Associate Professor Katrina Kirtsy Poppe



My background is in clinical cardiac physiology and in medical statistics, and my research bridges cardiovascular medicine, advanced clinical technology, data science, applied statistics and epidemiology, with applications ranging from public health to advanced cardiology. There is enormous potential for further development of this combined approach to cardiovascular research.

Research | Current

Everyone is at risk of cardiovascular (CV) or other chronic diseases. Improved detection of disease and/or improved accuracy of predicting the risk of future clinical events will lead to improved management and risk reduction for individuals and populations. The new era of “big data” has provided a significant opportunity to develop more personalised approaches to the continuum of chronic disease and risk management, i.e. where healthcare decisions, practices and interventions are tailored to individuals based on their predicted risk of disease.

Risk prediction for CVD is well established in New Zealand. However the type of risk and people that risk prediction is being used for has remained largely unchanged for the last 40 years. Expanding prediction to address the life-course of risk is long overdue, as is the progression and development of analytical techniques to deal with the data and clinical environments in which we now live. Equivalent with Vision Mātauranga, “to think about new ways of doing things, to find answers, to solve problems”, we need to think about new ways of developing risk algorithms to guide management of a person’s health and disease, and to do that in a way that accommodates an individual’s situation and needs. This is quite different from what the established techniques and thinking allow us to do.

My research is a combination of methodological and clinical studies to optimise and personalise CV disease risk prediction and management in the New Zealand healthcare environment. I aim to expand the methodologies and analytics of prognosis research, which is a central discipline of the rapidly developing field of personalised (or precision) medicine and has practical healthcare implications.

Teaching | Current

HLTHINFO 725: Navigating the Health Data Landscape


Postgraduate supervision

Current supervision

PhD in Population Health

PhD in Medicine

MD x2

Recently completed

BMedSci(Hons) x2

PhD in Population Health

MPH x2


2019: Early Career Research Excellence Award, University of Auckland

2018: Fellow of the European Society of Cardiology

2018-2020: Heart Foundation Hynds Senior Fellow

2011-14: Heart Foundation Post-Doctoral Research Fellow

2011: Nominated for Vice-Chancellor's Prize for the Best Doctoral Thesis

2007-10: Heart Foundation Postgraduate Scholar



Director of the VIEW Data Ecosystem and analytical practice

Director MENZACS Data Science Advisory Group


Areas of expertise

Prognosis research, particularly the development of risk scores.

Making sense of multiple large datasets that need to be combined and analysed

Cardiovascular epidemiology

Clinical cardiac physiology and technology

Selected publications and creative works (Research Outputs)

As of 29 October 2020 there will be no automatic updating of 'selected publications and creative works' from Research Outputs. Please continue to keep your Research Outputs profile up to date.

Contact details

Primary office location

M&HS BUILDING 507 - Bldg 507
Level 1, Room 1001
New Zealand