as Africa. This will be based on contemporary ‘omics technology using ancestry informative markers (AIM) and additional biomarkers.
Project to Enhance ALSPAC cohort through Record Linkage (PEARL), Wellcome, 2009-
The Avon Longitudinal Study of Parents and Children (ALSPAC) - which is also known as Children of the 90s - is a long-term health research project. More than 14,000 mothers enrolled during pregnancy in 1991 and 1992, and the health and development of their children has been followed in great detail ever since. The ALSPAC families have provided a vast amount of genetic and environmental information over the years. This resource is assisting scientists all over the world with research into a wide range of health problems. The children involved in the study have now reached the age of 18 and as such are now being given the opportunity to consent as adults in their own right. For a number of reasons, cohort members are likely to become dispersed from the ALSPAC recruitment area. PEARL provides follow up methods to accommodate this dispersal.
http://www.bristol.ac.uk/alspac/
http://www.swansea.ac.uk/medicine/research/researchthemes/patientpopulationhealthandinformatics/ehealth-and-informatics-research/pearl/
CLAHRC South London, NIHR, £18M, 2014-2019
The National Institute for Health Research (NIHR) Collaboration for Applied Health Research and Care (CLAHRC) South London pools the clinical and research expertise of both the NHS and universities in south London. As part of the Informatics stream of the CLAHRC Stroke project, we are looking into collecting data and providing information to clinicians when working with patients that suffer from stroke and other conditions often present in stroke patients – heart disease, diabetes, depression etc. This is an example of a generic problem, which is the provision of decision support in scenarios with multiple co-morbidities, where multiple information streams have to be combined and prioritized, while ensuring relevant information is communicated to the user. The provenance of the recommendations and reasoning is also routinely captured and analysed.
Electronic Health Records for Clinical Research (EHR4CR), EU IMI, EUR 13M, 2010-2015
EHR4CR consortium of 32 EU academic and industrial partners is concerned with enabling interoperable operations between multiple EHRs and leveraging their wealth of clinical data for use across different therapeutic areas to bridge to clinical research. Our work focused on provenance and developing efficient query models for EHR systems.
BRC STAR
Linkage of air polution data.
NHIC
Data sharing infrastructure among five BRCs for research, clinical and patient benefits (NIHR). Informatics for combined management and analysis of clinical and ‘omics’ data
Past projects
Translational Research and Patient Safety in Europe (TRANSFoRm), EU FP7, EUR 9.2M, 2010-15
The project is implementing the first working prototype of a Learning Health System in Europe. It is a collaboration with 20 partners in 10 EU states on developing methods, models, services, validated architectures to support three demonstrations of LHS use cases: Epidemiological research using GP records, including genotype-phenotype studies and other record linkages; clinical trial embedded in the EHR and driven by routinely collected data, evaluated with 5 commercial EHR tools in 4 EU countries; and decision support for diagnosis integrated with an EHR system in the UK.
http://www.transformproject.eu
ePCRN: The electronic Primary Care Research network
Funding: National Institutes of Health USA (2005-8) $3M, NIHR National School for Primary care Research (2008-11) £500,000
Collaborators: University of Minnesota, University of Birmingham
Aims: Working with the caBIG project, ePCRN has created a model for primary care research (Primary Care Research Object Model), and used this to develop a standards-based clinical trial data management system using meta-data and an xml-computable representation of clinical trial protocols to create electronic remote data capture forms and databases. ePCRN also integrates data from clinical records to enable secure, anonymous searches of the records with flagging of suitable subjects for research (for the identification of prevalent cases).
http://www.epcrn.bham.ac.uk/
DUTY: Diagnosis of Urinary Tract Infection in the Young
Funding: HTA Programme £3.5M
Collaborators: Led by Bristol (Hay), Cardiff, Kings’, Southampton
Aims: This diagnostic cohort study of 6,000 children under the age of 5 years presenting to the GP with fever or malaise will establish a clinical prediction rule for the diagnosis of UTI. Kings are responsible for recruiting 1500 children from approx 50 SE London practices and for the web-based data capture. We will be piloting ePCRN during the project.
LINNEAUS EURO-PC
Funding: European Commission Framework Programme 7 Co-ordination and Support Action (2009-12)
Collaborators: University of Manchester and 5 others
Aims: We will establish a network of researchers in the EU interested in the study of diagnostic error, produce recommendations on methods for the study of diagnostic error and a list of requirements for diagnostic decision support systems. We will hold two workshops.
http://www.linneaus-pc.eu
GPRD-RETROPRO
Funding: Wellcome Trust, HTA Programme
Collaborators: MHRA General Practice Research Database, London School of Hygiene and Tropical Medicine, University of York.
Aims: We are integrating ePCRN with the GPRD and developing a system to enable ‘real time’ identification of incident cases for research projects in conjunction with two GP health record systems (IPS and EMIS).
People & Contact Us
Academic:
Dr Vasa Curcin, Lecturer in Health Informatics & Group Lead
Email: vasa.curcin@kcl.ac.uk
Tel: +44 (0) 207 848 6637
King's College London
Department of Population Health Sciences
Faculty of Life Sciences & Medicine
Addison House
Guy's Campus
London
SE1 1UL
Researchers:
PhD students:
Software developers: