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Dr Katie Harron

BA MSc PhD

Assistant Professor
of Statistics

LSHTM
15-17 Tavistock Place
London
WC1H 9SH
United Kingdom

I joined LSHTM in January 2015 with a Sir Henry Wellcome Postdoctoral Fellowship, after completing my PhD in Statistics at the UCL Institute of Child Health. Prior to this, my first research position at the University of Leeds developed my interests in using linkage of administrative and electronic healthcare data for maternal and child health research. 

Affiliations

Department of Health Services Research and Policy
Faculty of Public Health and Policy

Research

Maternal health and social circumstances (e.g. age, BMI, depression) are known to be related to birth outcomes: for example, mothers who smoke during pregnancy are more likely to give birth to smaller babies. These maternal factors may also be related to how often children are admitted to hospital throughout childhood. Since information on maternal and baby healthcare records is not routinely linked, there is a lack of information on which maternal factors are most important, or on which mothers and babies would benefit most from increased support from health services either during pregnancy or after birth.

Hospital data that are collected for administrative purposes (e.g. for financial/clinical management) are a rich source of information for health research and avoid the time and cost involved with collecting new data on large numbers of people. Linkage of this healthcare information for mothers and babies provides new opportunities for finding out how maternity services could be improved.

My current research uses NHS hospital data to describe how maternal health during and prior to pregnancy affects birth outcomes (e.g. preterm birth) and how it affects use of health services in childhood. We explore whether women’s previous birth outcomes, the time between pregnancies, and health service use for mothers and her offspring are related to how often children are admitted to hospital. This research will provide a better understanding of how maternal and child health are related, provide opportunities to identify families who could benefit from increased support during pregnancy and after birth, and help inform improvements to maternity services and childhood health.  

My research aims to establish how linkage of nationally representative, population-level administrative data can be used to identify and measure determinants of variation in child health outcomes. I aim to use these data to quantify the burden of preterm birth throughout childhood using English and Canadian electronic healthcare data and to evaluate determinants of educational achievement in adolescents who were born preterm by linking health and education data sources. 

Research Area
Child health
Health services research
Maternal health
Perinatal health
Public health
Statistical methods
Electronic health records
Neonatal health
Discipline
Epidemiology
Statistics
Disease and Health Conditions
Chronic disease
Hospital acquired infection
Country
United Kingdom

Selected Publications

Impregnated central venous catheters for prevention of bloodstream infection in children (the CATCH trial): a randomised controlled trial.
Gilbert, R.E.; Mok, Q.; Dwan, K.; Harron, K.; Moitt, T.; Millar, M.; Ramnarayan, P.; Tibby, S.M.; Hughes, D.; Gamble, C.; CATCH trial investigators, .; COLLABORATORS;Mok, Q. ; Lee, T.Y. ; Riordan, S. ; Macintosh, I. ; McCorkell, J. ; Stearn, K. ; Mitchell, R. ; Tibby, S. ; Harris, J. ; Wellman, P. ; Bagshaw, O. ; Spry, J. ; Laker, S. ; Holdback, N. ; Roche, J. ; Cooper, S. ; Hewett, D. ; Kerr, S. ; Haigh, F. ; White, M. ; Schindler, M. ; Traub, C. ; Worrin, N. ; Ramaiah, R. ; Patel, R. ; Macrae, D. ; Bacon, S. ; Cooper, M. ; Abdulla, A. ; Brewer, A. ; Agbeko, R. ; Mackerness, C. ; Davies, P. ; Walsh, D. ; Crate, L. ; Agbeko, R. ; Simmister, C. ; Ramaiah, R. ; Patel, R. ; Tasker, R. ; Playfor, S. ; Vail, A. ; Roebuck, D. ; Gray, J. ; Greig-Midlane, H. ; Ewings, P. ; Sharland, M. ; Modi, N. ; Gilbert, R. ; Wade, A. ; Gamble, C. ; Dwan, K. ; Moitt, T. ; Breen, R. ; Hughes, D. ; Ridyard, C. ; Mok, Q. ; Ramnarayan, P. ; Tibby, S. ; Harris, J. ; Millar, M. ; Draper, L. ; Bagshaw, O. ; Muller-Pebody, B. ; Hewett, D. ; Blundell, M. ; Howlin, S. ; Finnetty, L. ; Pribramska, I. ;
Lancet
Linking Data for Mothers and Babies in De-Identified Electronic Health Data.
Harron, K. ; Gilbert, R. ; Cromwell, D. ; van der Meulen, J. ;
PLoS One
The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement.
Benchimol, E.I. ; Smeeth, L. ; Guttmann, A. ; Harron, K. ; Moher, D. ; Petersen, I. ; Sørensen, H.T. ; von Elm, E. ; Langan, S.M. ; RECORD Working Committee, . ;
PLoS Med
Evaluating bias due to data linkage error in electronic healthcare records.
Harron, K. ; Wade, A. ; Gilbert, R. ; Muller-Pebody, B. ; Goldstein, H. ;
BMC Med Res Methodol
Opening the black box of record linkage.
Harron, K. ; Wade, A. ; Muller-Pebody, B. ; Goldstein, H. ; Gilbert, R. ;
J Epidemiol Community Health
Making co-enrolment feasible for randomised controlled trials in paediatric intensive care.
Harron, K. ; Lee, T. ; Ball, T. ; Mok, Q. ; Gamble, C. ; Macrae, D. ; Gilbert, R. ; CATCH team, . ;
PLoS One
See all Dr Katie Harron's Publications