Louisa Jorm: A New Era of Dynamic Cardiovascular Risk Assessment
Louisa Jorm, Director at Centre for Big Data Research in Health, Professor at Faculty of Medicine and Health at UNSW, shared a post on LinkedIn about a recent article she and her colleagues co-authored, published in BMJ Open, adding:
“I’m pleased to share that our study protocol has now been published in BMJ Open.
Dynamic cardiovascular risk prediction using linked primary care electronic medical records: protocol for a model development and validation study.
This project will use the NSW Lumos linked health data asset to develop and validate models that update a patient’s cardiovascular disease (CVD) risk at every GP consultation, rather than relying on a single baseline assessment.
The work builds on our recent Heart paper, which showed that routinely collected Australian general practice electronic medical records can accurately estimate 5-year CVD risk (C-index approximately 0.80) using linked primary care data.
The next step is to investigate whether dynamic prediction can better reflect changes in patients’ health over time, including the effects of lifestyle modification and newer preventive therapies, while supporting more personalised and proactive care.
Beyond cardiovascular disease, we hope this work contributes to a broader conversation about how linked primary care data can underpin learning health systems and more integrated approaches to managing cardiometabolic health and multimorbidity.
Many thanks to all collaborators and our partners at NSW Health and the Lumos program.
This research is supported by the Australian Medical Research Future Fund.”
Title: Estimating 5-year absolute risk of cardiovascular disease using routinely collected electronic medical records from Australian general practices
Authors: Nicholas I-Hsien Kuo, Clare Arnott, Blanca Gallego, Ziba Gandomkar, Shahana Ferdousi, Kirsty Douglas, Mark Woodward, Louisa Jorm
Read the full protocol on BMJ Open.
Title: Dynamic prediction of cardiovascular risk from linked primary care records in New South Wales, Australia: protocol for a retrospective prognostic modelling study
Authors: Nicholas I-Hsien Kuo, Heidi Welberry, Sanja Lujic, Anna Campain, Daniel Wilson, Katie Harris, Michael Kidd, Patricia Correll, David Peiris, Louisa Jorm
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