Home / Supervisors / Lucy Hederman

Lucy Hederman

hederman@tcd.ie

Dr Lucy Hederman has been active in health informatics research for more than 25 years. Her main area of interest has been clinical decision support systems, patient generated health data, knowledge and data engineering. She has recently focussed on clinical research informatics, encompassing issues of health data integration and harmonisation, data quality, and data governance.

Dr. Hederman is the lead for the Heterogeneity & Interoperability challenge of the Transparency and Digital Governance (TDG) strand of the SFI funded ADAPT 2 centre. She is a collaborator on the SFI-funded PRECISION-ALS project which is developing an innovative and interactive platform for all clinical research in ALS (aka motor-neurone disease) across Europe, that will then harness artificial intelligence (AI) to analyse large amounts of data. She contributes to the patient-data platform workpackage.

Dr. Hederman is a collaborator on the EU-funded PARADISE project which seeks to develop a personalised prediction tool to assist in the management of recurrent autoimmune disease. On the EU-funded FAIRVASC project, which is making cross-Europe vasculitis registries interoperable to support research, she contributed to work packages on data uplift, data quality and data governance. She was a member of the doctoral studies committee of the HELICAL ITN which trained researchers in linking health data for clinical research.

Her relevant previous research collaboarations include the EU-funded TransFoRM FP7 project (2010-2015), the HRB funded Primary Care Research Centre (2009-2015), and the HEA funded PRTLI MediLink (2000-2004), which she coordinated. These three all aimed to bring research evidence to clinical practice.
Projects she is looking to supervise include:
In furtherance of the objectives of the Heterogeneity and Interoperability challenge of the Transparent Digital Governance strand of the ADAPT 2 research centre, He is seeking a post-doc that will develop methods and standards to support transparent, context aware, quality-controlled and policy-compliant data integration for clinical research.

Research Areas:

health informatics; clinical research informatics; data integration; data quality; data harmonisation; automated data pipelines